P OLITECNICO DI M ILANO
DEPARTMENT OF E LECTRONICS , I NFORMATION TECHNOLOGY
B IOENGINEERING
D OCTORAL P ROGRAMME IN XXVIII
AND
S ILICON D RIFT D ETECTOR ARRAYS FOR X- AND
G AMMA- RAY DETECTION APPLICATIONS
Doctoral Dissertation of:
Arslan Dawood Butt
Supervisor:
Prof. Carlo E. Fiorini
Tutor:
Prof. Angelo Geraci
The Chair of the Doctoral Program:
Prof. Andrea Bonarini
2016 – XXVIII
Abstract
T
HE aim of my Doctoral activity has been the study and development
of X- and γ-ray detection systems based on Silicon Drift Detectors
(SDDs) for diverse applications in the field of radiation detection
instrumentation.
Instrumentation for radiation detection is a very vast field with a variety
of detectors well suited for X- and γ-ray spectroscopy, imaging, timing and
tracking. Among these, Silicon Drift Detector is a relatively recent device,
being invented by E. Gatti and P. Rehak in 1983. Since its instigation, SDD
has become a widely used detector for applications demanding low-noise,
high-rate X-ray detection solutions (i.e. EDX, XRF, etc..) in the typical
range of 0.2-30 keV. However, these applications are always evolving with a
continuous demand for better performance SDDs and readout electronics.
Recent developments to meet these challenges have resulted in an ultra low
leakage SDD technology and an external CMOS based preamplifier solution
with input trans-conductance optimized for very low noise readout of SDDs.
In addition, many Application Specific Integrated Circuits (ASICs) have
recently been developed to provide compact analog readout of preamplifiers
to optimize energy resolution performances. The general trend in SDD
readout is moving towards development of modular detection modules, each
with a monolithic array of SDDs, preamplifiers and complementary support
mechanics. This modularity provides the possibility of scaling of the overall
detection system with the integration of multiple detection modules.
One application demanding state of the art SDD performance is an
upgrade of the SIDDHARTA experiment, which involves a large detector
I
surface area composed of multiple SDD arrays to detect X-ray emissions
of exotic atoms for study of strong nuclear interactions. This application
involves operation of the SDD arrays at cryogenic temperatures to reduce
SDD’s charge collection time. Such reduced charge collection time is
needed for implementation of a stricter timing logic to minimize collection
of asynchronous background events. Another application within ARDESIA
project involves development of compact SDD arrays for high count rate
X-ray Absorption Fine structure Spectroscopy (XAFS). In this application,
the SDD arrays are placed in fluorescence geometry to measure core-level
binding energies of samples containing light atomic elements. Contrary
to the common technique involving measurement of absorption spectra,
Ardesia utilizes fluorescence spectra which can be very useful when dealing
with diluted or supported (thick) samples.
In addition to X-rays, SDDs have also proved to be useful for scintillator
readout to perform γ-ray spectroscopy and imaging. Nominally for γ-ray
applications involving indirect conversion, Photo-Multiplier Tube (PMT)
represents the state of the art solution owing to the presence of signal
multiplication. Although PMT has the obvious advantage of simplicity
of use in lab environment and room temperature operation, SDD arrays
provide the advantage of relatively compact (low mass/volume) detection
module design with low voltage operation, compatibility with magnetic
fields and a higher quantum efficiency. A new kind of detector which
possesses advantages of both SDD and PMT, is the Silicon Photo-Multiplier
(SiPM) device whose only disadvantage at the moment is a lower overall
Photon Detection Efficiency (PDE) as compared to SDDs.
One application of SDDs, supported by European Space Agency (ESA),
involves a feasibility study to evaluate the use of SDD arrays to readout
large LaBr3 :Ce scintillators for planetary γ-ray observations. In this scope,
a wide nuclear transition region i.e. 150 keV to 15 MeV is considered
to investigate chemical composition of planetary surfaces. This scintillator+SDD approach is also a good candidate for use as a Compton camera in
gamma-ray observatories. In addition, large LaBr 3 :Ce scintillators readout
by SDD arrays can in principle also be used for a possible reduction of
Doppler Broadening effect. This Doppler Broadening effect occurs when
radioactive sources moving at high/relativistic velocities with respect to the
detector, emit γ-rays which undergo an apparent shift in energy. This results
in a broadening of the γ-ray lines at the detector which can in principle be
reduced by using a position sensitive γ-ray spectrometer.
This Doctoral dissertation is organized with the first chapter providing
a background to radiation detection systems with a description of major
II
challenges associated with the development of systems for X- and γ-ray
detection.
The second chapter introduces the device physics and working principle
of SDD. Also, different device parameters and their effect on the overall
performance of the SDD is also described. An outline of various stages
involved in the readout electronics and a description of noise performance
with SDDs is also described.
The third chapter describes the SDD device, the Charge Sensitive Amplifier (CSA) and the readout ASICs in the context of Siddharta upgrade
alongside with preliminary results pertaining to X-ray characterization of
these components. In addition, soft X-ray performance of a similar SDD
with a thin entrance window is also depicted. In the last part of this chapter,
a brief overview of Ardesia project and its targets is also presented.
The fourth chapter introduces indirect conversion in addition to an
overview of scintillation properties of LaBr3 :Ce crystal. Later on, a γray detection system based on the readout of large (100 and 200 ) LaBr3 :Ce
crystals readout by SDDs is described in the scope of ESA sponsored project
for γ-ray application. Spectroscopy results associated with both the 1 00 and
200 formats are presented to evaluate system performance. In the final part
of this chapter a comparison between the SDD and PMT based readout is
performed and an estimate of possible improvement with a new ultra low
leakage SDD device is provided.
The fifth chapter describes the position sensitivity experiments designed
with the same γ-camera described in chapter 4 and the corresponding measurement results are described.
The last chapter of this Doctoral dissertation contains the final discussions
and conclusion.
III
Contents
Abstract
I
Table of Contents
V
1 Introduction
1.1 History of ionizing radiation detection
1.2 Role of radiation detection in society .
1.3 Basics of radiation detection systems .
1.3.1 X-ray detection . . . . . . . .
1.3.2 Gamma-ray detection . . . . .
1.4 Summary . . . . . . . . . . . . . . .
2 Silicon Drift Detectors
2.1 Introduction . . . . . . . . . . . .
2.2 SDD Working principle . . . . . .
2.3 SDD performance parameters . .
2.3.1 Energy resolution relation .
2.3.1.1 Direct conversion .
2.3.1.2 Indirect conversion
2.3.2 Quantum Efficiency . . . .
2.3.3 Drift time . . . . . . . . .
2.3.4 Ballistic Deficit . . . . . .
2.4 SDD readout electronics . . . . .
2.5 Electronics readout noise . . . . .
2.6 Summary . . . . . . . . . . . . .
V
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1
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15
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33
Contents
3 SDD based X-ray spectrometry
3.1 Introduction . . . . . . . . . . . . . . . . . . . .
3.2 Siddharta Upgrade . . . . . . . . . . . . . . . .
3.3 Readout electronics . . . . . . . . . . . . . . . .
3.3.1 CUBE charge preamplifier . . . . . . . .
3.3.2 Readout ASIC . . . . . . . . . . . . . . .
3.4 Experimental characterization of single SDD unit
3.4.1 Characterization at room temperature . . .
3.4.2 Characterization with Peltier cooling . . .
3.4.3 Characterization at cryogenic temperatures
3.5 Experimental characterization of SDD array . . .
3.6 Ardesia project . . . . . . . . . . . . . . . . . .
3.7 Summary . . . . . . . . . . . . . . . . . . . . .
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35
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4 SDD for gamma-ray detection
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . .
4.1.1 Scintillation detectors . . . . . . . . . . . . . .
4.1.2 Lanthanum Bromide as a scintillator . . . . . .
4.1.3 ESA sponsored gamma-ray project . . . . . . .
4.2 Design of the gamma-ray detection system . . . . . .
4.2.1 Detection head . . . . . . . . . . . . . . . . . .
4.2.2 Readout Electronics . . . . . . . . . . . . . . .
4.2.3 System Mechanics . . . . . . . . . . . . . . . .
4.2.4 Cooling System . . . . . . . . . . . . . . . . .
4.3 Gamma-ray spectroscopy measurements . . . . . . . .
4.3.1 Detection head calibration and characterization .
4.3.2 Measurements with 100 LaBr3 :Ce . . . . . . . .
4.3.3 Measurements with 200 LaBr3 :Ce . . . . . . . .
4.4 Comparison of SDD with PMT based readout . . . . .
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . .
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5 Gamma-ray imaging measurements
5.1 Introduction . . . . . . . . . . . . . . .
5.1.1 Gamma-ray imaging . . . . . . .
5.1.2 A position sensitive spectrometer
5.2 Position sensitivity of 100 LaBr3 :Ce . . .
5.2.1 Experimental setup . . . . . . .
5.2.2 Measurement results . . . . . . .
5.3 Position sensitivity of 200 LaBr3 :Ce . . .
5.3.1 Experimental setup . . . . . . .
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103
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VI
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Contents
5.3.2 Measurement results . . . . . . . . . . . . . . . . . . 112
5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
6 Discussions and Conclusion
117
List of Acronyms
123
List of Figures
125
List of Tables
133
Bibliography
135
VII
CHAPTER
1
Introduction
1.1 History of ionizing radiation detection
Radiation was first discovered by Wilhelm Conrad Roentgen on 8th November 1895 while he was experimenting with Hittorf-Crookes vacuum tube to
study its effects on external objects near the tube. Rontgen observed that in a
dark room, a piece of cardboard coated with barium platinocyanide glowed
with a greenish glow (fluorescence) once electrical discharges took place
in the vacuum tube near this screen. This was particularly interesting as he
had covered the vacuum tube with opaque material and was sure that no
visible light was passing through. Later, Rontgen performed more experiments and came to the conclusion that the tube was generating some kind of
invisible rays which generated a glow upon hitting the fluorescence screen.
Unfamiliar with their origin, Rontgen named these invisible rays as X-rays
and continued his experiments. In one of these subsequent experiments, he
replaced the fluorescence screen with a photographic plate and achieved the
first ever recorded medical X-ray photograph on 22nd December 1895 (see
Figure 1.1). Hence, shortly after the discovery of radiation, the first ever
radiation imaging detector had been successfully developed.
A few months later in 1896, a French scientist Henri Becquerel discov1
Chapter 1. Introduction
Figure 1.1: One of the very first images ever taken using X-rays or "Rontgen Rays" by
Rontgen. This image shows the bones of hand and has been taken on 22nd December
1895.(Deutches Museum Munich)
ered natural radioactivity when he developed a photographic plate that had
stayed in his drawer for several days close to some uranium salts. Becquerel discovered some dark spots on the photographic plate where uranium
salt had been present. At a time when the origin of X-rays was still not
completely understood, Becquerel had discovered that effects similar to
the invisible X-rays can be observed on the photographic plate with all
compounds of Uranium metal. However, it was Marie Sklodowska Curie in
1897 who coined the term radioactivity while studying the ionizing nature
of these invisible rays emitted by Uranium. Furthermore by 1900,α, β and
γ rays had not only been discovered but information regarding the charge
they carried had also been understood by performing experiments where the
radiation sources were placed in magnetic fields.
The first instrument ever developed to detect each individual photon/particle interaction with matter is called the spinthariscope and it was invented
by Crookes in 1903. In this instrument, individual visible scintillation points
could be seen on a zinc sulfide screen generated by alpha particle interactions. These individual scintillation points were manually observed and
counted using a powerful magnifying glass. Another instrument developed
for detecting single radiation events by eye is the cloud chamber which was
developed in 1911 by C.T.R. Wilson. In the cloud chamber, a movable piston
2
1.1. History of ionizing radiation detection
is utilized to quickly expand the volume of enclosed gas in a glass chamber.
This results in a super saturated atmosphere in the chamber where the super
saturated vapors of water are capable of condensation around ions. Once
some ionizing radiation passes through the chamber, the ions created by its
interactions cause condensation which creates a visible trail of the radiation
trajectory. A flat glass front-plate, present in the cloud chamber is used for
observation of such radiation events while glass side-walls are used for their
illumination. Figure 1.2 shows one of the photographs of the earliest cloud
chambers showing the tracks of ionized electrons once ionizing X-rays pass
through the cloud chamber.
Figure 1.2: Early cloud chamber photograph taken by C. T. R. Wilson in 1911 showing the
tracks of electrons released when X-rays passed through the chamber. (Source: C. T. R.
Wilson, Cambridge)
Although photographic plates were used for radiation detection since
its discovery in 1895, new kinds of emulsions known as nuclear emulsions
were developed in 1930s to observe individual nuclear tracks. Furthermore
by 1942, quantitative photographic dosimetry had been introduced where
radiation film badges containing photographic emulsions were designed
to monitor radiation levels of routine personnel working in environments
with risk of radiation exposure. These photographic emulsions had also
begun assisting detections with cloud chambers and magnetic spectrographic
systems for particle spectrometry. Even today, these photographic emulsions
are extensively used in medicine, industry, and research.
As already mentioned, one of the first ever radiation detection and counting techniques involve estimation of intensity of ionizing radiation by counting the number of visible scintillation flashes caused by the radiation in
zinc sulphide. In 1940s, this method was revitalized by the invention of
electronic photomultiplier tubes. These electronic photomultiplier tubes
allowed conversion of weak flashes of light generated by radiation interac3
Chapter 1. Introduction
tion in scintillators into useful signal. One major discovery in the field of
radiation detection involves involves the discovery of NaI:Tl and organic
scintillators in 1947-1948 which became commercially available in 1950.
Liquid scintillators were also discovered in 1948 but they did not pique scientific community’s interest till the 1960s when more work was performed
to develop them.
In the history of radiation detectors, the ionizing nature of the radiation
has been greatly exploited to develop many detection instruments. In principle, the charge generated by the interaction of ionizing radiation with
matter in a gas filled chamber can be separated under the influence of an
electric field applied across the chamber. Hence the electric current that
flows through an ammeter connected in series with the chamber electrodes
is proportional to the number of the charge carriers in the chamber which
is directly related to the intensity of ionizing radiation. This principle is
shown in Figure 1.3. Rutherford and Geiger developed the first ionization
chamber counter to detect alpha particles in 1908. An Austrian physicist
Victor Hess used a similar ionization chamber in 1910 when he discovered cosmic-rays at high altitude during a balloon flight. Another major
achievement with the ionization chamber was its use to count beta particle
in 1913. A new type of gas filled detector utilizing ionization property of
the radiation was developed by Geiger and Muller in 1928 and is called the
Geiger-Muller or GM counter after its inventors. This detector is sensitive
to individual ionization events and provides a high-level of output signal. In
1940s, many new kinds of gas filled ionization chambers were developed
among which the gridded ionization chamber and the proportional counter
are worth mentioning. The gas filled detectors find many applications even
today however the gas-ionization chambers have now become obsolete.
Another category of detectors involving use of solid crystals instead of
gas as mediums for interaction of ionizing radiation were studied by Jaffe
in 1932 and later on by Van Heerden in 1945. One major advantage of
using solids instead of gases as detector material is the∼1000 times higher
density of solids as compared to gases. Hence such solid state detectors can
result in very compact size of the detectors. However, solid state detectors
were first developed in the late 1950s and early 1960s when solid dielectric
ionization mediums that worked on the same principle as the gas chambers
had been realized. These discoveries resulted in the development of many
new detectors employing semiconductor based materials. In 1960, Pell
performed some valuable work on ion drifting which resulted in fabrication
of semiconductor detectors with much larger radiation sensitive volumes.
This also opened the path for the development of "Drift Detectors".
4
1.2. Role of radiation detection in society
Figure 1.3: A schematic diagram depicting the working of a parallel plate ionization
chamber. [1]
In the present age, Silicon based semiconductor detectors dominate
arena of low energy X-ray detection and beta particle spectrometry. However, Germanium based detectors are more common in ion-drift detectors
for low to medium energy γ-ray measurements with very good energy
resolution performances. In chapter 2 of this dissertation, this discussion associated with history of radiation detectors is further carried on to introduce
a relatively recent silicon based photodetector for X-ray detection purposes.
1.2 Role of radiation detection in society
Since its discover in 1895, the study of radiation has played a very important
role in helping us understand the world we live in. Radiation detectors
developed to understand radiation has helped us perform experiments that
precipitated in the discovery of electrons, protons, neutrons and all the
other basic fundamental sub-atomic particles. All the research that has been
done so far to understand the structure of atom; beginning from the first
thin gold foil experiment performed by Rutherford in 1911 till the most
advance nuclear physics experiments like ATLAS being performed today in
the Large Hadron Collider (LHC) in CERN, utilize one or another form of
radiation detector. For Rutherford, it was a fluorescent screen while for the
ATLAS experiment there are six different detection subsystems to record
paths, momentum and energy of the particles (see Figure 1.4) [2]. Compared
5
Chapter 1. Introduction
to the aim of Rutherford’s experiment to verify Thomson’s plum-pudding
model, the modern ATLAS has already discovered Higgs boson [3], and is
now geared up to investigate extra dimensions and dark matter.
Figure 1.4: ATLAS detector probes, weighing over a 1000 tonnes, can be seen here
assembled to detect fundamental particles [2].
Detection systems are also being used in γ-ray astronomy where NASA’s
Fermi Gamma-ray Space Telescope (FGST) is one such telescope containing
particle detectors to detect radiation from 8 keV till 300 GeV [4]. Another
possible role for radiation detection systems is to remotely investigate composition of planetary surfaces by spectroscopic analysis of secondary γ-rays
emitted from these surfaces due to cosmic ray interactions as shown in
Figure 1.5 [5]. One detector for similar purpose has already been flown to
moon in a recent Chinese lunar mission Chang’E-2 [6].
In the field of nuclear medicine, a lot of improvement has been made
as compared to the first crude X-ray image shown in Figure 1.1. Fourth
generation Computerized Tomography (CT) scanners are now available
which employ up to 2000 X-ray detectors and perform a CT scan within
seconds. The use of Nuclear medicine techniques like Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography
(PET) have greatly improved the diagnosis of tumors as well as the study
of cancerous tissue growth. These devices perform 3D imaging of patient
by detecting the γ-rays emitted by the radio-tracers injected into the patient
which are absorbed primarily by the rapidly growing cancerous cells. Also in
the field of radiation therapy, a better understanding of the effect of radiation
on the human body has introduced techniques which are more precise and
6
1.2. Role of radiation detection in society
Figure 1.5: The principal γ-ray emissions due to both natural radioactivity and interaction
of cosmic rays with matter. [5]
reliable in controlling or killing the malignant cells. One such technique
is called proton therapy whose accuracy has been greatly enhanced by implementation of prompt gamma imaging. In prompt gamma imaging, the
secondary γ-rays emitted by the tissue being irradiated are detected by a
gamma camera (imaging detector) to identify the irradiation point. This is
in turn used to implement a feedback loop to ensure that only the tumorous
cells are targeted by the proton beam. This prompt gamma imaging principle
is represented in Figure 1.6 [7].
Nuclear power plants are now being used in many countries around the
world to provide electricity to consumers. Different radiation detection
instruments are employed in these facilities to ensure the safety and security
of the working personnel. In addition, at airports and other sensitive facilities, X-ray scanners are widely being used to quickly scan the luggage and
personal belongings of the passengers/visitors. A very efficient and cheap
method of detecting fires at homes and offices is the utilization of smoke
detectors employing a small quantity of Americium and an ionization gas
chamber to detect a wider range of fire conditions. Today, X-ray Fluorescence (XRF) spectrometry allows us to perform a non-destructive study of
works of art and cultural heritage [8]. This can allow us to understand the
fundamental composition of various paintings, mosaics, glasses, ceramics
e.t.c and can help us in preservation. Radioactive carbon dating is another
7
Chapter 1. Introduction
Figure 1.6: Proton beam range measurement with a slit gamma camera. [7]
application of radiation detection where the age of an object can be determined by measuring the ratio of radioactive 14 C as compared to the more
common 12 C within its structure. As this ratio is more or less constant in
the biosphere by the introduction of new 14 C by cosmic ray interactions,
for archaeological samples which have long since stopped interacting with
the biosphere, this ratio reduces at the half life rate of 14 C (5,730 years). A
spectral analysis of such samples can help estimate the age of the fossil.
1.3 Basics of radiation detection systems
There are different kinds of ionizing radiations in particular the X-rays,
γ-rays and particle beams. X- and γ-rays are basically photons which differ
from one one another based on their energies and source of origin. However,
particles on the other hand form a much larger family as they differ from one
another in their charge, rest mass, kinetic energy, etc. There is a very wide
variety of detectors which employ direct or indirect detection techniques to
estimate the charge and kinetic energy of the incident particle. Also many
detection systems have been developed to track high energy particles in the
field of both experimental and applied particle physics. However, in this
section the scope of our discussion will be limited to the detection of X- and
γ-rays only.
1.3.1
X-ray detection
In an X-ray detection system, the objective is to ensure that all the energy of
the incident photon is deposited in the detector material and is converted into
8
1.3. Basics of radiation detection systems
a useful electrical signal to be readout and processed by further electronics.
This processing of the electrical signal is aimed at retrieving the information
about the energy/arrival time of the incident X-ray photon.
Once an X-ray enters a detector material, it interacts with it using the
Photoelectric effect, Compton scattering and/or Rayleigh scattering. Details
about the theoretical fundamentals about these interaction processes can
be found in [9]. For most of the materials used for detecting X-rays, the
dominant interaction is because of the Photoelectric effect for energies below
100 keV. The photoelectric absorption in a material can be estimated by the
relation kconst ×Z n /E 3.5 for (n ∼ 4-5). Hence, a detector material with a very
high atomic number Z is more efficient in absorbing the incident X-rays. For
energies below 100 keV, Compton scattering is more or less negligible while
the Rayleigh scattering never exceeds 10% to 20% of the total absorption.
Figure 1.7 provides an overview of mass absorption coefficients of three
typical detector materials used of X-ray detection including Ar, Si, and
Ge [10].
Figure 1.7: Mass attenuation coefficients for Argon, Silicon and Germanium. The photoelectric, Compton and Rayleigh components of the total attenuation are also indicated
in the graphs. [10]
Once an X-ray is completely absorbed within the detector material, the
energy of the incident radiation is converted into a proportional amount
of charge which is later on collected at the output electrode of the device.
However, there are also some detection systems where scintillation crystals
are used to first convert the incoming radiation in to flashes of secondary
low energy photons which are converted into charge by the detector material
with a certain penalty owing to losses at the coupling interface between the
9
Chapter 1. Introduction
scintillator and the detector. This kind of detection is referred to as indirect
detection and is more common for high energy X-rays or γ-rays as the
typical detector materials shown in Figure 1.7 are not efficient in stopping
such high energy radiation. Cryogenic detectors are yet another kind of
indirect detectors which convert the energy of incoming radiation into heat
(phonons) and then utilize thermometers to estimate the energy by observing
the increase in detector’s temperature. Also in some cryogenic detectors the
incident radiation generates quasi-particles in a superconducting material
which can be measured with a Superconducting Tunnel Junction (STJ).
The number of electron hole pairs (Q) generated per unit energy (E)
of incoming radiation is defined by = E/Q. This conversion factor is
needed as different materials have different mechanisms and thereby different efficiencies for the generation of charge carriers. is 3.6 eV for each
e− /hole pair generated in Silicon while in Argon 26 eV is required to create
just one e− /ion pair. In a superconducting detector, ∼ 1 meV is sufficient for
generating one quasi-particle. The charge carriers are normally generated
within the first few picoseconds once the ionizing photon interacts within
semiconductor devices. However, electric fields are applied to separate
and collect these charge carriers in semiconductor and gas ionization detectors. This collection time largely depends on the charge carrier’s mobility
and can vary from a few nanoseconds in silicon based detectors to a few
microseconds in gas filled detectors.
In chapter 3, X-ray detection systems utilizing direct conversion will be
further discussed in the scope of experiments for nuclear physics research
and X-ray fluorescence application.
1.3.2
Gamma-ray detection
Gamma-ray detection systems differ substantially from X-ray detection because of the higher energies of individual γ-ray photons. Compared to X-ray
energies where the absorption is primarily dominated by photoelectric effect,
for γ-rays, Compton scattering is the dominant absorption mechanism. In
general, Compton scattering attains a significant role in radiation absorption
at incident photon energies above 100 keV and has a linear dependence on
the effective atomic number of the detector material.
For γ-ray energies above 1.022 MeV, a new interaction mechanism
appears which is known as the pair production. This phenomenon takes
place when a photon with energy greater than twice the rest mass energy
of electron creates an electron-positron pair near a heavy atomic nucleus.
The generated charged particles soon loose their energy inside the detector
10
1.3. Basics of radiation detection systems
material resulting in an increase in overall mass absorption coefficient at
high enough energies of the incident γ-rays.
Figure 1.8: Linear attenuation coefficients for photo absorption and Compton scattering
in CdTe, Si, Ge, and NaI:Tl. [11]
The major challenge in γ-ray detection is the fact that we need a detector
material which can effectively absorb the incoming radiation and should
also have a smaller conversion factor to convert photon energy into charge.
For γ-rays this represents a particular problem as most of the materials with
high atomic number and thereby good absorption coefficients have very poor
conversion factors. An exception to this generalization is CdTe and HpGe
detectors. The CdTe detector has a conversion factor of around 4.43 eV per
e− /hole pair and has an effective atomic number more than three times that
of Silicon. A plot of linear attenuation coefficient of CdTe as compared
to Si, Ge and Na:Tl is shown in Figure 1.7. However, even CdTe is no
longer efficient around 300 keV as very thick detectors need to be developed
to sufficiently absorb the radiation. For such thick detectors the biasing
voltage scales with the square law. However, many thin CdTe detectors can
be stacked together and in coincidence can be used to measure largerγ-ray
energies as well [11].
Another widely utilized solution is to go for indirect conversion detectors
11
Chapter 1. Introduction
already discussed in last section. With a CsI:Tl coupled to a silicon photodetector, a conversion factor of 25 eV per e− /hole pair can be achieved. The
advantage in case of scintillators is that they are very efficient in stopping the
incoming radiation as it can be seen in Figure 1.9 where a 2 inch Lanthanum
Bromide is still efficient at an energy of 10 MeV.
Figure 1.9: Gamma and X-ray absorption efficiency for various thicknesses of BrilLanCe
380 material (Saint Gobain commercial product name for Cerium doped Lanthanum
Bromide scintillator). [12]
For γ-ray energies much higher than 10 MeV, nominally the detection
probability is greatly reduced and interaction events become more and more
rare. One of the solutions to detect very high energy γ-rays (100 MeV to
100 GeV) is to develop an indirect conversion detector that relies on pair
production events in a scintillator medium. As the sum of the total energy
carried by the the particle and antiparticle pair is equivalent to the energy of
the incident gamma-ray photon, a calorimeter detecting the pair will actually
measure the energy of the incident γ-ray [13].
In chapter 4 and 5 of this dissertation, a new medium-high energy γ-ray
detection system using indirect conversion mechanism will be described in
the scope of gamma-ray astronomy and nuclear physics research applications
respectively.
1.4 Summary
This chapter has been aimed at providing a background to radiation detection
system and it describes some of the challenges associated with the devel12
1.4. Summary
opment of such systems. Being part of the experimental physics domain,
development of radiation detection systems has always lagged behind the
continuously evolving demand for evermore complex experiments to verify
new theoretical physics theories. However, the use of detection systems
are not only restricted to nuclear physics research but they have also found
applications in nuclear medicine and radiation therapy. Also fire alarms
employing radiation detection systems are providing us with economical
ways to keep us safe. In addition, radiation detection systems are not only
helping us explore outer space but are also providing us with an insight into
our past here on earth with carbon-14 dating. Nonetheless, there is still a
need for lots of improvement in the X- and γ-ray detection systems and
some of those improvements will be explained in the next chapters.
13
CHAPTER
2
Silicon Drift Detectors
2.1 Introduction
In the last chapter, an introduction to the basics of radiation detection and
its various applications has been discussed. In particular, the physics related
principles associated with interaction of various forms of radiation with
matter and challenges associated with their detection have been described.
In this chapter, we narrow down the scope of our discussion to a specific
radiation detector known as Silicon Drift Detector (SDD). SDDs have been
originally developed in 1983 by E. Gatti and P. Rehak and have the peculiar
feature of very low capacitance at the output electrode of the device [14–16].
In addition, the electrode capacitance at this output electrode is independent
of the total active area of the detector, resulting in an improvement in
electronics noise performance of the device at shorter peaking times of
the shaping amplifier. These properties make SDD an ideal candidate for
high-resolution X-ray spectroscopy measurements [17]. In addition, SDDs
have also earned a respectable status as preferred photo-detectors for X-ray
Fluorescence (XRF) applications [18, 19]. Moreover, SDD devices have
been utilized as a position sensitive photo-detector in high energy physics
applications as well [20, 21]. Over the years, the SDD devices have also
15
Chapter 2. Silicon Drift Detectors
proved themselves to be suitable alternatives to conventional photo-detectors
in scintillator-based indirect gamma-ray detection systems [22, 23].
In the beginning of this chapter, the device physics and associated working principle of the SDD element is described. Later on, different device
parameters and their effect on the overall noise performance of the device
are evaluated. The output signal provided by the SDD device needs to be
processed by a cascade of readout electronics chain before being acquired
by some Data Acquisition (DAQ) system. In this chapter, an outline of
various stages of readout electronics will be discussed while a thorough
discussion of its components and the DAQ will be discussed in next chapters
within the scope of the application under consideration. In the last portion
of this chapter, a model (available in literature) associated with the noise
performance of the SDDs and its readout electronics is discussed.
2.2 SDD Working principle
The basic working principle of the SDDs is similar to that of a simple PIN
diode detector for radiation detection: to develop a region within the device
depleted of all free charge carriers so that any electron-hole pairs generated
by an ionizing radiation can be readily separated. Both of these effects are
normally achieved by reverse biasing the PIN diode and this can be seen in
Figure 2.1(a). On the left side of Figure 2.1(a), a plot of the voltage potential
as a function of depth is also shown. Here, it can be seen that most of the
N-type substrate is at same potential and hence any −e /hole pairs generated
here cannot be separated from each other.
However, it is possible to grow a wafer with two p+ electrodes on both
sides of the device with a very small n+ electrode on one side as shown in
Figure 2.1(b). A quick look at the plot of voltage potential as a function
of depth for Figure 2.1(b) shows that now there are two different regions
where the detector has been depleted. Now if we keep on increasing the
positive biasing voltage Vbias at the n+ electrode, a moment comes when the
whole region between the two p+ electrodes is depleted. This voltage which
completely depletes the silicon wafer is known as the depletion voltage Vdep
and is nominally four times lower than the voltage needed to deplete the
PN diode of similar thickness. This last scenario is shown in Figure 2.1(c)
where the minimum potential across the depletion region lies between the
two p+ electrodes.
The Silicon Drift Detector basically works on the side-ward depletion
principle described for a PIN diode in Figure 2.1. However, in case of the
Silicon drift detectors an additional electric field is added parallel to the
16
2.2. SDD Working principle
Figure 2.1: (a) Depletion of a PIN diode. (b) Partial and (c)full side-ward depletion in a
modified PIN diode.
Figure 2.2: SDD working principle: e− /hole pairs generated by ionizing radiation within
the depletion region are separated by the electric field.
surface of the wafer so that the drifting electrons can be forced to move
towards the n + electrode. This is achieved by introducing two arrays of p +
electrodes on both sides of the wafer as shown in Figure 2.2 as compared
to single large p+ electrodes (Figure 2.1). These p+ electrode arrays are
suitably biased to create an additional potential gradient in the direction
of n+ electrode and toward the surface. A drawing of the potential energy
in the drifting region of the SDD device is shown in Figure 2.3(a) while
Figure 2.3(b) shows the same drawing of the potential energy close to the
n+ electrode. This field is basically for the electrons of the e− /hole pairs
17
Chapter 2. Silicon Drift Detectors
generated by the ionizing radiation as the holes are readily collected by the
p+ electrode arrays.
Figure 2.3: Diagrams showing (a) electron energy potential in the drift region of the SDD
and (b) in the region close to the anode where the potential valley is directed towards
the surface.
As the SDD has an array of p+ electrodes, these electrodes generate an
electrostatic shield which masks the presence of any charge carriers drifting
below them. Thereby, on the output n+ electrode no signal is observed
unless the electron cloud reaches it. On a macroscopic scale, we cannot
sense whether some ionization event has occurred within the detector till
the electrons generated in the process reach the output electrode. As a
consequence, the drift time of the electrons can also be used to measure one
of the coordinates of the radiation interaction while the collected charge
can allow measurement of the energy released by the incident ionizing
events [20]. One of the main advantage of a Silicon Drift Detector with
18
2.2. SDD Working principle
respect to a conventional PIN diode of same active area and thickness is its
very low value of the collection anode capacitance (∼100 fF). Furthermore
this output capacitance does not depend on the total active area of the device
as the size of the n+ electrode remains the same. The effect of output
electrode capacitance on the performance of SDD readout electronics will
be discussed later in this chapter.
Figure 2.4: SDD for X-ray spectroscopy: (a) schematic structure with the p+ back contact
and (b) electric potential energy diagram.
The SDD device shown in Figure 2.2 has some limitations for the detection of soft X-rays (energies below 5 keV). In the SDD device, the area
between p+ strips are generally covered with a thin layer of SiO2 close to
the surface which ends up trapping some positive charge over time. This
trapped positive charge within the oxide layer tends to bend the potential
distribution downward at the detector surface thus creating local energy
potential minima. As the soft X-rays and visible light are generally absorbed
within a few microns of the surface, most of the generated charge is lost in
19
Chapter 2. Silicon Drift Detectors
these energy potential minimas. This limits the use of this SDD design for
soft X-ray detection.
One relatively recent SDD device which has been optimized for X-ray
spectroscopy measurements in the soft X-ray range (below 5 keV) is shown
in Figure 2.4(a). It can be seen in this diagram that instead of having an array
of p + electrodes on both sides of the wafer, a very thin single p + electrode
has been introduced on one side of the wafer which acts as a light entrance
window [24] without any oxide layers. The thickness of this Back Electrode
is reduced to increase the low energy X-ray absorption of the device. In
addition the doping profiles in the SDD are also optimized to reduce charge
loss. Once a proper voltage is applied to the p+ back electrode, the drifting
fields are only generated by the p+ implant rings on the opposite side of
the detector. Similar to the SDD devices described so far, this device also
facilitates drifting of the electrons toward the n + collection anode as it can
be seen in Figure 2.4(b). The p+ implant rings in this SDD architecture can
be biased by only connecting the ring closest to the anode (called first ring
or ring 1) and the outermost ring (ring N). All the intermediate rings are
biased through a voltage partitioning circuitry between Ring 1 and Ring N.
The last SDD architecture shown in Figure 2.4 is the one which will be
considered for all further discussions from here onwards in this dissertation.
2.3 SDD performance parameters
2.3.1
Energy resolution relation
For both the X- and γ-ray spectroscopy, the main task for the detector and
consequent readout electronics is to estimate the energy distribution of the
incoming photon as accurately as possible. Thereby, the energy resolution
of the detection system (∆E) is a fundamental parameter that needs to be
minimized. In an ideal scenario, the energy distribution of an incident photon flux of fixed energy E0 should be a δ-like function. However, owing to
different statistical fluctuations that affect the measurement, there is a broadening of the ideal δ-like distribution. An important performance parameter
of the spectrometer to take this spread into account is known as the energy
resolution. This energy resolution can be measured in terms of full-width-athalf-maximum (FWHM) of the Gaussian fitting of the energy distribution
(FWHM=2.355 ×σ). The smaller the FWHM of the spectrometer, the better
is its capability to distinguish between small energy differences between
two incoming photon fluxes of nearly identical energies. Another important
parameter to represent the resolution of the detection system is to use the
ratio between FWHM and the incident photon energy (R=FWHM/E0 ).
20
2.3. SDD performance parameters
2.3.1.1
Direct conversion
The term Direct conversion means that the conversion of incident primary
radiation photon into equivalent e− /hole pairs takes place directly within
the body of the primary detector i.e. the SDD. This is normally the case for
detection of visible or soft to medium energy X-rays with the SDD. The main
factors affecting the resolution in a SDD-based X-ray spectroscopy system
employing direct conversion are the photo-generation statistics, which is a
property of the detector material, and the readout front-end electronic noise
associated with the SDD itself and the CSA:
2
2
∆E 2 = ∆Estatistics
+ ∆Eelectronics
(2.1)
For semiconductor detectors the variance of the number of charge-carriers
(σ ) is
√defined by a modified-Poisson distribution and has the expression
σ 2 = F × N , where N is the number of charge carriers and F is the Fano
factor [25] whose value is approximately 0.115 for silicon. The first term of
(2.1) becomes:
2
p
√
F W HMstatistics = 2.355 F.N = 2.355 F..E0
(2.2)
Where E0 is the photon energy and is the mean energy required to
extract an electron-hole pair, that in silicon is about 3.62 eV. Considering
the Mn-Kα energy line, a typical reference in X-ray spectroscopy and which
occurs at about 5.9 keV, the energy resolution is lower bounded at 119 eV,
the so-called the Fano limit. The electronic noise of the detection system is
instead measured in terms of ENC (often normalized by the unit charge to
have it expressed in e− rms), therefore the second term of (2.1) becomes:
F W HMelectronics = 2.355 × × EN C
2.3.1.2
(2.3)
Indirect conversion
The term Indirect conversion means that the conversion of incident primary
radiation photon does not take place within the detector but instead an
intermediate stage is introduced to first convert the primary photon into a
large number of secondary photons of much smaller individual energies and
then these secondaries are converted by the detector into equivalent charge.
In case of SDD, this technique is generally used for detection of incident
high energy X-rays (above 100 keV) or γ-rays. This conversion technique
21
Chapter 2. Silicon Drift Detectors
and the intermediate conversion stage (scintillating crystals) are explained
in more detail in chapter 4 and 5.
For γ-ray spectroscopy systems employing crystal scintillators, the energy resolution of the overall detection chain (∆E/E or R) is dictated by four
main contributions:
q
2
2
2
2
+ Rcol
+ Rst
+ REN
R = Rint
C
(2.4)
The terms Rint and Rcol refer respectively to the crystal intrinsic resolution and to the scintillator collection efficiency. The Rcol is nominally
negligible as compared to other terms. Rst accounts for the statistical spread
of the light generation in scintillators and of the photons-to-electrons conversion in the detector and REN C is the electronic noise contribution of
both the detector and the front-end. This latter contribution is also typically
negligible for detectors with internal multiplication as it is divided by the
multiplication factor. This is the reason why PMTs devices which have a
multiplication of ∼106 , provide such good energy resolution performances
when coupled to scintillators. For a given intrinsic resolution, which is a
property of the scintillator [26], achieving good spectroscopic performance
is mostly a matter of choosing a high quantum efficiency detectors and a
low-noise readout electronics to minimize Rst and REN C respectively.
Here, assuming now that the photon generation statistics inside the scintillator follows a Poisson distribution and that the collection efficiency term
Rcol is negligible, the energy resolution of a detector with no multiplication
can be written as [27]:
s
2
∆E
2.355σ
∆E
1
(EN CT OT )2
=
= 2.355
+
+
E
Epeak
E int Ne (1 − BD) (Ne )2 (1 − BD)2
(2.5)
where (∆E/E)int is the scintillator intrinsic resolution, BD is a parameter that takes into account the ballistic deficit effect, EN CT OT is the
total noise of the detector and finallyN e is the number of generated charge
carriers. The latter is equal to:
Ne = ηc ηq Eγ Y
(2.6)
With ηc representing the crystal collection efficiency, ηq the detector
quantum efficiency averaged over the whole scintillator emission spectrum,
22
2.3. SDD performance parameters
Eγ the input photons energy and Y the scintillation yield of the crystal. It
is worth noting that given the chosen scintillator, the intrinsic resolution
(∆E/E)int is a fixed contribution. The term Ne , worsened by the ballistic deficit effect (1 − BD), accounts for the statistical spread due both
to the scintillation-photons generation and the photon-to-electron conversion inside the detector. It can be minimized by using bright scintillators,
high quantum efficiency detectors, by covering the scintillator with high
reflectivity materials and also by optimizing the optical coupling. Finally,
(EN CT OT )2 /[(Ne )2 (1 − BD)2 ] represents the statistical spread due to the
readout front-end electronic noise and can be minimized by accurate lownoise designs.
2.3.2
Quantum Efficiency
Figure 2.5: Measurements of QE for a Diode (circles), a test SDD (squares) and a
theoretical limit (line). Courtesy Fondazione Bruno Kessler
One important performance parameter of radiation detectors, in general,
is Quantum Efficiency which is the ratio of total number of e− /hole pairs
generated to the total number of incoming photons. This means that all the
incoming photons are not always stopped by the detector. The quantum
efficiency ηq varies with the wavelength of the incoming photon. Figure
2.5 shows the quantum efficiency of SDD and a PIN diode for different
wavelengths of the incident photons. It can be seen that there is very less
23
Chapter 2. Silicon Drift Detectors
difference between the SDD and the diode and furthermore they are both
very close to the theoretical limit.
Table 2.1 shows th Quantum efficiency of some common photo-detectors
used for reading scintillators for indirect detection of X- and γ-rays. Here,
APD is an Avalanche Photo Diode, which has a multiplication gain of around
103 . Silicon photomultiplier (SiPM), developed originally in 1997 [28], is an
emerging device with a lot of application in medical applications to readout
scintillators. SiPMs undergo a multiplication of 105 -106 which is similar to
PMTs and have a maximum Photon Detection Efficiency (PDE) of around
40%.
Table 2.1: Property summary of the most common scintillation photo-detectors.
Quantum Efficiency
Multiplication
Topology
PMT
35%
106
vacuum
PIN
> 85%
1
solid-state
APD
> 85%
103
solid-state
∗
SiPM
PDE = 40%
105 -107
solid-state
SDD
> 85%
1
solid-state
∗ The quantum efficiency for the SiPM is replaced by the Photon Detection Efficiency (PDE).
Although quantum efficiency ηq determines the efficiency of the detector
in stopping high energy photons in systems employing detect detection, it
plays a much more prominent role in γ-ray spectroscopy employing indirect
conversion as depicted in the energy resolution relations (2.5) and (2.6).
Here, the statistical as well as the ENC contribution of the energy resolution
depend on the number of e− /hole pairs collected at the SDD collection and
thereby use of a photo-detector with low quantum efficiency can result in a
degradation in energy resolution performance of the detector. The advantage
of a higher QE of SDDs as compared to other devices like Photo-Multiplier
Tube used for γ-ray spectroscopy will be discussed in chapter 4.
2.3.3
Drift time
Drift time refers to the time delay between the instant the charge carriers
are generated inside the detector till the time we observe the corresponding
current peak iD (t) at the output collection anode. This time interval represented by tdrif t normally varies based on the position of the interaction event
within the detector as for a given SDD the mobility of the charge carriers
is fixed at a given temperature. An example of the output electrode current
waveforms for different drift times can be seen in Figure 2.6. For an incident
photon that completely deposits its energy within the detector to produce a
24
2.3. SDD performance parameters
net charge Q, an increase in the drift time results in a lower peak amplitude
of iD (t) in order to maintain the total area under the curve equal to Q.
Figure 2.6: Example of output electrode current ( iD (t)) waveform variation for different
drift times.
Macroscopically speaking, the drift time ( tdrif t ) of an SDD depends on
the geometry of the SDD as a larger device would mean that the electrons
have to travel much further to reach the collection anode. Considering a
simple case of a circular SDD with radius L and for charge carriers generated
in a single point at a distance d from the collection anode (that means the
electrons packet has a δ-dirac spatial distribution in that point), the drift time
is given by:
tdrif t =
d
d
=
vd
µE
(2.7)
Where vd is the drifting velocity while µ and E represent the electron
mobility in the substrate and the radial electric field intensity respectively.
During the drift from the generation point to the anode, the charge carriers
experience a diffusion process which is responsible for widening their spatial
distribution. From the mathematical analysis of this effect described in [29],
the standard deviation of the spatial distribution σS after the charge packet
has traveled for a time equal
p to tdrif t (which means when it is in proximity
to the anode) is σS = 2Dtdrif t . Here D is the diffusion coefficient of
Silicon. If we assume that the charge is collected at a constant speed vd , the
25
Chapter 2. Silicon Drift Detectors
time distribution standard deviation σt , which is an indication of the charge
collection time will have the following expression:
√
2Dp
σS
tdrif t
σt =
=
vd
vd
(2.8)
Equation 2.8 provides us with mathematical relation for the behavior of
iD (t) curves shown in Figure 2.6. Here it can be seen that the time of arrival
of the charge carriers forms a Gaussian distribution with a spread σt around
the mean time tdrif t . The top part of Figure 2.7 further shows equipotential
lines in a cross section from the center of an SDD similar to one shown in
Figure 2.4(a). Here it can be seen that for events that take place close to the
Ring N (last ring) in the SDD, the path to be taken by the electrons is very
large which can result in a very large tdrif t and σt especially for SDDs with
a much larger active area. These tdrif t estimates are shown on the bottom
part of Figure 2.7 which shows that for an SDD with a radius of 4 mm, the
drift time is already around 1 µs.
This drift time can be a serious limitation once an SDD needs to be used
for applications where the input event count rate is very high or the size of
the SDD is very large. One possible way to solve this issue of drift time is
by cooling the detector down to reduce increase the mobility µ of the charge
carriers.
2.3.4
Ballistic Deficit
The Ballistic deficit is an unwanted effect arising from the tdrif t effect that
tends to effect both the X as well as γ-ray detection systems. This effect
is largely correlated with the readout electronics and the processing of the
detector output signal. To explain this Ballistic Deficit effect we can consider
a detector readout electronics employing a shaping amplifier to reshape the
electrical signal corresponding to charge collection at detector output into a
Gaussian-like shape with the total area of the pulse being proportional to the
collected charge Q. Now for an idealδ-like signal provided by the detector,
Figure 2.8 depicts the output of the shaping filter which is the semi-Gaussian
pulse shown in blue. However, in reality as the SDD output is not a δ-like
signal (due to finite drift time), the filter response attains a peak amplitude
which is lower than the ideal one as represent by the red semi-Gaussian
pulse shown in Figure 2.8. This reduction in the signal peak amplitude is
known as the Ballistic Deficit.
It is worth mentioning here that in case of both pulses the area under
the curve is still proportional to the net charge Q, however as most of the
26
2.3. SDD performance parameters
Figure 2.7: (Top): Equipotential lines in a cross section of the device from the center, on
the left, where the anode is placed (top-left) to the boundary of the device, on the right.
The larger separation in space of the equipotential lines close to the border of the device,
on the right, implies a lower electric field in these regions. (Bottom): Drift time vs.
injection point of the charge along the radius of the SDD. [30]
electronic readout systems rely on the amplitude of the semi-Gaussian pulse
to evaluate the charge Q, this effect can worsen the ENC contribution of the
energy resolution relation. Given a certain input photon energy, the spectrum
energy peak Epeak measured in electrons has the expression:
27
Chapter 2. Silicon Drift Detectors
Figure 2.8: Example of filter output signals in case of ideal delta-like input (blue curve)
and real input signal from SDDs (red curve).
Epeak = Ne
max[y(t)]
max[h(t)]
(2.9)
Where h(t) is the filter impulse response once input current signal is an
ideal δ-like pulse. However, in case of a real detector output current signal
iD (t), the filter response changes to y(t) which is given by convolution of
iD (t) with h(t) i.e. (y(t) = iD (t) ∗ h(t)). It is clear from the example
presented in Figure 2.8, that (y(t) is lower than h(t) as the charge collection
time at the anode of the detector is not zero but a finite number. Thereby,
(2.9) can consequently be re-written as Epeak = Ne (1 − BD), which can
help us derive a relation of the BD factor:
BD =
max[h(t)] − max[y(t)]
max[h(t)]
=1−
max[y(t)]
max[h(t)]
(2.10)
This effect is also responsible for degrading the noise performance of the
detection system which can be approximated by the relation EN Creal =
EN Cideal /(1 − BD) . An important observation here is that the ballistic
deficit and the system noise performance follow opposite trends with the
filter peaking time. If the latter is increased, the ballistic deficit improves
(BD gets lower) but the noise worsens (ENC gets higher). This is because
28
2.3. SDD performance parameters
of the detector leakage current contribution, which is typically still relevant
at temperatures down around -20 ◦ C for most SDD technologies.
The ballistic deficit effect is more prominent in case of γ-ray detection.
In such cases the energy of the incident γ-ray is converted into a much larger
number of secondary low energy photons and depending upon the yield of
the scintillator Y , a flood of these secondaries enter the detector upon a
γ-ray event. In case of a very short scintillator decay time as compared to
the detector drift time, the secondary photons all enter the photo-detector
instantaneously over a broad SDD area. This results in a very large cloud of
charge carriers generated instantaneously inside the SDD. however, owing
to the position of generation, they take different times to reach the SDD
anode. This is shown in Figure 2.9(left) where simulation results show
regions of a 8×8 mm2 SDD surface corresponding to the time within which
charge carriers generated in those regions are collected. It can be seen here
that the edges of a square SDD take a very long time (>1.5 µs) to reach
the SDD anode. As the output current iD (t) is an integral of all of these
charge carriers over time, it attains the curve depicted in Figure 2.9(right).
Here, it can be seen that the peak of iD (t) always has a slow exponential tail.
This shape of iD (t) readout by the shaping amplifier results in a persistent
Ballistic deficit even for shaping amplifier peaking times around 1.5 µs as it
becomes comparable to the SDD output current pulse decay time.
Figure 2.9: (Left) Simulated drift time distribution and (right) anode signal composed as
result of charge collected in different zones (with different drift times) for an 8×8 mm2
square SDD. [31]
In addition, for scintillators with a light output decay time comparable
to the drift time of the detector, there is an additional penalty of mixing
29
Chapter 2. Silicon Drift Detectors
of piling up of charge carriers generated by incoming scintillation photons
(belonging to the same γ-ray interaction in the scintillator) at different time
instants. This further enhances the ballistic deficit effect resulting in a very
deteriorated performance of the overall detection system. A thorough study
on ballistic deficit effect for gamma-ray detection with SDDs is carried out
in [30].
Ballistic deficit also occurs in case of X-rays and become prominent
when the shaping filter processing times becomes comparable to the drift
time of the charge carriers. This effect is further explained in chapter 3 in
correspondence to SDD readout electronics.
2.4 SDD readout electronics
This section provides a very basic overview of different stages of the SDD
readout electronics which are needed to process the output anode current
pulse iD (t). These fundamental stages include the preamplifier, the shaping
filter amplifier and the ADC as it can be seen in Figure 2.10. Corresponding
to each of these analog signal processing stages, their output signals are also
represented. With the rapid advancement in Analog to Digital Converters
and digital signal processing, new solutions with blocks different from the
one shown in Figure 2.10 are also in use these days. In these new SDD
readout systems, the output of preamplifier is directly fed to a fast ADC
and the shaping filter is implemented in digital domain. Such readouts are
referred to as Digital Pulse processors (DPP). In this section we will only
introduce the solution involving analog filtering of the preamplifier output.
Figure 2.10: Basic SDD readout blocks depicting the Preamplifier, the Shaper amplifier,
the Peak stretcher and the ADC.
The first stage in the SDD readout deals with converting the peak of the
SDD output signal iD (t) into a proportional voltage by integrating it across
30
2.5. Electronics readout noise
the feedback capacitor of a Charge Sense Amplifier (CSA). CSA provides
the SDD output with an initial gain which makes the signal transmission
to next stage less susceptible to interference. Upon integration across the
CSA’s feedback capacitor, the output of the preamplifier becomes a step
corresponding to the input δ-like iD (t). The design of this preamplifier
stage is very important in determining the ENC performance of the readout
electronics. This factor will be discussed later on in this section.
The second stage in the SDD readout includes the shaping filter amplifier.
This stage converts the step signal into a semi-Gaussian pulse with the peak
amplitude proportional to the peak of iD (t). The time taken by the shaper
output to reach the peak is generally known as the shaper peaking time.
This peaking time is generally programmable and the energy resolution
performance of the detection system is greatly affected by the shape of this
pulse. The effect of choice of shaping filter on the system performance is
well explained in [32]. In this dissertation, all the shaping filters described
generate a semi-Gaussian output shape and have been implemented using
seven or nine poles in hardware. These shaping amplifiers will be further
discussed in chapter 3.
The shaper output is fed into a peak stretcher. This peak stretcher generally generates a digital signals to communicate to the ADC to begin
digitizing the peak amplitude information. This digital information is transferred to a computer for storage or processing. In case of only one SDD
unit the operation of the ADC and peak stretcher is very simple however
for multiple SDDs, normally a multiplexer is introduced to have only one
ADC for digitizing multiple peak stretcher outputs. Multiple SDDs readout
by a single ADC with the help of multiplexers will be explained further in
chapter 3.
2.5 Electronics readout noise
In this section we discuss the noise associated with the readout electronics
of a radiation detector specifically the one depicted in Figure 2.10. The main
task of the readout electronics is to measure with the highest achievable precision the amount of charge Q delivered by the detector as it is proportional
to the energy of the incident photon. This readout is affected by different
noise sources. The system’s noise performance is commonly measured in
terms of Equivalent Noise Charge (ENC), which is the charge delivered by
the detector at which the Signal-to-Noise Ratio (SNR) is unity.
The noise performance, referred in terms of ENC, is related to both the
detector and the front-end electronics. The electrical model of the analog
31
Chapter 2. Silicon Drift Detectors
Figure 2.11: Signal processing chain electrical-model with equivalent noise generators.
[17]
acquisition chain is shown in Figure 2.11. The detector is modeled as the
parallel of a generator delivering delta-like current pulses that carry the
charge Q and its depletion capacitance CD . For what concerns the preamplifier, CF and CG represent respectively its feedback and input capacitance
thus the output step amplitude is equal to Q/CF while the shaping filter is
represented with its transfer function T (s).
The SNR of the measurement is defined as the ratio between the signal
peak amplitude and the voltage noise root mean square, both referred to the
same point of the acquisition chain (i.e. the output of the shaper):
SN R =
max[vout (t)]
Q.max[vout,δ (t)]
=
hvnoise irms
hvnoise irms
(2.11)
where vout,δ (t) is the peak amplitude of the shaper output pulse when the
charge delivered by the detector is considered to be unitary. It follows that:
EN C =
max[vout,δ (t)]
hvnoise irms
(2.12)
All noise sources of the system can be modeled by the three inputreferred equivalent noise generators of Figure 2.11, whose magnitude is that
of a Power Spectral Density (PSD). They account for white voltage (Svw ),
current noise (Siw ) and flicker voltage noise (Svf ). Flicker current noise
is also present but usually negligible thus its mathematical analysis is not
performed here. The white voltage noise, also referred to as series noise, is
typically dominated by the preamplifier input transistor thermal noise:
Svw = a = α
2kT
2kT
=α
gm
CG ωT
32
(2.13)
2.6. Summary
here ωT and α are respectively the cut-off angular frequency and a
process-dependent constant whose value is about 2/3 for silicon FET. The
white current noise, or parallel noise, is due to the shot noise associated
with the leakage current of both the detector (ID ), the preamplifier input
gate transistor (IG ) and also to the current noise of any resistance connected
to the gate of the latter (IR ). Therefore the expression of the white noise
current PSD is:
Siw = b = q(ID + IG + IR ) = qIT OT
(2.14)
Finally, flicker noise is related to the charge trapping phenomena at the
oxide-semiconductor interface in the preamplifier input FET channel and its
PSD is equal to:
Svf = c = π
2kT |ωC | 1
Af
=α
|ω|
CG |ωT | |ω|
(2.15)
Where Af and ωC are the 1/f process parameter and the frequency at
which flicker and white voltage noise power spectral densities are equal.
According to the model developed in (2.12), the ENC of the system can be
expressed as [17]:
1
EN C 2 = (Cd + Cg )2 a A1 + (Cd + Cg )2 cA2 + bτ A3
τ
(2.16)
Here A1 , A2 and A3 are the so-called shaping factors, coefficients that
depend only on the filter output-pulse shape while τ is the characteristic
shaping time of the front-end which has also been explained in previous
sections. The latter can be defined arbitrarily, for instance, as the width or
the peaking time of the pulse, obviously having no impact on the ENC value,
provided the shaping factors are calculated accordingly.
As evident from the (2.16), the three terms respectively represent the series, parallel and flicker noise contributions to the ENC of the system. Figure
2.12 shows its typical trend with the shaping time of the filter, highlighting
the single contributions dependence from it.
2.6 Summary
This chapter introduces the working principle of Silicon drift detectors
alongside their evolution in design and concept from a simple PIN diode
33
Chapter 2. Silicon Drift Detectors
Figure 2.12: Typical trend of the system ENC as a function of the shaping time.
for the detection of incident photons. SDDs have a unique advantage in
terms of having a charge collection anode whose area and consequently
its capacitance is independent of the total area of the device. SDDs can
be used for both direct and indirect detection of X- and γ-ray photons
respectively and the energy resolution relation for both these topologies is
explained to understand the parameters of interest. These parameters include
quantum efficiency, drift time and ballistic deficit in particular which are
thoroughly explained. Different stages involved in the readout and frontend processing of the SDD output are also introduced. Furthermore, as the
readout electronics also introduces some noise factor in the energy resolution
relation, literature associated with this noise measured as the Equivalent
Noise Charge (ENC) is discussed in the last section of this chapter.
34
CHAPTER
3
SDD based X-ray spectrometry
3.1 Introduction
In last chapter, SDD device and its various parameters have been discussed.
In addition, SDD readout and its impact on the final performance of the
device have also been studied. In this chapter, the focus of the discussion is
shifted towards the utilization of SDDs and associated readout electronics
for X-ray spectroscopy. SDDs, because of their low readout anode capacitance and higher quantum efficiency (maximum around 85%) form the state
of the art for many X-ray detection applications. One of these applications
are in the field of X-ray Fluorescence (XRF) where the use of SDD-based
X-ray spectrometers help acquire XRF spectra at about 10 times higher
count rates than conventional Energy Dispersive Spectrometers (EDS). The
low electronic noise at high count rates make the SDDs suitable also for
X-ray spectroscopy experiments with synchrotron light, such as X-ray Fluorescence Holography (XFH) and Extended X-ray Absorption Fine Structure
(EXAFS) [33], [34].
The capability of the SDD devices to achieve high energy resolution at
temperature achievable by Peltier cooling; as compared to other detectors
like PIN diode, Si(Li), Superconducting Tunnel Junction (STJ) and High
35
Chapter 3. SDD based X-ray spectrometry
Purity Germanium (HpGe) detectors which require liquid nitrogen cooling;
allows compact and portable SDD spectrometers for analysis of cultural
heritage [35]. SDDs can also be used in radiology as detectors for X-ray
monochromatic beams, in which a single beam, composed of photons with
three different energies, target the patient. Owing to SDDs good noise
performance, they can be used to discriminate between these three different
energies.
Silicon Drift Detectors find applications also in the field of nuclear
physics, such as in the SIDDHARTA experiment. Siddharta (Silicon Drift
Detector for Hadronic Atom Research by Timing Application) is a Hadronic
physics experiment realized at the DAΦNE e− -e+ collider at the LNF (Laboratori Nazionali di Frascati, INFN, Rome) in 2009-2010, supported by the
European Community and involving several partners both in academia and
industry, including Politecnico di Milano. Following the successful path
of DEAR [36], [37], Siddharta exploits X-ray spectroscopy of the kaonic
atoms to determine the transition yields and the induced strong interaction
shift and width of the lowest experimentally accessible levels [38].
Figure 3.1: Diagram showing kaon knocking out and substituting an electron in Hdrogen
atom and resulting transitions of kaon to ground state.
Figure 3.1 shows how a Kaonic atom is generated in the Siddharta
experiment by knocking out the electron in the 1s shell of hydrogen atom.
As the kaon is more massive as compared to an electron, the ground state
energy level of the kaon is much closer to the nucleus of the newly formed
kaonic atom as compared to the hydrogen atom. Hence the kaon in the newly
formed atom is in energy level n≈ 25. Once the Kaonic atom is formed,
the kaon looses energy by producing characteristic x-rays and de-excites to
36
3.1. Introduction
the ground state. As the kaon is very close to the nuclear proton in its 1s
ground state, the kaon has strong nuclear interaction with the proton. This
strong interaction on the 1s ground state of the electromagnetically bound
K-p atom leads to a hadronic shift and a hadronic broadening of the 1s
state which can be precisely measured by a spectroscopic analysis of the
characteristic X-rays of the transitions of the Kaon in low-lying states of
light kaonic atoms. Siddharta aims to precisely measure such characteristic
X-rays [39].
One of the targets in Siddharta project is to reject all events that are not
synchronous with the kaonic signal, that is, those which are not generated
directly by the kaons that entered the target. This can be done by placing
a crystal scintillator in front of the Kaon beam so that a flash of photons
is generated in the scintillator once a kaon enters the target region. These
photons are then amplified by a Photo-Multiplier Tube (PMT) generating
a timing trigger signal in coincidence with the entrance of these kaons.
A timing window of inspection of approximately 1 µs is opened up after
receiving this trigger signal [40]. The width of this timing window is
determined by the drift time of kaons between the instant they enter the
cavity till the instant they collide with a hydrogen atom. Any signals detected
by the SDD within this window are presumably due to the useful signal (the
component of the background remains synchronous), while those photons
which fall outside of these time intervals are surely due to the background
and are discarded.
Figure 3.2: Strategy to reject asynchronous background events. [40]
To further improve this rejection, a scintillator is also placed on the
37
Chapter 3. SDD based X-ray spectrometry
opposite end in the path of the anti-kaons which are generated at the same
time as the kaon. This second scintillator provides another timing trigger
signal improving the timing resolution. These two triggers generate a triple
co-incidence window which is depicted in Figure 3.2. In order to properly
take advantage of this window, the SDD drift time should be much less as
compared to the time window duration (1 µs). As the readout electronics
employing shaping amplifiers has an intrinsic latency where a time difference
exists between the detector and shaper output peak due to causality, a fast
digital signal marking the moment of arrival of X-ray photon with a timing
accuracy much less than a microsecond can be used as a time stamp for
marking them.
Figure 3.3: A section of SIDDHARTA-1 detection ring of the machine (left) and single
detection module made of 3 SDDs each (right).
Contrary to the use of CCD detectors in DEAR, SIDDHARTA achieves
a better precision in the kaonic hydrogen detection by means of SDDbased detection modules, which facilitate the rejection of the asynchronous
background of DAΦNE, responsible for degrading the detection precision.
This improvement is mainly due to the high speed of SDDs compared to
CCDs, that guarantees real-time signal triggers and therefore allows the
implementation of a background rejection algorithm based on coincidence
time windows with the kaonic triggers. The detection module designed for
the first SIDDHARTA experiment (SIDDHARTA-1), is shown in Figure 3.3
along with a section of the detection ring which comprises of a total of 48
detectors. The results obtained with Siddharta-1 experiment can be found
38
3.2. Siddharta Upgrade
in [38].
In this chapter, we discuss the X-ray application of SDD device and its
readout electronics in the context of an upgrade of the Siddharta experiment
(Siddharta-2). In this context, the changes made in the Siddhata experiment
including detector upgrade, readout electronics and experimental setups
to evaluate preliminary results with the detector. In addition experimental
results pertaining to soft X-ray characterization of the detector are also
discussed. In the last part of this chapter, a brief overview of another project
(ARDESIA) for X-ray fluorescence applications is provided to complete the
X-ray related part of this dissertation.
3.2 Siddharta Upgrade
In the previous version of Siddharta experiment (Siddharta-1), the SDD
devices had been designed and manufactured by the MPI-HLL and the
readout electronics was based on a JFET integrated in the detector substrate.
The detectors were arranged in arrays of three units each with an active area
of 1 cm2 for a global area of 144 cm2 (48 arrays) as shown in Figure 3.3.
This chapter deals with an upgrade of the experimental set-up for a newer
series of experiments.
Figure 3.4: Anode side view of monolithic array of eight 64 mm 2 SDD units designed for
Siddharta-2 can be seen arranged in a 2×4 format with a total active area of 512 mm2 .
A zoom of the central anode region of the SDD shows the presence of anode and Ring 1
pads and absence of any integrated charge preamplifier.
This second experiment (SIDDHARTA-2) is planned to be performed
between 2016 and 2017 at the DA ΦNE and at the JPARK collider in order
39
Chapter 3. SDD based X-ray spectrometry
to overcome some of the intrinsic limitations of the first one, such as those
related to the use of SDDs with internal JFET. This includes the backgroundinduced JFET latch-up of the device which did not permit to run the machine
during injections. Also, the relatively high working temperature of JFETbased SDDs (typically above 120-130 K) as compared to solutions like
SDDs readout by CMOS preamplifiers (operational even below 50 K), does
not help in the real-time trigger generation owing to the high drift-time of
electrons. Thereby, the old detection modules based on integrated JFET
needed to be replaced by new SDD arrays with CMOS preamplifier in the
upgrade of the experiment.
The new detector of Siddharta-2 comprises of an array of eight squareshaped SDD units 64 mm2 of 450 µm thickness. These SDD elements
have been fabricated by Fondazione Bruno Kessler (FBK) [41], with an
average leakage current density of about 200 pA/cm2 and arranged in a 2×4
arrangement, as shown in Figure 3.4. The total active area of the monolithic
array of eight 64 mm2 SDD units is 512 mm2 . A zoom of the central anode
region of the SDD shows the presence of anode and Ring 1 pads and the
absence of any integrated charge preamplifier. The left portion of Figure
3.4 depicts two pads instead of one which are marked Ring 1. Both of these
pads are connected to the same Ring 1 and only one of these needs to be
bonded for SDD operation.
Figure 3.5: (a) The ceramic board of Siddharta-2 module can be seen with holes to
facilitated bonding of the SDD units and placement of charge pre-amplifiers. (b) Back
side view of the 2×4 SDD array.
40
3.2. Siddharta Upgrade
Siddharta-2 detector array is mounted on a ceramic carrier made of
Alunit using a thermally conductive bi-adhesive to facilitate cooling as it
can be seen in Figure 3.5. This ceramic carrier has some holes of 2.4 mm
diameter above the center of each SDD element. This allows the placement
of the charge preamplifiers in close proximity to the SDD readout anode
to minimize the capacitance at the readout anode. Also the SDD units are
provided Ring 1 and Ring N (high voltage) biasing through these openings
in the middle and on the side of the ceramic board respectively. A single
channel monolithic CMOS based preamplifier (CUBE) is utilized for the
readout of each individual channel (not shown in Figure 3.5) [42]. The
performance of CUBE in the scope of Siddharta-2 will be discussed later on
in this chapter.
Figure 3.6: SDD-based detection rings designed for the DAΦNE (left) and J-PARC (right)
colliders.
Both the complete detection rings intended for DAΦNE and JPARK
colliders, pictured in Figure 3.6, comprise 48 of these modules, resulting in
a total of 384 single SDD units. For the readout of every sixteen of these
SDD channels (Two SDD arrays), SFERA (SDDs Front-End Readout ASIC)
is utilized . SFERA (developed in Politecnico di Milano [43, 44]) is a new
multichannel ASIC suitable for both X- and γ-ray detection purposes. The
performance of SFERA in the scope of Siddharta-2 will be discussed later
on in this chapter.
41
Chapter 3. SDD based X-ray spectrometry
3.3 Readout electronics
3.3.1
CUBE charge preamplifier
As already mentioned in Section 3.2, there is a constant need to improve the
spectroscopic performance of the X-ray detectors. Apart from the improvements in the detector itself, there has been a search to look for alternative
solutions to JFET-based charge preamplifier that has been the preamplifier
used in Siddharta-1 in 2009-2010. Given the quick growth the microelectronics market encountered in the last decade, many efforts have therefore been
oriented to explore the feasibility of CMOS implementations as external
charge preamplifiers. This has lead to the development of monolithic CMOS
integrated circuits showing superior performance, both in terms of noise and
bandwidth as compared to the JFET-based counterparts.
As the general trend in most applications is to increase the count rate in
order to both reduce the measurement time and to increase the accuracy due
to the higher statistics, the system noise performance at short processing
times are a major concern. State-of-the-art spectroscopic performance at
high-speed have been achieved with a CMOS Charge Sensitive Amplifier
named CUBE in [42, 45]. The proposed circuit has been developed at
Politecnico di Milano and is intended to be wire-bonded to the SDD anode,
as shown in the block diagram of Figure 3.7.
Figure 3.7: SDD readout by the CUBE charge preamplifier.
The higher anode capacitance due to the wire-bond connection’s parasitic capacitance is compensated by the high trans-conductance of CUBE
input p-MOS compared to JFET preamplifiers. In order to maintain the
same trans-conductance value, the CMOS process scaling is performed
42
3.3. Readout electronics
to reduce transistor dimensions and thereby gate capacitance. However,
a well-engineered anode-to-preamplifier connection is anyway required
to minimize the overall capacitance. This is why the CUBE is typically
mounted in close proximity to the SDD anode and therefore it is cooled
down to the detector operating temperature, leading to compact detection
modules. An example of such assembly can be seen in Figure 3.8. The
ceramic carrier of Siddharta-2 also utilizes the same principle as it can be
seen in Figure 3.5.
Figure 3.8: Example of detection module characterization setup made of a single SDD unit
and a CUBE charge preamplifier.
During the operation of the CUBE preamplifier, the SDD device signal
(constant leakage current and random signal spikes) is integrated across
the feedback capacitor of the preamplifier till a reset pulse is applied. Due
to this integration, at the output of the preamplifier (VOU T ), one can see a
ramp corresponding to the integration of the leakage current and a steps
corresponding to the integration of the δ-like charge spike. The amplitude
of the step height is proportional to the charge spike amplitudes. For proper
operation of the device, CUBE preamplifier operated in pulsed-reset regime
which means that a digital reset pulse Vrd eliminates the charge integrated
across the feedback capacitor CF and VOU T drops to zero as it can be seen in
Figure 3.9. The same principle is also used for JFET-based preamplifiers,
however, CUBE employs a physical capacitor of about 25 fF in feedback
as compared to JFET which utilizes a parasitic feedback capacitance. The
pulsed reset operation can be seen in Figure 3.9.
To briefly provide some idea of the spectroscopic performances with
CUBE, results obtained with a single 450 µm thick circular SDD (10 mm 2
active area) can be considered. This circular SDD belongs to the class of
43
Chapter 3. SDD based X-ray spectrometry
Figure 3.9: Charge preamplifier output voltage behavior and the digital pulsed-reset
signal.
SDDs manufactured by FBK with an average of 2 nA/cm 2 leakage current
at room temperature. Utilizing a commercial semi-Gaussian analog shaper
(Tennelec Tc244) a FWHM of about 123 eV (ENC of 3.7 e− rms) and 126.4
eV (ENC of 5 e− rms) has been achieved with shaper peaking times of 2 and
0.5 µs respectively. These results have been achieved for 55 Fe Mn-Kα line
at a temperature of -40 ◦ C [46].
It is worth mentioning that CUBE performance are even better by processing its signals with a digital pulse processor (DPP), because of the shorter
shaping times compared to the analog solutions, that allow to achieve higher
count rates. By way of example, an energy resolution of 156 eV has been
obtained for the same operating conditions described above, with an input
photons rate of 800 kcps and using a XIA trapezoidal DPP with 100 ns
peaking time [42]. An output count rate of 490 kcps has been reported,
resulting in a 39% dead time. Short processing times represent a benefit
also in reducing the detector leakage current noise contribution, thus making CUBE particularly suitable not only for high-throughput applications
but also in case of high-leakage SDDs, such as detector with large area or
operated at warmer temperatures.
3.3.2
Readout ASIC
The results presented in the previous subsection corresponding to the CUBE
preamplifier readout by commercial semi-Gaussian analog shaper (Tennelec
TC244) and the DPP showing state of the art performance with the SDD device. However, these readout methodologies can only be utilized effectively
for a limited number of SDD channels simultaneously and for a very large
number of SDD elements, this approach is no longer a smart choice. This
holds true for many applications employing a large number of SDDs with
44
3.3. Readout electronics
CUBE preamplifiers for X- and γ-ray spectroscopy/imaging applications
including Siddharta. One of the reasons is that the complexity of the system
increases drastically with an increase in the number of detector channels. If
a bulky rack-mounted external shaper or the powerful but fairly expensive
digital pulse processors are dedicated for every channel, the complexity and
cost of such solutions can be understood. For Siddharta with 384 individual
SDD channels, such solutions are also not practical.
Instead a common solution for such experiments is the use of compact
Application Specific Integrated Circuits (ASICs) which perform most of the
initial processing of the CUBE output signals. There are many ASIC chips
with analog channels tailor suited for different applications. In this section,
two such ASIC solutions are briefly discussed.
ESA - Astronomy application also benefits from SDD detection modules
based on monolithic SDD arrays of nine units each for the readout of
crystal scintillators forγ-ray spectroscopy and imaging applications. These
applications are described in more detail in Chapter 4 and Chapter 5 however
the readout ASIC is introduced here. This ESA chip has been designed to
read up to 27 analog channels and the multichannel architecture of the ASIC
is shown in Figure 3.10.
Each analog channel of this chip comprises of a cascade of semi-Gaussian
shaper amplifiers, a Baseline Holder, a peak stretcher and corresponding
peak stretcher logic. The output of all these 27 peak stretchers are fed to a
27:1 multiplexer so that only one ADC can be used to convert the analog
information into digital format for later data processing stages. The output
multiplexer is driven by an internal digital logic section, which performs
a "global trigger" operation implemented in an older chip designed for
similar γ-ray application known as the HICAM chip [47]. In ESA chip,
once a trigger is received on any of the analog channels suggesting that
this particular channels has a valid event, a global trigger is generated.
Upon receiving this global trigger, all peak stretchers are activated and the
signal on all the analog channels are readout one by one through the output
multiplexer. The concept behind such readout operation is the intended
use of such chips for γ-ray detection employing a monolithic scintillation
crystal. With a scintillator, each γ-ray event generates scintillation light
which spreads across multiple photo-detectors. In order to evaluate the
energy of the incoming gamma-ray, the signal received by all these channels,
needs to be summed up as it is proportional to the energy of the incident γ-ray
photon. Thereby, all analog channels must be readout for every event. This
readout strategy will here on be referred to as the "polling gamma" readout.
This readout can also, in principle, be used for X-ray application but it is not
45
Chapter 3. SDD based X-ray spectrometry
an optimal readout strategy especially for high count rate applications. More
strategies will be discussed later for the subsequent SFERA chip (developed
in Politecnico di Milano [43, 44]) which is to be used for Siddharta-2.
Figure 3.10: Simplified Model of ASIC Block Diagram for ESA project.
The shaping filter in the ESA chip contains a 7th order shaping filter
which converts the minute signal steps on leakage current ramps of Figure
3.9 into Gaussian-like pulses with their peak amplitudes proportional to the
charge collected by the preamplifier (heights of signal steps). The Shaper is
made up of a cascade of complex conjugate poles, implemented using analog
components to get the desired response. As the CUBE output depicted in
Figure 3.9 is a ramp instead of a fixed voltage level, the Baseline Holder is
utilized to ensure a fixed baseline at the shaper output.
The Shaping Amplifier has peaking times that can be programmed among
2, 3, 4, and 6 µs while three different gain settings are available. Low-noise
bias current and voltage references are generated and programmed on-chip
by the integrated DACs. Given the 20 kcps expected input photon-rate specification, the MUX operational frequency is set to 2.5, 5 or 10 MHz without
introducing any considerable dead-time penalties in the measurements. The
chip also provides external signals to communicate with the DAQ to facilitate sequential readout of the internal multiplexer. Results pertaining
to performance of this chip for gamma-ray spectroscopy and imaging are
discussed in more detail in Chapter 4 and Chapter 5.
SFERA - is primarily designed for X-ray spectroscopy [43], specifically
as an upgrade of the SIDDHARTA-1 readout electronics [48], thus requiring
a digital data multiplexing logic able to derandomize detected events, thus
exploiting a sparse readout protocol, and also a digital control interface compatible with the already existing SIDDHARTA-1 data acquisition hardware
46
3.3. Readout electronics
apparatus.
A chip dedicated to readout of photo-detectors for X-ray applications
significantly differs from one intended for readout of Monolithic crystal
scintillators for γ-ray applications like the ESA chip. X-ray readout frontends require sparsification of events, thus only those channels that detect
an event are multiplexed together with their digital address. Furthermore,
for high throughput X-ray applications, an asynchronous, high-frequency
sequential multiplexing is more preferable. Other important differences can
be found in the choice of shaping amplifier peaking times and gains. This
is because of the different energy ranges to be accommodated and because
of the crystal scintillator which pushes the electronics to exploit quite long
processing times to minimize the ballistic deficit effect which has already
been discussed in Chapter 2.
Figure 3.11: SFERA simplified block diagram and complete acquisition chain. [49]
In SFERA, each channel is characterized by a 9th order semi-Gaussian
complex-conjugate poles filter with selectable peaking times (0.5, 1, 2, 3,
4 and 6 µs) and gains, a fast channel (fixed 200 ns peaking time) used for
pile-up rejection, a baseline holder circuit and a peak detector. A block
diagram representation of the SFERA chip can be seen in Figure 3.11. The
outputs of the channels are connected to an analog multiplexer that can work
with different modalities (sparse or polling) according to the application.
For Siddharta-2 application, SFERA is coupled to a data acquisition system
composed by National Instruments hardware, in particular a NI-7962R
FlexRIo FPGA module. This module manages all the digital signals and
clocks required by the chip. However, SFERA also has a built-in ADC
module which can directly provide digitized signals at the output of the
47
Chapter 3. SDD based X-ray spectrometry
chip. As the digital signals are more robust as compared to analog signals,
this integrated ADC can be very useful for many applications requiring
robustness against electromagnetic interferences.
Figure 3.12: Fast and main SA output semi-Gaussian pulse at 0.2, 0.5, 2, 3, 4, and 6 µs
peaking time respectively.
Figure 3.12 shows the superposition at the oscilloscope of the output of
the shaper amplifier with different peaking times and with the fast channel.
The shortest shaping time of 200 ns shown in Figure 3.12, corresponds to
a fast shaper which is used for Pile Up Rejection (PUR). The PUR logic
is designed to discard two events that are too close to each other in time,
thereby changing each others’ pulse amplitudes. If the time difference
between two peaks is less than the FWHM of the shaper pulse while the first
peak has been properly stretched, only the second peak is rejected as it gets
corrupted because of the tail of the first peak. Finally, both the peaks are
processed in case that the time delay (td ) between them is much larger than
the FWHM of the shaper pulse. This can be seen in Figure 3.13 for peaking
time of 500 ns.
Figure 3.13: Pile-up rejection cases for the 500 ns peaking time: both pulses are discarded
(a), only the first is processed (b) and both of them are acquired (c).
This PUR is specifically useful for high count rate applications. The
SFERA chip also possesses the "Polling gamma" multiplexing modality
48
3.4. Experimental characterization of single SDD unit
allowing it to be used for readout of SDDs arrays coupled to monolithic
scintillators.
3.4 Experimental characterization of single SDD unit
This section is aimed at the evaluation of the performance of SDD photodetector, CUBE preamplifier and front-end electronics solutions for X-ray
spectroscopy. Measurement results pertaining to the X-ray spectra acquired
with 55 Fe Mn-Kα line at different temperatures and peaking times provide
an overview of the detection system’s performance. CUBE preamplifier is
readout with Tennelec TC244 (commercial semi-Gaussian analog shaper)
as well as SFERA readout ASIC (developed for Siddharta-2 project) to
compare the two readout systems.
3.4.1
Characterization at room temperature
With the recent advancements in SDD technology, low leakage SDD devices are now available with a leakage current density Jleakage of average
200 pA/cm2 at room temperature [41]. This results in very good X-ray
spectroscopic performance of the SDDs at temperatures close to the room
temperature as the parallel noise component of the electronic noise is greatly
reduced due to much lower detector leakage current. As the SDD leakage
current Ileakage = Jleakage × Area is also dependent on the area of the detector, this effect can be capitalized primarily with SDD devices having smaller
active area. Here, we report the results obtained with a 10 mm2 circular SDD
characterized by a Jleakage of ∼120 pA/cm2 . The trend in energy resolution
FWHM, measured in eV, is shown on the left side of Figure 3.14 for SDD
temperature of 10 and 20 ◦ C. For these measurements a commercially available Tennelac TC244 shaping amplifier and CUBE preamplifier, described
in subsection 3.3.1, has been utilized for SDD readout.
It can be seen in Figure 3.14 that we are still limited by parallel component of the ENC noise as the series noise and the best result is at the shortest
shaping time of 0.25 µs at both temperatures. Still an energy resolutions of
around 140 eV and 136 eV FWHM have been measured at temperatures of
20 and 10 ◦ C respectively. At 10 ◦ C, it can be seen that around 0.25 µs the
FWHM curve is flattening depicting that the parallel noise is low enough at
this shaping time. On the other hand, at 20 ◦ C, the FWHM still has some
slope depicting a major contribution of detector parallel noise contribution.
Hence at room temperature it is beneficial to use small SDDs with shortest
possible peaking times for best achievable performance.
49
Chapter 3. SDD based X-ray spectrometry
Figure 3.14: (Left)Energy resolution (FWHM) at Mn-Kα energy line achieved with a 10
mm2 SDD at temperature of 10 and 20 ◦ C. (Right) 55 Fe spectrum for a shaping time of
0.25 µs and temperature of 20 ◦ C.
3.4.2
Characterization with Peltier cooling
X-ray spectroscopy tests are initiated with a circular single SDD unit of 450
µm thickness and 10 mm2 active area. This SDD unit has been fabricated
by FBK. At room temperature, this SDD has a leakage current around 25
pA/cm2 and is cooled down to -35 ◦ C to -40 ◦ C to further reduce this leakage
current parameter. This circular SDD which has an extremely low leakage
current needs to be compared to the more conservative estimate of SDD
arrays developed for Siddharta-2 upgrade. Although Siddharta-2 will utilize
SDD arrays with a higher average leakage current (200 pA/cm2 leakage
current at room temperature [41]) and larger active area of individual SDD
units (64 mm2 ), the Siddharta-2 SDDs will be cooled down to cryogenic
temperatures reducing most disadvantages of larger area and higher leakage
current like ENC and drift time. Hence, utilizing an SDD array of smaller
area and leakage current at a relatively higher temperature of -40 ◦ C provides
a close enough equivalence with the Siddharta-2 array and serves as a good
starting point for characterization of the remaining readout electronics like
the CUBE preamplifiers and the readout ASIC. A block diagram depicting
the experimental setup used for these preliminary tests is shown in Figure
3.15.
Figure 3.15 shows that the SDD unit is mounted on a ceramic carrier and
is then placed on top of a copper block. The ceramic carrier is used instead
50
3.4. Experimental characterization of single SDD unit
Figure 3.15: Experimental setup for single SDD unit.
of FR4 board owing to its good thermal conductivity (180 Wm−1 K−1 ). The
detector is cooled down to a temperature of -40 ◦ C by fixing the ceramic
carrier and copper block to the cold surface of a Peltier thermoelectic module.
Water is circulated through a liquid heat exchanger placed on the hot surface
of the Peltier module to remove excess heat generated by it. In order to avoid
condensation of humidity on the detector surface, the entire setup is enclosed
in a sealed box and dry nitrogen is pumped into this box. A humidity sensor
is used to measure the humidity content of the box. A small hole is drilled
in the top lid of the box above the SDD to irradiate the SDD element with
55
Fe source. This hole is covered with a thin layer of dark adhesive tape
to prevent any visible light from entering the box. Only X-rays are able to
penetrate this layer.
Figure 3.16: Experimental set-up test PCBs arrangement (left) and detail of the chip
carrier hosting the CQZ package in which the IC is wire-bonded (right). [43]
51
Chapter 3. SDD based X-ray spectrometry
Once the setup has been cooled down between -35 and -40 ◦ C, both
Tennelec TC244 and SFERA ASIC are used one after the other to evaluate
the X-ray performance of the SDD + CUBE. In case of SFERA chip an
ASIC test board has been designed which can be seen in Figure 3.16. Here a
motherboard can be seen which hosts Chip carrier board containing SFERA
chip. The motherboard contains various electronic circuitry to provide
filtered power to the SFERA chip and the SDD units. The motherboards also
communicates with a National Instruments board which acts as a DAQ. The
SFERA chip contains various registers which need to be programmed i.e.
peaking times, CUBE reset time etc. These registers are also programmed by
the National instruments hardware including an NI-7962R FlexRIo FPGA
module. More details about the DAQ, ASIC programming and multiplexing
techniques can be found in [43].
Figure 3.17: Energy spectrum of a 55 Fe source measured with a round-shaped 10 mm2 area
single SDD at -35 ◦ C and 4 µs peaking time. A signal amplification of 4 is interposed
between CUBE and SFERA.
The SFERA chip carrier board can be seen on the right side of Figure
3.16. This board has been designed to readout two siddharta-2 SDD modules,
however, for preliminary tests a second connector has been placed. This
connector is compatible with the ESA SDD module which contains 9 SDD
elements. For tests with a single SDD element, a Lemo connector is used to
directly provide preamplifier signal to the SFERA chip. In Figure 3.16, The
position of the connector is marked by solder pads on the top left. For single
SDD, the CUBE pulsed reset is provided by a dedicated auxiliary PCB from
XGLab S.R.L. [50], responsible also for generating both preamplifier and
detector voltage references and bias decoupling, thus leaving for SFERA or
TENNELEC external shaper the sole task of shaping the signals.
Figure 3.17 presents the 55 Fe energy spectrum measured at 4 µs shaping
52
3.4. Experimental characterization of single SDD unit
Figure 3.18: SFERA energy resolution for all the implemented peaking times compared with
the commercial shaping amplifier Tennelec TC 244 performance. A signal amplification
of four is interposed between CUBE and SFERA.
Figure 3.19: SFERA energy resolution for all the implemented peaking times and compared
with the external shaper Tennelec TC 244 performance. Direct connection between
CUBE and SFERA with no amplification in between.
time, showing an energy resolution of 122.1 eV FWHM on the Mn-Kα
emission line. This is equivalent to an ENC of 3.2 e− rms, which is the
best ever reported in literature so far with a silicon drift detector [49]. For
noise characterization at different peaking times, the curves obtained with
the Tennelec TC 244 commercial Shaping amplifier and SFERA are shown
53
Chapter 3. SDD based X-ray spectrometry
in Figure 3.18. An energy resolution of 130.3 eV FWHM on the Mn-Kα
line (ENC of 6.2 e− rms) has been measured at 500 ns of SFERA peaking
time. The slightly better performance of the Tennelec SA at short shaping
times (below 2 µs in this case) are due to the semi-Gaussian 7th order filter
response, which indeed exhibits a better noise filtering behavior at short
peaking times. In all the results discussed so far, the dedicated auxiliary
PCB from XGLab S.R.L. amplifies CUBE signals by a factor 4 by means of
an analog output stage. However, it is also possible to read the CUBE signal
prior to such amplification and X-ray spectroscopy results with no gain of
the CUBE preamplifier are shown in Figure 3.19.
3.4.3
Characterization at cryogenic temperatures
Square shaped single SDD unit of 8×8 mm2 active area has also been cooled
down to temperatures as low as 50 K to evaluate its X-ray spectroscopic
performance as a function of SDD temperature and shaping times. The SDD
is placed in a vacuum chamber to achieve such low temperature. The SDD
element is glued to a ceramic board which is attached to a copper support
block as shown in Figure 3.20. This copper block is further fixed on the
cold finger with screws. For these measurements Tennelac shaping amplifier
TC224 is utilized.
Figure 3.20: Block diagram depicting a 8×8 mm2 SDD attached to a cold finger. In
vacuum chamber, the SDD had successfully been cooled down to 50 K with such a setup.
X-ray spectroscopy performance with a square shaped 8×8 mm2 SDD
with a leakage current of 2 nA/cm2 at room temperature can be seen in
Figure 3.21. The CUBE preamplifier used in these measurements is similar
54
3.4. Experimental characterization of single SDD unit
to the one used for Siddharta project. Here measurements are performed
at temperatures ranging from 50 to 240 K and are reported as a function of
the shaping time. The slight worsening in the energy resolution at higher
temperatures is due to the higher leakage current of the used SDD.
Figure 3.21: (Top)Energy resolutions achieved with CUBE coupled to an 8×8 mm2 squareshaped SDD at different filter shaping times and temperatures. (Bottom) Energy resolution of the 64 mm2 SDD at the Mn-Kα line at 50 K with shaping time of 2 µs.
The best result obtained with the TC 244 is 124.7 eV FWHM at 2 µs
shaping time (see Figure 3.21) which is similar to the best result obtained
with TC244 in the last section with the ultra low leakage 10 mm2 round SDD
cooled down to -40 ◦ C. however an important observation here is that with
the SFERA readout ASIC utilized with the round SDD had resulted in an
55
Chapter 3. SDD based X-ray spectrometry
energy resolution around 2 to 3 eV lower than the Tennelec shaper. Although
experiments have not been performed with 64 mm2 SDD readout by SFERA
at cryogenic temperatures, X-ray spectroscopy performance similar to the
one reported in last section can be expected.
All the SDD elements developed for Siddharta upgrade have been designed to have a thin light entrance window to facilitate detection of soft
X-rays. In order to evaluate the performance of this thin light entrance
window, X-ray fluorescence measurements have been performed with an
experimental setup and SDD similar to the ones described in the first part
of this subsection at ≈ 150 K. In order to generate characteristic X-rays, a
test sample composed of different elements, including light elements like
Fluorine, Aluminum and Carbon, has been irradiated with an X-ray tube
(Mini-X by Amptek with Rhodium target). The spectrum of the X-ray emitted by fluorescence have been acquired with TC 244. The spectrum acquired
can be seen in Figure 3.22 and shows many distinct characteristic lines for
very low energies like Fluorine and Carbon as well validating the thin light
entrance window’s operation.
Figure 3.22: Low energy X-ray lines measured with a 8×8 mm2 detector. L and K lines of
various elements including Fluorine and Aluminum are indicated. This measurement
has been obtained at a temperature of 150 K. [49]
56
3.5. Experimental characterization of SDD array
3.5 Experimental characterization of SDD array
In this section, we perform X-ray spectroscopy with an SDD array of 3 ×3
individual SDD units, developed originally for γ-ray spectroscopy for an
ESA sponsored project. The SDD array is readout with SFERA chip as
well as the readout ASIC developed for ESA γ-ray spectroscopy. It is worth
noting that although X- and γ-ray applications are very different, X-ray
spectroscopy can in principle be used to calibrate the SDD arrays and to
evaluate their noise performance prior to γ-ray measurements as described
in detail in Chapter 4.
Figure 3.23: Back (a) and front view (b) of the 3×3 SDD matrix hosted on the ceramic
PCB and mounted on a copper cooling block.
The monolithic SDD array developed for ESA project is shown in Figure
3.23 for reference and is described in more detail in next chapter. This SDD
array is mounted on a ceramic carrier similar to the one used for single
SDD unit. A flexible PCB is utilized to readout and bias the SDD array.
In the setup box for cooling the detector (Figure 3.24), the SDD array can
be seen connected to a support copper block which is fixed on top of yet
another additional copper block with a bi-adhesive glue. This additional
copper block is attached to the Peltier module’s cold surface. The Peltier
stage is capable of cooling the setup down to a temperature of -35 ◦ C. Once
the setup is cooled down, the flexible cable is connected to both the ESA
and SFERA setups to perform X-ray spectroscopy. The SFERA setup has
already been explained in section 3.4 while the ESA setup is the same one
described in section 4.2.2 for the readout of four similar SDD arrays.
An important detail about this ESA array is that each individual SDD unit
has an active area of 8×8 mm2 which is approximately six times the area
of the single circular SDD element readout in the last section. In addition,
57
Chapter 3. SDD based X-ray spectrometry
Figure 3.24: Experimental setup for characterization of SDD array.
this array developed by FBK belongs to a wafer with an average leakage
current density of 1800 pA/cm2 at room temperature as compared to the
single circular SDD unit (25 pA/cm2 ) utilized in last section. Considering
both the difference in active area and the leakage current density, it can
be calculated that this array has a leakage current 360 times higher than
the circular element. Nonetheless, the SDD array is cooled down to -35
◦
C to reduce the leakage currents of all SDD channels (except the central
one) below 1 pA. The central SDD channel has a higher leakage current
even at room temperature and does not follow the same trend of leakage
current reduction upon SDD cooling as the others. This channel is therefore
characterized by a leakage current of 20 pA at -35 ◦ C.
The best spectra with 55 Fe source are acquired at peaking times of 4 µs
for both ESA chip and SFERA as shown in Figure 3.25 and Figure 3.26
respectively. Owing to the higher leakage current technology, the energy
resolutions of these detectors are not as good as the ones measured with the
low-leakage single SDD presented in the previous section. With ESA chip
an ENC of 7.8 e − rms (minimum among all channels for all peaking times)
has been measured at the same temperature. Similarly with the relatively
recent SFERA ASIC, an ENC of 6.2 e− rms (energy resolution of 130.1 eV
FWHM) has been measured on the Mn-Kα energy line for array channel
3 (CH3). This is the minimum energy resolution with SFERA for this
array among all peaking times and channels. Channel 5 has had the worst
performance among all the channels on the SDD array. With ESA chip, it
has an ENC of 24.5 e− rms as compared to 21.6 e− rms achieved with SFERA
chip at the same 4 µs peaking time. These ENC values agree with the 20 pA
58
3.5. Experimental characterization of SDD array
Figure 3.25: SDD array characterization result with ESA chip at a temperature of -35 ◦ C
with 4 µs shaping time.
leakage current of this channel at this temperature.
Figure 3.26: SDD array characterization result with SFERA chip at a temperature of -35
◦
C with 4 µs shaping time.
A channel by channel comparison of the ESA and SFERA chip shows
that SFERA has much better performance as compared to the ESA chip. The
difference is more or less around a few e − rms. The primary reason for this
difference is that ESA chip has been designed for γ-ray application and the
design has not been optimized for X-ray applications. For instance, the gain
of the shaper amplifier is very low for X-ray spectroscopy of sources around
the Mn-Kα energy line. This results in a very small amplitude of the shaper
59
Chapter 3. SDD based X-ray spectrometry
amplifier output signal which is much more susceptible to pick up noise and
fluctuations as compared to a large gain as utilized in case of SFERA chip.
This slight degradation of X-ray spectra was understood during the ESA
chip design as well but parameters such as gain of the shaper were chosen
to optimize γ-ray spectroscopy performance. This is why SFERA can be
programmed with very high gains with dynamic range as low as 10 keV
(optimal for soft X-ray detection) have been implemented in SFERA chip.
In addition, two additional real poles have been introduced in the first stage
of the shaping filter of SFERA chip so as to reduce as much as possible
its noise contribution and hence raising the order of the shaper amplifier
to nine. It has already been explained in subsection 3.4 that a 9th order
shaper amplifier is slightly better in performance at larger peaking times
as compared to a 7th order filter. This difference is more prominent for
detectors with very low ENC (as in case of single round SDD). In case of
SDD arrays the application oriented design of both chips is the dominant
reason for difference in their X-ray spectroscopy performance.
The SFERA chip is also capable of operating at a very low gain enabling
a high dynamic range up to 20,000 e− per SDD channel for γ-ray applications. Just for perspective, 20,000 e − per analog channel for an SDD array
composed of nine individual SDD units corresponds to a total of 180,000
e− which for a coupled scintillator conversion yield of 30 phe/keV corresponds to incident γ-rays of 6 MeV. This dynamic range can, of course,
be further increased to a total of 640,000 e− once two SFERA ASICs are
used to readout thirty two analog SDD channels coupled to a scintillator.
In this scenario, similar scintillator conversion yield of 30 phe/keV results
in a dynamic range of 21 MeV assuming that the light signal is uniformly
distributed among all SDD channels.
Experiments have been performed with the SDD array cooled down to a
temperature around 150 K as well. The experimental setup for these tests is
shown in Figure 3.27 where the SDD can be seen mounted on a cold finger
in a vacuum chamber. The aim of these tests is to evaluate the performance
of the array at cryogenic temperatures with a very high background. These
tests have been performed at Paul Scherrer Institute (PSI) using a piM1
beam line (momentum range 100 and 500 MeV/c) to generate a fast trigger
on a scintillator coupled to a PMT. This fast trigger is used to compare
the response time delay of the trigger signal generated by the fast shaper
amplifier of SFERA chip (200 ns peaking time). In addition, spectroscopy
measurements are also performed by exposing the SDD array simultaneously
to 90 Sr and 55 Fe sources. 90 Sr decays by producing β − emission of 546
keV energy. This β − emission undergoes a series of interactions generating
60
3.6. Ardesia project
Figure 3.27: SDD array mounted on a cold finger in vacuum chamber to perform spectroscopy at around 150 K.
X-ray events caused by both fluorescence and scatterings, providing the
SDD with a high background. On the other hand, the 55 Fe source produces
emissions at Mn-Kα and Mn-Kβ emission lines. These sources are used to
test the X-ray spectroscopy performance of the detection system in case of
high background. The results of these experiments are still being processed.
All the characterizations in this section have been performed using an
SDD array developed for ESA project with nine individual SDD units.
This array developed by FBK possesses an average leakage current of
1800 pA/cm2 . However, the SDD array to be utilized in the Siddharta-2
upgrade has eight individual SDD units (Figure 3.5) and possess an average
leakage current of 200 pA/cm2 at room temperature which is an order of
magnitude smaller. These Siddharta arrays are currently in the process of
being characterized and tested prior to be mounted on the ring structure
shown in Figure 3.6. The only difference expected with the results presented
here is an improvement in ENC performance of the overall detection system
as the CUBE preamplifiers and the SFERA readout ASIC remain largely
unchanged.
3.6 Ardesia project
The work described in Section 3.4 is not limited only to Siddharta project but
has also lead the way for the development of another detection system for
X-ray detection applications. This application of SDDs readout by CUBE
preamplifier and SFERA ASIC is within ARDESIA (ARray of DEtectors for
Spectroscopy and Imaging Applications) project involving X-ray absorption
61
Chapter 3. SDD based X-ray spectrometry
fine structure spectroscopy (XAFS) [51]. XAFS is associated with study
of X-ray absorption of atoms around their core-level binding energies and
is generally performed in transmission mode for samples containing light
atomic elements like Mg, Al, Si and S. However, the ARDESIA detector is
to be utilized to measure XAFS spectra in fluorescence geometry which can
be very useful when dealing with diluted or supported (thick) samples. For
fluorescence based XAFS measurements, the detector needs to be designed
to cover a large solid angle around the target sample. In addition the detector
must be able to provide good energy resolution performance in addition to
high count rate operation.
Figure 3.28: Energy resolution for Mn-Kα energy line for a 10 mm2 SDD vs. peaking times
and temperature. The SDD belongs to SDD class with 200 pA/cm 2 leakage current at
room temperature. [51]
As there is no application defined limitation on the total active area of the
SDD element for florescence detection, in principle, even a 10 mm2 circular
SDD unit can be utilized as the basic detection unit for ARDESIA. An
estimation of FWHM achievable with such a 10 mm2 SDD at Mn-Kα energy
line is shown in Figure 3.28. The SDD used in this estimation belongs to the
class of 200 pA/cm2 leakage current at room temperature. It can be seen in
Figure 3.28 that at very low peaking times i.e. 200 ns, it is sufficient to cool
the detector down to 10 ◦ C to get energy resolution performance below 140
eV. This can also be seen in the measurement results presented in Figure
62
3.6. Ardesia project
3.14 where 136 eV FWHM @10 ◦ C has been achieved at 250 ns shaping
time with a similar SDD unit having a leakage current density of 120 pA/cm2
at room temperature. However, to simplify SDD array design and readout
electronics board, SDDs being developed for ARDESIA have SDD active
area around 2 to 2.5 times higher. Consequently, in order to achieve similar
energy resolution performances, a relatively lower operational temperature
of -20 ◦ C is considered.
The layout of the detector being developed by FBK for ARDESIA project
is shown in Figure 3.29. Each SDD array is composed by four individual
SDD units and in the first run experiments will be performed with both a
square and a circular shape of the basic SDD units. The square units have
an active area of 25 mm2 while the circular unit possesses an active area
of 19.6 mm2 . The primary reason for a smaller size of these SDD units as
compared to the Siddharta SDD array, is to reduce the electron drift time for
operation at much smaller shaper peaking times and thereby have a larger
throughput at high input count-rates. In addition the smaller size of the SDD
array also reduces the leakage current of the device and hence it does not
need to be cooled down to cryogenic temperatures for a very good energy
resolution performance.
Figure 3.29: SDD array layout of the two realized detector topologies, with (a) squared
and (b) circular detectors being developed at FBK
Figure 3.30 shows a 3D model showing an exploded view of the detection
module of the ARDESIA project with a single SDD array. Here a collimator
63
Chapter 3. SDD based X-ray spectrometry
is shown with circular holes of 4 mm diameter above the SDD units. This
collimator is made up of Molybdenum and serves to reduce the drift times
by reducing the effective area to 16 mm2 per SDD unit. As the XAFS
fluorescence depends on the solid area formed by the detector around the
target sample, a collimated detector unit placed closer to the target maintains
the same solid angle while achieving a higher count-rate due to less electron
drift time. Figure 3.30 also depicts a Peltier stage and a copper cold finger
which have been simulated to cool the detector unit from room temperature
to -20 ◦ C in under 5 minutes in vacuum. This short cooling time is just as
necessary as the high output count rate requirement of the detectors i.e. to
reduce the time needed to perform fluorescence measurements.
Figure 3.30: Ardesia detection module design for single SDD array.
A state of art, silicon based X-ray detector solution currently available
for similar high count rate application is called MAIA [52]. This detector
employs 96 up till 384 1 mm2 detector units arranged in a 10×10 and 20×20
format. With this detector array, a maximum of 4 Mcps can be achieved
with the 10×10 and although the 20×20 detector array has not been tested
yet, a simple scaling puts the estimate to 16 Mcps. However, these detectors
are very complex in the sense that each of the detector output electrode
is wire bonded to a readout board in addition to the yield of fabricating
a detector with all 96 or 384 individual units properly functioning. For
comparison, with Ardesia estimates show an output count rate of about 500
kcps per channel with integrated analog shaping solution while the relatively
64
3.7. Summary
expensive DPP solutions can achieve an output count rates ranging from 1
to 3 Mcps per channel. Considering the conservative estimate of 1 Mcps
with DPP and 500 kcps with analog solution, a single Ardesia module with
four SDD channels can reach up to 2 Mcps till 4 Mcps. Furthermore, the
modular nature of the ARDESIA module allows for arranging up to nine
such SDD modules together in a 3×3 format to achieve consequently 18 to
36 Mcps throughput. Another advantage of Ardesia as compared to Maia
is the modular nature of individual SDD modules which can be produced
with high fabrication yield and can also be easily replaced. However, such
modular structure generates dead areas for multiple module arrangements.
Work is currently in progress on the ARDESIA project.
3.7 Summary
This chapter has been dedicated to the application of SDD photo-detectors
for X-ray spectroscopy applications. In particular, the main discussion
has been oriented towards an upgrade of the Siddharta experiment for the
detection of shifts/broadening in the energy transition levels of kaonic atoms
to study the strong nuclear interactions. For this upgrade, a new SDD
element has been developed which is readout by a CUBE charge sharing
preamplifier. An dedicated ASIC known as SFERA has been developed to
read up to 2 Siddharta SDD modules (16 channels) and possesses sixteen
9th order shaping amplifiers, a fast shaper for Pile Up Rejection and an
integrated ADC.
Measurement results have also been reported to evaluate that with a single
SDD unit with 25 pA/cm2 leakage current at room temperature, SFERA
has been able to achieve an energy resolution of 122.1 eV FWHM at a
peaking time of 4 µs and a temperature of -35 ◦ C. SFERA also outperforms a
commercial 7th order shaping amplifier by Tennelec TC244 at larger peaking
times however at smaller peaking times Tennelec has better performance
(as 7th order SA normally perform better at smaller peaking times). With
SDD arrays with a higher average leakage current (1800 pA/cm2 at room
temperature), SFERA is able to achieve an ENC of minimum 6.2 e− rms with
4 µs peaking time at a temperature of -35 ◦ C. This result is slightly better than
performance achieved with another readout ASIC developed for gamma-ray
spectroscopy application within an ESA sponsored project as SFERA has
been optimized for both X- and γ-ray spectroscopy measurements.
Experiments have also been performed to evaluate the performance of
the Siddharta detection system in the presence of high background and to
evaluate the timing performance of the detection system at cryogenic tem65
Chapter 3. SDD based X-ray spectrometry
peratures. In the final portion of this chapter, another application of SDDs
in combination with CUBE and SFERA has been introduced. ARDESIA
project is aimed at development of SDD arrays for fluorescence purposes in
X-ray absorption fine structure spectroscopy (XAFS) which is an application demanding operation at very high input count rates with good energy
resolution performance. Also for such fluorescence application, the solid
angle formed by the detector around the target sample is important. SDD
modules design and estimates of expected performance with the 200 pA/cm2
at room temperature for this project are provided.
66
CHAPTER
4
SDD for gamma-ray detection
4.1 Introduction
Chapter 3 discusses the use of SDDs for X-ray spectroscopy purposes in
the scope of Siddharta and Ardesia applications. Initial results pertaining
to X-ray characterization of the SDD elements and spectroscopy results
with soft X-rays have been presented to provide an overview of expected
performance of the X-ray detector.
In this chapter the focus is shifted from X-rays to γ-ray detection under
the scope of a European Space Agency (ESA) sponsored project (Contract
No. 4000102940/11/NL/NR) to study the use of SDDs to readout large
LaBr3 :Ce scintillators for planetary gamma-ray observations. In this scope,
a wide nuclear transition region i.e. 150 keV to 15 MeV is considered to
investigate chemical composition of planetary surfaces. In this framework,
detector prototypes based on the use of monolithic arrays of SDDs coupled
to 100 ×100 and 200 ×200 LaBr3 :Ce scintillators are developed to study their
spectroscopy performance and compare them to the state of the art. The noise
performance of these SDD arrays is evaluated using X-ray spectroscopy
prior to the γ-ray measurements. An extensive study regarding the role of
this noise on the overall γ-ray spectroscopy performance is also performed
67
Chapter 4. SDD for gamma-ray detection
in this framework of studies supported by ESA. Most of the description
of experimental setups and corresponding results presented in this chapter
regarding the 100 ×100 and 200 ×200 gamma-cameras have been taken from [53]
and [54] respectively.
The first part of this chapter introduces the reader to the scintillator based
detectors and their role in high energy γ-ray spectroscopy before explaining
the scintillation properties of LaBr3 :Ce and its position among other scintillators. Later on, a brief overview of ESA project and challenges associated
with the readout of large LaBr3 :Ce scintillators with SDD arrays are presented. In addition, an overview of different components of the developed
gamma-cameras involving readout electronics, mechanics, cooling system,
experimental characterization tests and corresponding γ-ray measurements
are described. These measurement results include study of the linearity,
energy resolution, conversion gain, noise performance e.t.c for both the 1 00
and 200 formats. In the final part of this chapter, the role of SDD noise on the
energy resolution performance are described alongside possible improvements in detector performance using the new SDD technology with low
leakage. A comparison of the SDD based readout to the state of the art PMT
readout is also performed with both SDD technologies in later sections of
this chapter.
4.1.1
Scintillation detectors
The Basic purpose of a gamma-ray detector/spectrum-analyzer is to convert
the incoming gamma radiation into electrical signal. This electrical signal
can then be processed by suitable electronics to find out the energy, point of
interaction and/or time of interaction of the photon. Gamma-ray detectors
are basically divided into two different categories depending on the means by
which they convert the incoming radiation into the electrical signal. These
categories are as follows:
First category is Direct Conversion detectors. These detectors directly
convert incoming radiation into electrical energy in the detector. Examples of
detectors employing direct conversion are gas detectors, Cadmium Telluride
detectors etc. As gamma radiation has very high penetration power so these
detectors need to be very bulky in size. Also we need to apply very high
reverse biased voltages across these bulky detectors to deplete them and
to be able to efficiently separate and detect the charge carriers generated
due to the absorption of the radiation. If the voltage is not high enough
to completely deplete the detector body of free charge carriers then the
electron/hole or ion pairs may recombine within this bulky detector before
68
4.1. Introduction
reaching the anode/cathode. Also application of such high voltage creates
leakage currents that can degrade performance of the detector over time.
Second category of gamma-ray detectors is the Indirect Conversion
detectors. As the name suggests, these detectors do not directly convert the
incoming gamma radiation into electrical signal. In fact they employ an
intermediate stage to first convert incoming radiation into photons of lower
energy (larger intensity) and then to convert it into electrical energy using
a low energy photo-detector. The most commonly used intermediate stage
is the scintillation stage. This stage employs a crystal scintillator which
is capable of efficiently stopping the incoming high energy radiation and
converting it into flashes of visible light of well-defined wavelengths. These
scintillators can be either organic or inorganic. However, organic scintillators
have very poor performance compared to inorganic ones. Examples of
inorganic scintillators are Cesium Iodide (CsI), Lanthanum Bromide (LaBr3 ),
Sodium Iodide (NaI) etc. Unlike the direct conversion detectors, these
scintillator crystals do not need any electrical power to operate and can be as
thick as needed to completely absorb all of the incident radiation. However,
scintillator is not capable of converting the absorbed radiation into electrical
energy as it is a simple chunk of crystal. For this purpose we couple a photo
detector (i.e. Photomultiplier Tube, Photodiode, Silicon Drift Detector etc.)
with the scintillator to efficiently convert the visible light produced by it into
electrical energy. In case of indirect conversion, the photo detector needs
to be of relatively much smaller thickness and hence requires much lower
biasing voltage to be completely depleted.
Indirect conversion, in fact uses two stage conversion and both of these
stages are optimized in their respective fields. However, losses occur when
these stages are coupled together. Some of the light created by the scintillator
is lost at the contact surface between the scintillator and the photo detector.
This lowers the efficiency of indirect conversion detectors. However these
detectors are still easier to realize because of the lower reverse biased
voltages needed to completely deplete them.
4.1.2
Lanthanum Bromide as a scintillator
Lanthanum Bromide is an inorganic halide salt of Lanthanum. In its pure
form is a white powder. Cerium activated lanthanum bromide is an inorganic
scintillator which has a very high light yield and a remarkably good energy
resolution. The scintillation properties of Lanthanum bromide were discovered at Delft University of Technology and the University of Bern [55] and
since then it has been used in making high energy scintillator detectors.
69
Chapter 4. SDD for gamma-ray detection
Table 4.1: Comparison between emitted light wavelength, yield and decay time of some
scintillators. [56]
NaI:Tl
CsI:Tl
CsI:Na
CsI
BGO
BaF2 (fast)
BaF2 (slow)
LaCl3 :Ce
LaBr3 :Ce
LYSO
Peak scintillation wavelength
(nm)
415
550
420
315
480
220
310
350
380
420
Light yield
(phe/keV)
38
54
41
2
10
1.8
10
49
63
32
Decay time
(ns)
250
1000
630
16
300
0.8
630
28
16
41
Table 4.1 briefly takes a look at the scintillation yield and light pulse
decay time of Lanthanum Bromide and some other commonly used inorganic
scintillator crystals [56]. A higher scintillation yield results in a higher light
output which provides more counts to the coupled photo-detector stage.
This improved statistics, results in a better performance of spectrometer
and improves the achievable energy resolution. Similarly a smaller light
pulse decay time allows for a faster acquisition of the incoming signal for
timing applications. In addition, it allows high count rate operation and
reduces chances of pile up. LaBr3 :Ce has a very high scintillation yield of
63 phe/keV with a light pulse decay time of 16 ns. This scintillation yield
is comparable to 54 phe/keV achievable with the commonly used Thallium
doped Cesium Iodide (CsI:Tl). However, CsI:Tl has a very long scintillation
pulse decay time of 1 µs making it unsuitable for applications requiring
fast timing. On the contrary, Barium Fluoride (BaF2 ) has the fastest decay
time of 0.8 ns but possesses a yield of only 1.8 phe/keV. The next best
alternative to LaBr3 :Ce in terms of all round performance is the Cerium
doped Lanthanum Chloride (LaCl3 :Ce) which is characterized by a yield
of 49 phe/keV and a light decay time of 28 ns. However, the Bromide of
Lanthanum is slightly better than its chloride in both of these scintillator
parameters.
LaBr3 :Ce enjoys a very good temperature stability of the light output
that limits the problem of the whole detector stabilization. A variation in
temperature from -65 ◦ C to +140 ◦ C results in a variation of only 5% in light
output yield [12]. In addition it can be seen in Figure 4.1 that the scintillation
70
4.1. Introduction
yield of Lanthanum Bromide (B380)is relatively more flat with temperature
as compared with other scintillators. In Figure 4.1, the measurements were
performed with a PMT while its temperature was kept constant during each
measurement.
Figure 4.1: Response of scintillator as a function of temperature with a fixed PMT temperature. [57]
Another important property of scintillators is the stability of the scintillation yield for different energies of the incident radiation. LaBr3 :Ce is
known for a very good linearity between the number of scintillation photons
produced versus the energy of the incident γ-ray photons (63 phe/keV)
above 150 keV [58]. The linearity of the scintillator (independent of photodetector) makes it possible to calibrate the detection system in scenarios
where scintillation yield is time variant and accessibility to the scintillator
is limited. This can happen, for example, in environments with high in71
Chapter 4. SDD for gamma-ray detection
tensity background radiation like spectrometers working in space shuttles
and probes. These high radiation backgrounds can damage the scintillator
causing a variation in its scintillation yield over time [59]. In such a scenario
if the scintillator is linear w.r.t. energy, it can still be calibrated and used.
Figure 4.2: The spectrum of the self-activity of the LaBr3 :Ce detector. [60]
LaBr3 :Ce possesses self-activity primarily due to the presence of radioactive isotopes 138 La and 227 Ac. Figure 4.2 shows the self-activity spectrum
of LaBr3 :Ce where events with energy smaller than 1.5 MeV are due to the
decay of 138 La while the structure between 1.5 and 3 MeV is produced by the
decay chain of 227 Ac contaminant. In the inset, the peak structure centered
around 1460 keV can be seen together with the result of a fit procedure. The
two peaks centered at 1440 and 1472 keV belong to de-excitation of 138 Ba
nucleus formed by 138 La electron capture. This spectrum has been obtained
with a 100 ×100 crystal and an activity of 0.85 cps/cc (counts per second/ cubic
centimeter) is measured in [60]. Recent advances in scintillator manufacturing process by Saint Gobain have reduced the self scintillation counts to an
activity of 0.393 cps/cc for a 1.500 ×1.500 crystal. Here, the primary reduction
has been the reduction of the alpha activity by reducing 227 Ac contaminants.
In a recent study described in [61], drastically reduced intrinsic activity of a
similar halide scintillator CeBr3 :Ce has resulted in an order of magnitude
improvement in gamma-ray detection sensitivity as compared to LaBr 3 :Ce
at energies of 40 K (1461 keV) and 208 Tl (2614.5 keV). However, owing
to a lower scintillator light yield, CeBr3 :Ce coupled to Hamamatsu PMT
has been characterized by an energy resolution of more than 4% [61] as
compared to 3% achieved with LaBr3 :Ce. The self activity of LaBr3 :Ce does
72
4.1. Introduction
not pose any major concern for spectrometry and imaging applications for
gamma-ray energies other than 1461 keV and 2614.5 keV. On the contrary,
characteristic self activity peaks of the LaBr3 :Ce scintillator can in principle
be used to calibrate the detector as well.
LaBr3 :Ce crystal possesses robust mechanical properties and is at least
a as rugged as NaI:Tl. Lanthanum Bromide can survive 1000g shock and
about 30g rms random vibration and temperature as high as 200◦ C temperatures [12, 57]. However, it is highly water soluble and it can form many
kinds of hydrates upon contact with water. This humidity can degrade performance and in the worst case, it may even change the physical shape of
the scintillator from a crystal to a gel like material. In order to solve this
problem, the scintillator must be covered by some waterproof layer that
cannot be penetrated by humidity. The LaBr3 :Ce scintillators provided by
Saint-Gobain, are enveloped by a layer of aluminum (approx. 0.5 mm) to
solve this problem. In addition, a few layers of Teflon are present between
the scintillator and the aluminum casing to internally reflect the scintillation
light to reduce losses at these interfaces. A quartz optical window at the
bottom surface is used to guide the light towards the coupled photodetector.
Lanthanum bromide has a hexagonal crystalline structure with considerable anisotropy in properties like thermal expansion. This creates a problem
if its temperature is changed very quickly or if different parts of the crystal
possess a big temperature difference ∆T. This can create extra stress on
the scintillator and can break it. These issues become more problematic
once the size of the scintillator is increased. Therefore, It is important to
maintain a uniform temperature profile across the scintillator and to ensure
that it is not subjected to temperature shocks (higher values of ∆T/δt, where
T= temperature and t=time). The limit for maximum allowed temperature
gradient across the scintillator for safe operation ∆Tmax is 3 ◦ C whereas
the maximum rate of change of temperature (∆T/∆t)max is 8 ◦ C per hour.
These limits are set by Saint-Gobain, one of the manufacturers and supplier
of these scintillator.
4.1.3
ESA sponsored gamma-ray project
In astronomy, most of the exploration is done by optical and radio telescopes which can observe the universe in terms of radio waves, visible
light and other low frequency electromagnetic radiation. In the 1960s, it
was discovered that there exists radiation emitted by some massive entities
in the universe which lies at much higher energies in the electromagnetic
spectrum. These include exploding stars (supernovae), material falling into
73
Chapter 4. SDD for gamma-ray detection
black holes, Gamma-Ray Bursts (GRBs) and radio-active isotopes that exist
on the surface of different planets. In Figure 4.3, images taken by gammaray detectors on board ESA’s INTEGRAL mission [62] show a Black-hole
slowly devouring a companion star and emitting intense gamma-radiation in
the process.
Figure 4.3: Images of the Cygnus X-1 region from INTEGRAL four detectors are superimposed on an artist’s impression of the black hole and companion star discovered in
autumn of 2002. Copyright: ESA. Illustration by the Integral team and ESA/ECF.
In order to observe phenomenon like the ones shown in Figure 4.3, special
purpose γ-ray detectors need to be developed and transported to space where
they can perform measurements without any interference of Earth’s thick
atmosphere. In this context, European Space Agency (ESA) has initiated
many studies within the Technology Research Programme (TRP) and Core
Technology Research Programme (CTP) to support gamma-ray detection
technology development. This programme evaluates these detection systems
for possible integration with satellites/inter planetary probes for future space
missions.
Gamma-ray detectors, can also help us study the surface composition of
different celestial bodies of our solar system. For planets like Mercury and
Mars which possess little to no atmosphere with the consequence of having
the planetary surface fairly exposure to energetic interstellar cosmic rays,
74
4.2. Design of the gamma-ray detection system
it is possible to understand the composition of the planet’s surface from
the planetary orbit. In such environments, the cosmic rays interact with the
planetary surface to produce fast neutrons which upon further interaction
with nearby matter can generate gamma radiation. In addition, naturally
occurring radioactive isotopes within the regolith, also produce gamma-rays
upon decay. Thereby, using gamma-ray spectrum analyzer, it is possible
to detect these planetary gamma-ray emissions from orbit to identify the
surface composition of the planet [63].
Recently, the use of large LaBr3 :Ce scintillators readout out by photodetector has been thoroughly investigated for use in planetary gamma-ray
observations [64,65] and as a consequence of these studies, Mercury Gamma
and Neutron Spectrometer (MGNS) is to be flown on board the Mercury
Planetary Orbiter of ESAs BepiColombo mission [63]. Here, Mercury
Gamma-Ray Spectrometer (MGRS) is aimed is the primary gamma-ray
spectrometry instrument which needs to operate over a wide dynamic range
from 150 keV to 15 MeV with an energy resolution performance around
3% @662 keV. Owing to the large dynamic range requirement, LaBr3 :Ce
crystals as large as 300 ×300 have been chosen owing to increase detection efficiency at higher energies. Typically for such applications, detector modules
are based on the use of PMTs where a similar detector has been used in the
Chinese lunar mission Chang’E-2 [6]. However, for spectrometry applications requiring large dynamic range operation, PMTs can suffer limitations
in terms of non-linearity, an issue which can be addressed by reducing the
biasing voltage or the number of dynodes [56, 66–68]. In addition the mass,
volume and high voltage biasing requirements of classical PMT technology renders this approach less favorable than a state-of-the-art solid state
approach e.g. Silicon Drift Detector (SDD) or silicon photomultiplier.
In this context, the design issues of a small prototype based on lanthanum bromide crystal coupled with a single SDD (8×8 mm2 )have already
been studied in [30]. However, this chapter describes various challenges
and stages of development of a gamma-camera based of large (100 and 200 )
LaBr3 :Ce crystals readout by SDD arrays and the results are compared to
the PMT based readout.
4.2 Design of the gamma-ray detection system
In order to systematically investigate the spectroscopy performance of lanthanum bromide readout by SDDs, Gamma-cameras based on 100 ×100 and
200 ×200 LaBr3 :Ce crystals are developed with possibility of expansion towards a 300 crystal as well. These detection systems are composed of the
75
Chapter 4. SDD for gamma-ray detection
detection head, read out electronics, acquisition systems, gamma-camera
mechanics and cooling systems. The gamma camera based on 100 crystal
00
acts as a prerequisite for the development of larger scintillator detectors (2
and 300 crystals). In addition, this incremental approach allows for study of
effects of scaling scintillator size and corresponding photo-detector area on
the final achievable energy resolution.
4.2.1 Detection head
The basic building block of the detection head is a monolithic SDD array
of nine individual SDDs with an active area of 24×24 mm2 . Within the
SDD array, individual SDDs of 8×8 mm2 active area each are arranged
in a 3×3 format with a 1 mm dead area all around the border of the array.
The anode side view of a single SDD and the layout of the SDD array
are shown in Figure 4.4 (a) and (b) respectively. These SDDs have a thin
light entrance window and a Nitride Anti-Reflective Coating (ARC) to
optimize their quantum efficiency (QE): A QE > 80% has been measured
at the emission wavelength of LaBr3 :Ce (380 nm) [30]. The SDD array
has been biased using the punch-through mechanism which is explained
in detail in [69]. Contrary to the standard biasing method, which requires
an electrical bonding of the back electrode, in punch-through mechanism
the back electrode is left floating. However, once the last ring is biased to
-2Vdep , leakage holes generated within the bulk are collected by the back
electrode. These collected holes generate a reach-through current between
the back and the last ring, passing through the depleted bulk as depicted
in Figure 4.5. This biasing mechanism has a slight penalty in terms of the
charge collection time. However, for gamma-ray detection applications,
where large shaper peaking times are utilized to avoid ballistic deficit, no
penalty has been observed using punch-through mechanism for single [30]
as well as arrays of SDDs [70].
Figure 4.4 (b) shows a single SDD array with an area of 26×26 mm2
which is sufficient to read a 100 LaBr3 :Ce crystal as the crystal has a diameter
of 25.4 mm. Furthermore, in order to readout a 200 ×200 LaBr3 :Ce crystal, a
total of four SDD arrays can be arranged in a 2×2 format as shown in Figure
4.4 (c). The total area formed by the four SDD arrays is 52×52 mm2 (including all dead areas) as compared to the 50.8 mm diameter of the lanthanum
bromide crystal. Owing to the cylindrical shape of the scintillator and a
square format of the photo-detector array, the SDD elements on the extreme
corners of the 2 ×2 arrangement, practically get no light signal. Also other
SDDs are only partially covered by the scintillator and the consequences of
76
4.2. Design of the gamma-ray detection system
Figure 4.4: (a) Anode side of single SDD with active area 8×8 mm2 . (b) Layout of one
SDD monolithic array (26×26 mm2 ), suitable for 100 crystal readout. (c) Drawing of 4
SDD modules arranged in a 2×2 format. The total photo-detector area is 52×52 mm2 ,
suitable for the 200 crystal readout.
this are discussed in subsections 4.2.2 and 4.3.3.
Figure 4.5: Biasing of the back electrode by punch-through mechanism.
Each of the SDD arrays is mounted on an alumina ceramic carrier to bias
and read the SDD array as shown in Figure 4.6 (a). The ceramic carrier is
used, instead of the traditional FR4 carrier, for its higher thermal conductivity.
The carrier contains small holes (2.5 mm diameter) corresponding to the
position of the central anode of each SDD element in the attached array, as
77
Chapter 4. SDD for gamma-ray detection
shown in Figure 4.6 (a). These holes, as well as one chamfered corner of
the ceramic, allow for electrical connections between the SDD electrodes
and the carrier via bonding wires. The bonds on the chamfered corner
allow for high voltage biasing (typically -140 V) of the last ring and ground
connection of the SDD substrate while the bonds from the holes provide low
voltage biasing (typically -25 V) and readout of individual SDD elements.
Owing to the punch-through mechanism, no additional biasing connection
is required on the back of the SDD.
Figure 4.6: (a) An SDD array mounted on a ceramic carrier hosting CUBE preamplifiers.
(b) An SDD module containing an SDD array, ceramic carrier, copper cooling block
and a flexible PCB.
Pre-amplifiers are placed on the ceramic carrier in near proximity of the
SDD anode. In this work, a monolithic CMOS based pre-amplifier (CUBE)
has been used [42]. 9 CUBEs corresponding to nine SDD channels can be
seen mounted on the ceramic carrier in Figure 4.6 (a). In comparison with
the FET (Field Effect Transistor) based solution [71], CUBE simplifies the
readout electronics while maintaining good noise performances [30], [70],
[45]. In addition, as the CUBE generates the pre-amplifier output signal
very close to the input SDD anode, it is able to derive relatively longer
interconnections between the ceramic carrier and the following electronic
readout chain.
The ceramic board with the SDD array is mounted on a copper holding
block to provide mechanical support and to cool the array. A flexible PCB
can be used to connect each ceramic carrier to a biasing board which is in
turn connected to ASICs dedicated to the processing of the signals. The
SDD array, ceramic carrier, copper block and the flexible PCB form an
independent SDD module as shown in Figure 4.6 (b). However, as the γ-ray
detection system developed for a 100 crystal is of preliminary nature, an
interconnection board and flat cables were used instead of the flexible PCB
78
4.2. Design of the gamma-ray detection system
Figure 4.7: One SDD modules can be seen connected to an interconnection PCB. The total
photo-detector area is 26×26 mm2 which is sufficient to read a 100 ×100 crystal.
to connect to the intermediate biasing board. This interconnection board
can be seen in the detection head shown in Figure 4.7. However, in order to
readout a 200 crystal, four of the SDD modules shown in Figure 4.6 (b) with
the flexible PCB are used which can be seen fixed on an aluminum base as
shown in Figure 4.8.
Figure 4.8: Photodetector with four SDD modules mounted in 2×2 format to achieve a
total detector area of 52×52 mm2 .
79
Chapter 4. SDD for gamma-ray detection
4.2.2
Readout Electronics
The flat cable connectors containing CUBE preamplifier outputs and SDD/CUBE biasing signals are connected from the interconnection board (
shown in Figure 4.7 ) to an intermediate PCB using flat ribbon cables. This
intermediate PCB is capable of reading only one SDD array and can be seen
in Figure 4.9. This preliminary PCB is designed to be able to calibrate the
detection chain by applying voltage pulses to the first ring with a waveform
generator. This procedure emulates charge pulses produced in the SDD
when light signal is detected. In addition, this board contains a circuit to
reset the charge integration across the feedback capacitor of the CUBEs
to allow its optional use with external shaper, which can be disabled when
used with the integrated readout electronics. This feature is used in the
preliminary phase to compare the performance of external shaper and with
the one integrated in the Application Specific Integrated Circuit (ASIC).
Power line filters and buffers for CUBE output lines are also present on this
board to reduce the noise on the power lines and to avoid degradation of
CUBE output signals. This preliminary intermediate board is connected to
the ASIC board via flat cable connector shown on the right side of Figure
4.9. This board is capable of reading only 100 crystal and hence the board
was upgraded once a larger crystal format was used.
Figure 4.9: Preliminary intermediate PCB dedicated to biasing and routing signals of 1
SDD module.
Figure 4.10 shows the upgraded intermediate board where the flexible
PCBs shown on the left side of Figure 4.8 can be seen connected. This
80
4.2. Design of the gamma-ray detection system
board is designed to bias up to nine different SDD modules which can in
principle be used to readout a 300 ×300 LaBr3 :Ce crystal as well. Each row of
connectors shown in Figure 4.10 has slots to connect 3 SDD modules. These
modules are all biased with the same voltages and are connected to the same
electronic readout chain via flat cables. For the 2-inch gamma-camera, only
two slots of each row are utilized.
Figure 4.10: Upgraded intermediate PCB dedicated to biasing and routing signals of up
to nine SDD modules.
Similar to the upgraded biasing board, the processing electronics is also
designed to readout up to 81 photo-detectors (9 SDD modules), comprising
three custom designed 27-channel ASICs. One of these ASICs can be seen
mounted on a carrier board in Figure 4.11 (b). Each channel of this ASIC
features a semi-Gaussian shaping amplifier with selectable peaking times, a
baseline holder and a peak stretcher. The ASIC has already been introduced
in chapter 3 and is further described in detail in [72]. The ASIC provides at
its output a 27:1 analog multiplexing of all the channels. It also incorporates
a differential buffer to drive an external ADC. Three ASIC carrier boards
can be seen mounted on a motherboard in Figure 4.11 (a).
Three parallel sampled data streams from the differential output buffer of
the ASICs are driven into the digital processor, which is based on ADCs and
an FPGA device. Three LTC-2215 ADCs are used to convert the multiplexed
analog data into digital format in the DAQ board. Each of the three LTC2215 ADC is mounted on a separate carrier board and the ADC boards are
plugged in corresponding slots of the DAQ board. The FPGA device plays
the role of main processor and control logic. An Atmel secondary processor
manages the Ethernet communication interface with the PC.
81
Chapter 4. SDD for gamma-ray detection
Figure 4.11: (a) Motherboard hosting three ASIC carrier boards capable of reading out
81 SDD channels. (b) Board that hosts the custom designed ASIC directly bonded on
the board.
Figure 4.12: Block diagram of readout and acquisition system of the gamma-camera with
capability of readout of up to 81 SDDs corresponding to a 300 scintillator.
The intermediate biasing board, the ASIC motherboard and the DAQ
board, all have been designed to read out a total of 81 SDD channels, for a
possible use with 9 SDD modules to readout a 300 ×300 LaBr3 :Ce crystal. The
block diagram of the readout electronics in Figure 4.12 shows all possible
scintillator readout options. Even though 36 SDD channels are readout in
82
4.2. Design of the gamma-ray detection system
case of a 200 crystal, only 32 of them are covered by the scintillator and carry
useful information as shown in Figure 4.12. Similarly for a possible 300
extension, only 69 out of 81 SDD channels are covered by the scintillator.
4.2.3
System Mechanics
The SDD modules shown in Figure 4.7 and Figure 4.8 need to be cooled
down to temperatures as low as -20 ◦ C to reduce their electronic noise
contribution due to leakage current. This contribution limits the energy
resolution of the gamma-camera, and it is discussed in detail in sections 4.3
and 4.4.
Figure 4.13: Steady-state thermal simulation result of 100 gamma-camera’s mechanics with
9.6 Watts of power being removed from the setup. Temperature gradient across the
crystal is expected to be always less than the one measured by temperature sensors.
Owing to the anisotropic thermal properties of LaBr3 :Ce, the temperature
gradient across crystal’s volume has to be maintained lower than 3 ◦ C
and cooling/warming procedures have to be performed no faster than 8
◦
C/hour to guarantee safety of the LaBr3 :Ce crystal. Furthermore, the
83
Chapter 4. SDD for gamma-ray detection
scintillator is in close proximity to the SDDs that require cooling. These
factors impart significant importance to the design of a mechanical structure
and a cooling system for the gamma-camera to satisfy the safety conditions
of the scintillator. As a consequence, a series of steady and transient-state
thermal simulations have been performed using COMSOL Multiphysics
simulation software to better understand the performance of gamma-camera
mechanics while cooling is applied. These simulations have been performed
for both the 100 and the 200 gamma-camera and the result of steady state
simulations can be seen in Figure 4.13 and Figure 4.14 respectively. These
simulation results correspond to assembled 100 gamma-camera mechanics
shown in Figure 4.15 and the exploded view of 3D model of 200 gammacamera shown in Figure 4.16.
Figure 4.14: Steady-state thermal simulation result of 200 gamma-camera’s mechanics
with 31 Watts of power being removed from the setup. Temperature gradient across the
crystal is expected to be always less than the one measured by temperature sensors.
In case of 100 mechanics assembly, the scintillator is placed on top of the
SDD module visible in Figure 4.7 and is held in place by an aluminum grip.
This grip is fixed to the aluminum base to minimize the temperature gradient
84
4.2. Design of the gamma-ray detection system
across the scintillator. A temperature sensor is placed on the aluminum base
and on top of the scintillator to estimate the temperature gradient across the
scintillator as shown in Figure 4.13. These thermal simulation results show
that a temperature difference of 1.3 ◦ C is expected to be measured by the
temperature sensors when the temperature across the scintillator is 0.7 ◦ C.
Hence if the temperature difference measured by the sensors is maintained
to be lower than 3 ◦ C, the scintillator’s safety is guaranteed in case of the 100
gamma-camera.
Figure 4.15: Assembled gamma-camera mechanics for cooling single SDD modules coupled with a 100 ×100 LaBr3 :Ce crystal
For the 200 gamma-camera, the scintillator is gripped by four aluminum
pieces to ensure thorough lateral contact between the crystal’s aluminum
enclosure and the cooling structure. This grip also ensures that the crystal
stays fixed in the center of the SDD arrays’ assembly. This aluminum
structure is attached on top of a copper frame which is in turn fixed to the
aluminum base shown in Figure 4.8. On the top, an aluminum lid (2 mm
thick) is placed to cool the top of the scintillator. Through a hole in the
middle of the top lid, a temperature sensor is placed in contact with the
top surface of the crystal’s enclosure to monitor its temperature (Figure
4.14). Two temperature sensors are also placed on the aluminum base to
estimate the temperature of the SDDs and the bottom of the scintillator
during cooling/warming procedure. The outer surface of the aluminum
grip and the copper frame shown in Figure 4.16 are covered with 2 mm
thick thermally insulating polyethylene layer to reduce ambient heating and
is considered in the thermal simulation result of Figure 4.14. The entire
85
Chapter 4. SDD for gamma-ray detection
mechanics is, later on, enclosed in a plastic box and dry air is circulated to
ensure a humidity free atmosphere.
Figure 4.16: Exploded view of 3D model of mechanics for cooling down four SDD modules
coupled with 200 ×200 LaBr3 :Ce crystal.
Copper has been used to manufacture components of the system mechanics where low thermal resistance is needed like the copper frame which
acts like a choke point for cooling between the bulky metallic pieces above
and thick metallic base below. However, for the remaining bulky components, a lighter and cheaper metal with acceptable thermal conductivity like
aluminum has been used.
The thermal simulation result of Figure 4.14 shows that a temperature difference of 2.2 ◦ C exists among the temperature sensors when the temperature
gradient across the scintillator is 1.4 ◦ C. Further transient-state simulations
have shown that due to the low cooling/warming rate of 8 ◦ C/hour, the
system is expected to be nearly always in steady state and the temperature
86
4.2. Design of the gamma-ray detection system
gradient safety condition is expected to be always followed. The simulation
results show that the temperature difference measured by the temperature
sensors is always higher than the temperature difference across the actual
scintillator. Thereby if the temperature difference across the sensors can be
limited to 3 ◦ C, the scintillator’s safety is guaranteed.
During the mechanics design and development phase, thermal simulations have been performed to ensure that the temperature gradient across
the scintillators in both the gamma-cameras will be less than 3◦ C in steady
state. In addition, it has also been simulated that the cooling/warming of the
gamma-cameras are performed at 8 ◦ C/hour, the systems are nearly always
in more or less steady states. However, in order to ensure that the system
can in fact be cooled smoothly at 8 ◦ C/hour, dedicated cooling systems need
to be developed. In addition, it is also important that no abrupt changes
in temperature occur across the scintillators and theses processes are performed smoothly. The dedicated cooling system developed to ensure this is
described in the next sub-section.
4.2.4 Cooling System
In order to cool the gamma-camera mechanics while ensuring the safety of
the scintillators, dedicated cooling systems with feedback control systems
have been developed. The cooling system development and testing for the
100 crystal is explained in detail in [73] and in this subsection, the aim of the
discussion is the cooling system for the 200 scintillator.
Figure 4.17: Block diagram of the second stage of the cooling system depicting the
interconnections of temperature sensor, Peltier modules, power supply and the PC in
the cooling system.
The 200 gamma-camera’s cooling system consists of two stages. In the first
stage, a liquid coolant is circulated through the heat sink (see Figure 4.16) to
87
Chapter 4. SDD for gamma-ray detection
maintain a constant temperature on its top surface. This stage works in open
loop without any regulation. The second stage consists of thermoelectric
Peltier modules (MCPF-161-12-10-E), temperature sensors (TC-NTC-1) and
a centralized PID (proportional-integral-derivative) controller implemented
in Matlab. A simplified block diagram of this second stage is shown in Figure
4.17. Four output channels of a programmable power supply (HMP4040)
are used to provide electrical power to each of the four Peltier modules
independently. The Peltier modules reduce temperature of the aluminum
base by removing heat from the setup and pass it to the liquid coolant
(through the copper heat sink) which carries it away from the setup. The
amount of heat being removed and consequently the temperature of the setup
depend on the quantity of electrical current being provided to the Peltier
modules by the power supply. Therefore, the power supply is remotely
controlled by the Matlab routine to adjust cooling. Temperature sensors
placed in the system mechanics also provide feedback to the Matlab routine
to implement a PID feedback control system.
Figure 4.18: Measured temperature gradient across the scintillator, while the SDDs are
being cooled down to -20 ◦ C @8 ◦ C/hour. A zoom of the response of last 20 minutes (on
the top right) shows that temperature gradient across temperature sensors is ensured to
be less than 3 ◦ C.
88
4.3. Gamma-ray spectroscopy measurements
Figure 4.18 shows a plot of the measured values of the temperature sensors while the SDDs are cooled down. Following the 8 ◦ C/hour cooling rate,
the system takes 240 minutes to cool the SDDs from 10 ◦ C to approximately
-20 ◦ C. The curve marked "Desired temperature @ 8◦ C/hr" in Figure 4.18
shows the set-point temperature values being provided to the PID controller
for tracking. Difference between the "Desired Temperature @ 8 ◦ C/hr" and
the average of the two bottom sensors is used to calculate the control error
in the PID controller. The cooling system is characterized by a maximum
control error of ±0.2 ◦ C throughout cooling. The estimated temperature gradient across the scintillator is measured as the maximum difference among
all three temperature sensors. This temperature difference is continuously
monitored and the cooling is halted, if necessary, to ensure that it does not
exceed 2.7 ◦ C as seen in the inset of Figure 4.18. A threshold limit of 2.7
◦
C, instead of 3 ◦ C, is utilized to provide safety margin to the Matlab’s
temperature difference monitoring algorithm. The cooling is once again
resumed when this temperature difference reduces below 2.65 ◦ C.
4.3 Gamma-ray spectroscopy measurements
Gamma-ray spectroscopy measurements are performed by irradiating the
gamma-camera mechanics with un-collimated γ-ray sources once the setups
have been cooled down. These experiments are designed to characterize the
energy resolution and linearity performance of the SDD based readouts of
the 100 and 200 LaBr3 :Ce crystals. However, prior to the characterization of
the entire gamma-camera’s performance, X-ray spectroscopy measurements
are performed without the scintillators to calibrate and characterize the SDD
detection heads. In this section, the X-ray calibration and γ-ray spectroscopy
measurements are discussed.
4.3.1
Detection head calibration and characterization
In order to perform γ-ray measurements with multiple SDD channels covered by a scintillator, these individual SDD elements need to be calibrated.
Experiments are performed with the SDD arrays to obtain gain and offset matrices useful for the energy calibration of the final detection array
irradiated by γ-rays.
Uncollimated 55 Fe source (Mn-Kα 5895 eV, Mn-Kβ 6492 eV) is used as
an X-ray source to irradiate the detector prior to mounting the scintillator.
When an array of SDDs coupled to the ASIC is subjected to such a source,
the response of these SDDs is different from one another in terms of position
of the energy noise and signal peaks. So in order to perform a comparison
89
Chapter 4. SDD for gamma-ray detection
between different SDDs and obtain their accurate energy spectra, gain and
offset calibration is needed.
Figure 4.19: Energy spectrum in channels of the 55 Fe source measured at -20 ◦ C. Only
one channel is presented for the sake of simplicity.
A Matlab routine is utilized to process the raw data provided by the DAQ
in order to ensure that the photoelectric peak corresponding to the Mn-K α
radiation is at its expected energy value (5895 eV) and that the noise peak
(corresponding to the noise of the baseline, detector, and preamplifier in the
absence of incident photon) is at 0 eV. Gaussian fitting is used to identify
the position of the the noise, Mn-Kα and Mn-Kβ in number of channels.
Later on, the script performs a transformation of the x-axis of the energy
spectrum first from channels to e− and then from e− to eV.
Figure 4.19 shows a typical spectrum acquired with a single SDD channel.
The noise peak can be seen at approximately 9500 channels while the MnKα and Mn-Kβ are at approximately 14000 and 14300 channels. In Figure
4.19, the peak to the left of the noise peak corresponds to the events where
the SDD had not received any incident X-ray photon. The noise peak,
attributed to the noise of the baseline, detector, and preamplifier is due to
the reading of SDD channel upon X-ray event occurring on another SDD
channel (polling-gamma readout). The x-axis is transformed into ’e− ’ by
first subtracting a constant from each SDD channel output to have all noise
peaks at 0 ’e− ’ and later on by multiplying each channel with a scaling
factor to have all Mn-Kα peaks at 1637.5 e− (corresponds to 5895 eV). The
magnitude of the subtraction in channels is defined to be the offset while the
ratio of the difference between the noise peak and Mn-Kα signal peak in e−
to channels is defined to be the gain. Figure 4.20 shows the x-axis calibrated
in equivalent number of photoelectrons.
90
4.3. Gamma-ray spectroscopy measurements
Figure 4.20: Spectrum in e− of the 55 Fe source measured at -20 ◦ C. The black lines are
the spectra, and the red lines are their Gaussian fittings. For Silicon the conversion
factor is 3.6 eV for each generated e− /hole pair.
ENC of the SDD channels for characterization is calculated for each SDD
channel from the Gausian fittings shown in Figure 4.20. This is achieved
by subtracting the intrinsic fanno contribution (119 eV at 5.895 keV) in
quadrature from the standard deviation of the Mn-Kα peak. The same can
be evaluated from the Gaussian fitting of Mn-Kβ peak as well. Figure 4.21
shows nine X-ray spectra of all the SDD channels acquired with of the
detection head shown in Figure 4.7. In Figure 4.21, under each spectrum,
the electronic noise in equivalent noise charge (ENC) is reported in electrons.
At a temperature of -20 ◦ C, the detection head is characterized by an average
ENC of 22 e− at 6 µs shaper peaking time. Similarly, Figure 4.22 shows
36 X-ray spectra corresponding to all SDD channels of the detection head
shown in Figure 4.8. Here, at a temperature of -20◦ C, the detection head is
characterized by an average leakage current of 14.8 pA while the average
ENC is 17.8 e− and 23.5 e− at shaper peaking times of 2 µs and 6 µs
respectively.
The average ENC and leakage current in Figure 4.22 have been calculated
by excluding channels on the extreme corners of the detector, which would
not be covered by the scintillator during γ-ray measurements owing to its
cylindrical geometry, as explained on page 82. In Figure 4.21 and Figure
4.22, the slight variations in ENC from channel to channel within an SDD
array exist because of different leakage current values of individual SDDs
91
Chapter 4. SDD for gamma-ray detection
Figure 4.21: 9 55 Fe spectra acquired with the one SDD module at -20 ◦ C with a peaking
time of 6 µs.
within that array due to statistical spread of fabrication process. In addition,
the detector on the extreme bottom right of Figure 4.22 has a very high
ENC due to back side damage during SDD mounting procedure. The SDD
array on the top left of Figure 4.8 belongs to a silicon wafer with higher
average leakage current and thereby possesses relatively higher ENC values.
The common high voltage biasing of all SDDs in an array (explained in
Section 4.2.2), does not produce penalties in the performance of individual
SDDs, except in a few, which show a much more significant tail on the left
of the Mn-Kα peak as seen in Figure 4.22. This tail exists in non-optimally
biased SDDs where the SDD unit’s depletion voltage is different from the
mean depletion voltage of the entire SDD detection head. This results in a
non optimal drift field within such an SDD unit resulting in a larger charge
collection time. For shorter shaper peaking times, this precipitates in a
much more prominent ballistic deficit effect specifically for X-ray events
occurring on the outer rim of the detector. However, this effect cannot be
seen in Figure 4.21 where a longer peaking time (i.e. 6 µs) is used for the
acquisition.
92
4.3. Gamma-ray spectroscopy measurements
Figure 4.22: 36 55 Fe spectra acquired with the four SDD modules at -22 ◦ C with a peaking
time of 2 µs.
4.3.2
Measurements with 100 LaBr3 :Ce
After performing X-ray calibration and characterization of the single SDD,
100 ×100 LaBr3 :Ce crystal is mounted on top of the detector by means of an
optical grease (BC-630 - Saint Gobain) and measurements are performed
at a temperature of -20 ◦ C. The detector is simultaneously irradiated with
three different sources: 57 Co, 137 Cs and 60 Co. In Figure 4.23(a), the energy
spectrum measured with 6 µs peaking time is shown, with a 3.0% energy
resolution measured at the 662 keV line. For reference, the same scintillator
sample, readout with a conventional PMT detector, shows an energy resolution of 3.2% at the same energy (private communication F. Quarati, Delft
University, Netherlands).
Non-linearity of the 100 gamma camera is evaluated by means of a linear fitting between the measured positions of the peaks in photoelectrons
(phe) and the nominal energies in keV, as depicted in Figure 4.23(b). The
maximum non-linearity calculated with this method is below 0.5
% over the
122 keV to 1330 keV energy range. A conversion gain of 21 phe/keV has
been measured with the 100 scintillator system at a peaking time of 6 µs.
This conversion gain corresponds to a configuration where no optical pad is
93
Chapter 4. SDD for gamma-ray detection
Figure 4.23: (a) Spectrum acquired with a SDDs matrix coupled to a 100 ×100 LaBr3 :Ce
scintillator and irradiated with three gamma-ray sources 57
( Co, 137 Cs and 60 Co). The
◦
temperature is -20 C and peaking time is 6 µs. (b) Linearity plot of the lines in the
spectrum. The maximum deviation from linear fitting is below 0.5%.
placed between the detector and the scintillator. However, in the presence
of the optical pad, the conversion gain drops to 18 phe/keV due to loss of
scintillation light at the interfaces.
4.3.3
Measurements with 200 LaBr3 :Ce
Figure 4.24: Detection head layout depicting the number of excluded channels in dark
blue.
Gamma-ray spectroscopy measurements are performed with the 200 LaBr3 :Ce
crystal by irradiating it separately with uncollimated133 Ba (302.9 keV, 356
keV), 22 Na (511 keV, 1274 keV), 137 Cs (661.7 keV), 88 Y (898 keV, 1836
94
4.3. Gamma-ray spectroscopy measurements
keV) and 60 Co (1173 keV, 1333 keV) sources. These spectra have been acquired with a shaper peaking time of 6 µs to minimize the "Ballistic deficit"
effect. "Ballistic deficit" occurs due to partial collection of charge generated
by incoming optical photons at the central charge collection electrode of the
SDD when the shaper peaking time is comparable to the drift time of the
charge carriers. The effect of ballistic deficit on achievable energy resolution
of a scintillator readout by SDDs and its relation with shaper peaking times,
are discussed in detail in subsection 2.3.4.
Figure 4.25: Gamma-ray spectra obtained with the gamma-camera at -25 ◦ C with 6 µs
shaper peaking time. A slight asymmetry in the left side of γ-ray peaks is due to scatter
from metallic components of the gamma-camera mechanics.
Owing to the cylindrical geometry of the scintillator in contrast to the
square format of SDD modules in the detection head as shown in Figure
4.4(c), certain SDD channels need to be excluded to improve performance
of the gamma camera. In addition, a few channels were slightly damaged
during the scintillator mounting procedure suffering an increase in their
leakage currents (and consequently ENC) due to back side damage. These
channels with low signal to noise ratio worsen the final achievable energy
resolution performance. Thereby, a series of optimizations are performed
on raw data to identify such SDD channels with very low signal/noise ratio
which are degrading the overall system’s performance. As a result of these
optimizations, the channels shown in Figure 4.24 in dark blue are excluded
from gamma-ray energy reconstruction. This optimization algorithm is
95
Chapter 4. SDD for gamma-ray detection
utilized only once for optimizing energy resolution of 661.7 keV peak and
the identified channels are excluded in all spectroscopic measurements
thereafter with the same detector configuration. Figure 4.25 shows the
spectra obtained separately with the different γ-ray sources (after excluding
channels with low signal/noise ratio) at a temperature of -25 ◦ C. Here, the
y-axis of the spectrum corresponding to each γ-ray source has been re-scaled
arbitrarily for better visualization.
Table 4.2: Measured photo-peak energies and corresponding linearity error
133
Ba
Ba
22
Na
137
Cs
88
Y
60
Co
22
Na
60
Co
88
Y
133
EPK
(keV)
302.9
356
511
661.7
898
1173
1274
1333
1836
Measured peak
(phe)
6617
7954
11790
15550
21390
28210
30680
32140
44510
Linearity Error
(%)
-0.469
-0.149
-0.081
+0.155
+0.078
+0.111
+0.040
+0.076
-0.119
A maximum linearity error less than 0.5% has been measured with the
100 ×100 LaBr3 :Ce readout by four SDD arrays in the energy range between
303 keV and 1836 keV. This linearity error has been evaluated by linearly
fitting the photo-peak energy in electrons to the corresponding energy in keV
(EP K ). These photo-peak energies and related errors are listed in Table 4.2
and plotted in Figure. 4.26. A maximum conversion gain of 27.24 phe/keV
has been measured with the gamma camera. In order to compare these
measurements, results obtained with the 200 LaBr3 :Ce readout by state of
the art PMTs in [56] can be referred. The conversion gain achieved with
our SDD-based camera can be compared to 20.5 phe/keV measured with a
similar 200 scintillator readout by a PMT. The higher conversion gain in case
of SDDs coupled to 200 ×200 LaBr3 :Ce is due to the relatively higher quantum
efficiency of SDDs. However, once the channels shown in dark blue in
Figure 4.24 are excluded to optimize energy resolution performance, the
conversion gain of the gamma-camera reduces to 24.73 phe/keV. In addition,
the exclusion of noisy SDD channels and a lower SDD temperature of -25
◦
C, improve the EN Cavg to 20.75 e− (@ 6 µs shaping time).
The energy resolution (R) in terms of percentage FWHM for γ-ray peaks
96
4.3. Gamma-ray spectroscopy measurements
Figure 4.26: (a) Linear fitting of photo-peak energy measured in photoelectrons vs the
corresponding energy in keV (b) Percentage error in linear fitting.
shown in Figure 4.25 are listed in Table 4.3. In addition, the statistical (RST ),
ENC (REN C ) and intrinsic ( RIN T ) contributions to the final energy resolution (R) are also listed. These contributions are obtained from the energy
resolution formula developed to consider ballistic deficit in subsection 2.3.4.
However, as for 6 µs shaper peaking time the effect of ballistic deficit is
negligible, the simplified formulas (4.1), (4.2) and (4.3) are used to calculate
RST , REN C and RIN T respectively.
r
1
RST = 2.355 ×
(4.1)
EP K × G
√
NSDD × EN Cavg
REN C = 2.355 ×
(4.2)
EP K × G
p
R = RIN T 2 + RST 2 + REN C 2
(4.3)
97
Chapter 4. SDD for gamma-ray detection
Where:
EP K = Peak Energy (keV)
G = Conversion gain = 24.73 phe/keV
NSDD = Number of SDDs = 28
EN Cavg = 20.75 e− @(-25 ◦ C, 6 µs)
Table 4.3: Measured energy resolution and its statistical, ENC and intrinsic contributions
for various gamma-ray peaks.
133
Ba
Ba
22
Na
137
Cs
88
Y
60
Co
22
Na
60
Co
88
Y
133
EPK
(keV)
302.9
356
511
661.7
898
1173
1274
1333
1836
R
(%)
5.22 ±0.09
4.98 ±0.07
4.01 ±0.04
3.38 ±0.06
2.83 ±0.08
2.39 ±0.03
2.38 ±0.05
2.25 ±0.04
1.96 ±0.04
RST
(%)
2.74
2.52
2.11
1.85
1.59
1.39
1.33
1.30
1.11
RENC
(%)
3.43
2.92
2.03
1.57
1.16
0.89
0.82
0.78
0.57
RINT
(%)
2.83
3.15
2.74
2.36
2.04
1.73
1.79
1.66
1.52
RST and REN C listed in Table 4.3 have been calculated for each energy
peak EP K with the conversion gain (G), number of SDDs (NSDD ) and
EN Cavg corresponding to the non-excluded channels depicted in light blue
in Figure 4.24 operated at a temperature of -25 ◦ C with 6 µs shaper peaking
time. The intrinsic contribution RIN T of the detection system is evaluated
by subtracting in square RST and REN C contributions from the measured
energy resolution R using (4.3).
The trend followed by the energy resolution and its contributing components as a function of energy is shown in Figure 4.27. An energy resolution
of 3.4% FWHM has been obtained at 662 keV, while 5.2% and 2% have
been obtained at 303 keV and 1856 keV respectively. It can be seen in
Figure 4.27 that as compared to the statistical and intrinsic contributions,
the ENC contribution undergoes a much sharper increase once we move to
lower gamma-ray energies. This ENC contribution is consistent with the
used SDD technology (leakage current ∼2 nA/cm2 @ room temperature).
However, a newer SDD technology with reduced leakage current is now
available and estimates of performance of the gamma-camera potentially
98
4.4. Comparison of SDD with PMT based readout
equipped with SDDs fabricated with the newer technology are discussed in
Section 4.4.
Figure 4.27: Measured energy resolution and its ENC, statistical and intrinsic components
as a function of energy.
4.4 Comparison of SDD with PMT based readout
The gamma-ray measurements presented in this chapter have been achieved
with large (100 and 200 ) LaBr3 :Ce crystals readout by SDD arrays with an
average leakage current of ∼2 nA/cm2 @ room temperature. With this
SDD technology, a 100 LaBr3 :Ce readout by a single SDD array is able
to achieve energy resolution performances similar to the PMT device as
described in Subsection 4.3.2. However, the scenario is different for the 2 00
LaBr3 :Ce readout by four SDD arrays. Comparing the energy resolution
measurements with SDDs (in Table 4.3) to results with PMT (in [56]), it
can be observed that at 1333 keV, the energy resolution achieved with SDDs
(2.25%) and with a PMT (2.30%) are more similar compared to 661.7 keV
(3.38% with SDD and 3.05% with a PMT). This occurs because at this energy
(1333 keV) the ENC contribution (which is negligible in PMT devices) is
smaller compared to lower energies as can be seen in Figure 4.27, where all
contributions to the energy resolution are plotted. As a consequence, the
99
Chapter 4. SDD for gamma-ray detection
statistical contribution starts to become the second dominating contribution
to the final energy resolution in case of SDD based gamma-camera, as it
does for the PMT based readout (intrinsic contribution is supposed to be
similar in both readouts). Here, the advantage of SDDs higher conversion
gain (maximum 24.73 phe/keV) compared to the PMT (maximum 20.5
phe/keV) and the lack of spread due to multiplication statistics starts to be
advantageous.
To thoroughly understand the limitation due to ENC contribution, SDD
electronic noise relation expressed by (4.4) can be considered [32]. Equation
(4.4) shows that the ENC depends on the noise contribution of input FET shot
noise (first term), the noise contribution due to input FET 1/f noise (second
term) and the contribution due to the shot noise of SDD’s leakage current
(third term). In case of current SDD technology and CUBE preamplifier,
the first two components of (4.4) are negligible as compared to the third
component at a temperature of -25 ◦ C and 6 µs shaper peaking time. Thereby
(4.4) can be approximately reduced to only the third contribution which is
reported in (4.5). Here, q is the electron’s charge, ILeakage is the leakage
current of the SDDs while τ and A3 are the shaper peaking time and shaping
filter’s coefficient.
1
EN C 2 = (Cd + Cg )2 a A1 + (Cd + Cg )2 cA2 + bτ A3
τ
(4.4)
EN C 2 ≈ 2qILeakage τ A3
(4.5)
From (4.5), we can see that reduction in ILeakage can significantly reduce
the ENC of the detector. An improved SDD technology with about 10
times lower leakage current of ∼ 200 pA/cm2 @ room temperature is
now available [41]. Comparison of the expected performances for the two
technologies are reported in Table 4.4. At -25 ◦ C and 6 µs peaking time, the
measured EN Cavg value of 20.8 e− has been obtained with the current SDD
technology. Supposing a reduction of 101/2 of the ENC using (4.5) at the
same peaking time, a value of 6.6 e− is expected with the newer technology.
In the estimations reported in Table 4.4, the measured conversion gain of
27.24 phe/keV and intrinsic contribution value of 2.36% @662 keV are
utilized. The number of SDD channels considered for the readout of 100 , 200
and 300 scintillators in Table 4.4 depend on the number of SDDs covered by
the cylindrical shape of the scintillators and has already been discussed in
Subsection 4.2.2.
With the current technology, an energy resolutions of 3.0% and 3.4%
have been achieved with 100 and 200 crystals as described in Subsections 4.3.2
100
4.4. Comparison of SDD with PMT based readout
Table 4.4: Noise estimation and corresponding energy resolution for different SDD technologies and scintillator sizes for 662 KeV energy peak.
ENCavg
(8×8 mm2 , -25 ◦ C )
Energy Resolution
100 crystal (9 SDDs)
Energy Resolution
200 crystal (32 SDDs)
Energy Resolution
300 crystal (69 SDDs)
Current SDD
Technology
(2 nA/cm2 @RT)
Improved SDD
Technology
(200 pA/cm2 @RT)
20.8 e−
6.6 e−
3.05 %∗
2.95 %
3.32 %∗∗
2.98 %
3.71 %
3.03 %
∗ To be compared with 3.0 % measured with 100 crystal with 21 phe/keV conversion.
∗∗ To be compared with 3.4 % measured in this work with 200 crystal with 24.73 phe/keV conversion
gain, 20.8 electrons of ENC and 28 SDDs.
and 4.3.3 respectively. In case of a 300 crystal, 3.71% is estimated with the
same technology owing to a larger number of SDDs needed for its readout.
The increase in number of readout SDDs from 9 to 69 for 1 00 to 300 crystals
respectively increases the projected energy resolution from 3.05% to 3.71%
according to (4.2) and (4.3). This degradation of performance which is
associated with the increase in the ENC contribution and is dependent upon
the number of readout SDDs and the leakage current of the SDD technology
used. Thereby, an improvement in SDD leakage current to an average of
200 pA/cm2 at Room temperature (10 times lower) can improve the final
energy resolution to 3% for all three formats at 662 keV.
In case of the newer SDD technology, the ENC contribution with a 200
and 300 crystal for 133Ba (302.9 keV) using (4.2) amounts to 1.17% and
1.72% respectively as compared to the current value of 3.43% with the
200 crystal. These contributions are much smaller as compared to the RST
and RIN T as listed in Table 4.3 for the same energy. With the reduced
leakage current values of the new SDD technology, the SDDs’ energy
resolution performance is expected to be dominated by statistics and intrinsic
contribution at energies as low as 300 keV. As SDDs have a higher quantum
efficiency and no multiplication spread, the final energy resolution at 300
keV is expected to be at least similar (if not better) to the PMT based readout
for both 200 and 300 LaBr3 :Ce scintillators with the new technology.
101
Chapter 4. SDD for gamma-ray detection
4.5 Summary
Although SDD devices were originally developed for X-ray applications,
they can also be used as photo-detectors for indirect detection of gammarays. SDDs have been coupled to various scintillators like CsI, NaI e.t.c to
achieve good energy resolution and linearity performances. In this chapter,
the first ever results obtained with large (100 and 200 ) LaBr3 :Ce readout by
SDD arrays are presented. The spectroscopy performance of the developed gamma-cameras have been evaluated to be slightly lower than the
PMT-based readout, however, the measured performance is consistent with
the leakage current of the used SDD technology. The SDD devices look
valuable for readout of large scintillators in the perspective of a reduction
of the leakage current. In the last subsection of this chapter, spectrometer
performance is estimated with low leakage SDDs (based on an improved
technology) for large sized LaBr3 :Ce crystals and the results have been
compared to PMT readout.
102
CHAPTER
5
Gamma-ray imaging measurements
5.1 Introduction
In last chapter, gamma-ray spectroscopy performance of SDDs coupled to
LaBr3 :Ce scintillators has been discussed in detail under a European Space
Agency sponsored technology research programme. In the reported discussion, thorough importance has been given to design issues and challenges
pertaining to the development of the gamma-cameras for the 100 and 200
LaBr3 :Ce crystals. Later on, this SDD based readout has been compared to
the state of the art PMT based solution to complete the arguments regarding
applications of SDD in gamma-ray spectroscopy.
This chapter focuses on study of position sensitivity of large LaBr3 :Ce
scintillators for nuclear physics research purposes. Experimental setups and
test results aimed at evaluation of position sensitivty of 100 and 200 LaBr3 :Ce
crystals coupled to SDD arrays are presented in this chapter.
5.1.1 Gamma-ray imaging
In many gamma-ray detectors, imaging instead of spectroscopy is the primary target to better investigate the radiation source. This is true for many
applications including gamma-ray astronomy, nuclear medicine, nuclear
103
Chapter 5. Gamma-ray imaging measurements
physics research and nuclear security purposes. This is generally achieved
by utilizing pixellated detectors employing direct and indirect conversion.
Among detectors employing direct conversion, coaxial HpGe detectors and
CdTe/CdZnTe detectors have been developed for medical and industrial
imaging in [74] and [75] respectively. These direct conversion imaging
detectors have really good energy resolution and imaging performances at
low gamma-ray energies however for energies above 150 keV they are no
longer that effective in stopping the incoming radiation. Thereby, indirect
detectors employing scintillators are coupled to photo-detector arrays to
perform imaging of high energy radiation sources. A collimation stage
followed by pixelated schintillators coupled to photo-detector pixels in a
1:1 ratio are used to achieve high position resolution performances. This
approach with pixellated scintillators is shown on the left of Figure 5.1.
Figure 5.1: (Left) Gamma camera based on a pixel-structured scintillator, the spatial
resolution is related to physical dimension of the pixel itself. An example of pixellated
scintillator is shown. (Right) Anger camera concept with a continuous scintillator.
However, an alternative strategy is to develop an Anger Camera which
can be seen on the right side of Figure 5.1 [76]. In this camera architecture,
instead of pixellated scintillator elements, a large continuous scintillator
is employed. This way the scintillation light generated by a gamma-ray
event is distributed among multiple photo-detector pixels. Later on, image
104
5.1. Introduction
reconstruction algorithms like a centroid method can be utilized to recover
the x and y coordinate of the incident gamma-ray. In pixellated cameras,
the position sensitivity of the device is determined by the size of the pixel
as per the Nyquist criteria. However, owing to the use of a continuous
scintillator, Anger camera enjoys a position resolution capability around ten
times smaller than the pixel size because of light signal sharing between
pixels. Hence larger pixels can be used for scintillator readout. Anger
camera imaging performances with SDDs and SiPMs coupled to CsI:Tl
scintillator are detailed in [77] and [78] respectively.
A major difference between the Anger camera and indirect detection
systems optimized for spectroscopy purposes is the thickness of the scintillator. In case of spectroscopy, a thick scintillator is desired to achieve high
detection efficiency and a larger dynamic range. However, in case of Anger
camera optimized for imaging, the scintillators are much thinner to avoid
the scintillation light spread over a large number of photo-detector units.
Furthermore, all four sides and top surface of the scintillator are processed
to make them less reflective to avoid totally internal reflections within the
scintillator to increase the useful field of view. These optimizations of the
scintillator has been thoroughly investigated with thick Cesium Iodide scintillator in [79]. Contrary to this, scintillators optimized for spectroscopy
are wrapped in layers of diffusers to avoid any loss of light signal from all
surfaces.
5.1.2
A position sensitive spectrometer
In this chapter, gamma-cameras described in chapter 4 are utilized to evaluate
the imaging capability of large LaBr3 :Ce crystals in the scope of an Instituto
Nazionale di Fisica Nucleare (INFN) sponsored project within GAMMA
experiment. The position sensitivity of LaBr3 :Ce readout by SDDs can in
principle be used in nuclear physics basic research to study nuclei far from
the stability line [80]. The imaging capability if exploited jointly with the
spectroscopy capability can help reduce an effect known as the Doppler
Broadening effect. Radioactive sources moving at high/relativistic velocities
with respect to the detector, emit gamma-rays which undergo an apparent
shift in energy similar to the acoustic Doppler. This apparent change in the
energy gives rise to a broadening of the gamma-ray peaks at the detector
and is referred to as the Doppler broadening effect. This effect is shown in
Figure 5.2 and is described in (5.1)
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Chapter 5. Gamma-ray imaging measurements
Figure 5.2: Principle of Doppler Broadening of a gamma-ray source moving at high/relativistic velocity.
Eγ =
Eγ0
q
1−
v2
c2
1 − vc cos(θ)
(5.1)
In principle, Information about the gamma-ray point of interaction inside
the crystal can be used in conjunction with particle velocity to determine
the angle of incidence of the incoming gamma radiation. This information
can help in reducing the Doppler worsening effect so that the intrinsic
performance of the detector can be recovered. Also in all such applications,
thick scintillators (1 cm) are mandatory to improve the detection efficiency
in combination with spatial and energy resolution.
In general, scintillators with a thickness/diameter ratio near or even
exceeding unity, are not suitable for imaging. This happens because the
correlation between light distribution and corresponding point of interaction
is degraded in crystals having larger thickness as compared to their diameter.
Furthermore, Halide scintillators are in general sold pre-packaged by the
manufacturer with Teflon wrapping on all sides (except for the optical
window) to optimize them for gamma-ray spectroscopy. Some hygroscopic
Halide scintillators like LaBr3 :Ce, LaCl3 :Ce, NaI e.t.c. are further sealed
in aluminum housing with a quartz optical window to protect them from
humidity. Although this Teflon wrapping, enclosed by the aluminum casing
for humidity protection, helps enhance the spectroscopic performance of the
scintillator, it aggravates the relation of gamma-ray’s point of interaction
in the crystal volume with the light distribution. Consequently, the image
sensitivity with such scintillators is degraded.
Another aspect to be considered in performing imaging with large crystals
106
5.1. Introduction
Figure 5.3: γ-ray simulation results showing points of interactions within a 300 LaBr3 :Ce
for a flood of incident radiation of (a) 150 keV and (b) 15 MeV.
is the depth of interaction of the incoming gamma-ray radiation especially
for low energy gamma-rays. This can be seen in Monte Carlo simulation
results depicting points of interactions within a 300 ×300 LaBr3 :Ce for a flood
of incident radiation in Figure 5.3. Here it can be seen that the large size of
the crystal, needed to achieve a high dynamic range, results in the absorption
of most low energy gamma-rays within the first few centimeters of the
crystal. This results in the generation of scintillation light which becomes
very diffused irrespective of the point of interaction as shown in Figure
5.3(a). Contrary to this, gamma-ray energies around 15 MeV at various
depths resulting in a photo-detector light collection which has a significant
signal from high depth interactions. As the scintillation light from these
high depth scintillation events is absorbed primarily by the photo-detectors
immediately below the interaction point, better imaging results are expected
to be attained using centroid methods.
Despite all the challenges, a position sensitivity of 1-2 cm in large volume
LaBr3 :Ce scintillators (100 ×100 and 300 ×300 ) has already been proved using
Position Sensitive PMTs (PSPMT) in [80]. In this context, experiments
are performed with SDD arrays to evaluate whether their high quantum
efficiency and multiple sub-units, provides any improvement over the 1-2
cm position sensitivity observed with PSPMT. With these aims, position
sensitivity experiments designed with 100 and 200 LaBr3 :Ce crystals and
corresponding measurements are carried out.
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Chapter 5. Gamma-ray imaging measurements
5.2 Position sensitivity of 100 LaBr3 :Ce
5.2.1
Experimental setup
In order to evaluate position sensitivity of 1 00 LaBr3 :Ce, a monolithic SDD
array with 9 individual SDD elements, each with an active area of 8×8 mm2
(overall 26×26 mm2 ) is used. This SDD array produced by FBK and detailed
architecture of the 100 gamma-camera used for these measurements are
described in chapter 4. This gamma-camera is cooled down to a temperature
of -20 ◦ C to lower the leakage current of the photodetector. Later on, a 1
mm collimated 137 Cs source is introduced to evaluate the distribution of
scintillation light among different SDD channels due to this point like source.
The 137 Cs source is collimated by placing it behind a 10 cm long block of
Tungsten-based alloy with a 1 mm hole drilled throughout its length. Setup
arrangement can be seen in Figure 5.4.
Figure 5.4: Cross section view of experimental setup depicting a 1 mm collimated 137 Cs
source and 100 gamma-camera.
It can be seen in Figure 5.4 that there is approximately 5 cm of distance
between the tungsten collimator and the scintillator. The scintillator cannot
be placed immediately next to the collimator as the gamma-camera mechan108
5.2. Position sensitivity of 100 LaBr3 :Ce
ics is placed in a 1 cm thick plastic casing necessary to maintain a humidity
free environment around the gamma-camera. Dry air is passed through
this plastic enclosure to ensure that no condensation occurs on the sensitive
electronics. The collimated source is fixed on a mechanical structure with
capability of movement in two axes in a plane parallel to the top plastic
surface of the gamma-camera. Using this assembly, the top of the scintillator
is scanned with steps of 5 mm (with an accuracy ±1 mm) along both the
horizontal and vertical directions to assess the position sensitivity of the
system. By position sensitivity, we refer to the capability of the detection
system to show variation in the light signal collected by every SDD based
on the position of the collimated source during the scan. Unfortunately,
after placing the scintillator for these measurements, one SDD on the corner
showed an anomalous behavior and hence its corresponding channel has
been excluded from this measurement.
Figure 5.5(left) refers to the scan along the vertical direction, where
the numbers 1 to 5 represent five different irradiation points, with one
acquisition of 2 minutes for each point. These measurements are performed
with a shaper peaking time of 6 µs at a temperature of -20 ◦ C. Since the
system must perform both spectroscopy and position measurements, it is
essential to verify that the measured spectra, determined as the sum of the
eight signals of the array, are position-independent, otherwise an undesired
broadening in the energy resolution is introduced. Figure 5.5(right) shows
the five spectra superimposed, with reduced resolution due to the missing
channel, whilst no relevant distortion of the 662 keV peak is evident.
5.2.2
Measurement results
The position sensitivity measurement results are presented in Figure 5.6(left).
The eight sub-plots represent the eight SDDs signals, while the x-axis is
related to the five irradiation spots with the notation introduced in Figure
5.5(left). The y-axis reports the number of photoelectrons measured by the
related SDD, calculated as the average value for all the detected gamma-rays
events. Therefore, the figure shows the average fraction of light readout by
each SDD as a function of the point of interaction. Moving the source from
the bottom (position 1) to the top part (position 5) of the scintillator, the
average signals vary with a coherent behavior. For example, subplot B and
H have an opposite trend: the average number of photoelectrons decreases
when the source moves away and increases as it gets closer. On the other
hand, subplot E reaches its maximum when the source is exactly on the
center of the scintillator.
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Chapter 5. Gamma-ray imaging measurements
Figure 5.5: (left) Scheme of the position measurement: the dashed green line is the
scintillator, the five circles represent the different points of irradiation. The upper left
SDD was not working properly and hence switched off. (right) The spectra of the five
irradiation points are well aligned, showing a negligible position-dependence on light
collection.
Figure 5.6: (left) Average distribution of photoelectrons readout by each SDD as a function
of the five points of irradiation. (right) The average signal is composed by a predominant
baseline (Φ) and a varying contribution (∆) which contains information about the
position of interaction.
In order to retrieve the position of interaction and to represent the acquisitions in a planar image, thorough analysis of the data is needed. In fact,
the Teflon wrapping and the ratio 1:1 between thickness and diameter of the
scintillator tend to spread light quite uniformly over all photodetector units,
with limited dependence from the point of interaction of the gamma event in
the crystal. It can be observed in Figure 5.6(right) that the average signal is
composed by a dominant constant component ( Φ), a baseline of thousands
110
5.3. Position sensitivity of 200 LaBr3 :Ce
of photoelectrons spread uniformly over all units, and an additional contribution (∆), which depends on the position of interaction, of only few hundreds
photoelectrons. One possibility to calculate the position of interaction is to
use a modified version of the centroid formula [81] shown in (5.2).
XC =
Σ(Qi − Φi )n xi
Σ(Qi − Φi )n
YC =
Σ(Qi − Φi )n yi
Σ(Qi − Φi )n
(5.2)
Here, Qi is the signal collected by the i-th detector, xi the coordinate of
its center and Φi is the baseline value to subtract. In the original formula,
Φ is a value equal for all the detectors, but not in our case, in which, e.g.
in the four corners, the units are only partially covered by the scintillator
and hence they receive less light than the central SDD. The parameter n is
usually set empirically with values between 1 and 3. In these reconstructions
n is considered 1.8. Figure 5.7 shows the reconstruction of five irradiation
points distributed on along both x and y axes. In the reconstruction of the
corresponding measured data with the mentioned algorithm, the system
seems to correctly track the change of position of the different irradiation
points.
5.3 Position sensitivity of 200 LaBr3 :Ce
5.3.1
Experimental setup
The experimental setup for performing imaging test with 200 LaBr3 :Ce is
similar to the one explained in subsection 5.2.1. However, in case of the 200
setup, four monolithic SDD arrays already described in detail in chapter 4
have been are utilized. Once, the gamma-camera is cooled down to a temperature of -22 ◦ C to lower the detector leakage current, a 1 mm collimated
137
Cs source is introduced to evaluate the distribution of scintillation light
among different SDD channels.This collimation is achieved by placing a 10
cm long block of Tungsten-based alloy with a 1 mm hole between the 137 Cs
source and the target. Setup arrangement can be seen in Figure 5.8.
It can be seen in Figure 5.8 that there is approximately 6.5 cm of distance
between the lead collimator and the scintillator. This distance results in
a slightly broadened gamma-ray beam. However, this broadening is very
minute and can be ignored. The top side of the 200 scintillator is scanned
with steps of 5 mm along both the horizontal and vertical directions to
assess whether the corresponding light distribution across the photodetector
is sensitive to this change. The detector configuration used for these tests is
different from the one described in subsection 4.3.3 as in case of imaging,
111
Chapter 5. Gamma-ray imaging measurements
Figure 5.7: Image reconstruction of five points arranged on a half cross on both x and y
coordinates. Even using a simple centroid method, a different position can be observed
in the reconstruction of the different points of irradiation. For reference, the squares
corresponding to the SDD units (8 mm side each) are also reported in the figure.
the signal to noise ratio of individual SDD units is not as important as it
is for spectroscopy. However, the SDD element on the extreme corners of
the detection-head have been excluded from measurements as they are not
covered by the scintillator.
5.3.2
Measurement results
Figure 5.9(left) refers to the scan of the gamma-camera where the positions
of the collimated beam with respect to the scintillator and the SDD arrays
can be seen. Here, the numbers marked 1 to 11 represent eleven different
irradiation points acquired along the horizontal axis. These measurements
are performed with a shaper peaking time of 6 µs at a temperature of -22
◦
C for a duration of 2 minuted each. Figure 5.9(right) shows the average
signal acquired by each SDD channel corresponding to 662 keV peak for all
11 of these points. It can be seen here that this average signal in each SDD
channel is sensitive to the position of the collimated SDD with the channel
in the center showing highest sensitivity. This additional sensitivity at the
center exists as most of the scintillation light finds its way towards the center
112
5.3. Position sensitivity of 200 LaBr3 :Ce
Figure 5.8: Cross section view of experimental setup depicting a 1 mm collimated 137 Cs
source and 200 gamma-camera.
Figure 5.9: (left) Scheme of the position measurement: the large circle represents the
scintillator, the twenty one filled circles represent the different points of irradiation.
(right) Average distribution of photoelectrons readout by each SDD as a function of
eleven points of irradiation along the horizontal axis are shown.
113
Chapter 5. Gamma-ray imaging measurements
of the scintillator owing to its cylindrical geometry and Teflon wrapping. In
addition, considering that most of the 662 keV gamma-rays are absorbed at
the same depth inside the 200 LaBr3 :Ce crystal’s volume as in case of the 100
crystal, the light undergoes more internal reflections and is more diffused
at the detector level. Figure 5.10(right) shows the same behavior for the
SDD channels for a vertical scan with numbers marked 1 to 11 in Figure
5.10(left)showing the eleven positions of the collimated source during the
scan. with reduced resolution due to the missing channel, whilst no relevant
distortion of the 662 keV peak is evident.
Figure 5.10: (left) Scheme of the position measurement: the large circle represents the
scintillator, the twenty one filled circles represent the different points of irradiation.
(right) Average distribution of photoelectrons readout by each SDD as a function of
eleven points of irradiation along the vertical axis are shown.
In order to reconstruct different point of interactions, the modified centroid method shown in (5.2) is utilized. However, the constant component
(Φ) is considered to be the average signal received by the SDD channels once
irradiated by the uncollimated 137 Cs source. In addition, the parameter n is
considered to be 1. The result of these reconstructions can be seen in Figure
5.11. Here the reconstructions are shown only for source positions marked
from 1 to 9 in the top left of the same figure. Here position 5 represents
the center of the scintillator. The reconstructed images are slightly shifted
toward top left as the collimation beam was not properly aligned with the
center of the scintillator and possessed a slight offset towards top left.
5.4 Summary
In this chapter, sensitivity of light distribution to the point of interaction of
the incoming gamma-rays has been studied. In case of both the 100 and 200
114
5.4. Summary
Figure 5.11: Image reconstruction of nine points arranged on a half cross on both x and y
coordinates. Utlizing a simple centroid method, differences in the reconstructed images
can be observed for different points of irradiation. The squares corresponding to the
SDD units (8 mm side each) are reported for reference.
LaBr3 :Ce readout by SDDs, this sensitivity has been found to exist. However,
the 1:1 ratio between the height and the diameter of these scintillators
thoroughly diffuse the light output and position sensitivity is greatly reduced.
In case of 100 crystal, utilizing a modified centroid method an apparent
position resolution FWHM of minimum 8 mm has been observed at its
center. The useful field of view is also reduced from 25.4 mm diameter to
approximately 16 mm diameter.
In case of 200 crystal, utilizing the modified centroid method an apparent
position resolution FWHM of minimum 12 mm has been observed. The
useful field of view is also reduced from 50.8 mm diameter to around 35
mm diameter.
115
CHAPTER
6
Discussions and Conclusion
The first part of this dissertation provides a background of radiation detection
systems while providing an insight to their evolution throughout history and
the positive role such systems are playing in the modern day society. Before
1980, all the solid state detectors were basically Lithium Drifted Detectors,
however this all changed in the early 1980s when Silicon based detectors
like Planar PN diodes, Silicon micro-strip detectors and Multi-electrode
Silicon detectors were introduced for radiation detection. During these
times, Silicon Drift Detector was introduced by E. Gatti and P. Rehak in
1983 with the unique concept of sidewards depletion. SDD, similar to most
solid state detectors, relies on generation of charge carriers due to interaction
of ionizing radiation in the depleted region which are then collected at the
output charge collection anode. The SDD devices, however, stand out among
the rest as they have a fixed output capacitance at the signal readout anode
which is independent of the total device active area. A small detector output
capacitance results in a much lower series and flicker noise contributions
during detector readout. This also allow development of large area detectors
as well as operation at shorter acquisition times allowing operation at higher
input count rates. This makes SDD devices the detector of choice for X-ray
detection even today.
117
Chapter 6. Discussions and Conclusion
Chapter 3 of this dissertation describes the development and characterization of monolithic arrays of SDDs and readout electronics for X-ray
applications. One of these applications requires SDDs, readout by CUBE
preamplifier, to be cooled down to cryogenic temperatures to reduce the drift
time of electrons as electron mobility increases at such low temperatures.
In this application for Siddharta experiment, a lower SDD drift time allows
placement of a strict timing window to maximize detection of X-rays generated by kaonic atoms as compared to the asynchronous background events.
A fast trigger signal corresponding to indirect conversion with a scintillator
readout by a PMT is provided to the readout electronics to begin such a timing window. For Siddharta like experiments where the useful events are very
rare as compared to the background events, the detection efficiency of such
rare events is optimized by the implementation of timing window as well as
by increasing the geometrical efficiency of the detector. In Siddharta a total
of 384 individual SDD units of 8×8 mm2 are employed in the form of a ring
to maximize useful signal detection signal. At cryogenic temperature, such
large area of individual SDD unit does not penalize their X-ray spectroscopy
performance due to leakage current or ballistic deficit. The last statement
has been thoroughly tested by designing conclusive experiments performed
at different temperatures with single as well as array of SDDs (8×8 mm2
individual SDD active area). At a temperature of 75 K, an energy resolution
of 124.7 eV has been measured with the single SDD utilizing commercially
available shaping amplifier Tennelec 244. With a hexagonal SDD (active
area of 10 mm2 ) readout with the CUBE preamplifier, an energy resolution
of 122.1 eV has been measured with SFERA readout ASIC which is the
best result available in literature with SDDs. This CUBE and SFERA used
for this measurement are specifically designed to achieve best X-ray spectroscopy performance for Siddharta project. More experiments are currently
underway to evaluate the minimum timing window achievable with SDDs
as well as characterization of Siddharta array at cryogenic temperatures.
Another solution to reduce SDD output signal collection time to achieve
faster operation is to decrease SDD’s active area. This is possible for
applications like fluorescence where the solid angle formed by the detector
around the target instead of the absolute area of the detector itself is the
key factor determining detector’s geometrical efficiency. This strategy is
being opted for X-ray imaging by a new detector called Maia, employing
monolithic silicon detector array with individual units of 1 mm2 [52]. With
Maia, a maximum output count rate of 4 to 16 Mcps is achievable with
96 and 384 individual pixels respectively with a normalized count rate of
maximum 41.66 kcps/mm2 . Maia detector forms a very complex design
118
with electrical bonding connections from each SDD unit to a readout board.
Also the probability of successfully fabricating a monolithic array with all
96 or 384 SDD units functioning is very low explaining why Maia took
many years just to achieve a working 96 unit array. Compared to this,
we are developing a much more simple modular detector with monolithic
SDD arrays with four individual elements within Ardesia project for X-ray
absorption fine structure spectroscopy (XAFS) application. In Ardesia, each
SDD unit has an active area of 25 mm2 which is cooled down to -20 ◦ C
to achieve an acceptable energy resolution under 150 eV FWHM (200 ns
shpaing time). Also for each channel, an output count rate of 500 to 1000
kcps (maximum 40 kcps/mm2 ) can be achieved in Ardesia with analog and
digital pulse processing solutions respectively. This can result in a single
module of four being capable of operation at output count rates of 2 Mcps to
4 Mcps with a fill factor of 79% due to collimation. The biggest advantage
of Ardesia is that owing to modular detector design, four and nine individual
modules can be put together to achieve maximum count rates up to 16 and
36 Mcps with fill factors of 43.5% and 37% respectively. The increase in
dead area is a penalty associated with the modular nature of the Ardesia
module design. Work is in progress on this project.
When we compare SDD with other available detectors, we find that an
an energy resolution of 115 eV FWHM (at Mn Kα line) has already been
achieved with high purity Germanium (HpGe) detectors in 2003 [82] while
an incredibly low energy resolution of 15.5 eV FWHM (at Mn Kα line) has
been achieved with a Superconducting Tunnel Junction in 2000 [83]. Contrary to these devices, SDD has an intrinsic Fano limitation of around 119
eV FWHM (at Mn Kα line) and performance better than this is not possible.
However, the major advantage of SDD is the possibility of operation at much
higher temperatures with room temperature operation already within reach
for small device areas. Another advantage of SDD and other silicon based
X-ray detectors is the very low cost of the detectors themselves owing to the
large scale development of the silicon based semiconductor technology over
the years. For example, for applications similar to Siddharta where detector
arrays are needed to populate a ring to form ∼ 300 cm2 of detector surface
area, solutions based on HpGe and STJ are not practical due to extremely
high cost. In addition, energy resolution achievable with SDDs is more than
sufficient for many X-ray detection applications. However, there is still a
lot of room for improvement to fully reach the maximum potential of SDD
devices in the field of X-ray spectroscopy and this thesis explains some of
these improvements.
SDDs are not only confined to X-ray spectroscopy and Chapter 4 and
119
Chapter 6. Discussions and Conclusion
Chapter 5 discusses its use for γ-ray spectroscopy applications using indirect conversion detection. The high quantum efficiency QE (around 80%
at 380 nm) of SDDs, which is similar to the PIN diode and Avalanche
Photodiodes (APDs), helps achieve a really good statistics to reduce the
overall energy resolution of the detection system. This provides SDD with
an advantage over the traditionally used Photomultiplier tube (PMT) and
a relatively recent device Silicon PhotoMultiplier (SiPM) which have a
QE of ∼ 30% and a Photon detection efficiency PDE of around ∼ 35%
respectively. However, these devices employ multiplication which greatly
reduces the electronics noise of subsequent readout stages as compared to
SDDs which have a significant electronics noise worsening contribution of
the achievable energy resolution relation especially for large photo detector
areas for readout of continuous scintillator for spectroscopy applications.
Such continuous scintillators for γ-ray spectroscopy are generally made
with a 1:1 ratio between thickness to diameter to improve detection efficiency and have a nearly uniform scintillation light output. The primary
reason for worsening of the energy resolution performance of SDDs with
such continuous scintillators is the low Signal to noise ratio per SDD. If
we further split the SDD into multiple smaller units to reduce the ballistic
deficit and leakage current of individual SDD subunits, the equivalent noise
charge ENC per SDD will reduce but so will the light signal per SDD unit.
This results in a low light signal to electronic noise ratio per SDD providing
a relatively worse energy resolution performance irrespective of the absolute
value of ENC of individual SDD subunit. In this dissertation, this effect
has been experimentally evaluated in the scope of a European space agency
sponsored project by reading out 100 ×100 and 200 ×200 Lanthanum Bromide
scintillators and comparing the results with a PMT. An energy resolution
of 3% at 662 keV has been achieved with a 100 LaBr3 :Ce readout by both
SDD (total active area of 576 mm2 ) and a PMT. However, once a larger
200 LaBr3 :Ce is utilized, an energy resolution of 3.05% is achieved with a
PMT while 3.38% is achieved with SDDs (total active area of 1792 mm2 )
respectively at 662 keV. This situation is seen to gradually improve with
increase in the energy of the incidentγ-ray photon and around 1 MeV both
the devices have similar performance and at higher energies SDDs begin
to show better performance even with a 200 crystal. The answer is again
embedded in the SNR ratio as a higher incident photon energy generates
a larger number of scintillation photon which improve the signal vs noise
ratio per SDD channel. Also as the SDDs basically have a higher quantum
efficiency as compared to the PMT device, the SDDs begin to dominate
at higher energies as both devices are now being limited only by Poisson
120
statistics.
This SNR issue with SDD based readout of large LaBr 3 :Ce is expected
to be greatly improved as new SDD devices with ten times lower leakage
current have now being developed by FBK. Estimates have shown that
this decrease is sufficient to match the energy resolution performance with
SDDs and PMTs for energies as low as 662 keV even for the readout
of 300 crystals. However, for lower energies, the SNR per SDD sub-unit
again drops low while PMT regains its advantage. One possible solution to
improve the situation for SDD with all scintillator format and all energies
is by replacing the continuous scintillator into pixelated form with Teflon
wrapping covering each pixelated crystal. As 576 mm2 SDD photo-detector
readout active area has no penalty in reading the scintillator, four and nine
pixelated crystals with 576 mm2 ×762 mm of readout surface area each,
can be used instead of the 200 and 300 crystal respectively. This way, the
total size of the scintillator remains the same with the same geometrical and
detection efficiency, however, for every scintillation event, the amount of
light received per pixel is maximized.
Utilizing the SDD arrays, position sensitivity of the cylindrical 100 ×100
and 200 ×200 LaBr3 :Ce have also been evaluated with SDD arrays for a possible application in reduction of Doppler broadening effect. This effect
takes place when γ-rays, produced by a radioactive nuclei traveling at near
relativistic speeds, produces γ-rays that undergoes Doppler shifts resulting
in a broadening of the energy resolution. Measurements performed with a
collimated γ-ray source have shown that despite the large height to diameter
ratio of these scintillators, position sensitivity does in fact exist in both the
scintillator formats. Post processed data shows that the light signal received
by individual SDD units undergoes a changes based on the position of the
collimated beam. The next step in this work is to develop use this γ camera
to perform measurements with γ-ray source moving at relativistic tangential velocity and attempt to reduce the Doppler broadening of the acquired
energy spectra.
121
List of Acronyms
ARDESIA Arrays of Detectors for Synchrotron Radiation Applications
ASIC Application Specific Integrated Circuit
CSA Charge Sensitive Apmlifier
CUBE CMOS based charge sensitive preamplifier
DAQ Data Acquisitionon
DPP Digital Pulse Processors
EDS Energy Dispersive Spectrometers
EDX Energy-Dispersive X-ray spectroscopy
ENC Equivalent Noise Charge
ESA European Space Agency
EXAFS Extended X-ray Absorption Fine Structure
FBK Fondazione Bruno Kessler
FWHM Full-Width-at-Half-Maximum
HpGe High Purity Germanium
INFN Instituto Nazionale di Fisica Nucleare
MGNS Mercury Gamma and Neutron Spectrometer
123
MGRS Mercury Gamma-Ray Spectrometer
PDE Photon Detection Efficiency. It is defined for SiPMs as the quantity of
photon-discharged cells divided by the quantity of incident photons.
PMT Photo-Multiplier Tube
PSD Power Spectral Density
PUR Pile Up Rejection
SDD Silicon Drift Detector
SIDDHARTA SIlicon Drift Detector for Hadronic Atom Research by Timing Application
SiPM Silicon Photo-Multiplier
SNR Signal-to-Noise Ratio
STJ Superconducting Tunnel Junction
XAFS X-Ray Absorption Fine structure Spectroscopy
XFH X-ray Fluorescence Holography
XRF X-Ray Fluorescence
124
List of Figures
1.1 One of the very first images ever taken using X-rays or "Rontgen Rays" by Rontgen. This image shows the bones of hand
and has been taken on 22nd December 1895.(Deutches Museum Munich) . . . . . . . . . . . . . . . . . . . . . . . . .
2
1.2 Early cloud chamber photograph taken by C. T. R. Wilson
in 1911 showing the tracks of electrons released when Xrays passed through the chamber. (Source: C. T. R. Wilson,
Cambridge) . . . . . . . . . . . . . . . . . . . . . . . . . .
3
1.3 A schematic diagram depicting the working of a parallel plate
ionization chamber. [1] . . . . . . . . . . . . . . . . . . . .
5
1.4 ATLAS detector probes, weighing over a 1000 tonnes, can
be seen here assembled to detect fundamental particles [2]. .
6
1.5 The principal γ-ray emissions due to both natural radioactivity and interaction of cosmic rays with matter. [5] . . . . . .
7
1.6 Proton beam range measurement with a slit gamma camera. [7] 8
1.7 Mass attenuation coefficients for Argon, Silicon and Germanium. The photoelectric, Compton and Rayleigh components
of the total attenuation are also indicated in the graphs. [10]
9
1.8 Linear attenuation coefficients for photo absorption and Compton scattering in CdTe, Si, Ge, and NaI:Tl. [11] . . . . . . . 11
1.9 Gamma and X-ray absorption efficiency for various thicknesses of BrilLanCe 380 material (Saint Gobain commercial
product name for Cerium doped Lanthanum Bromide scintillator). [12] . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
125
List of Figures
2.1 (a) Depletion of a PIN diode. (b) Partial and (c)full side-ward
depletion in a modified PIN diode. . . . . . . . . . . . . . .
2.2 SDD working principle: e− /hole pairs generated by ionizing
radiation within the depletion region are separated by the
electric field. . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Diagrams showing (a) electron energy potential in the drift
region of the SDD and (b) in the region close to the anode
where the potential valley is directed towards the surface. . .
2.4 SDD for X-ray spectroscopy: (a) schematic structure with
the p+ back contact and (b) electric potential energy diagram.
2.5 Measurements of QE for a Diode (circles), a test SDD (squares)
and a theoretical limit (line). Courtesy Fondazione Bruno
Kessler . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6 Example of output electrode current (iD (t)) waveform variation for different drift times. . . . . . . . . . . . . . . . . .
2.7 (Top): Equipotential lines in a cross section of the device
from the center, on the left, where the anode is placed (topleft) to the boundary of the device, on the right. The larger
separation in space of the equipotential lines close to the
border of the device, on the right, implies a lower electric
field in these regions. (Bottom): Drift time vs. injection point
of the charge along the radius of the SDD. [30] . . . . . . .
2.8 Example of filter output signals in case of ideal delta-like
input (blue curve) and real input signal from SDDs (red curve).
2.9 (Left) Simulated drift time distribution and (right) anode
signal composed as result of charge collected in different
zones (with different drift times) for an 8×8 mm2 square
SDD. [31] . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.10 Basic SDD readout blocks depicting the Preamplifier, the
Shaper amplifier, the Peak stretcher and the ADC. . . . . . .
2.11 Signal processing chain electrical-model with equivalent
noise generators. [17] . . . . . . . . . . . . . . . . . . . . .
2.12 Typical trend of the system ENC as a function of the shaping
time. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Diagram showing kaon knocking out and substituting an
electron in Hdrogen atom and resulting transitions of kaon to
ground state. . . . . . . . . . . . . . . . . . . . . . . . . .
3.2 Strategy to reject asynchronous background events. [40] . .
126
17
17
18
19
23
25
27
28
29
30
32
34
36
37
List of Figures
3.3 A section of SIDDHARTA-1 detection ring of the machine
(left) and single detection module made of 3 SDDs each (right).
3.4 Anode side view of monolithic array of eight 64 mm2 SDD
units designed for Siddharta-2 can be seen arranged in a
2×4 format with a total active area of 512 mm 2 . A zoom of
the central anode region of the SDD shows the presence of
anode and Ring 1 pads and absence of any integrated charge
preamplifier. . . . . . . . . . . . . . . . . . . . . . . . . . .
3.5 (a) The ceramic board of Siddharta-2 module can be seen with
holes to facilitated bonding of the SDD units and placement
of charge pre-amplifiers. (b) Back side view of the 2×4 SDD
array. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.6 SDD-based detection rings designed for the DAΦNE (left)
and J-PARC (right) colliders. . . . . . . . . . . . . . . . . .
3.7 SDD readout by the CUBE charge preamplifier. . . . . . . .
3.8 Example of detection module characterization setup made of
a single SDD unit and a CUBE charge preamplifier. . . . . .
3.9 Charge preamplifier output voltage behavior and the digital
pulsed-reset signal. . . . . . . . . . . . . . . . . . . . . . .
3.10 Simplified Model of ASIC Block Diagram for ESA project.
3.11 SFERA simplified block diagram and complete acquisition
chain. [49] . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.12 Fast and main SA output semi-Gaussian pulse at 0.2, 0.5, 2,
3, 4, and 6 µs peaking time respectively. . . . . . . . . . . .
3.13 Pile-up rejection cases for the 500 ns peaking time: both
pulses are discarded (a), only the first is processed (b) and
both of them are acquired (c). . . . . . . . . . . . . . . . .
3.14 (Left)Energy resolution (FWHM) at Mn-Kα energy line
achieved with a 10 mm2 SDD at temperature of 10 and 20
◦
C. (Right) 55 Fe spectrum for a shaping time of 0.25 µs and
temperature of 20 ◦ C. . . . . . . . . . . . . . . . . . . . . .
3.15 Experimental setup for single SDD unit. . . . . . . . . . . .
3.16 Experimental set-up test PCBs arrangement (left) and detail
of the chip carrier hosting the CQZ package in which the IC
is wire-bonded (right). [43] . . . . . . . . . . . . . . . . . .
3.17 Energy spectrum of a 55 Fe source measured with a roundshaped 10 mm2 area single SDD at -35 ◦ C and 4 µs peaking
time. A signal amplification of 4 is interposed between CUBE
and SFERA. . . . . . . . . . . . . . . . . . . . . . . . . . .
127
38
39
40
41
42
43
44
46
47
48
48
50
51
51
52
List of Figures
3.18 SFERA energy resolution for all the implemented peaking
times compared with the commercial shaping amplifier Tennelec TC 244 performance. A signal amplification of four is
interposed between CUBE and SFERA. . . . . . . . . . . .
3.19 SFERA energy resolution for all the implemented peaking
times and compared with the external shaper Tennelec TC
244 performance. Direct connection between CUBE and
SFERA with no amplification in between. . . . . . . . . . .
3.20 Block diagram depicting a 8×8 mm2 SDD attached to a cold
finger. In vacuum chamber, the SDD had successfully been
cooled down to 50 K with such a setup. . . . . . . . . . . .
3.21 (Top)Energy resolutions achieved with CUBE coupled to
an 8×8 mm2 square-shaped SDD at different filter shaping
times and temperatures. (Bottom) Energy resolution of the
64 mm2 SDD at the Mn-Kα line at 50 K with shaping time
of 2 µs. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.22 Low energy X-ray lines measured with a 8×8 mm2 detector. L and K lines of various elements including Fluorine
and Aluminum are indicated. This measurement has been
obtained at a temperature of 150 K. [49] . . . . . . . . . . .
3.23 Back (a) and front view (b) of the 3×3 SDD matrix hosted
on the ceramic PCB and mounted on a copper cooling block.
3.24 Experimental setup for characterization of SDD array. . . .
3.25 SDD array characterization result with ESA chip at a temperature of -35 ◦ C with 4 µs shaping time. . . . . . . . . . . .
3.26 SDD array characterization result with SFERA chip at a
temperature of -35 ◦ C with 4 µs shaping time. . . . . . . . .
3.27 SDD array mounted on a cold finger in vacuum chamber to
perform spectroscopy at around 150 K. . . . . . . . . . . .
3.28 Energy resolution for Mn-Kα energy line for a 10 mm2 SDD
vs. peaking times and temperature. The SDD belongs to SDD
class with 200 pA/cm 2 leakage current at room temperature.
[51] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.29 SDD array layout of the two realized detector topologies,
with (a) squared and (b) circular detectors being developed
at FBK . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.30 Ardesia detection module design for single SDD array. . . .
63
64
4.1 Response of scintillator as a function of temperature with a
fixed PMT temperature. [57] . . . . . . . . . . . . . . . . .
71
128
53
53
54
55
56
57
58
59
59
61
62
List of Figures
4.2 The spectrum of the self-activity of the LaBr3 :Ce detector. [60]
4.3 Images of the Cygnus X-1 region from INTEGRAL four
detectors are superimposed on an artist’s impression of the
black hole and companion star discovered in autumn of 2002.
Copyright: ESA. Illustration by the Integral team and ESA/ECF.
4.4 (a) Anode side of single SDD with active area 8×8 mm2 .
(b) Layout of one SDD monolithic array (26×26 mm2 ), suitable for 100 crystal readout. (c) Drawing of 4 SDD modules
arranged in a 2×2 format. The total photo-detector area is
52×52 mm2 , suitable for the 200 crystal readout. . . . . . . .
4.5 Biasing of the back electrode by punch-through mechanism.
4.6 (a) An SDD array mounted on a ceramic carrier hosting
CUBE preamplifiers. (b) An SDD module containing an SDD
array, ceramic carrier, copper cooling block and a flexible PCB.
4.7 One SDD modules can be seen connected to an interconnection PCB. The total photo-detector area is 26×26 mm2 which
is sufficient to read a 100 ×100 crystal. . . . . . . . . . . . . .
4.8 Photodetector with four SDD modules mounted in 2×2 format to achieve a total detector area of 52×52 mm2 . . . . . .
4.9 Preliminary intermediate PCB dedicated to biasing and routing signals of 1 SDD module. . . . . . . . . . . . . . . . .
4.10 Upgraded intermediate PCB dedicated to biasing and routing
signals of up to nine SDD modules. . . . . . . . . . . . . .
4.11 (a) Motherboard hosting three ASIC carrier boards capable
of reading out 81 SDD channels. (b) Board that hosts the
custom designed ASIC directly bonded on the board. . . . .
4.12 Block diagram of readout and acquisition system of the
gamma-camera with capability of readout of up to 81 SDDs
corresponding to a 300 scintillator. . . . . . . . . . . . . . .
4.13 Steady-state thermal simulation result of 100 gamma-camera’s
mechanics with 9.6 Watts of power being removed from the
setup. Temperature gradient across the crystal is expected to
be always less than the one measured by temperature sensors.
4.14 Steady-state thermal simulation result of 200 gamma-camera’s
mechanics with 31 Watts of power being removed from the
setup. Temperature gradient across the crystal is expected to
be always less than the one measured by temperature sensors.
4.15 Assembled gamma-camera mechanics for cooling single
SDD modules coupled with a 100 ×100 LaBr3 :Ce crystal . . .
129
72
74
77
77
78
79
79
80
81
82
82
83
84
85
List of Figures
4.16 Exploded view of 3D model of mechanics for cooling down
four SDD modules coupled with 200 ×200 LaBr3 :Ce crystal. .
86
4.17 Block diagram of the second stage of the cooling system
depicting the interconnections of temperature sensor, Peltier
modules, power supply and the PC in the cooling system. . .
87
4.18 Measured temperature gradient across the scintillator, while
the SDDs are being cooled down to -20 ◦ C @8 ◦ C/hour. A
zoom of the response of last 20 minutes (on the top right)
shows that temperature gradient across temperature sensors
is ensured to be less than 3 ◦ C. . . . . . . . . . . . . . . . .
88
55
4.19 Energy spectrum in channels of the Fe source measured at
-20 ◦ C. Only one channel is presented for the sake of simplicity. 90
4.20 Spectrum in e− of the 55 Fe source measured at -20 ◦ C. The
black lines are the spectra, and the red lines are their Gaussian
fittings. For Silicon the conversion factor is 3.6 eV for each
generated e− /hole pair. . . . . . . . . . . . . . . . . . . . .
91
◦
55
4.21 9 Fe spectra acquired with the one SDD module at -20 C
with a peaking time of 6 µs. . . . . . . . . . . . . . . . . .
92
55
4.22 36 Fe spectra acquired with the four SDD modules at -22
◦
C with a peaking time of 2 µs. . . . . . . . . . . . . . . . .
93
4.23 (a) Spectrum acquired with a SDDs matrix coupled to a
100 ×100 LaBr3 :Ce scintillator and irradiated with three gammaray sources (57 Co, 137 Cs and 60 Co). The temperature is -20
◦
C and peaking time is 6 µs. (b) Linearity plot of the lines in
the spectrum. The maximum deviation from linear fitting is
below 0.5%. . . . . . . . . . . . . . . . . . . . . . . . . . .
94
4.24 Detection head layout depicting the number of excluded channels in dark blue. . . . . . . . . . . . . . . . . . . . . . . .
94
4.25 Gamma-ray spectra obtained with the gamma-camera at -25
◦
C with 6 µs shaper peaking time. A slight asymmetry in
the left side of γ-ray peaks is due to scatter from metallic
components of the gamma-camera mechanics. . . . . . . . .
95
4.26 (a) Linear fitting of photo-peak energy measured in photoelectrons vs the corresponding energy in keV (b) Percentage
error in linear fitting. . . . . . . . . . . . . . . . . . . . . .
97
4.27 Measured energy resolution and its ENC, statistical and intrinsic components as a function of energy. . . . . . . . . .
99
130
List of Figures
5.1 (Left) Gamma camera based on a pixel-structured scintillator,
the spatial resolution is related to physical dimension of the
pixel itself. An example of pixellated scintillator is shown.
(Right) Anger camera concept with a continuous scintillator.
104
5.2 Principle of Doppler Broadening of a gamma-ray source
moving at high/relativistic velocity. . . . . . . . . . . . . . 106
5.3 γ-ray simulation results showing points of interactions within
a 300 LaBr3 :Ce for a flood of incident radiation of (a) 150 keV
and (b) 15 MeV. . . . . . . . . . . . . . . . . . . . . . . . . 107
5.4 Cross section view of experimental setup depicting a 1 mm
collimated 137 Cs source and 100 gamma-camera. . . . . . . . 108
5.5 (left) Scheme of the position measurement: the dashed green
line is the scintillator, the five circles represent the different
points of irradiation. The upper left SDD was not working
properly and hence switched off. (right) The spectra of the
five irradiation points are well aligned, showing a negligible
position-dependence on light collection. . . . . . . . . . . . 110
5.6 (left) Average distribution of photoelectrons readout by each
SDD as a function of the five points of irradiation. (right) The
average signal is composed by a predominant baseline (Φ)
and a varying contribution (∆) which contains information
about the position of interaction. . . . . . . . . . . . . . . . 110
5.7 Image reconstruction of five points arranged on a half cross
on both x and y coordinates. Even using a simple centroid
method, a different position can be observed in the reconstruction of the different points of irradiation. For reference,
the squares corresponding to the SDD units (8 mm side each)
are also reported in the figure. . . . . . . . . . . . . . . . . 112
5.8 Cross section view of experimental setup depicting a 1 mm
collimated 137 Cs source and 200 gamma-camera. . . . . . . . 113
5.9 (left) Scheme of the position measurement: the large circle represents the scintillator, the twenty one filled circles
represent the different points of irradiation. (right) Average
distribution of photoelectrons readout by each SDD as a function of eleven points of irradiation along the horizontal axis
are shown. . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
131
List of Figures
5.10 (left) Scheme of the position measurement: the large circle represents the scintillator, the twenty one filled circles
represent the different points of irradiation. (right) Average
distribution of photoelectrons readout by each SDD as a function of eleven points of irradiation along the vertical axis are
shown. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
5.11 Image reconstruction of nine points arranged on a half cross
on both x and y coordinates. Utlizing a simple centroid
method, differences in the reconstructed images can be observed for different points of irradiation. The squares corresponding to the SDD units (8 mm side each) are reported for
reference. . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
132
List of Tables
2.1 Property summary of the most common scintillation photodetectors. . . . . . . . . . . . . . . . . . . . . . . . . . . .
24
4.1 Comparison between emitted light wavelength, yield and
decay time of some scintillators. [56] . . . . . . . . . . . . 70
4.2 Measured photo-peak energies and corresponding linearity
error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
4.3 Measured energy resolution and its statistical, ENC and intrinsic contributions for various gamma-ray peaks. . . . . . 98
4.4 Noise estimation and corresponding energy resolution for
different SDD technologies and scintillator sizes for 662 KeV
energy peak. . . . . . . . . . . . . . . . . . . . . . . . . . 101
133
Bibliography
[1] G. F. Knoll in Radiation detection and measurement, New York: Wiley, third ed., 1999.
[2] http://home.web.cern.ch/about/experiments/atlas.
[3] G. Aad, T. Abajyan, B. Abbott, J. Abdallah, S. A. Khalek, and A. A. et. al., “Observation of a
new particle in the search for the standard model higgs boson with the {ATLAS} detector at the
{LHC},” Physics Letters B, vol. 716, no. 1, pp. 1 – 29, 2012.
[4] http://www.nasa.gov/content/fermi/overview.
[5] S. Kraft, E. Maddox, E.-J. Buis, A. Owens, F. Quarati, P. Dorenbos, W. Drozdowski, A. J.
Bos, J. de Haas, H. Brouwer, C. Dathy, V. Ouspenski, S. Brandenburg, and R. Ostendorf,
“Development and characterization of large la-halide gamma-ray scintillators for future planetary
missions,” Nuclear Science, IEEE Transactions on, vol. 54, pp. 873–878, Aug 2007.
[6] T. Ma, J. Chang, N. Zhang, W. Jian, M. Cai, Y. Gong, H. Tang, R. Zhang, N. Wang, M. Yu,
J. Mao, Y. Hu, A. Xu, and M. Zhu, “Gamma-ray spectrometer onboard chang’e-2,” Nuclear
Inst. and Methods in Physics Research, A, vol. 726, pp. 113–115, 2013.
[7] J. Smeets, F. Roellinghoff, D. Prieels, F. Stichelbaut, A. Benilov, P. Busca, C. Fiorini, R. Peloso,
M. Basilavecchia, T. Frizzi, J. C. Dehaes, and A. Dubus, “Prompt gamma imaging with a slit
camera for real-time range control in proton therapy,” Physics in Medicine and Biology, vol. 57,
no. 11, p. 3371, 2012.
[8] P. Moioli and C. Seccaroni, “Analysis of art objects using a portable x-ray fluorescence spectrometer,” X-Ray Spectrometry, vol. 29, no. 1, pp. 48–52, 2000.
[9] S. U. Hooshang Nikjoo and D. Emfietzoglou, Interaction of Radiation with Matter. first ed.,
2012.
[10] M. Berger and J. Hubbell, XCOM: Photon cross sections on a personal computer. Jul 1987.
[11] T. Takahashi and S. Watanabe, “Recent progress in cdte and cdznte detectors,” Nuclear Science,
IEEE Transactions on, vol. 48, pp. 950–959, Aug 2001.
[12] Saint-Gobain Crystals, Scintillation Products, BrilLanCe 380.pdf. available on http://www.
crystals.saint-gobain.com/BrilLanCe_380_Scintillator.aspx.
[13] “Space detectors for gamma rays (100 MeV-100 GeV): From {EGRET} to Fermi {LAT} ,”
Comptes Rendus Physique, 2015.
135
Bibliography
[14] E. Gatti and P. Rehak, “SEMICONDUCTOR DRIFT CHAMBER - AN APPLICATION OF A
NOVEL CHARGE TRANSPORT SCHEME,” Nucl. Instrum. Meth. , vol. A225, pp. 608–614,
1984.
[15] E. Gatti, P. Rehak, and J. T. Walton, “Silicon drift chambers - first results and optimum
processing of signals,” Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 226, no. 1, pp. 129 –
141, 1984.
[16] E. Gatti, P. Rehak, A. Longoni, J. Kemmer, P. Holl, R. Klanner, G. Lutz, A. Wylie, F. Goulding,
P. Luke, N. Madden, and J. Walton, “Semiconductor drift chambers,” Nuclear Science, IEEE
Transactions on, vol. 32, pp. 1204–1208, April 1985.
[17] A. Longoni and C. Fiorini, “X-ray detectors and signal processing,” in Handbook of Practical
X-Ray Fluorescence Analysis, pp. 203–259, Springer Berlin Heidelberg.
[18] C. Gauthier, J. Goulon, E. Moguiline, P. Elleaume, S. Feite, Z. Gaburro, A. Longoni, E. Gatti,
P. Dressler, M. Lampert, and R. Henck, “A high-resolution silicon drift chamber for x-ray
spectroscopy,” Nuclear Instruments and Methods in Physics Research Section A: Accelerators,
Spectrometers, Detectors and Associated Equipment, vol. 349, no. 1, pp. 258 – 262, 1994.
[19] P. Lechner, S. Eckbauer, R. Hartmann, S. Krisch, D. Hauff, R. Richter, H. Soltau, L. StrÃ14 der,
C. Fiorini, E. Gatti, A. Longoni, and M. Sampietro, “Silicon drift detectors for high resolution
room temperature x-ray spectroscopy,” Nuclear Instruments and Methods in Physics Research
Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 377, no. 2-3,
pp. 346 – 351, 1996.
[20] P. Rehak, E. Gatti, A. Longoni, J. Kemmer, P. Holl, R. Klanner, G. Lutz, and A. Wylie,
“Semiconductor drift chambers for position and energy measurements,” Nuclear Instruments and
Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated
Equipment, vol. 235, no. 2, pp. 224 – 234, 1985.
[21] J. Takahashi, R. Bellwied, R. Beuttenmuller, H. Caines, W. Chen, D. DiMassimo, H. Dyke,
D. Elliot, M. Grau, G. Hoffmann, T. Humanic, P. Jensen, I. Kotov, H. Kraner, P. Kuczewski,
W. Leonhardt, Z. Li, C. Liaw, G. LoCurto, D. Lynn, N. Mazeh, P. Middelkamp, R. Minor,
S. Nehmeh, G. Ott, S. Pandey, D. Pinelli, C. Pruneau, V. Rykov, J. Schambach, J. Sedlmeir,
J. Sheen, R. Soja, D. Stefani, E. Sugarbaker, and W. Wilson, “Silicon drift detectors for the
star/svt experiment at {RHIC},” Nuclear Instruments and Methods in Physics Research Section
A: Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 439, no. 2-3, pp. 497
– 506, 2000.
[22] C. Fiorini, A. Longoni, F. Perotti, C. Labanti, P. Lechner, and L. Struder, “Gamma ray spectroscopy with csi(tl) scintillator coupled to silicon drift chamber,” Nuclear Science, IEEE
Transactions on, vol. 44, pp. 2553 – 2560, Dec 1997.
[23] L. Strueder, R. Hartmann, S. Kemmer, N. Krause, D. Stoetter, G. Lutz, P. Solc, P. Holl,
P. Lechner, P. Leutenegger, J. Kemmer, H. Soltau, R. Stoetter, U. Weber, A. Castoldi, C. Fiorini,
E. Gatti, C. Guazzoni, A. Longoni, and M. Sampietro, “Room-temperature x- and gamma-ray
spectroscopy with silicon drift detectors,” vol. 4141, pp. 29 – 47, 2000.
[24] J. Kemmer, G. Lutz, E. Belau, U. Prechtel, and W. Welser, “Low capacity drift diode,” Nuclear
Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors
and Associated Equipment, vol. 253, no. 3, pp. 378 – 381, 1987.
[25] U. Fano, “Ionization yield of radiations. ii. the fluctuations of the number of ions,” Phys. Rev.,
vol. 72, pp. 26–29, Jul 1947.
[26] W. Mengesha, T. Taulbee, B. Rooney, and J. Valentine, “Light yield nonproportionality of csi(tl),
csi(na), and yap,” Nuclear Science, IEEE Transactions on, vol. 45, pp. 456–461, Jun 1998.
136
Bibliography
[27] Gamma detectors for spectroscopy and imaging based on scintillators coupled to semiconductor
detectors, vol. 4141, 2000.
[28] A. Akindinov, A. Martemianov, P. Polozov, V. Golovin, and E. Grigoriev, “New results on
mrs apds,” Nuclear Instruments and Methods in Physics Research Section A: Accelerators,
Spectrometers, Detectors and Associated Equipment, vol. 387, no. 1, pp. 231 – 234, 1997.
[29] D. Neamen, “Semiconductors physics and devices,” in Handbook of Practical X-Ray Fluorescence Analysis, Third edition, McGraw Hill, 2003.
[30] C. Fiorini, L. Bombelli, P. Busca, A. Marone, R. Peloso, R. Quaglia, P. Bellutti, M. Boscardin,
F. Ficorella, G. Giacomini, A. Picciotto, C. Piemonte, N. Zorzi, N. Nelms, and B. Shortt,
“Silicon Drift Detectors for Readout of Scintillators in Gamma-Ray Spectroscopy,” Nuclear
Science, IEEE Transactions on, vol. 60, pp. 2923–2933, Aug 2013.
[31] R. Quaglia, A family of readout ASICs for X and γ-rays spectroscopy. PhD thesis, Politecnico
di Milano, Italy, 2014.
[32] E. Gatti, P. F. Manfredi, M. Sampietro, and V. Speziali, “Suboptimal filtering of 1/f noise in
detector charge measurements,” Nucl. Instrum. Meth., vol. A297, pp. 467–478, 1990.
[33] P. Lechner, W. Buttler, C. Fiorini, R. Hartmann, J. Kemmer, N. Krause, P. Leutenegger, A. Longoni, H. Soltau, D. Stoetter, R. Stoetter, L. Strueder, and U. Weber, “Multichannel silicon drift
detectors for x-ray spectroscopy,” vol. 4012, pp. 592–599, 2000.
[34] A. Longoni, C. Fiorini, C. Guazzoni, A. Gianoncelli, L. Struder, H. Soltau, P. Lechner,
A. Bjeoumikhov, J. Schmalz, N. Langhoff, and R. Wedell, “A new xrf spectrometer based
on a ring-shaped multi-element silicon drift detector and on x-ray capillary optics,” Nuclear
Science, IEEE Transactions on, vol. 49, pp. 1001–1005, Jun 2002.
[35] C. Fiorini and A. Longoni, “Application of a new noncryogenic x-ray detector in portable instruments for archaeometric analyses,” Review of Scientific Instruments, vol. 69, no. 3, pp. 1523–
1528, 1998.
[36] G. Beer, A. M. Bragadireanu, M. Cargnelli, C. Curceanu-Petrascu, J.-P. Egger, H. Fuhrmann,
C. Guaraldo, M. Iliescu, T. Ishiwatari, K. Itahashi, M. Iwasaki, P. Kienle, T. Koike, B. Lauss,
V. Lucherini, L. Ludhova, J. Marton, F. Mulhauser, T. Ponta, L. A. Schaller, R. Seki, D. L.
Sirghi, F. Sirghi, and J. Zmeskal, “Measurement of the kaonic hydrogen x-ray spectrum,”
Phys.
Rev. Lett., vol. 94, p. 212302, Jun 2005.
[37] C. Curceanu (Petrascu), M. Bazzi, G. Beer, L. Bombelli, A. Bragadireanu, M. Cargnelli,
M. Catitti, C. Fiorini, T. Frizzi, F. Ghio, B. Girolami, C. Guaraldo, M. Iliescu, T. Ishiwatari,
P. Kienle, P. Lechner, P. Levi Sandri, A. Longoni, V. Lucherini, J. Marton, D. Pietreanu,
T. Ponta, D. Sirghi, F. Sirghi, H. Soltau, L. Struder, E. Widmann, and J. Zmeskal, “Precision
measurements of kaonic atoms at DAΦNE and future perspectives,” The European Physical
Journal A, vol. 31, no. 4, pp. 537–539.
[38] M. Bazzi, G. Beer, L. Bombelli, A. Bragadireanu, M. Cargnelli, G. Corradi, C. C. (Petrascu),
A. dÊ 41 Uffizi, C. Fiorini, T. Frizzi, F. Ghio, C. Guaraldo, R. Hayano, M. Iliescu, T. Ishiwatari,
M. Iwasaki, P. Kienle, P. L. Sandri, A. Longoni, V. Lucherini, J. Marton, S. Okada, D. Pietreanu,
T. Ponta, A. Rizzo, A. R. Vidal, A. Scordo, H. Shi, D. Sirghi, F. Sirghi, H. Tatsuno, A. Tudorache,
V. Tudorache, O. V. Doce, E. Widmann, and J. Zmeskal, “Kaonic hydrogen x-ray measurement
in {SIDDHARTA},” Nuclear Physics A, vol. 881, pp. 88 – 97, 2012.
[39] M. Bazzi, G. Beer, L. Bombelli, A. Bragadireanu, M. Cargnelli, G. Corradi, C. C. (Petrascu),
A. d’Uffizi, C. Fiorini, T. Frizzi, F. Ghio, C. Guaraldo, R. Hayano, M. Iliescu, T. Ishiwatari,
M. Iwasaki, P. Kienle, P. L. Sandri, A. Longoni, V. Lucherini, J. Marton, S. Okada, D. Pietreanu,
T. Ponta, A. Rizzo, A. R. Vidal, A. Scordo, H. Shi, D. Sirghi, F. Sirghi, H. Tatsuno, A. Tudorache,
V. Tudorache, O. V. Doce, E. Widmann, and J. Zmeskal, “Kaonic hydrogen x-ray measurement
137
Bibliography
in {SIDDHARTA},” Nuclear Physics A, vol. 881, pp. 88 – 97, 2012. Progress in Strangeness
Nuclear Physics.
[40] L. Bombelli, “Sviluppo di un circuito cmos con derandomizzazione degli eventi per spettroscopia
x in misure su atomi esotici.,” Master’s thesis, Politecnico di Milano, Italy, 2005.
[41] G. Bertuccio, M. Ahangarianabhari, C. Graziani, D. Macera, Y. Shi, A. Rachevski, I. Rashevskaya, A. Vacchi, G. Zampa, N. Zampa, P. Bellutti, G. Giacomini, A. Picciotto, and
C. Piemonte, “A silicon drift detector-cmos front-end system for high resolution x-ray spectroscopy up to room temperature,” Journal of Instrumentation, vol. 10, no. 01, p. P01002,
2015.
[42] L. Bombelli, C. Fiorini, T. Frizzi, R. Alberti, and A. Longoni, “A low-noise cmos preamplifier
as alternative to jfet front-end for high-count rate spectroscopy,” in Nuclear Science Symposium
and Medical Imaging Conference (NSS/MIC), 2011 IEEE, pp. 1972–1975, Oct 2011.
[43] F. Schembari, Development and characterization of a low noise multichannel readout ASIC for
X- and γ-ray spectroscopy applications. PhD thesis, Politecnico di Milano, Italy, 2016.
[44] F. Schembari, R. Quaglia, G. Bellotti, and F. C., “Sfera: a general purpose readout ic for x and
gamma-ray detectors.,” in IEEE NSS-MIC 2015, Seattle, USA, Conference Record, 2015.
[45] L. Bombelli, C. Fiorini, T. Frizzi, R. Nava, A. Greppi, and A. Longoni, “Low-noise cmos charge
preamplifier for x-ray spectroscopy detectors,” in Nuclear Science Symposium Conference
Record (NSS/MIC), 2010 IEEE, pp. 135–138, Oct 2010.
[46] R. Quaglia, L. Bombelli, P. Busca, C. Fiorini, M. Occhipinti, G. Giacomini, F. Ficorella,
A. Picciotto, and C. Piemonte, “Silicon drift detectors and cube preamplifiers for high-resolution
x-ray spectroscopy,” Nuclear Science, IEEE Transactions on, vol. 62, pp. 221–227, Feb 2015.
[47] A. Gola, L. Bombelli, C. Fiorini, T. Frizzi, G. Membretti, R. Nava, and R. Peloso, “A multichannel asic for the readout of the hicam gamma camera,” in Nuclear Science Symposium
Conference Record, 2008. NSS ’08. IEEE, pp. 1810–1814, Oct 2008.
[48] T. Frizzi, L. Bombelli, C. Fiorini, and A. Longoni, “The siddharta chip: a cmos multi-channel circuit for silicon drift detectors readout in exotic atoms research,” in Nuclear Science Symposium
Conference Record, 2006. IEEE, vol. 2, pp. 850–856, Oct 2006.
[49] R. Quaglia, F. Schembari, G. Bellotti, A. Butt, C. Fiorini, L. Bombelli, G. Giacomini, F. Ficorella,
C. Piemonte, and N. Zorzi, “Development of arrays of silicon drift detectors and readout asic
for the siddharta experiment,” Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment, 2015.
[50] http://www.xglab.it/.
[51] C. Fiorini, “Ardesia: an x-ray spectroscopy detection system for synchrotron experiments based
on arrays of silicon drift detectors,” Workshop on X-ray Spectroscopy Detectors for Present and
Future Synchrotron Storage rings: Opportunities for Horizon 2020, Paris, March 2015.
[52] C. G. Ryan, D. P. Siddons, R. Kirkham, P. A. Dunn, A. Kuczewski, G. Moorhead, G. De Geronimo, D. J. Paterson, M. D. de Jonge, R. M. Hough, M. J. Lintern, D. L. Howard, P. Kappen, and
J. Cleverley, “The new maia detector system: Methods for high definition trace element imaging
of natural material,” AIP Conference Proceedings, vol. 1221, no. 1, pp. 9–17, 2010.
[53] P. Busca, A. D. Butt, C. Fiorini, A. Marone, M. Occhipinti, R. Peloso, R. Quaglia, L. Bombelli,
G. Giacomini, C. Piemonte, F. Camera, A. Giaz, B. Million, N. Nelms, and B. Shortt, “Development of a detector based on silicon drift detectors for gamma-ray spectroscopy and imaging
applications,” Journal of Instrumentation, vol. 9, no. 05, p. C05005.
138
Bibliography
[54] A. Butt, R. Quaglia, C. Fiorini, P. Busca, M. Occhipinti, G. Giacomini, C. Piemonte, F. Camera,
N. Nelms, and B. Shortt, “Development of a Detector for Gamma-Ray Spectroscopy Based on
Silicon Drift Detector Arrays and 200 Lanthanum Bromide Scintillator,” Nuclear Science, IEEE
Transactions on, vol. 62, pp. 2334–2342, Oct 2015.
[55] K. W. Kramer, P. Dorenbos, H. U. Gudel, and C. W. E. van Eijk, “Development and characterization of highly efficient new Cerium doped rare earth halide scintillator materials,” J. Mater.
Chem., vol. 16, pp. 2773–2780, 2006.
[56] F. Quarati, A. Owens, P. Dorenbos, J. de Haas, G. Benzoni, N. Blasi, C. Boiano, S. Brambilla,
F. Camera, R. Alba, G. Bellia, C. Maiolino, D. Santonocito, M. Ahmed, N. Brown, S. Stave,
H. Weller, and Y. Wu, “High energy gamma-ray spectroscopy with LaBr3 :Ce scintillation
detectors,” IEEE Trans.Nucl.Sci., vol. 629, no. 1, pp. 157 – 169, 2011.
[57] Saint-Gobain Crystals, Scintillation Products, BrilLanCe Performance Summary.pdf, Revision: January, 2009. available on http://www.crystals.saint-gobain.com/
BrilLanCe_380_Scintillator.aspx.
[58] M. Moszynski, L. Swiderski, T. Szczesniak, A. Nassalski, A. Syntfeld-Kazuch, W. Czarnacki,
G. Pausch, J. Stein, P. Lavoute, F. Lherbert, and F. Kniest, “Study of LaBr3 :Ce crystals coupled
to photomultipliers and avalanche photodiodes,” in Nuclear Science Symposium Conference
Record, 2007. NSS ’07. IEEE, vol. 2, pp. 1351–1357, Oct 2007.
[59] A. Owens, A. Bos, S. Brandenburg, E.-J. Buis, C. Dathy, P. Dorenbos, C. van Eijk, S. Kraft,
R. Ostendorf, V. Ouspenski, and F. Quarati, “Assessment of the radiation tolerance of labr3:ce
scintillators to solar proton events,” Nuclear Instruments and Methods in Physics Research
Section A: Accelerators, Spectrometers, Detectors and Associated Equipment , vol. 572, no. 2,
pp. 785–793, 2007.
[60] R. Nicolini, F. Camera, N. Blasi, S. Brambilla, R. Bassini, C. Boiano, A. Bracco, F. Crespi,
O. Wieland, G. Benzoni, S. Leoni, B. Million, D. Montanari, and A. Zalite1, “Investigation of
the properties of a 100 ×100 LaBr3 :Ce scintillator,” IEEE Trans.Nucl.Sci., vol. 582, no. 2, pp. 554
– 561, 2007.
[61] F. Quarati, P. Dorenbos, J. van der Biezen, A. Owens, M. Selle, L. Parthier, and P. Schotanus,
“Scintillation and detection characteristics of high-sensitivity cebr3 gamma-ray spectrometers,”
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers,
Detectors and Associated Equipment, vol. 729, pp. 596–604, 2013.
[62] C. Winkler, T. J.-L. Courvoisier, G. Di Cocco, N. Gehrels, A. Gimenez, S. Grebenev, W.
Hermsen, J. M. Mas-Hesse, F. Lebrun, N. Lund, G. G. C. Palumbo, J. Paul, J.-P. Roques, H.
Schnopper, V. Schonfelder, R. Sunyaev, B. Teegarden, P. Ubertini, G. Vedrenne, and A. J. Dean,
“The integral mission,” A&A, vol. 411, no. 1, pp. L1–L6, 2003.
[63] I. Mitrofanov, A. Kozyrev, A. Konovalov, M. Litvak, A. Malakhov, M. Mokrousov, A. Sanin,
V. Tretykov, A. Vostrukhin, Y. Bobrovnitskij, T. Tomilina, L. Gurvits, and A. Owens, “The mercury gamma and neutron spectrometer (mgns) on board the planetary orbiter of the bepicolombo
mission,” Planetary and Space Science, vol. 58, no. 1-2, pp. 116–124, 2010.
[64] W. Drozdowski, P. Dorenbos, A. Bos, J. de Haas, S. Kraft, E. Maddox, A. Owens, F. Quarati,
C. Dathy, and V. Ouspenski, “Effect of proton dose, crystal size, and cerium concentration on
scintillation yield and energy resolution of labr3 :ce,” Nuclear Science, IEEE Transactions on,
vol. 54, pp. 736–740, June 2007.
[65] W. Drozdowski, P. Dorenbos, A. Bos, S. Kraft, E.-J. Buis, E. Maddox, A. Owens, F. Quarati,
C. Dathy, and V. Ouspenski, “Gamma-Ray Induced Radiation Damage in LaBr3 :5%Ce and
LaCl 3 :10%Ce Scintillators,” Nuclear Science, IEEE Transactions on , vol. 54, pp. 1387–1391,
Aug 2007.
139
Bibliography
[66] P. Dorenbos, J. de Haas, and C. van Eijk, “Gamma ray spectroscopy with a o19×19 mm3
labr3 :0.5% ce3 + scintillator,” Nuclear Science, IEEE Transactions on, vol. 51, pp. 1289–1296,
June 2004.
[67] F. Quarati, A. Bos, S. Brandenburg, C. Dathy, P. Dorenbos, S. Kraft, R. Ostendorf, V. Ouspenski,
and A. Owens, “X-ray and gamma-ray response of a 200 ×200 LaBr3 :Ce scintillation detector,”
Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers,
Detectors and Associated Equipment, vol. 574, no. 1, pp. 115 – 120, 2007.
[68] M. Ciemala, D. Balabanski, M. Csatlos, J. Daugas, G. Georgiev, J. Gulyas, M. Kmiecik,
A. Krasznahorkay, S. Lalkovski, A. Lefebvre-Schuhl, R. Lozeva, A. Maj, and A. Vitez, “Measurements of high-energy γ-rays with LaBr3 :Ce detectors ,” Nuclear Instruments and Methods in
Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment,
vol. 608, no. 1, pp. 76 – 79, 2009.
[69] C. Fiorini, A. Longoni, and P. Lechner, “Single-side biasing of silicon drift detectors with homogeneous light-entrance window,” Nuclear Science, IEEE Transactions on, vol. 47, pp. 1691–
1695, Aug 2000.
[70] R. Quaglia, L. Bombelli, P. Busca, C. Fiorini, M. Occhipinti, G. Giacomini, F. Ficorella,
A. Picciotto, and C. Piemonte, “Silicon Drift Detectors and CUBE Preamplifiers for HighResolution X-ray Spectroscopy,” Nuclear Science, IEEE Transactions on, vol. 62, pp. 221–227,
Feb 2015.
[71] T. Nashashibi, “The pentafet and its applications in high resolution and high rate radiation
spectrometers,” Nuclear Instruments and Methods in Physics Research Section A: Accelerators,
Spectrometers, Detectors and Associated Equipment, vol. 322, no. 3, pp. 551 – 556, 1992.
[72] R. Quaglia, A. Abba, L. Bombelli, P. Busca, F. Caponio, A. Cusimano, C. Fiorini, A. Geraci, and
R. Peloso, “Readout electronics and DAQ system for silicon drift detector arrays in gamma ray
spectroscopy applications,” in Nuclear Science Symposium and Medical Imaging Conference
(NSS/MIC), 2012 IEEE, pp. 922–926, Oct 2012.
[73] A. D. Butt, “Study and development of a cooling system for a LaBr3 :Ce-based prototype of
gamma-ray spectrometer for space exploration. ,” Master’s thesis, Politecnico di Milano, Italy,
2012.
[74] T. Niedermayr, K. Vetter, L. Mihailescu, G. Schmid, D. Beckedahl, J. Blair, and J. Kammeraad,
“Gamma-ray imaging with a coaxial {HPGe} detector,” Nuclear Instruments and Methods in
Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment,
vol. 553, no. 3, pp. 501 – 511, 2005.
[75] Y. Eisen, A. Shor, and I. Mardor, “Cdte and cdznte gamma ray detectors for medical and
industrial imaging systems,” Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 428, no. 1, pp. 158 –
170, 1999.
[76] H. O. Anger, “Scintillation camera,” Review of Scientific Instruments, vol. 29, no. 1, pp. 27–33,
1958.
[77] C. Fiorini, P. Busca, R. Peloso, A. Abba, A. Geraci, C. Bianchi, G. Poli, G. Virotta, K. Erlandsson, B. Hutton, P. Lechner, H. Soltau, L. Struder, A. Pedretti, P. Van Mullekom, L. Ottobrini,
and G. Lucignani, “The hicam gamma camera,” Nuclear Science, IEEE Transactions on, vol. 59,
pp. 537–544, June 2012.
[78] P. Busca, C. Fiorini, A. Butt, M. Occhipinti, R. Quaglia, P. Trigilio, G. Nemeth, P. Major,
T. Bukki, K. Nagy, C. Piemonte, A. Ferri, A. Gola, J. Rieger, and T. Niendorf, “Development of
a high-resolution detection module for the insert spect/mri system,” EJNMMI Physics, vol. 1,
no. 1.
140
Bibliography
[79] P. Busca, C. Fiorini, A. Marone, M. Occhipinti, R. Peloso, N. Blasi, F. Camera, B. Million, and
O. Wieland, “Study and experimentation of a high resolution gamma camera based on thick
csi(tl) crystals,” in Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC),
2012 IEEE, pp. 1937–1940, Oct 2012.
[80] F. Birocchi, N. Blasi, F. Camera, F. Crespi, C. Boiano, S. Brambilla, F. Coniglio, R. Avigo,
B. Millon, S. Riboldi, O. Wieland, J. Brosamer, M. Cinti, R. Pani, C. Fiorini, and A. Marone,
“Position sensitivity of large volume LaBr3 :Ce detectors,” in Nuclear Science Symposium
Conference Record (NSS/MIC), 2009 IEEE, pp. 1403–1405, Oct 2009.
[81] R. Pani, P. Bennati, R. Pellegrini, M. Cinti, S. Nourbakhsh, P. Pani, V. Cencelli, F. De Notaristefani, F. Navarria, S. Lo Meo, A. Perrotta, N. Lanconelli, G. Moschini, P. Boccaccio, and
R. Scafe, “Investigation of depth dependent response of continuous labr3:ce scintillation crystals,” in Nuclear Science Symposium Conference Record (NSS/MIC), 2009 IEEE, pp. 3839–3839,
Oct 2009.
c
[82] M.-C. LÃpy,
J. Plagnard, and L. Ferreux, “"study of the response function of a hpge detector
for low-energy x-rays",” Nuclear Instruments and Methods in Physics Research Section A:
Accelerators, Spectrometers, Detectors and Associated Equipment, vol. 505, no. 1-2, pp. 290 –
293, 2003.
[83] P. J. Potts, A. T. Ellis, M. Holmes, P. Kregsamer, C. Streli, M. West, and P. Wobrauschek,
“"x-ray fluorescence spectrometry",” J. Anal. At. Spectrom., vol. 15, pp. 1417–1442, 2000.
141