Build-up of Atomic Oxygen Densities in the
Discharge Core of a Micro-Scaled
Atmospheric Pressure Plasma Jet
Dissertation zur Erlangung des Grades
eines Doktors der Naturwissenschaften
in der Fakultät für
Physik und Astronomie
der Ruhr-Universität Bochum
vorgelegt von
Nikolas Knake
aus Bottrop
Bochum 2010
Versicherung gemäß § 7 Abs. 2 Nr. 5 PromO 1987
Hiermit versichere ich, dass ich meine Dissertation selbständig angefertigt und verfasst habe
und keine anderen als die angegebenen Hilfsmittel und Hilfen benutzt habe.
Meine Dissertation habe ich in dieser oder ähnlicher Form noch bei keiner anderen Fakultät
der Ruhr-Universität Bochum oder bei einer anderen Hochschule eingereicht.
Bochum, den 28. Oktober 2010
Nikolas Knake
Tag der Einreichung: 28. Oktober 2010
Tag der Disputation: 18. Januar 2011
1. Gutachter: Prof. Dr. J. Winter
2. Gutachter: Prof. Dr. U. Czarnetzki
Contents
List of Figures
V
List of Tables
XI
1 Introduction
1.1 Preface . . . . . . . . . . . . . . . . . .
1.2 Thesis outline . . . . . . . . . . . . . .
1.3 Plasma . . . . . . . . . . . . . . . . . .
1.4 Atmospheric pressure plasmas . . . . .
1.5 The micro-scaled Atmospheric Pressure
1.6 Parameters, Species, and Interactions .
1.6.1 Parameters and Setup . . . . .
1.6.2 Species and Diagnostics . . . .
1.6.3 Modeling . . . . . . . . . . . .
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Plasma Jet
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2 Foundations
2.1 Laser Induced Fluorescence . . . . . . . . . . . . . . . . .
2.2 TALIF . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2.1 Two-photon excitation . . . . . . . . . . . . . . . .
2.2.2 Line broadening . . . . . . . . . . . . . . . . . . . .
2.2.3 Selection rules . . . . . . . . . . . . . . . . . . . . .
2.2.4 Collisional de-excitation . . . . . . . . . . . . . . .
2.2.5 Rate equation model and fluorescence photon yield
2.2.6 Calibration for absolute values . . . . . . . . . . . .
2.3 Optical emission spectroscopy . . . . . . . . . . . . . . . .
2.3.1 Phase resolved optical emission spectroscopy . . . .
2.4 Modeling approaches . . . . . . . . . . . . . . . . . . . . .
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Contents
Contents
3 Setup
3.1 The micro-scaled Atmospheric Pressure Plasma Jet
3.2 Gas supply and experiment chamber . . . . . . . .
3.3 Power supply . . . . . . . . . . . . . . . . . . . . .
3.4 Optical setup TALIF . . . . . . . . . . . . . . . . .
3.4.1 Coordinate system . . . . . . . . . . . . . .
3.4.2 Signal acquisition and evaluation . . . . . .
3.4.3 Xenon calibration . . . . . . . . . . . . . . .
3.5 Optical setup PROES . . . . . . . . . . . . . . . .
3.6 Setup for temperature measurements . . . . . . . .
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4 Results
4.1 Discharge characterization . . . . . . . . . . . . . . . . .
4.1.1 Operation range . . . . . . . . . . . . . . . . . . .
4.1.2 Gas temperature . . . . . . . . . . . . . . . . . .
4.2 Calibration and benchmarking of the TALIF system . . .
4.3 TALIF measurements in the plasma core. . . . . . . . . .
4.3.1 Transversal profiles . . . . . . . . . . . . . . . . .
4.3.2 Longitudinal profiles . . . . . . . . . . . . . . . .
4.3.3 Parameter variations in the dynamic equilibrium .
4.3.4 Comparison to numerical simulations . . . . . . .
4.4 PROES measurements to benchmark the simulation . . .
4.4.1 Model predictions . . . . . . . . . . . . . . . . . .
4.4.2 PROES emission results . . . . . . . . . . . . . .
4.5 Dependence on the gas flow . . . . . . . . . . . . . . . .
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5 Summary and outlook
123
Bibliography
127
IV
List of Figures
1.1
Schematic diagram of the complexity of adjustable outer parameters, created
and transported species and interactions among them. . . . . . . . . . . . . .
5
1.2
Schematic diagram of the micro-scaled atmospheric pressure plasma jet. . . .
7
1.3
Exemplary Paschen-curves as shown in [20] . . . . . . . . . . . . . . . . . . .
9
1.4
Schematic U-I characteristic of a typical DC (low pressure) glow discharge
operated in helium as can be found in [14]. (I) ”Townsend” mode, (II) ”Normal
glow” mode, (III) ”Abnormal glow” mode, and (IV) ”arc” mode. . . . . . . .
10
Schematic U-I characteristic of an APPJ operated in helium as can be found
in [14]. (I) ”Townsend” mode, (II) ”Normal glow” mode, (III) ”Abnormal glow”
mode, and (IV) ”arc” mode. . . . . . . . . . . . . . . . . . . . . . . . . . . .
11
2.1
Typical setup for a laser induced fluorescence (LIF) experiment. . . . . . . .
20
2.2
Simplified scheme for laser induced fluorescence. . . . . . . . . . . . . . . . .
20
2.3
Partial Grotrian diagram of atomic oxygen as compiled in [47]. . . . . . . . .
23
2.4
Simplified scheme for two-photon absorption laser induced fluorescence (TALIF). 25
2.5
Two-Photon excitation and fluorescence scheme for atomic oxygen and xenon
as utilized in this work. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
34
Temperature dependence of the TALIF calibration factor (normalized to 1 at
300K) for one atmosphere of helium with admixtures of 0.0%, 0.6%, and 1.0%
of O2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
36
Illustration of possible transitions between energetic states within a two-state
system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
38
1.5
2.6
2.7
V
List of Figures
2.8
List of Figures
Illustration of possible transitions between energetic states within a multistate system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
38
Main possible excitation and de-excitation processes for non-equilibrium plasmas at atmospheric pressure. . . . . . . . . . . . . . . . . . . . . . . . . . . .
40
2.10 PROES principle. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
41
2.9
2.11 Example of differing or incomplete cross-section data for various helium electronexcitation cross-sections as compiled and printed in [67]. Upper: He (1s2 1 S
→ 1s2s 3 S). Lower: He (1s2 1 S → 1s5f 3 F). . . . . . . . . . . . . . . . . . . . 49
3.1
Sketch of the modified micro-scaled atmospheric pressure plasma jet with
extended effluent channel as used in this work. . . . . . . . . . . . . . . . . .
52
3.2
Diagram of the gas supply for the µ-APPJ. . . . . . . . . . . . . . . . . . . .
54
3.3
Diagram of the power supply and electrical circuit. . . . . . . . . . . . . . .
55
3.4
Diagram of the applied U-I probe. . . . . . . . . . . . . . . . . . . . . . . . .
55
3.5
Sketch of the TALIF setup. . . . . . . . . . . . . . . . . . . . . . . . . . . .
57
3.6
Coordinate system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
58
3.7
Oscilloscope waveform recorded for the UV diode as a reference for the laser
intensity and PMT as a reference for the fluorescence. . . . . . . . . . . . . .
59
3.8
Signals shifted due to y0 (averaged outside cursor 1 and 2). . . . . . . . . . .
60
3.9
PMT signal on logarithmic scale and decay-rate fit (Cursor 3 and 4 marking the fluorescence interval after laser excitation and before late scattering
reflexions). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
60
3.10 Measured line profiles for the respective two-photon transition of atomic oxygen incl. Voigt profile best fit. . . . . . . . . . . . . . . . . . . . . . . . . . .
61
3.11 Variation of the laser intensity to validate the quadratic dependence of the
TALIF signal. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
62
3.12 Measured line profiles for the respective two-photon transition of xenon incl.
Voigt profile best-fit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
63
3.13 Calibration signal for several xenon partial reference densities. . . . . . . . .
63
3.14 Optical setup for phase resolved optical emission spectroscopy. . . . . . . . .
65
VI
List of Figures
List of Figures
3.15 Evaluation of phase resolved optical emission data. a) Emission image of
the µ-APPJ discharge channel during operation at a fixed temporal position
within the excitation cycle. b) Emission image at a different temporal position
within the excitation cycle. Lateral position and averaging spatial interval of
evaluation is marked. c) Electrode reference position is derived from a back
light image. d) Phase resolved emission plot obtained from images at several
temporal positions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
66
3.16 Scheme of the setup for temperature measurements. . . . . . . . . . . . . . .
68
4.1
Dependency of the rms voltage on the generator output power. . . . . . . . .
70
4.2
Dependency of ignition voltage and arcing voltage on the admixture of oxygen
to the helium base gas flow of 1500 sccm at atmospheric pressure . . . . . .
70
4.3
Dependency of the total current on the generator output power. . . . . . . .
71
4.4
Rms voltage versus total rms current shows a linear dependence due to the
large stray capacitance of the system. . . . . . . . . . . . . . . . . . . . . . .
72
Dependency of the phase shift between total current and voltage under variation of the generator power. . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
Rms voltage plot against the rms conduction current obtained from the phase
shift. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
73
U-I characteristic of the APPJ as measured by Park et al. in [25], current
normalized to electrode area of 100 cm2 . . . . . . . . . . . . . . . . . . . . .
74
U-I characteristic of the µ-APPJ as measured in this work normalized to
electrode area of 0.4 cm2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
75
Sample measured spectrum and simulated emission spectrum best fitting for
a temperature of 320 K. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
77
4.10 Variation of the generator power at a helium flow of 1500 sccm with an admixture of 0.6% of oxygen. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
78
4.11 Variation of the oxygen admixture at a power of 12 W for a gas flow of 1500
sccm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
78
4.12 Variation of the total gas flow at an admixture of 0.6% and 16 W generator
power. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
79
4.5
4.6
4.7
4.8
4.9
VII
List of Figures
List of Figures
4.13 Vignetting caused by imaged fluorescence light partially blocked in the vicinity
of the electrodes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
82
4.14 Vignetting caused by partially blocked laser focus in the vicinity of the electrodes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
83
4.15 TALIF signal of a homogeneous low pressure xenon atmosphere between the
electrodes at -0.5 and +0.5 mm. . . . . . . . . . . . . . . . . . . . . . . . . .
83
4.16 Composition of the total vignetting (solid line) as a convolution of the gap
profile (dashed line) with the radial functions of the laser (dash-dot) and
imaging (dot). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
84
4.17 Calculated total O(3p3 PJ ) decay rate under variation of the degree of O2
dissociation for several admixtures of O2 to one atmosphere of helium. . . . .
86
4.18 Measured de-excitation rate of O(3p3 PJ ) state for a helium base gas flow of
1500 sccm at atmospheric pressure. . . . . . . . . . . . . . . . . . . . . . . .
86
4.19 Measured de-excitation rate of O(3p3 PJ ) state for a helium base gas flow of
4500 sccm at atmospheric pressure. . . . . . . . . . . . . . . . . . . . . . . .
87
4.20 O density measured under variation of the applied voltage from ignition to
arcing. Measured in the center of the effluent gas stream at a distance of 3
mm to the nozzle. Helium flow is 1400 sccm with an admixture of 0.6% O2 . .
88
4.21 Variation of the O2 admixture in a distance of 3 mm. Measured at a peak to
peak voltage of 230V at a helium flow of 1.4 slm. . . . . . . . . . . . . . . .
89
4.22 Variation of the distance at a fixed admixture of 0.6% O2 . Measured at a peak
to peak voltage of 230V at a helium flow of 1.4 slm . . . . . . . . . . . . . .
90
4.23 TALIF signal map as obtained for a gas flow of 1500 sccm helium with an
admixture of 9 sccm O2 at 12 W rf generator power. . . . . . . . . . . . . . .
92
4.24 Transversal fluorescence signal profiles measured in various axial positions (z
= 0, 5, 10, 15, 20, 25, 30, 35, and 40 mm) in comparison to the vignetting
obtained from xenon calibration. . . . . . . . . . . . . . . . . . . . . . . . . .
93
4.25 Transversal atomic oxygen density distributions at various axial positions after
vignetting and xenon calibration applied. . . . . . . . . . . . . . . . . . . . .
93
VIII
List of Figures
List of Figures
4.26 Measured atomic oxygen density along the gas channel (z axis) measured in
the center of the channel cross-section. Operation parameters are a helium
flow of 1500 sccm with an admixture of 0.6% O2 a generator power of 12 W
calibrated to a gas temperature of 345 K. . . . . . . . . . . . . . . . . . . . .
94
4.27 Ascent distance L in respect to the rf generator power at 1.5 slm helium gas
flow and 0.6% oxygen admixture. . . . . . . . . . . . . . . . . . . . . . . . .
96
4.28 Ascent distance L in respect to the oxygen admixture at 16 W rf generator
power at 1.5 slm helium gas flow. . . . . . . . . . . . . . . . . . . . . . . . .
96
4.29 Atomic oxygen density at z = 35 mm under variation of rf generator power
and O2 admixture to a 1500 sccm helium gas flow. . . . . . . . . . . . . . .
98
4.30 Comparison of the measured atomic oxygen densities to numerical simulation
data from [4]. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 100
4.31 Phase and space averaged production processes of atomic oxygen obtained
from the numerical simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.32 Phase and space averaged loss processes of atomic oxygen obtained from the
numerical simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
4.33 Simulation results for the spatial profile of the phase averaged atomic oxygen
total production rate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.34 Simulation results for the spatial profile of the phase averaged atomic oxygen
total destruction rate. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
4.35 Ratio of the three main loss processes under variation of the power. . . . . . 103
4.36 Simulation results for the spatial profile of the steady state atomic oxygen
density. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
4.37 Simulation of the excitation of the 5 So state for a power of 0.25 W. . . . . . 105
4.38 Simulation of the excitation of the 5 So state for a power of 0.5 W. . . . . . . 106
4.39 Simulation of the excitation of the 5 So state for a power of 0.75 W. . . . . . 106
4.40 Simulation of the excitation of the 5 So state for a power of 1.00 W (transition
to arcing). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
4.41 Phase resolved emission plot of the 777 nm atomic oxygen line at a generator
power of 20 W (close to ignition). . . . . . . . . . . . . . . . . . . . . . . . . 108
IX
List of Figures
List of Figures
4.42 Phase resolved emission plot of the 777 nm atomic oxygen line at a generator
power of 30 W. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
4.43 Phase resolved emission plot of the 777 nm atomic oxygen line at a generator
power of 40 W (close to arcing). . . . . . . . . . . . . . . . . . . . . . . . . . 109
4.44 Increase of the three observed PROES emission structures with power. . . . 110
4.45 Increase of the three simulated excitation structures with power. . . . . . . . 111
4.46 Spatial ascent of the three observed emission structures along the discharge
channel at 20 W generator power. . . . . . . . . . . . . . . . . . . . . . . . . 112
4.47 Spatial ascent of the three observed emission structures along the discharge
channel at 30 W generator power. . . . . . . . . . . . . . . . . . . . . . . . . 112
4.48 Spatial ascent of the three observed emission structures along the discharge
channel at 40 W generator power. . . . . . . . . . . . . . . . . . . . . . . . . 113
4.49 Spatial ascent of the three observed emission structures along the discharge
channel at 45 W generator power for an elevated gas flow of 4500 sccm helium
with an elevated admixture of 1% O2 . . . . . . . . . . . . . . . . . . . . . . . 113
4.50 Spatial atomic oxygen density profile at different total gas flows at a fixed
generator power of 16 W and a fixed O2 admixture of 0.6 vol.%. . . . . . . . 115
4.51 Ascent distance L in respect to the total gas flow at a fixed generator power
of 16 W and a fixed O2 admixture of 0.6 vol.%. . . . . . . . . . . . . . . . . 115
4.52 Plateau atomic oxygen density in dependence of the total gas flow. . . . . . . 116
4.53 Spectrum (z=39 mm) at a total gas flow of 0.5 slm. . . . . . . . . . . . . . . 117
4.54 Spectrum (z=39 mm) at a total gas flow of 3.0 slm. . . . . . . . . . . . . . . 117
4.55 Emission intensity of helium oxygen and nitrogen impurities as a function of
the total gas flow. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118
4.56 Ratio of nitrogen to helium emission along the discharge channel. . . . . . . 119
4.57 Distribution of the gas velocity in laminar helium flow at atmospheric pressure
inside a rectangular channel of 1x1 mm2 cross-section. . . . . . . . . . . . . . 120
4.58 Calculated spatial nitrogen concentration (back diffusion) against a laminar
helium flow with parabola-shaped velocity profile. . . . . . . . . . . . . . . . 121
X
List of Tables
2.1
4.1
Selection rules for the two-photon transitions of an atom (S=spin, L=orbital
angular momentum, and J=total angular momentum). . . . . . . . . . . . .
28
Ozone reactions and dependence on the gas temperature. The ratio of the
reaction rate coefficients is exemplified for 320 K and 370 K . . . . . . . . .
81
XI
1 Introduction
1.1 Preface
The aim of this work is to contribute to the understanding of the process dynamics of a
micro-scaled atmospheric pressure plasma jet (µ-APPJ) with reactive gas admixture.
Cold jet-like plasmas operated under a gas flow at atmospheric pressure have a huge application potential [1]. Such plasmas offer treatment of sensitive surfaces such as polymers or
even biological tissue with no need for vacuum equipment. They are usually operated in
noble gases with small molecular admixtures. In particular, reactive oxygen species (ROS)
such as atomic oxygen, ozone or meta-stables are supposed to be responsible for many surface modifying effects of such plasmas [2, 3]. Despite their huge potential for technological
exploitation, the underlying physics of such homogeneous non-equilibrium discharges at atmospheric pressure are not well understood, yet.
The high collision rate and the convective gas flux represent an additional challenge for
modeling and numerical simulation. According to the large number of open parameters –
such as choice of considered species, reactions, cross sections, and simplifying assumptions–,
proposed models are highly dependent on experimental evidence. However, due to the small
sizes of the confining structures and high collision rate, most customary diagnostics –as
known from low pressure experiments– become highly sophisticated or even fail.
This work will focus on the generation of atomic oxygen inside a µ-APPJ as it represents
one of the supposed key agents interesting for surface modification and possible bio-medical
application. Spatial atomic oxygen density profiles inside the discharge are investigated by
two-photon absorption laser induced fluorescence spectroscopy (TALIF), and compared to
numerical simulations under variation of the operation parameters. (Phase resolved) optical
emission spectroscopy (PR)OES is applied to investigate the transient discharge dynamics
and to further benchmark the proposed model of the underlying physics.
1
Chapter 1. Introduction
1.2. Thesis outline
1.2 Thesis outline
The first chapter will give a brief introduction into plasmas and their benefits in general,
then introduce cold atmospheric pressure plasmas and finally specialize on advantages and
challenges of the µ-APPJ. The distinct components attributing to the physics of this device
such as fields, particles, radiation, energy transfer, and boundaries will be named here as
well as their possible interactions and effects on the underlying processes and physics. State
of the art methods to investigate each of these components, their respective advantages
and disadvantages will be discussed as well as how to approach the underlying physics.
The necessity of quantitative measurements to benchmark according models and numerical
simulations will be considered.
The basic theory of the applied optical diagnostics i.e. two-photon laser induced fluorescence
spectroscopy and (phase resolved) optical emission spectroscopy will be introduced in chapter two. Additionally, the basic foundation of the respective modeling approaches will be
discussed here.
Chapter three will introduce the experimental setup and technical components applied in
this work as well as their respective specifications and signal evaluation schemes.
The results obtained in this work will be presented in chapter four. A characterization of the
µ-APPJ operation range in terms of driving power, gas mixture, and temperature is given.
To calibrate the built TALIF system, measurements of optical vignetting and collisional
de-excitation will be presented as well as a comparison to independent mass spectroscopy
measurements. Transversal and longitudinal atomic oxygen density profiles will be presented
for a wide range of operation conditions such as variation of gas mixture, gas velocity and
generator power. The results will be compared to a one dimensional fluid model with a semikinetic treatment of the electrons [4]. To visualize the plasma dynamics, phase and spatially
resolved emission profiles will be presented for a variation of operation parameters. The
measured emission profiles will then be compared to the excitation profiles predicted from
the simulation. Finally, the explicit dependence on the feed gas velocity will be examined.
The last chapter will summarize the results and give a prospect on further investigations and
future refinement.
2
Chapter 1. Introduction
1.3. Plasma
1.3 Plasma
From the middle of the last century on several relevant technical applications have been
developed to control and thus to exploit each single component of a plasma. For welding,
drilling, cutting and even nuclear fusion the benefit derives from the thermal energy of ions
and neutrals. To switch high current electric circuits, plasma is used to benefit from its high
conductivity while avoiding spark formation e.g. in gas-blast switches.
However, in many other applications high temperatures need to be avoided. To mention only
a few of them, a controlled momentum of ions can be used both in etching of semi-conductor
structures and space propulsion technologies. Radiation is of major interest for illumination
industries. The enhanced chemistry in plasmas can be used to either synthesize desired
species such as acetylene, ozone, carbon-nano-tubes etc. or to destruct undesired species
such as nitric or sulfur oxides e.g. in combustion industries.
In general, energy needs to be coupled preferably into the most desired component –i.e.
neutrals for thermal energy, ions for propulsion and etching, electrons for chemistry or light
for radiation– and preferably not into the others. In that sense, technical plasmas are distinct
non-equilibrium systems and thus, the more far away a technical plasma is from thermal
equilibrium, the more parameters are necessary to describe and understand the system.
Plasmas are usually confined and sustained by electric and or magnetic fields. Energy is coupled into the system by controlling these external fields as charges are accelerated until their
kinetic energy is sufficiently high for momentum transfer, dissociation, excitation, ionization,
or even nuclear fusion.
As high temperatures i.e. high isotropic energies of heavy particles are mostly undesired
in technical application, fast oscillating fields are applied to accelerate preferably the light
electrons. Due to inertia, heavier ions are not able to follow the electric field and thus the gas
temperature remains cold. Operating with common voltages of a few hundred volts or some
kilovolts, the mean free path of charged particles needs to be long enough to gain sufficient
energy before a subsequent collision i.e. deceleration. Hence, most technical plasmas depend
on a low gas pressure i.e. a low particle density. Treated materials are therefore placed
in vacuum chambers which are rather expensive, require high maintenance and are rather
inconvenient to handle due to load locks, remote assembly etc.. Further, it limits the plasma
treatment to rather small and vacuum-compatible substrates.
3
Chapter 1. Introduction
1.4. Atmospheric pressure plasmas
1.4 Atmospheric pressure plasmas
As mentioned before, to sustain a discharge, charges need to be accelerated quickly to gain
sufficient energy for further ionization before the next collision. Since particle densities are
high at atmospheric pressure i.e. the mean free paths between collisions are small, the electric
fields must be higher than at low pressure –a fact which is also visible from the well known
Paschen-curves– (figure 1.3).
For operation under similar voltages, the distance between electrodes needs to be reduced
resulting e.g. in so-called micro-plasmas. Within the last few decades the invention of several non-thermal plasmas operating at atmospheric pressure improved the application within
process chains and provided the ability to treat larger, more complex and more importantly
vacuum-incompatible objects such as some polymers and biological systems. The recent
interest of medical and food industries in plasmas is thus rapidly increasing. Hence, atmospheric pressure plasmas are recently tested for the treatment of tissue [5], dental caries [6],
disinfection of wounds [7] or dermatology [8].
However, most of these discharges still remain prototypes as their actual interaction with
biological material and complex chemistry is not yet fully understood. Further, the higher
number of collisions and the resulting higher surface to volume ratio cause atmospheric pressure plasmas to be more sensitive to instabilities. Over-linear, avalanche-like secondary electron production e.g. due to more probable stepwise ionization, surface-impact and penningionization from meta-stables easily causes transitions from a stable, self-sustaining e.g. glow
discharge mode to an undesired thermal arc discharge.
One concept to prevent secondary electron emission from the surfaces –and thus suppressing
the development into an arc discharge– is to cover at least one of the electrodes with a
dielectric resulting in the so-called dielectric barrier discharges (DBD). These DBDs appear
to be homogeneous glow discharges on first sight, but in many cases actually consist of many
single filaments called streamers.
Apart from DBDs, since the publications of Bartnikas and Okazaki in the end of the 1990s
[9, 10, 11, 12, 13] diffuse, non-thermal, non-equilibrium discharges of large uniformity have
been developed and investigated which mostly suppress filamentary streamers and transitions
into thermal arcs.
A special type of these discharges are the jet-like discharges as introduced by Selwyn in
1998 [14]. In the atmospheric pressure plasma jet (APPJ) a gas stream with a velocity of
around 10 m/s is guided through the electrode gap of around one millimeter distance. One
4
Chapter 1. Introduction
1.4. Atmospheric pressure plasmas
Figure 1.1: Schematic diagram of the complexity of adjustable outer parameters,
created and transported species and interactions among them.
electrode is grounded and the other one is driven with an rf voltage of some hundred volts at
a frequency of typically 13.56 MHz. Whereas the original design by Selwyn is of cylindrical
symmetry to prevent the influence of confining non-electrode walls, this encapsulation limits
diagnostic access to external electric measurements and local optical or mass-spectroscopic
investigations only in the post discharge effluent. This results in a still incomplete and
indirect understanding of its process dynamics.
Many of these discharges are operated with noble gases containing small admixtures of
molecular reactive species and thus provide high densities of radical species. One example is
the usage of helium with an admixture of around one percent of oxygen providing reactive
oxygen species (ROS) densities of several 1015 cm−3 . Such ROS are ozone, meta-stable
singlet delta oxygen and atomic oxygen. Different and more complex gas admixtures such
as hydrogen, nitrogen, acetylene, and HMDSO have been tested for application as well.
However, the discharge chemistry becomes even more sophisticated and thus more complex
to address.
To understand the process dynamics (including the plasma dynamics and chemistry of
such a complex system as indicated in figure 1.1), it is mandatory not only to –preferably
instantaneously– measure the values of each involved component (local and instant fields
and particle densities and velocities) under a fixed set of input parameters such as gas
5
Chapter 1. Introduction
1.5. The micro-scaled Atmospheric Pressure Plasma Jet
(mixture, pressure, temperature, velocity) and confining materials (electrodes/wall material,
temperature, geometry, size, chemical reactivity) but also to know the underlying processes
of how these components influence and interact with each other (excitation, de-excitation,
acceleration by fields, collisions, chemical reactions, convection, diffusion, etc.).
Thus, the concept of the APPJ recently led to the development of the so-called micro-scaled
atmospheric pressure plasma jet (µ-APPJ), which is particularly designed to provide excellent
optical access for diagnostics to the plasma core and providing a rather simple geometry for
modeling and numerical simulations.
1.5 The micro-scaled Atmospheric Pressure Plasma Jet
Figure 1.2 shows the micro-scaled atmospheric pressure plasma jet as introduced by Niemi
et al. [15]. It consists of two U-shaped plan parallel stainless steel electrodes of 1 mm
thickness and 30 mm length inserted tightly into a quartz glass cuvette forming a 1x1x30
mm3 discharge channel. The quartz glass in combination with the small discharge crosssection provides a large solid angle for optical diagnostics from the far ultra violet to the
infra red within a range of 170-3500 nm. Helium with an admixture of around 1% of diatomic
oxygen is flushed through the cuvette forming a gas stream of some 10 m/s. One electrode is
grounded, the other one is powered by a commercial 13.56 MHz rf generator. Due to the low
and non-uniform plasma impedance of approximately 1 Ω, an additional matching network
is required for impedance matching. Typical rms voltages are 50-200 V, typical generator
powers are in the range of 5-50 W in consequence of the applied impedance matching. The
power actually coupled into the plasma is assumed to be much lower, nevertheless difficult
to measure due to the low capacitance of ≈ 0.3 pF and the fluctuating impedance of the
plasma. Measurements of the U-I characteristics and measurements of the post-discharge
effluent ensure comparability to the original APPJ [16, 17, 18, 19].
Atomic oxygen densities in the effluent of some 1014 cm−3 were found while the gas temperatures remain (far) below 100◦ C according to gas mixture flow and applied power. Atomic
oxygen is supposed to be of major importance for most of the surface modifying effects (e.g.
bacteria inactivation or modification of wettability).
Thus, this work will mainly focus on the spatial and temporal atomic oxygen densities inside
the discharge core and effluent and the corresponding mechanisms of creation, destruction
and transportation. Nevertheless, due to the complex interactions, the temporal and local
influence of possibly all other components needs to be considered and discussed as well.
6
Chapter 1. Introduction
1.5. The micro-scaled Atmospheric Pressure Plasma Jet
Figure 1.2: Schematic diagram of the micro-scaled atmospheric pressure plasma
jet.
A first approach is to discriminate the system into three major aspects.
• Outer parameters: The outer parameters such as gas (mixture, pressure, temperature, flow, feed gas, and outer atmosphere), electrodes/wall (material, geometry, temperature), applied power (voltage waveform, current supply) can mostly be influenced
or directly set by the operator.
• Interactions: The interactions of the outer parameters (ambipolar diffusion, formation of a sheath, ionization, excitation, chemical reactions) lead to a steady-state
discharge (phase averaged dynamic equilibrium) containing a large variety of further
species interacting with each other, as well. To understand these interactions, it is
necessary to know e.g. the respective cross-sections, mobilities, reaction rates, probabilities, etc.. These values are not always known and several assumptions on possible
neglecting and estimations need to be made. However, these interactions are the actual
model of the underlying physics for the whole discharge dynamics. The major goal is
thus to identify the most important interactions and to find or validate the according
values such as cross-sections, rates, etc..
• (Steady-state) species densities and values: After the system has reached a
steady state, one can find a distinct spatial and temporal distribution of numerous
species and values such as radical densities, electron and ion (energy) distributions,
7
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
radiation, internal fields etc.. These values derive from the previously mentioned interaction and the outer parameters and need to be measured.
1.6 Parameters, Species, and Interactions
To understand the interactions, i.e. physics, one needs to study how the final equilibrium
state changes with the applied outer parameters. In the following section the three aspects
of outer parameters, interactions, and density distributions (and values) will be discussed
more comprehensively.
1.6.1 Parameters and Setup
The controllable outer parameters basically consist of the three subgroups of gas mixture,
confining material and applied voltage waveform and current supply.
Gas
The feed gas is probably the most determining aspect of a discharge. Electrons must gain
sufficient energy in the outer fields to cause ionization upon collision with a neutral background gas atom or molecule. If the ionization rate is high enough to compensate for charge
losses e.g. to the confining walls, a self-sustaining discharge can be obtained. The ionization
process can either be direct or indirect via meta-stable intermediate energy levels. These
two effects are only correlated to the gas. Further, so-called secondary electrons can be
emitted from the cathode’s surface upon ion impact or thermal emission of electrons due to
heated up electrodes. They strongly depend on the electrode’s material and the electrode’s
temperature. Depending on the pressure, the mean free path for electrons varies and thus
the necessary field strength (i.e. the voltage over distance ratio) to sufficiently accelerate
them for ionization. From this general behavior the so-called Paschen-law derives as shown
e.g. in [21]. The corresponding so-called Paschen-curves for some gases are shown in figure
1.3 :
V =
B·p·d
ln(A · p · d) − ln[ln(1 + γ −1 )]
(1.1)
8
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
5
10
voltage [V]
air
4
10
Ar
H
N
2
2
N
3
10
e
He
2
10
-1
10
0
1
10
10
pd [cm T
orr]
2
10
3
10
Figure 1.3: Exemplary Paschen-curves as shown in [20]
The breakdown voltage V commensurates to the product of gas pressure p and electrode
distance d. A and B are constants depending on the type of gas. γ is the second Paschen
coefficient which elevates the breakdown voltage to the left side due to the secondary electron
emission. It is dependent on the electrode’s material and temperature.
These curves are most common for the direct current case but show a similar behavior also
for the radio frequency case. As can be seen in the upper Paschen-curve, the minimum of
breakdown voltage for helium is shifted to the right side in comparison to many other gases,
i.e. it ignites at higher pressures or electrode distances more easily than other gases, which
makes it a good choice for atmospheric pressure plasmas. The ionization threshold is higher
than for molecular gases which prevents to some extend the avalanche electron multiplication
within the bulk.
As helium is a noble gas, it further shows few reactions with other gas species and confining
walls. The major species of helium created within a plasma at atmospheric pressure are
neutral helium atoms He, ions He+ , helium meta-stables He∗ , helium dimer ions He+
2 , and
∗
helium dimer meta stables He2 . Hence, the plasma chemistry remains rather simple. The
second component for the feed gas is an admixture of around one percent of oxygen.
Oxygen is a reactive, electro-negative, molecular gas, which shows a more complex chemistry
than helium. Major species to be considered are two-, one- and three-atomic species: Molec−
ular ground state oxygen O2 , positive and negative ions O+
2 , O2 and two meta-stable states
9
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
1200
I
1000
II
III
IV
voltage [V]
800
600
400
200
0
10
-5
10
-4
10
-3
10
-2
curren
10
-1
10
0
10
1
10
2
t [A]
Figure 1.4: Schematic U-I characteristic of a typical DC (low pressure) glow discharge operated in helium as can be found in [14]. (I) ”Townsend”
mode, (II) ”Normal glow” mode, (III) ”Abnormal glow” mode, and
(IV) ”arc” mode.
O∗2 (1 ∆) and O∗2 (1 Σ), atomic ground state oxygen O, atomic positive and negative ions O+
and O− and atomic meta-stables O∗ (1 D), further three-atomic species such as ground state
ozone O3 and negative ozone ions O−
3 . Excited resonant states are usually neglected due to
their short lifetime (especially at atmospheric pressure) and thus short interaction time.
Due to the electro-negativity, the negative charges inside an oxygen plasma might switch from
electrons to negative ions at significant amounts. The chemistry i.e. the number of possible
reactions increases dramatically due to the amount of possible oxygen species (around one
hundred possible reactions). However, the chemistry of helium and oxygen remains rather
simple in comparison to more complex gases or further gases admixed (e.g. more than 500
reactions for an admixture of water vapor [22]). Most interesting species for application
in the helium-oxygen case are atomic oxygen O, ozone O3 and singlet-delta-oxygen O∗2 (1 ∆)
[23] as high densities of them appear even in the post discharge effluent (some 1015 cm−3
depending on operation conditions).
Electric Supply
As mentioned before, due to Paschen’s law a certain voltage over the electrode’s gap is
mandatory to sustain a discharge. On the other hand, a too high voltage will amplify
10
Chapter 1. Introduction
300
1.6. Parameters, Species, and Interactions
I II
III
IV
voltage [V]
m
200
m
ode
arcing
ode
t
i
hys eres s
100
0
0
1
curren
2
t [A]
Figure 1.5: Schematic U-I characteristic of an APPJ operated in helium as can be
found in [14]. (I) ”Townsend” mode, (II) ”Normal glow” mode, (III)
”Abnormal glow” mode, and (IV) ”arc” mode.
secondary electron production and cause an avalanche effect which promotes the transition
into a high current or arcing mode and thus should be prevented. For dc current and low
pressures of a few Pa, a typical glow discharge shows the typical U-I characteristic as shown
in figure 1.4. A measured example can be found e.g. in [24].
In the so-called ”Townsend” discharge mode or ”dark” discharge mode (I) the slope of the U-I
characteristic is positive and there are high voltages for small currents as the plasma is not
yet self sustaining i.e. there are more charge losses to the electrodes and confining walls than
can be supplied by ionization from seed electrons (e.g. cosmic radiation). When a certain
threshold value for the voltage is reached, the ionization has sufficiently increased to equalize
charge losses and a self sustaining ”normal glow discharge” (II) develops. Here the voltage
(and current density [A/mm2 ]) remains constant or even slightly decreases while the total
current increases due to expansion of the discharge along the electrode area. The transition
from ”Townsend” to ”normal glow” is considered to be the ignition of the discharge. As soon
as the plasma has filled the whole electrode area, a further increase of the total current can
only be obtained by a further increase of the applied voltage which is called the ”abnormal
glow” (III) mode. In this mode ionization increases more than linearly due to secondary
effects such as electron emission due to ion impact at the cathode and thermal emission from
the heated electrodes.
11
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
At elevated pressure another source for ionization becomes increasingly important, which is
the step-wise ionization of meta-stables and penning-ionization by meta-stables. This leads
to a flattening of the U-I slope and finally results in a transition to the thermal so-called
”arc discharge” (IV) of high currents at low voltages. As in this mode the U-I curve shows a
negative slope, the discharge can only be controlled by limiting the supplied current.
With increasing pressure the interval of ”normal glow” and ”abnormal glow” tends to shrink
and in many cases the ignition is directly followed by the thermal arc mode. The transition
between ”dark” and ”normal glow” as well as between ”abnormal glow” and ”arc” may show
a slight hysteresis for a decrease of current due to the inertia of the whole discharge device
(heat-relaxation etc.). However, for the atmospheric pressure plasma jet type of discharge
several concepts mostly avoid this direct transition into a thermal arc. One of these concepts
covers the application of an alternating voltage. 13.56 MHz is chosen as the electron inertia
is still low enough to follow the oscillating field but ion inertia is high enough to assume
the ions at rest [25]. As the temperature is mainly carried by the heavy particles, the gas
temperature remains low and electron emission due to ion impact and thermal emission can
effectively be suppressed to some extend.
A sketch of the typical U-I characteristic of an APPJ is found in figure 1.5. According
measurements can be found e.g. in [26, 27]. The waveform of the supplied voltage i.e. the
addition of higher Fourier modes can influence the discharge significantly [28, 29]. As the
slope of the U-I characteristic i.e. the impedance of the discharge changes significantly along
the operation modes, impedance matching is another very important aspect for operation.
It can influence the final voltage waveform at the electrodes (possible creation of harmonics)
and significantly influences the efficiency of power coupling. Even more importantly, it can
also influence the current supply [30] depending on the type of generator (voltage limited,
power limited, or current limited source).
Confining Walls
Apart from the electric supply and the used gas, the confining materials (powered, grounded
or insulating/floating) and geometry can influence the discharge as well. The overall size
of the discharge apparatus determines the surface to volume ratio. At elevated pressures,
the electrode distance needs to be decreased due to Paschen’s law and the surface to volume
ration naturally becomes larger. As secondary electron production by ion impact and thermal
emission occurs close to the electrodes, a larger surface to volume ratio will result in an
increasing importance of these effects and thus in an easier transition to an arcing mode.
Accordingly, the choice of electrode material is important with respect to the secondary
12
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
electron emission coefficient, the heat transfer, and heat capacitance and electric conductivity
of the electrode material. Thermal emission by heated up electrodes can be suppressed e.g.
by active cooling or an appropriate geometry of the electrode shape. An asymmetric electrode
shape however will influence the electric fields (e.g. self biasing) and thus the overall plasma
homogeneity. Electrodes of high resistive material may limit the conducting current when
turning into a thermal arc mode. At low pressures the kinetic energy of charged particles
is mostly directed along the electric field between the electrodes. At elevated pressures,
however, the increase of collisions leads to a more and more isotropic distribution of kinetic
energy and thus also to an increasing importance of confining non-electrode walls. Chemical
surface reactions, sputtering, deposition, and surface charging need to be considered for these
materials as well as for the electrodes themselves.
1.6.2 Species and Diagnostics
Once the outer parameters are applied, after some time the plasma will develop into a
certain dynamic equilibrium state where new species such as ions, radicals, new chemical
products, radiation etc. are created and reach (rf-time-averaged) steady state values. To
fully understand the discharge physics, it is mandatory to know the spatial and temporal
behavior of all these species with regards to the applied outer parameters. For each value
or species several measurement techniques can be applied, however each of them has certain
advantages and disadvantages. The most common diagnostics which can be or have been
applied to atmospheric pressure non-equilibrium plasmas, as well as their major advantages
and disadvantages, will be discussed in the following. The two major techniques applied
in this work i.e. Two-Photon Absorption Laser Induced Fluorescence (TALIF) and (Phase
Resolved) Optical Emission Spectroscopy (PR)-OES will be discussed more comprehensively
within the next chapter.
Probe measurements and mass spectroscopy
• Voltage and Current Probes: Voltage and current probes can be applied to the
electrodes and supply a general overview of the discharges U-I characteristic such as
threshold values for ignition, transition to arc etc.. This rather simple method can offer
a good temporal resolution, on the other hand it completely lacks of spatial resolution
and species discrimination i.e. whether the current is driven by electrons, secondary
electrons, positive ions or negative ions of which species. Further, the application
of voltage and current probes –to a certain amount– always decreases the voltage or
13
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
current supplied to the plasma. Thus, it must be assured that the influence of the probe
application remains insignificant. This is mostly automatically true for large industrial
plasmas of several hundred watts of power consumption, but becomes delicate for microplasmas which consume few watts or less. Stray capacitances are difficult to distinguish
from the actual plasma and the insertion of probes may represent an additional stray
capacitance itself.
• Langmuir Probes: An additional spatial resolution can be supplied using so-called
”Langmuir Probes”, which basically consist of a thin wire entered into the plasma and
the evaluation of its respective U-I characteristic. At micro-plasmas however, these
probes are usually of the same size as the plasma itself and thus would significantly
change and disturb the plasma to be measured. Even if further miniaturization is possible, data evaluation is strongly based on the understanding of the plasma boundary
sheath forming around the probe’s surface. This plasma boundary sheath is collision
dominated at atmospheric pressure and the evaluation of the probe data thus becomes
sophisticated. A similar concept is the retarding field analyzer [31].
• Mass spectroscopy: Mass spectroscopy can be applied to distinguish the kind of
charges by evaluation of charge to mass ratios and even evaluate the kinetic energy distribution among the detected charges. Mass spectroscopic measurements, on the other
hand, do depend on low pressures at the detector side. Thus, complicated pumping
stages need to be applied for the use at atmospheric pressure [19, 32]. Due to effects
such as composition distortion within these pressure stages a reliable calibration is sophisticated. The large size of such apparatus limits investigations to the post discharge
effluents. High pressure gradients at the entrance orifice may also disturb the plasma
itself.
• Down-scaled probes follow the idea of using probes small enough not to disturb the
plasma dynamics. Dust particles either created within or inserted into the plasma may
charge up and then be evaluated in terms of competing forces (gravitation, electric, iondrag etc.)[33] similar to Millikan’s famous experiment. Here again, it has to be ensured,
that the dust particles’ chemical interaction with the plasma remains negligible.
• Chemical Probes can be applied only in limited cases. Test strips or tracers exist
for some species but are in most cases highly disturbing the plasma. One prominent
application of a chemical tracer is titration. Atomic oxygen for example can be detected
by adding NO2 to the discharge, which has the following two reactions with atomic
14
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
oxygen:
N O2 + O −→ N O + O2
(1.2)
N O + O −→ N O2 + hν
(1.3)
Adding a slight amount of NO2 to the discharge, one can observe a recombination
fluorescence according to the second reaction. Increasing the NO2 admixture, this fluorescence light slowly diminishes due to the dominant first reaction (all atomic oxygen
is consumed in first reaction, no remains of atomic oxygen for second reaction). At the
moment of disappearing fluorescence, the (known) molar admixture of NO2 is equal to
the molar density of atomic oxygen. This method, however, highly relies on the ideal
mixing of the two gases, ideal chemistry, and no further interactions of the admixed
nitric oxide (e.g. dissociation by electrons, reactions with other species etc.).
Passive optical diagnostics
High temporal and spatial resolution can be achieved by optical diagnostics. Heavy particles
such as neutrals, radicals, and meta-stables can be excited into energetically higher states
either by absorption of resonant photons or by inelastic collisions with electrons or further
heavy particles. In most cases the majority of species to be investigated is in the lowest
possible energetic state and only a small fraction of them exists in a higher excited state.
For a non-equilibrium plasma the ground-state population is even more dominant than for
a thermal plasma.
• Optical emission spectroscopy (OES) evaluates the fluorescence light of such excited species, thus not disturbing or interfering with the discharge itself. Observations
can be performed by many kinds of optical filters and detectors. Advanced techniques
utilizing fast gated intensified cameras in combination with interference filters allow
high spatial and temporal resolution. However, to obtain absolute data on species
densities they highly relate on the knowledge of the excitation mechanisms (radiation, inelastic collisions with electrons or other heavy species), competing de-excitation
mechanisms such as radiative branching and collisional de-excitation (quenching) and
possible optical thickness. In other words, these diagnostics are highly model based.
• Actinometry e.g. can be applied when there is limited knowledge on the exciting
electrons (density and energy). A controlled amount of a further tracer gas (preferably
a noble gas to avoid major disturbance of the plasma) with an electron-excitation crosssection similar (threshold and shape) to that of the investigated species is added. Then,
15
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
the fluorescence of both, the desired and the tracer gas are compared. The ratio of
the respective fluorescence light becomes mostly independent of the exciting electrons
due to the similar cross-sections. It remains depending on the fluorescence branching
ratio and collisional de-excitation. However, not for all species an adequate tracer can
be found and the admixture of the tracer gas may cause significant disturbances of the
discharge dynamics. Additionally, cross-sections are never ideally similar.
Active optical diagnostics
Active optical diagnostics apply further radiation to the system to cause resonant absorption
for excitation into a higher state. As these processes highly rely on the resonant wavelength
and excitation cross-sections usually show a low probability for absorption, mostly laser
sources are used to deliver a high photon flux at the respect resonant wavelength. Only a
small choice of possible techniques will be presented in the following.
• Absorption Spectroscopy is based on the absorption of the incident light. Very
often the ratio of absorbed light is small in comparison to the light source’s emission
and is linearly increasing with the penetrating length of the absorbing medium. The
small signal to noise ratio can be addressed by lock-in amplifiers applied in case of
low absorption cross-sections. Small observed volumes must be compensated with
sophisticated multi-pass cells. The line-of-sight integrated signal can limit the spatial
resolution in one dimension and must be addressed by symmetry considerations or
extrapolated from various measurements at different incident angles such as in Abelinversion or tomography. Measurements of ozone [34, 35] and meta-stables of oxygen
[23], helium and argon [36] have recently been applied to atmospheric pressure nonequilibrium plasmas.
• Laser Induced Fluorescence spectroscopy (LIF): The small signal to background
ratio and the issue of line-of-sight integration can be overcome by evaluation not of
the absorbed light but of the consecutive de-excitation fluorescence radiation as in
LIF. In some cases, especially for light atomic species to be observed, the energy gap
between ground state and higher excited levels is too large to be addressed by visible
or ultra-violet radiation. Thus, either vacuum-ultra-violet radiation is applied or the
energy gap is bridged by the simultaneous non-resonant absorption of two or more
photons in the UV or VIS. This is covered e.g. by two-photon absorption laser induced
fluorescence (TALIF) spectroscopy.
16
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
As vacuum-ultra-violet radiation is by no means trivial to generate and transport –
especially at higher pressures– TALIF spectroscopy established for the detection of
medium densities of light atomic species at atmospheric pressure [16, 34, 37, 38].
Cross-sections for multi-photon absorption are usually very small and thus require high
photon fluxes generated by pulsed and focused laser beams. These high intensity laser
beams –on the other hand– must be ensured not to cause major disturbance to the
plasma itself. The observed fluorescence light can further be dominated by collisional
de-excitation and thus the observed photon yield can become diminishingly small at
elevated pressures.
• Higher order non-linear processes such as degenerate four-wave mixing (DFWM)
are a possible solution for the problem of competitive collisional de-excitation. A third
beam is applied orthogonally to the TALIF excited atoms and a third de-excitation
channel similar to stimulated emission is induced. This additional loss channel exceeds
fluorescence and collisional de-excitation and can be detected and evaluated [39, 40].
These techniques are usually applied for the investigation of combustion processes but
are highly complex as they depend cubically on the incident radiation (LIF linearly,
TALIF quadratically). Accordingly, they are highly sensitive to fluctuations of the
laser intensity. Further the data base for the nonlinear susceptibility tensors χ(3) –
necessary for absolute evaluation– is small which makes these techniques attractive
especially for relative density distribution measurements. Double-resonant four-wave
mixing [41] is capable to study light atomic species, as well. Further multi-photon
techniques such as Coherent-Anti-Stokes-Raman-Scattering (CARS) can be applied to
measure molecule densities. The CARS technique can also be applied assuming one
of the four interacting beams to have zero frequency i.e. to be a static electric field.
If the density of the species observed (i.e. Nitrogen) is known, this technique can be
used to optically determine the local electric field strength [42].
• Interferometry such as micro-wave interferometry can by applied to study the refractive index of a plasma and thus deduce the electron density. This technique can
especially be applied if the electron density is high and a significant change in the
refractive index can be expected. For low electron densities however, this technique
fails.
17
Chapter 1. Introduction
1.6. Parameters, Species, and Interactions
1.6.3 Modeling
To understand how the measurable quantities of charged particles, neutrals, radicals, metastables, photons and fields etc. are generated from the set of outer parameters, it is necessary
to create a model of the underlying physics, in other words find the right set of equations
delivering the measured densities and values from the set of outer input parameters (gas
mixture, applied voltage, etc.).
Plasma modeling is a complex field in general as a set of equations can be stated for almost
all of the supposed underlying processes, but not necessarily be solved (in a reasonable
amount of time or at all). Equations of motion, Lorentz forces, Poisson’s equation and energy
conservation equations (covering collisions including chemical reactions) may be stated for
each involved particle but –apart from quantum mechanical uncertainties– the number of
equations will by far exceed a reasonable i.e. solvable order of magnitude.
Scales
Assuming an ideal gas at atmospheric pressure, the particle density is 2.4×1019 cm−3 . Fields
and radiation can be assumed to establish instantaneously, the driving voltage is applied at
13.56 MHz, the collisional frequency at atmospheric pressure, however, exceeds the GHz
range. To resolve one period of excitation a temporal resolution of sub nanoseconds is
mandatory. On the other hand chemical reactions find an equilibrium in the range of microto milliseconds. Convective processes and thermal stabilization however may finally find an
equilibrium after milliseconds to minutes.
Therefore, more simple models with an appropriate set of assumptions must be stated and
solved, which offer a powerful tool to improve the fundamental understanding –not only of
non-equilibrium low temperature plasma sources–. Nevertheless, the validity of these
assumptions can only be proved by experimental evidence.
The basic foundations of different modeling approaches and prominent numerical simulation studies of atmospheric pressure discharges will be introduced within the next chapter.
Beforehand, firstly the foundations of the applied diagnostics will be presented.
18
2 Foundations of the applied diagnostics
and model approaches
To investigate the spatial distribution of atomic oxygen a two-photon absorption laser induced fluorescence (TALIF) experiment was setup which represents a special case of laser
induced fluorescence (LIF) spectroscopy. Thus, the basic fundamentals of LIF and TALIF
spectroscopy will be explained in the following. Subsequently the main ideas of (phase
resolve) optical emission spectroscopy (PR)OES will be presented as well as the basic foundations of possible plasma modeling approaches.
2.1 Laser Induced Fluorescence
A typical LIF experiment is depicted in figure 2.1 and the simplified respective processes and
process rates of a system of only two energetic states are shown in figure 2.2.
A laser beam is focused into the plasma containing the species to be measured. As almost all
of the species particles are in their lowest energetic state i.e. ground state |1i, the incident
photons may cause induced excitation into a higher energetic state |2i. Perpendicular to the
incident laser beam fluorescence light can be imaged into a detector and evaluated to obtain
the local particle density of the investigated species. To obtain number densities from the
intensity of the fluorescence light, each competing excitation and de-excitation process and
the respective process rates must be known and the resulting set of rate equations needs to
be solved.
Due to the high photon flux of the focused laser, the most dominant excitation process can
be assumed to be induced absorption (process rate R12 ). However, competing processes (rate
X2 ) populating state |2i such as electron impact excitation or cascade processes from higher
excited states cannot always be neglected.
19
Chapter 2. Foundations
2.1. Laser Induced Fluorescence
Figure 2.1: Typical setup for a laser induced fluorescence (LIF) experiment.
Figure 2.2: Simplified scheme for laser induced fluorescence.
20
Chapter 2. Foundations
2.1. Laser Induced Fluorescence
De-population of state |2i is ideally dominated by spontaneous fluorescence (rate A21 ) but
must compete against collisional de-excitation (rate Q2 ), photo-ionization (rate Γ2 ) and
induced fluorescence by the laser (rate R21 ).
The process rate for induced excitation R12 (in s−1 ) depends on the excitation cross-section
σ12 (in cm2 s−1 ), the spectral line profile g(∆ν), and the local laser intensity I(~r, t) (in
W cm−2 ) as follows:
R12 = σ12 · g(∆ν) ·
I(~r, t)
hνL
(2.1)
Here the spectral line profile denotes the convolution of the absorption line profile g12 (ν − νL )
and the spectral laser beam profile gL (ν − νL ). In the most simple case, the absorption line
profile is again the convolution of a Lorentzian profile resulting from the natural lifetime and
the Gaussian profile of the Doppler broadening. However, at elevated pressures it can be
dominated by pressure broadening.
The fluorescence rate A21 is the inverse of the natural lifetime τ2 of the excited state |2i, the
collisional de-excitation or ”quenching” can be expressed as:
Q2 =
X
k2,q nq
(2.2)
q
Here each particle species q represented by its density nq (in each quantum state) that may
collide with the excited state |2i contributes to the total collisional de-excitation. Each must
be weighted by its respective collisional de-excitation coefficient kq .
The rate of photo-ionization from the excited state |2i into the continuum state of ionization
creating photo-electrons of average energy Ee is obtained from the ionization cross-section
σi and the laser intensity as:
Γ2 =
Z
σi (ν + Ee /h)gL (ν)dν
I(~r, t)
hνL
(2.3)
As the number of fluorescence photons NF commensurates to the population density of the
excited state as NF = A21 · n2 , the system of rate equation for the number densities n1 , n2 ,
and ni of particles in the respective energetic states |1i, |2i, and |i > remains to be solved:
21
Chapter 2. Foundations
2.1. Laser Induced Fluorescence
dni
= Γ2 (t)n2
dt
dn2
= R12 (t)n1 − (R21 (t) + A21 + Q2 + Γ2 (t)) n2 + X2 (t)nx
dt
dn1
= −R12 (t)n1 + (R21 (t) + A21 + Q2 ) n2
dt
(2.4)
(2.5)
(2.6)
For a sufficiently weak and fast laser excitation one can assume induced emission R21 and
photo-ionization Γ2 as well as losses for the ground state population to be insignificant (R21 ,
1
Γ2 , and dn
≈ 0). If further competing processes such as cascades and electron impact
dt
excitation can be neglected, only one differential equation remains:
dn2
= R12 (t)n1 − (A21 + Q2 ) n2
dt
(2.7)
For a laser pulse of length T, integration over time shows n2 to be:
n2 (t) =
(
R∞
n1 0 R12 (τ )e−(A21 +Q3 )(t−τ ) dτ for 0 < t < T
n2 (T )e−(A21 (t−T )+Q2 (t−T ))
for t > T
(2.8)
For light atomic species such as atomic oxygen, hydrogen or nitrogen, the energy gap between
ground state and higher energetic states would require vacuum ultra violet radiation for the
laser excitation (as e.g. shown in figure 2.3). VUV radiation is not only sophisticated to
generate and guide but also contradicts measurements at atmospheric pressure due to strong
absorption. Apart from the energy, exciting photons must as well meet the corresponding
dipole selection rules. This issue can be addressed by replacing the excitation from one
VUV-photon by the excitation from simultaneous non-resonant absorption of two near UV
photons i.e. TALIF.
22
Chapter 2. Foundations
2.1. Laser Induced Fluorescence
Figure 2.3: Partial Grotrian diagram of atomic oxygen as compiled in [47].
23
Chapter 2. Foundations
2.2. TALIF
2.2 TALIF
For two-photon absorption LIF (TALIF) the excitation from the ground state |1i into an
energetically higher state |3i takes place by the simultaneous absorption of two photons.
The energy gap between both states must be equivalent to the sum energy of both photons
and the states need to be coupled non-resonantly according to the two-photon transition
selection rules. A simplified scheme for these processes can be found in figure 2.4.
The first photon excites the atom into a virtual intermediate state |vi which is not an eigenstate of the stationary Schroedinger equation and thus is strongly limited in its lifetime (in
the order of 10−16 s).
On an evanescent timescale resonances of all possible energy eigen-states |mi are broadened
due to the uncertainty principle leading to a manifold of possible two-step resonant excitations but each with an evanescent probability. The sum of all these evanescent transition
probabilities can then be considered as the probability for a non-resonant transition into a
virtual intermediate state |vi.
For two-photon absorption the second photon needs to be absorbed within this lifetime to
provide further excitation into the real state |3i.
Cross-sections for the two-photon excitation are thus orders of magnitude smaller than crosssections for resonant single-photon excitation (in the order of 10−34 cm4 ) and hence high
photon fluxes, i.e. pulsed and focused lasers, are required for two-photon excitation (rate
R13 ).
The two-photon excitation rate R13 again commensurates to the two-photon absorption
cross-section σ (2) , the photon fluxes (expressed by the laser intensities I1 (~r, t) and I2 (~r, t) at
central wavelengths ν1 and ν2 ), the normalized line profile g(∆ν) and a photon-statistical
factor G(2) .
(2)
R13 = σ13 · g(∆ν) · G(2) ·
I1 (~r, t) I2 (~r, t)
hν1
hν2
(2.9)
G(2) = hI(t)2 i / hI(t)i2 attributes to the temporal correlation of the radiation fields [50]. For
a pulsed dye-laser –as used in this work– coherence time is in the order of picoseconds whereas
pulse duration and timescales of the detection systems are slower by orders of magnitude.
24
Chapter 2. Foundations
2.2. TALIF
Figure 2.4: Simplified scheme for two-photon absorption laser induced fluorescence
(TALIF).
25
Chapter 2. Foundations
2.2. TALIF
For measurements, this resembles an average over several phase-uncorrelated laser modes
resulting in G(2) = 2 according to [51].
2.2.1 Two-photon excitation
The two-photon excitation cross-section σ (2) can be obtained from perturbation theory[48]
as follows:
(2)
σ1→3
π 2 ν 1 ν2
= 2 2 2
c ǫ0 h
X h3|µ̂e |mi hm|µ̂e |1i h3|µ̂e |mi hm|µ̂e |1i 2
2
1
1
2
+
m
ν1m − νL1
ν1m − νL2
(2.10)
Here, |mi denotes all possible resonant intermediate and even resonant continuum states
P
with corresponding resonance frequency ν1m , µ̂ = i qi r̂i denotes the dipole operator (r̂i is
the space operator and qi the charge of the i-th charge carrier), and e1 and e2 denotes the
polarization of the two laser photons at frequencies νL1 and νL2 .
For the case of two identical photons R13 and σ (2) simplify to:
R13 =
(2)
σ1→3 =
(2)
σ13
· g(∆ν) · G
πνL
cǫ0 h
(2)
·
I(~r, t)
hνL
2
(2.11)
2
2 X
h3|µ̂e|mi
hm|µ̂e|1i
m
ν1m − νL
(2.12)
2.2.2 Line broadening
The area normalized line profile g(∆ν) = g(ν1 + ν2 − ν13 ) is composed of the homogeneous
Lorentzian line profile Gh (ν, ~v ), the Doppler-shifted velocity distribution of the atoms gD (~v ),
the two laser line profiles g1 (ν − ν1 ) and g2 (ν − ν2 ) and the pressure-broadened line profile
gP due to elastic and inelastic collisions.
26
Chapter 2. Foundations
2.2. TALIF
g(∆ν) = Gh (ν, ~v ) ∗ gD (~v ) ∗ g1 (ν − ν1 ) ∗ g2 (ν − ν2 ) ∗ gP
(2.13)
For the case of two photons from the same laser pulse the natural line profile becomes:
Gh (ν, ~v ) =
1
A3 /4π
π (2νL − ν13 + k~v /π)2 + (A3 /4π)
(2.14)
Assuming a Maxwellian distribution for thermodynamic equilibrium the Doppler broadening
is equal to:
gD (~v ) = π
−3/2
2
p
−3 √
− |~v |/ 2kB T ln(2)/m0
2kB T ln(2)/m0
e
(2.15)
Here m0 denotes the mass of the atom, kB Boltzmann’s constant, T temperature, A3 is the
inverse of the natural lifetime of state |3i.
Since measurements in this work were performed at atmospheric pressure, pressure-broadening
dominates the overall line profile. It is caused by elastic and inelastic collisions. For elastic
collisions the temporary shift of energy levels of two particles in vicinity causes a line broadening. The shortening of the effective lifetime of the excited state due to inelastic collisions
results in a broader absorption profile due to uncertainty principle [49].
In general, one can calculate e.g. the gas temperature from the Doppler broadening by
deconvolution of the overall line profile in case all other contributing profiles are known.
Similarly one may calculate the collisional de-excitation from the total line width if all other
broadening processes are known.
In our case, the collisional broadening is dominant at atmospheric pressure but its value is
not well known since both elastic and inelastic collisions contribute to the broadening. A
further challenge appears for overlapping energetic sub states with an energy difference in
the same order as the line broadening of each. Accordingly, in that case one cannot obtain
gas temperatures from the total absorption line width.
27
Chapter 2. Foundations
2.2. TALIF
2.2.3 Selection rules
(2) The two-photon transition selection rules derive from the matrix elements M13 and can be
found in [37, 52] for the excitation from two similar laser beams or one laser beam:
(2) −1/2
h1|µ̂e|mi hm|µ̂e|3i
M13 = (ǫ0 ~)
(2.16)
For LS-coupled light atoms these rules result in the selection rules as noted in table 2.1.
However, several exceptional cases exist. E.g. ∆J = 1 is forbidden for the absorption of two
similar photons.
angular momentum
∆S
∆L
∆J
two-photon selection rules
0
0, ±2
0, ±1, ±2
(∆J = 1 forbidden for two similar photons)
Table 2.1: Selection rules for the two-photon transitions of an atom (S=spin,
L=orbital angular momentum, and J=total angular momentum).
For stimulated two-photon de-excitation back into the ground state (rate R31 ) cross-sections
are small in comparison to one-photon fluorescence (rate A32 ) into a resonant state |2i and
thus usually negligible. However, at elevated population of the excited state |3i i.e. high
laser pulse energies, it may compete with the fluorescence.
2.2.4 Collisional de-excitation
The most dominant competitive de-excitation process at elevated pressure remains collisional
de-excitation –also called collisional quenching– which is due to the non-radiative energy
transfer in inelastic collisions with other heavy particles.
The effective de-excitation rate A∗i of an excited state |ii then becomes the sum of the
natural fluorescence rate Ai (sum of all possible radiative transition rates with respective
”escape-factors” gik attributing to optically non-thin transitions) and the effective collisional
de-excitation rate Qi which is the composite contribution of all colliding species q with
respective densities nq and collisional de-excitation coefficients kq .
28
Chapter 2. Foundations
2.2. TALIF
Actually, each quantum state of each species must be considered separately, but in most cases
it is sufficient to attribute only to the major species in the ground state. Contributions of
minor species can be neglected in case of negligible densities and/or negligible coefficients.
A∗i
=
X
Aik (gik ) +
X
kqi nq
(2.17)
q
k<i
Similar considerations must be made for multi-body collisions Qm =
P
(m)
q,s
kqs
Q
s
nsq .
Not only the densities of the colliding species but also the quenching coefficients are temperature dependent. Assuming the collisional cross-sections σqi to be independent of the
temperature, the quenching coefficient’s only temperature dependence occurs due to the
mean velocity |vi of the colliding species. For a thermal velocity distribution (kB denotes
Boltzmann’s constant, µ the reduced mass), this becomes:
kqi = σqi hvi = σqi
s
8kB T
πµ
(2.18)
Data for collisional de-excitation coefficients are not always available. Nevertheless, the total
collisional quenching can be accessed by the reduced lifetime τi∗ of the excited state (τi is
the natural lifetime) from the temporal decay of the fluorescence signal according to:
1
1
=
+ Qi
∗
τi
τi
(2.19)
2.2.5 Rate equation model and fluorescence photon yield
According to the previously discussed rate model of the simplified LIF processes, for the
TALIF process a similar rate model of the population and de-population processes has to be
solved.
29
Chapter 2. Foundations
2.2. TALIF
dn3
= R13 (t)n1
dt
+X2 (t)nx
(2.20)
− (R31 (t) + A32 + Q3 + Γ3 (t) + Z(t)) n3
dn2
= − (A21 + Q2 ) n2 + (A32 + Z(t)) n3
dt
dn1
= − (R13 (t) + X2 (t)) n1 + (A21 + Q2 ) n2 + (R31 + Q3 ) n3
dt
(2.21)
(2.22)
It is important to note the existence of further competing population and de-population
processes, i.e. excitation due to electron-impact (here the corresponding rate coefficient is
marked X) which can either be direct or indirect e.g. via cascades, photo-ionization (Γ) and
amplified spontaneous emission (ASE) (here the rate coefficient is marked Z). The latter
one may occur upon population inversion of |2i and |3i due to much quicker population
than de-population of |2i. In that case an amplification of the fluorescence A32 may occur
in or against the direction of the incident laser beam leading to a strong anisotropy in the
fluorescence and thus complicating the evaluation.
An estimation of the critical density n3,crit. of |3i for AES can be derived from the frequency
ν32 , spontaneous fluorescence rate A32 , Doppler-width ∆D , and the amplification length L
according to [37, 53]:
n3,crit.
2
ν32
∆D
< 7.5 × 10 2
c A32 L
2
(2.23)
For the 844 nm atomic oxygen line (∆D (300K) = 1.1 × 109 s−1 , Aik = 3.22 × 107 s−1 ) this
results in a critical density of n3 < 3.6×1013 cm−3 for an amplification length of 1 mm. Close
to saturation, the population ratio of excited state and ground state n3 /n1 is in the order of
one percent, and thus the critical ground state density for the onset of ASE becomes some
1015 cm−3 . However, since TALIF measurements were performed in the unsaturated regime
(low laser intensity i.e. dn1 /dt ≈ 0), ASE may be neglected even for higher ground state
densities. Photo-ionization rate Γ3 is proportional to the laser intensity and the population
of |3i. Thus, both competing effects can be addressed by keeping the population of |2i and
|3i low, i.e. utilizing low laser intensities.
The excitation due to electrons can be addressed by evaluation of the distinct transient
30
Chapter 2. Foundations
2.2. TALIF
behavior of laser and electron excitation e.g. subtraction of the temporal background emission at the fluorescence wavelength. In our case, we can average over some 100 laser shots
non-synchronized to the electric plasma excitation frequency.
Under the assumption of keeping the laser intensity low enough to not significantly depopulate the ground-state, negligible photo-ionization, ASE, and electron excitation, the
rate equation system reduces to one equation for n3 which can be integrated over time for a
laser pulse of duration T :
dn3
= R13 (t)n1 − (A32 + Q3 ) n2
dt
(
R∞
n1 0 R13 (τ )e−(A32 +Q3 )(t−τ ) dτ for 0 < t < T
n3 (t) =
n3 (T )e−(A32 (t−T )+Q3 (t−T ))
for t > T
(2.24)
(2.25)
The number of fluorescence photons NF commensurates to the population of the excited state
n3 via the branching ratio a32 = P A3iA+32P Q3q which is the ratio of observed de-excitation
i
q
path to the sum of any possible de-excitation path. Two-photon absorption cross-section,
line profile and photon-statistic factor can be summarized in terms of a generalized twophoton-absorption cross-section σ̂ (2) = G(2) g(∆ν)σ (2) . Then, the total number of emitted
fluorescence photons NFtot can derived from integrating equation 2.25 over time t and excitation volume V .
NFtot
= A32
Z Z
V
n3 (t)dtdV
(2.26)
t
A32
P
= n0 P
G(2) g(∆ν)σ (2) (∆ν)
A
+
Q
3q
i 3i
q
2
Z Z IL (~r, t)
(2)
= n0 a32 σ̂ (∆ν)
dtdV
hνL
V t
Z Z V
t
IL (~r, t)
hνL
2
dtdV
(2.27)
(2.28)
From this we can conclude that the total number of fluorescence photons divided by the
squared laser intensity is proportional to the ground state density if a32 is a constant (i.e. at
constant gas composition, pressure, and temperature).
31
Chapter 2. Foundations
NFtot
R R IL (~r,t) 2
V
t
hνL
dtdV
2.2. TALIF
∝ n0
(2.29)
A deviation from this characteristic indicates an infraction of the above mentioned precondition of weak excitation e.g. an onset of laser induced competing effects such as photoionization or ASE. Another deviation may occur at high laser intensities due to artificial
generation of atoms from photo-dissociation of the corresponding molecules. Both can be
handled by reduction of the laser intensity until the above mentioned quadratic behavior is
valid again.
2.2.6 Calibration for absolute values
Direct evaluation of equation (2.28) is sophisticated due to several reasons.
Firstly, databases for the corresponding two-photon excitation cross-sections are small.
Secondly, it is difficult to count the total number of fluorescence photons NFtot . Usually
only a small solid angle ∆Ω of the fluorescence emission NF is imaged into a detector –
e.g. photomultiplier tube (PMT)– via several optics (lenses, filters, apertures, etc.) with
transmissivity T (νF ).
Further, one has to account for a possibly non-isotropic radiation pattern KF (Θ).
NF = T (νF ) ·
∆Ω
· KF (Θ) · NFtot
4π
(2.30)
The recorded voltage signal U (t) commensurates also to the quantum efficiency η(νF ), the
PMT amplification factor G, the instrument shunt R (typ. 50 Ω), and the elementary charge
e. Each contributes with an additional factor of uncertainty.
32
Chapter 2. Foundations
Z
t
2.2. TALIF
U (t)dt = η(νF ) · G · e · R · NF
(2.31)
∆Ω
= n0 · η(νF ) · G · e · R · T (νF ) ·
· KF (Θ)
4π
2
Z Z IL (~r, t)
(2)
dtdV
·a32 · σ̂ (∆ν) ·
hνL
V t
(2.32)
Finally, the dependence on the temporal and spatial laser intensity remains, which is difficult
to determine directly. An integrated transient behavior can be detected with a fast UV diode
as a reference, however measuring the transient spatial distribution of the laser beam IL (~r, t)
and the size of the contributing laser focal volume is rather sophisticated.
Thus, the system must be calibrated for absolute density measurements. This can be performed either by an alternative method such as Rayleigh-calibrated LIF, titration or mass
spectrometry, or –more conveniently– by comparison to a reference density.
For atomic oxygen, a defined reference density is difficult to produce. A noble gas with
a similar two-photon excitation and fluorescence scheme can be utilized as a substitution
[54, 55]. A reference density of this noble gas can easily be produced by controlling pressure
and temperature of a filled vessel.
For the detection of atomic oxygen the respective excitation and fluorescence schemes of
atomic oxygen and xenon were chosen according to figure 2.5. The same imaging optics
and the same photo multiplier setting can be used for subsequently measuring the unknown
density of atomic oxygen and the known reference density of xenon. Thus, the contributing
geometric and electric factors of imaging optics and photomultiplier are the same for both
measurements and cancel out.
Accordingly, the ratio of the measured PMT signal normalized to the laser pulse intensity
R
U (t)dt
S = R R t
2
IL (~
r,t)
V
t
hνL
dtdV
commensurates to the ratio of ground state densities as follows:
33
Chapter 2. Foundations
2.2. TALIF
Figure 2.5: Two-Photon excitation and fluorescence scheme for atomic oxygen and
xenon as utilized in this work.
34
Chapter 2. Foundations
2.2. TALIF
(2)
SO
aij (O)σ̂O
TO ηO
nO
×
=
×
(2)
SXe
T η
nXe
| Xe{z Xe} aij (Xe)σ̂Xe
(2.33)
≈1
As visible from figure 2.5 both, atomic oxygen ground state 2p4 3 P2,1,0 and excited state 3p
3
P1,2,0 show a triple degeneration of their fine structures. The degeneration of the upper state
is weak and in the same order as the broadened line profile for each sub state. As it is less
pronounced than the degeneration of the ground state, usually each two-photon excitation
cross-section from the ground state is given as an integrated cross-section over the sum of
all 3p 3 P1,2,0 fine structure levels.
(2)
The ratio of the two-photon excitation cross-sections
σ̂Xe
(2)
σ̂O
= 1.9 was measured in [34] with
an accuracy of 20%. Here the cross-section denotes the transition from the most populated
J = 2 ground state to the sum of all 3p 3 P states.
The total ground state population ntot
0 in dependence of the gas temperature can be obtained
from the Boltzmann distribution:
n3p3 P2
ntot
0
−
EJ
(2J + 1)e kB T |J=2
= P
E
− k JT
B
J (2J + 1)e
(2.34)
Finally, the total atomic oxygen ground state density can be calculated from the normalized
signal SO(3p3 P2 ) , SXe , and the xenon reference density via the calibration factor χ:
nXe
· SO(3p3 P2 )
SXe
(2)
TXe ηXe aij (Xe)σ̂Xe ntot
·
χ =
· 0
(2)
TO ηO
n3p3 P2
aij (O)σ̂O
ntot
= χ·
0
(2.35)
(2.36)
35
Chapter 2. Foundations
2.2. TALIF
TAL
IF calibration factor
1.00
0.99
0.98
0.97
0.96
0.95
0.0% O
0.6% O
0.94
1.0% O
0.93
300
320
2
2
2
admixture
admixture
admixture
340
360
380
400
temperature [K]
Figure 2.6: Temperature dependence of the TALIF calibration factor (normalized
to 1 at 300K) for one atmosphere of helium with admixtures of 0.0%,
0.6%, and 1.0% of O2 .
Temperature dependence
One can see that the calibration factor χ depends on the gas temperature in terms of aij (O) =
ntot
AP
32
P
and n 3 0 (T ) . An increase in temperature at constant pressure results in
A3i +
Q3q (T )
i
q
3p P2
a linear decrease of colliding species densities nq ∝ T1 and a square-root increase of the
√
collisional de-excitation coefficients kq ∝ T . Thus, Q3q ∝ √1T decreases with temperature
and aij (O) increases with temperature. In the denominator this contributes to a decrease.
ntot
However, n 3 0 (T ) increases with temperature thus partially compensating the previously
3p P2
mentioned effect.
In our special case of helium at atmospheric pressure with an admixture of around 0.6% of
oxygen, this results in a calibration factor which is very robust against temperature variation
in the range of 300 K to 400 K. The maximum deviation at high admixtures of 1.0% oxygen
and a temperature of 400 K instead of 300 K results in an error of below 7% as can be seen
in figure 2.6.
36
Chapter 2. Foundations
2.3. Optical emission spectroscopy
2.3 Optical emission spectroscopy
Whereas for (TA)-LIF experiments one can simplify the excitation processes to laser absorption and de-excitation processes to fluorescence and collisional quenching, for optical emission
spectroscopy there are more competing processes for radiative excitation and de-excitation.
Both, absorption and emission of light, are an indication for transitions between energetic
states of the respective particle species. Absorption into the upper state |ui is related to
the population density nl of the lower state |li via the excitation rate Rlu and emission is
related to the population density of the upper state via the spontaneous emission rate Aul
and induced emission rate Rul . Both can be expressed via rate equations for each energy
level similar to the previously mentioned LIF and TALIF scheme.
dnu
= Rlu (t)nl − (Rlu (t) + A21 ) nu
dt
(2.37)
The same transitions can further occur non-radiatively via inelastic collisions due to excitation from electrons (rate Xlu ) or heavy particles (rate Qlu ). Vice-versa, collisional deexcitation occurs also for electrons (rate Xul ) and heavy particles (rate Qul ) as illustrated in
figure 2.7.
dnu
= (Rlu (t) + Xlu (t) + Qlu (t)) nl
dt
− (Rlu (t) + A21 + Xul (t) + Qul (t)) nu
(2.38)
However, there may be much more than two energetic states (including ionization states,
vibrational and rotational states as indicated in figure 2.8) for each species, expanding the
balance equation to:
dni
=
dt
X
j=1→n
(Rji + Xji + Qji ) nj − (Rij + Aij + Xij + Qij ) ni
37
(2.39)
Chapter 2. Foundations
2.3. Optical emission spectroscopy
Figure 2.7: Illustration of possible transitions between energetic states within a
two-state system.
Figure 2.8: Illustration of possible transitions between energetic states within a
multi-state system.
38
Chapter 2. Foundations
2.3. Optical emission spectroscopy
Equation (2.40) shows how electron densities and electron energy distribution functions are
related to the respective cross-sections. The equation for heavy particles impact is similar
and thus not shown here.
Xji (t) = ne (t)
Z
0
∞
r
(e)
σji (ǫ)
2ǫ
f (ǫ)dǫ
me
(2.40)
Further, excited states may be populated as a result of recombination of positively and
negatively charged particles or during the formation and dissociation of molecules such as
electron-ion recombination or dissociative excitation.
As the number of total emitted photons Nλtot
at wave length λij is proportional to the
ij
spontaneous fluorescence rate Aij and the population of |ii, one must solve this system of
rate equations for each energetic state. Then, one may relate the fluorescence yield to the
desired plasma parameters such as ground state densities or electron densities or energy
distribution functions.
In most cases, some assumptions can be made to simplify this system of coupled differential
equations. Radiative transitions are limited e.g. by the corresponding optical dipole selection
rules.
Furthermore, in non-equilibrium atmospheric pressure plasmas, excitation via electrons mostly
dominates radiative excitation. De-excitation is mostly dominated by fluorescence and inelastic collisions with heavy particles.
The most simple assumption on a collisional radiative model is the corona model. The corona
model assumes excitation only occurring via electron excitation from the ground state and
de-excitation solely occurring via fluorescence and collisional de-excitation.
For a more realistic model, one must include stepwise excitation via meta-stables |mi, cascade processes from higher excited states, recombination and dissociative excitation, and
collisional de-excitation as shown in figure 2.9.
Excitation depends on the population density of the lower state. Thus, the majority of
excitation processes appears only from the most populated states i.e. the ground state |gi.
Short effective lifetimes of resonant states |ri –especially at atmospheric pressure– lead to a
negligible contribution of excited states to further excitation as the excitation process must
occur within its lifetime.
39
Chapter 2. Foundations
2.3. Optical emission spectroscopy
Figure 2.9: Main possible excitation and de-excitation processes for nonequilibrium plasmas at atmospheric pressure.
Meta-stable states |mi on the other hand, show a significantly longer effective lifetime in the
order of seconds or more and may be significantly populated, thus contributing as a source of
stepwise excitation processes. De-excitation does not only occur back into the ground state
but may also occur stepwise, thus populating lower energetic states via cascades.
As both, electron density and electron distribution function (EEDF) contribute to the excitation rate coefficients, two free parameters remain.
Similar to the xenon-calibration for TALIF, comparative measurements can be performed
for electron excitation of several species with similar excitation cross-sections. This leads to
a signal ratio which becomes independent of the electron properties. The method is applied
e.g. in actinometry to determine species densities.
In most cases, the temporally averaged fluorescence signals are evaluated assuming a spatiotemporally averaged electron energy distribution function within the detection volume. The
less similar the two involved cross-sections are, the more significant deviations may appear
for the results. It is thus necessary to explicitly account for the transient and spatial EEDF
[45, 56, 57].
The EEDF and electron density can either be calculated ab-initio from appropriate plasma
models, or can be reconstructed from absolutely calibrated spatio-temporal emission profiles
of several emission lines with significantly different excitation thresholds.
40
Chapter 2. Foundations
2.3. Optical emission spectroscopy
Figure 2.10: PROES principle.
In our case, phase resolved optical emission spectroscopy is applied to the µ-APPJ as a
further benchmark of the hybrid discharge model [4] by comparison of the measured spatiotemporal emission structures to the simulated excitation.
2.3.1 Phase resolved optical emission spectroscopy
To gain inside into the excitation processes during one rf period of 74 ns, the effective
temporal resolution of the recorded fluorescence signal must be significantly higher (e.g. 1
ns). The fluorescence yield within this short time interval is very low and constitutes a
challenge even for highly intensified sensors such as diodes, cameras, and photo multipliers.
As homogeneous rf discharges show a repetitive dynamic equilibrium, the emission shows a
periodical behavior synchronized to the driving rf frequency. In other words, the emission
shows a distinct transient behavior within one rf cycle, but is similar for each following rf
cycle.
Gating the incident light to the very same moment (delay d and gate width g) of each rf
cycle and integrating the obtained signal over several thousands of rf cycles, one can achieve
a high total photon yield with the benefit of a high temporal resolution within the rf-cycle.
For spatial and temporal resolution, a CCD chip in combination with a fast gated optical
amplifier (multi channel plate MCP) can be used. Spectral resolution can be achieved when
41
Chapter 2. Foundations
2.4. Modeling approaches
inserting filters into the optical path.
As the measured values of each diagnostic must be compared to modeling results to understand the underlying physics, the basic foundations of the most common modeling approaches
will be introduced in the following.
2.4 Modeling approaches
The most general distinction of plasma models can be made for self-consistent and non-selfconsistent models. The latter one describes the creation of species not exclusively by the set
of input parameters, but highly relates on the measured values of other measured species
as an input parameter. As an example, the density of meta-stable oxygen molecules can be
calculated by an adequate set of chemical reactions from a set of measured ozone and atomic
oxygen densities [58]. However, this is done completely neglecting the creation and destruction processes of atomic oxygen and ozone by electrons (these species are created in the
plasma themselves). Thus, non-self-consistent models can be a very quick and powerful tool
to predict quantities, which are not directly accessible to diagnostics, from other measured
quantities. Hence, they are rather to be considered advanced diagnostic tools.
Self-consistent models, on the other hand, derive all values solely from the known set of input
parameters as mentioned before and thus are most suitable to understand the underlying
physics of the complete discharge dynamics. They can further be divided into analytical and
numerical models. To remain analytically solvable, the latter models are mostly restricted
to a zero dimensional (global) model including a vast number of assumptions to be made.
An extension to one dimension can be made e.g. by separating the plasma into three regions
i.e. the bulk and two plasma boundary sheaths. Analytical models are accordingly the
fastest and simplest approach to simulate the global electric properties of non-equilibrium rf
plasmas, but not necessarily the most easiest [59, 60].
More common is the numerical solving of the stated equations. This offers access to two- or
three-dimensional resolution and the inclusion of more species and a more complex chemistry
(diffusion, convection, reactions). On the other hand, this method depends on the accuracy
of the applied numerical solvers and is further limited by the capability of the calculating
machine (speed of CPU and amount of memory to store intermediate results). Within the
last decades the tremendous progress in developing highly potent computers for the consumer
market has made numerical simulations the most common ones.
42
Chapter 2. Foundations
2.4. Modeling approaches
Kinetic, Fluid and Hybrid Description
According to the method of treating the charged particle dynamics, one can distinguish
between three major methods of modeling and numerical simulation: Particle-In-Cell MonteCarlo-Collision (PIC-MMC), Fluid and Hybrid models.
Kinetic Models:
PIC-MCC models simulate the kinetics of electrons and ions and sometimes neutrals. The
very intuitive approach is to track the kinetics of at least the charged particles (which are still
in the order of 1010 −1012 cm−3 ) within a grid of cells and benefit from the collective behavior
of charged particles in plasmas. Thus a huge number (≈ 106 ) of particles can be abstracted
to one so-called ”super-particle”. These super-particles then can be tracked by solving the
motion equations of charged particles in combination with Maxwell’s equations. Collisions
are treated by means of probability in a Monte-Carlo-Scheme. This method promises the
most accurate results based on the fewest a-priori assumptions. At increasing plasma density
the number of considered super-particles to be tracked can still exceed values of over a million.
Further the time intervals between collisions to account for decreases rapidly with pressure.
Increasing the size of super-particles, i.e. decreasing their number, leads to a worse statistical
representation of higher energetic particles which are actually most crucial for ionization
and excitation processes. Neutrals (if considered at all) can be addressed this way, though.
Despite the enormous capability of common computer systems, kinetic models have thus
not yet fully established for atmospheric pressure plasmas but switching to highly optimized
multi-processor systems (such as available on modern graphics card’s co-processors) promise
a huge potential.
Fluid Models:
Fluid models are much faster than kinetic models and thus capable to handle two- or threedimensional problems and complex chemistry. However, in general they are less accurate
than kinetic models as they rely on more a-priori assumptions to speed them up. In fluid
models, each species is described as an independent fluid with a density n, mean velocity ~u
and mean energy density E. The values of these global quantities are obtained solving the
equations of mass (2.41), momentum (2.42) and energy conservation (2.43) for each species.
These three equations can be derived from the according moments of the Boltzmann equation
2.47 and they are closed by Maxwell’s equations.
43
Chapter 2. Foundations
2.4. Modeling approaches
If no magnetic fields are present and each characteristic length of the discharge is well below
the wavelength of the applied voltage waveform, it can be sufficient to assume electrostatic
behavior. Hence, it is sufficient to solve only Poisson’s equation 2.44 instead of the full set
of Maxwell’s equations. A more comprehensive derivation can be found e.g. in chapter two
of [21].
∂ni
=
∂t
~ ~Γ +
∇
}
|−{z
transport
S
|{z}
prod. / destr.
~Γ = n~u
∂(~u)
~ u−
mn
= −mn(~u∇)~
{z
}
|
∂t
var. velocity field
∂
∂t
3
E
2
(2.41)
var.
~ + ~u × B)
~ + Ccoll.
+ qn (E
| {z }
|
{z
} collisions
pressure field
~
∇Π
|{z}
(2.42)
el. magn. fields
3
~u − ∇
~
~Q
~ − Lcoll.
∇~
= −∇
E~u − |E{z
}
|{z}
|{z}
2
{z
} compr. exp. conduction collisions
|
(2.43)
convection
∆φ = −
1 X
q i ni
ǫ0 i
(2.44)
The mass conservation equation (2.41) reveals a temporal change of a species density n can
either be attributed to transport i.e. flux ~Γ of density into or forth a small volume, or be
generated or destructed by reactions S with other species due to collisions.
Momentum conservation equation (2.42) is a little bit more delicate. It reveals a temporal change in momentum can either be caused by gradients of the velocity field, pressure
gradients, external fields or by collisions with other species.
Further body forces such as gravitation or buoyancy may be included on the right hand side.
~ and B
~ are electric and magnetic field.
Here m, ~u, q denote mass, velocity, and charge. E
Π is the pressure tensor and C represents a time rate term of momentum transfer due to
collisions (usually represented by a Krook collision tensor).
Ccoll. = −
X
β
mnνmβ (~u − ~uβ ) − m(~u − ~uG )G + m(~u − ~uL )L
44
(2.45)
Chapter 2. Foundations
2.4. Modeling approaches
A further common approximation, which is discussed in [21], leads to:
Ccoll. = −mnνm~u = −mνm~Γ
(2.46)
Here, νmβ is the collision frequency with species β. ~uG and ~uL denote the mean velocities of
newly created (G) or lost particles (L). As the pressure tensor Π is not determined in most
cases, usually it is replaced by the isotropic pressure p and the equations are closed using a
thermodynamic equation of state to relate p to n.
The energy conservation equation (2.43) can be derived from the third momentum of Boltzmann’s equation. It reveals a temporal change of the thermal energy density 3/2E can either
be caused by a flux of thermal energy density (i.e. convection), by compression or expansion
~ (i.e. conduction), or by collisions L (both
of the gas, by gradients of the heat flow vector Q
elastic and inelastic).
Again, the energy conservation equation must be closed by a further equation for the heat
~ which is usually done setting Q
~ = 0 or Q
~ = −κT ∇T
~ , where κT denotes
flow vector Q
the thermal conductivity and T the temperature. Common assumptions to simplify these
equations are e.g temporally and spatially uniform velocity fields, absence of magnetic fields,
and thermal energy flux balancing the collisional processes.
If heavy particles (ions, neutrals, meta-stables) can be assumed to remain at room temperature, for self-consistent treatment an energy distribution function remains to be calculated
only for the electrons explicitly.
A further simplification consists of the so-called Local Field Approximation (LFA) which
assumes the local energy gain of electrons in the local electric field to be outbalanced by
energy losses due to collisions. Accordingly, the electron energy distribution function (EEDF)
at each time and in each location is the same as in a uniform DC glow discharge of the same
respective field strength. Under these assumption also the electron energy conservation
equation does not need to be solved explicitly.
Nevertheless, the question remains under which conditions this assumption is valid.
The relaxation time of energy needs to be short. In other words, the mean free path needs
to be small in comparison to the spatial gradients of the electric field [62, 63]. This means,
the energy loss due to collisions takes place in the same evanescent volume as the energy
gain by the field, i.e. there is no diffusion or convection for the electron energy. Strong
field gradients are obviously present in the plasma boundary sheath. Here the LFA fails due
45
Chapter 2. Foundations
2.4. Modeling approaches
the neglected non-local effects. Another common approach is to explicitly treat the electron
energy conservation equation (including diffusion and convection) under the assumption of
a Maxwellian EEDF. However, non-equilibrium plasmas –as their name implies– typically
strongly deviate from a Maxwellian EEDF.
Based on several assumptions, fluid models can achieve a much faster speed than kinetic
models in terms of calculation time and thus can be applied to two- or three-dimensional
problems. However, their accuracy is often below the kinetic models due to the assumptions
e.g. for the energy distribution functions.
Hybrid Models:
A common approach to combine the benefits of both the PIC-MMC’s accuracy and fluid
model’s speed is called a hybrid model. Particles are again treated as independent fluids,
and –based on the cross-section of the respective reaction– a Monte Carlo Collision scheme
evaluates the collisions and transfers its probability back to the fluid equations in form of
collision or reaction rates [66].
∂f
~ − qE
~ ·∇
~ vf =
+ ~v ∇f
∂t
m
∂f
∂t
(2.47)
c
Here f denotes the species six-dimensional phase space, ~v is the mean velocity, e the charge
~ is the local external electric field and ∇
~ v is the velocity-gradient operaand m the mass. E
tor.
∂f
represents the temporal change of f with respect to the collisions. The most common
∂t c
approach to numerically calculate the kinetics is the two-term-approximation. Boltzmann’s
equation is expanded into spherical harmonics solving the equation only for the first two
expansion terms: The isotropic term, and the first anisotropic term as a minor deviation
form the isotropic one.
Since deviations from isotropy are small in most cases, this scheme is usually sufficient. For
high mean electron energies E/N , the anisotropy becomes more significant and thus higher
order expansion terms in Boltzmann’s equation must be considered for accuracy.
Here the challenge is to create the communication between both processes.
One way to implement collisions into the fluid model is to use electron transport coefficients
(diffusivity D and mobility µ) and electron impact reaction rates k (obtained from solving
Boltzmann’s equation (2.47) for the electrons).
46
Chapter 2. Foundations
2.4. Modeling approaches
For the momentum conservation equation (2.42) at atmospheric pressure the so-called ”driftdiffusion approximation” can be made. It assumes the collisional momentum transfer frequency to become high enough that velocity thermalizes almost instantaneously (vthermic >>
vconvective ). Thus, the mean velocity does not change much over time and the velocity’s temporal derivative can be neglected.
The mean free path becomes small and thus the first term on the right hand side can be
neglected as well. With p = nkB T and the collisional term solved for ~Γ, the following
expression can be used for momentum conservation:
~Γ = ne
q ~
kB T ~
E−
∇n
mνm
mνm
| {z }
| {z }
µ
(2.48)
D
The production and destruction term in the mass conservation equation (2.41) can then be
expressed by reaction rates k. What remains is mass and momentum conservation for each
species i and energy conservation equation only for the electron energy ǫ:
X
∂ni
~ ~Γi +
= −∇
ni nj kij
∂t
j
Γ~i =
~
∓ni µi E
| {z }
zero for neutrals
(2.49)
~ i
−Di ∇n
(2.50)
X me
X
∂(ne ǫ)
loss
~ ~Γǫ − e~Γǫ E
~−
−
3
= −∇
ne nj kej
kb νn ne (Te − Tg )
∂t
m
n
n
j
{z
}
{z
} |
|
inelastic losses
5~
5
~
with: ~Γǫ =
Γe ǫ − ne De ∇ǫ
3
3
1 X
q i ni
∆φ = −
ǫ0 i
(2.51)
elastic losses
(2.52)
Besides the choice of modeling approach and assumptions, another critical issue is the right
choice of species and reactions to consider.
Actually, each possible appearing species in each quantum state may differ in its contribution
to the overall behavior of the discharge. Quantum states with a short natural lifetime are
usually neglected within kinetic and fluid models as their contribution to the dynamics is
47
Chapter 2. Foundations
2.4. Modeling approaches
assumed to be small (due to fast depletion). Radiation as a form of energy transport is
usually neglected in each of the above mentioned modeling approaches.
Summarizing, no matter if a kinetic or fluid or hybrid model is applied, all of them must
be capable to handle collisions with electrons but also with ions and neutrals. Hence, they
depend on input data for the collision cross-sections to calculate the respective collision or
reaction rates from them.
However, for many reactions the database is still small and calculations are not necessarily
an easier source of reference. For other reactions there are several referenced values, but
coefficients can differ by some orders of magnitude from one reference to the other (exemplarily shown in figure 2.11 for two electron excitation cross-sections for helium as compiled
and printed in [67]).
Due to the vast number of assumptions and the uncertainty in available data for each reaction,
each model can only be found to be reliable if experimental evidence is shown for a huge
number of operational parameters.
Several models and numerical simulations have been developed to describe the underlying
plasma dynamics of rf excited atmospheric pressure plasma discharges. Only a few will be
named here.
Sakiyama et al. studied the corona-glow transition in an rf plasma needle discharge in
atmospheric pressure helium [76]. The applied two-dimensional fluid model attributes for
the special geometry of this discharge. Parallel plate configurations, on the other hand, have
been studied e.g by Yuan and Raja [27]. Balcon et al. investigated the discharge dynamics
in an argon discharge [64], whereas Shi and Kong investigated the mode transition in an
atmospheric pressure helium glow discharge by a one-dimensional fluid model [65]. Here,
the exciting rf frequency of 13.56 MHz and a discharge gap of 2.4 mm represent conditions
similar to the µ-APPJ. However, an admixture of oxygen is not addressed in this study.
Other studies e.g. focus on the oxygen chemistry in the plasma afterglow, neglecting the
discharge dynamics [58] or e.g. focus on the complex chemistry of H2 O admixtures in a
helium discharge by means of a global model [22].
Two recent models self-consistently describing the creation of reactive oxygen species inside a
He/O2 atmospheric pressure plasma jet are the models of Park et al. [43, 44] and Waskoenig
et al. [4, 45]. Both models consider a variety of helium and oxygen species and charges, such
as electrons, positive and negative ions, neutrals, radicals, and meta-stables and some tens
to more than hundred reactions among them. Further, both models predict a steady state
atomic oxygen density of some 1015 to few 1016 cm−3 for a plasma power of a few watts.
48
Chapter 2. Foundations
2.4. Modeling approaches
Figure 2.11: Example of differing or incomplete cross-section data for various helium electron-excitation cross-sections as compiled and printed in [67].
Upper: He (1s2 1 S → 1s2s 3 S). Lower: He (1s2 1 S → 1s5f 3 F).
49
Chapter 2. Foundations
2.4. Modeling approaches
The former one, however, is a global model. Transport effects such as convection, diffusion
and drift are neglected. It assumes a Maxwellian electron energy distribution function and
does not resolve the high dynamics of the rf excitation. As the electron driven reactions
–such as excitation, ionization and dissociation– non-linearly depend on the local and transient electron energy distribution function and electron density, the assumption of spatially
and temporally averaged values may cause misleading results. Due to the overall averaging,
transitions of the operation mode such as the transition to arcing cannot be resolved. Measured spatially and temporally averaged steady state densities thus remain the only possible
parameters to benchmark the model. Surface losses are considered by an abstract thermal
flux and a surface to volume ratio. As unity surface quenching is assumed, the dominant loss
process for atomic oxygen is predicted to be surface loss. Although the quantitative value of
the atomic oxygen surface loss coefficient is not known exactly (may vary with temperature,
pressure, surface material etc.), it is found to be significantly smaller than one [46].
The model by Waskoenig et al. was developed in a close collaboration (regarding discharge
geometry, operation range, possible reaction rates and processes) and consists of a onedimensional fluid model with a semi-kinetic treatment of the electrons. Due to the small
surface loss coefficient, surface quenching here is considered to be zero. Hence, volumetric
losses are predicted to be dominant in this model. The spatial dimension of the discharge
gap is explicitly considered as well as the transient charge dynamics of the rf excitation
frequency. Accordingly, the model can resolve the transition between distinct discharge
modes. The rf transient dynamics and the spatial resolution of the discharge gap represent
a further possibility for experimental evidence.
The experimental results obtained in this thesis will be compared to the latter model as
the numerical implementation is implemented for a commercially available solver (COMSOL Multiphysics [75]) and it consists of less a priori assumptions. In the following, the
applied diagnostics will be introduced and subsequently the measured densities will be presented. Afterwards, the experimental results will be compared to recent model predictions
and respective conclusions will be drawn.
50
3 Experimental setup and evaluation
methods
3.1 The micro-scaled Atmospheric Pressure Plasma Jet
The original design of the µ-APPJ –consisting of a quartz cuvette and U-shaped electrodes
inserted from the front side– shows some uncertainty in the vicinity of the transition area
from plasma core to post-discharge effluent. In that area where the quartz cuvette’s edge is
already reached, there is still plasma generated between the out-sticking electrodes. Several
unwanted effects may occur here, as there is the mixture with the outer atmosphere (air),
formation of possible vertices, a widening of the gas stream due to non-constant cross-section
of the gas channel, and a limited access for laser diagnostics due the material’s edges.
For this work a modified version of the micro-scaled atmospheric pressure plasma jet (µAPPJ) was build as shown in figure 3.1. Two rectangular stainless steel electrodes of 1
mm thickness and 40 mm length in a distance of 1 mm are extended with rectangular glass
panes of 1 mm thickness and 50 mm length. From bottom and top electrodes and extensions
are covered by two rectangular quartz panes of 100x10x1 mm3 forming the gas channel of
1x1 mm2 cross-section. Electrodes and extensions are mounted on stainless steel blocks
of which one is grounded, the other one is powered. The whole construct is fitted into a
polyoxymethylene (POM) case and luted with viton seals. At the electrodes side a gas inlet
is assembled and connected to the Swagelok compatible gas supply system by silicone hose
and hose clips. Impermeability was validated under distilled water.
This construction was chosen to suppress back diffusion of outer atmosphere and ensures a
continuous access for optical diagnostics along the plasma channel, post-discharge effluent,
and the transition area in between. Due to the constant channel cross-section, spatial and
temporal data can be conveniently converted via gas flow velocity.
51
Chapter 3. Setup
3.1. The micro-scaled Atmospheric Pressure Plasma Jet
Figure 3.1: Sketch of the modified micro-scaled atmospheric pressure plasma jet
with extended effluent channel as used in this work.
52
Chapter 3. Setup
3.2. Gas supply and experiment chamber
3.2 Gas supply and experiment chamber
The feed gas is supplied from helium and oxygen gas cylinders. Impurities are below 6 ×
10−5 . Gas flows are controlled by mass flow controllers (AnalytMTC, accuracy 0.8%) with
maximum values of 100 sccm for oxygen and 5000 sccm for helium. The mass flow can be
set digitally via connection to a PC. Xenon can be admixed via a needle valve. Each gas
supply can be additionally by-passed for quick evacuation as well as cut-off via additional
valves. The whole gas feed line consists of Swagelok compatible 6 mm stainless steel tubes.
It ends inside a stainless steel vacuum-tight experiment chamber (see figure 3.2). From there
the gas line is connected to the µ-APPJ via silicone hose and hose clips.
For TALIF measurements the µ-APPJ is mounted on a three-orthogonal-axis stepper-motor
controlled actuator in the center of the chamber. Including transmission (≈ 20.000 Steps/mm)
the actuator offers a reproducible positioning within an accuracy of 0.1 mm.
During plasma operation the chamber lock is masked only by black cloth to prevent overpressure. During xenon calibration, the chamber is locked vacuum-tightly, evacuated and
then filled with few pascals of xenon while the µ-APPJ is not powered. This guarantees a
homogeneous distribution of xenon inside and outside the µ-APPJ.
Evacuation is performed by a membrane pump and a turbo molecular pump. Pressure is
monitored by a wide range ionization gauge (Edwards: Widerange Gauge WRG-S, Active
Gauge Control 10−4 to 102 Pa) with an accuracy of 5%.
53
Chapter 3. Setup
3.3. Power supply
Figure 3.2: Diagram of the gas supply for the µ-APPJ.
3.3 Power supply
The electrical circuit for the power supply is shown in figure 3.3. A commercial rf power
generator (Dressler CESAR 1312D, 200 - 240 V, 13.56 MHz, 1200W) is connected to a
commercial tunable Π-Type impedance matching network (Dressler VM 700 A) via an Ntype 50 Ω rf cable. The output power of the rf generator can be controlled in 1 W steps.
However, the power consumption of the µ-APPJ is a few watts only. Thus, an additional
load (50 Ω, 100W) is inserted parallel between generator and matching unit to increase the
generator power interval for operation.
A custom made U-I probe built according to [68] (see figure 3.4) is inserted between matching
network and µ-APPJ. BNC cables are used for all connections behind the matching network.
Inner and outer conductor are separated a few cm in front of the µ-APPJ and attached to
the respective electrodes. For TALIF operation the cable is guided via a BNC type vacuum
connection into the vessel.
The U-I probe was calibrated to a 50 Ω shunt. Probe signals were recorded at an oscilloscope
and guided to a phase detector (ANALOG DEVICES AD8302) which delivers the phase angle
between two input signals as a DC voltage of 10 mV/◦ . During TALIF operation the U-I
probe is not attached.
For phase resolved emission spectroscopy measurement the µ-APPJ is mounted outside the
54
Chapter 3. Setup
3.3. Power supply
Figure 3.3: Diagram of the power supply and electrical circuit.
Figure 3.4: Diagram of the applied U-I probe.
55
Chapter 3. Setup
3.4. Optical setup TALIF
vessel on an optical bench and a further custom made rf- trigger box is attached in parallel
behind the matching network.
3.4 Optical setup TALIF
The optical setup for TALIF measurements can be found in figure 3.5. A Nd:YAG pumped
tunable DYE laser (Continuum Powerlite 8000, Continuum ND6000) provides 10 Hz repetitive laser pulses of approximately 7 ns length and 70 mJ pulse energy in the necessary
spectral range of 670 to 680 nm. The output wavelength can be scanned in 1 pm steps via
a stepper motor controlled grating (Dual 2400 lines/mm).
The second harmonic of the laser frequency is generated via a KDP non-linear optical crystal
and mixed with the fundamental mode within a BBO crystal to generate the desired third
harmonic in the UV range of 224.31 nm for xenon excitation and 225.65 nm for atomic
oxygen generation.
The UV laser beam of approximately 5 mm diameter is guided through a mutable attenuator
consisting of a dielectric-coated thin quartz substrate. A stepper motor controlled tilt causes
a variable attenuation of 95 to 5 percent within an angular interval of approximately 5◦ .
This kind of external attenuation is applied to vary the laser pulse intensity without changing
further beam attributes.
An adjacent beam splitter images a few percent of the laser light onto a fast UV photo-diode
as a reference for the attenuated laser pulse intensity. The majority of the laser beam is
focused into the center of the experiment vessel by a quartz lens of 300 mm focal length
under a vertical angle of 45◦ . The laser focus is imaged onto an infra-red sensitive, actively
cooled, and gated photo multiplier tube (PMT, BURLE C31034A) by a BK7 lens of 130 mm
focal length and 56 mm diameter.
An aperture slot of 0.5 mm in the focal plane in front of the PMT limits the imaged length of
the laser focal volume. The beam profile in the laser focus could not be determined directly.
However, measuring the vignetting at the electrode edges revealed a radius of the laser focal
volume of approximately 200 µm (assuming a homogeneous distribution in a cylindrical focal
volume).
An interference filter (∆λF W HM = 19 nm at a central wavelength of λc = 842 nm) between
aperture slot and the photo-sensitive area of the PMT transmits the fluorescence wavelengths
of oxygen at 844 nm and xenon at 835 nm.
56
Chapter 3. Setup
3.4. Optical setup TALIF
Figure 3.5: Sketch of the TALIF setup.
57
Chapter 3. Setup
3.4. Optical setup TALIF
Figure 3.6: Coordinate system
Nd:YAG laser and PMT gate are triggered by an external digital pulse-delay generator (DG
535). PMT and UV diode signal are recorded with a digital sampling oscilloscope (HP 5410A
250 MHz 1 GSa/s) and subsequently evaluated on a PC.
The µ-APPJ is mounted on the actuator and positioned vertically (gas stream directed
upwards) in the center of the vessel with the optical foci inside the center of the plasma
channel. Spatial resolution of the TALIF signal is achieved by translation of the µ-APPJ
through the fixed optical setup.
3.4.1 Coordinate system
For orientation within the spatial TALIF measurements, a coordinate system is defined
according to the three axes of the discharge as shown in figure 3.6. Axis x and y span the
area of the discharge channel cross-section. The x axis denotes the direction of the electrode
gap, the y axis directs along the gap between the quartz panes. Origin of both axes is set to
the center of the gas channel cross section. The z axis is set in the direction of the gas flow
within the channel. Its origin is the electrode edge at the side of the gas inlet.
The µ-APPJ is mounted upright within the experiment vessel, laser excitation and fluorescence imaging are performed in the z-y-plane.
58
Chapter 3. Setup
3.4. Optical setup TALIF
iode
PMT (x50)
UV d
oscilloscope signal [V]
0.5
0.4
0.3
0.2
or 1
or 2
curs
0.1
curs
y
0
0.0
-200
-150
-100
-50
0
50
100
150
200
time [ns]
Figure 3.7: Oscilloscope waveform recorded for the UV diode as a reference for the
laser intensity and PMT as a reference for the fluorescence.
The three axis of the stepper motor controlled stage overlap with the three axis of the µAPPJ. According to the large ratio of electrode length (40 mm) to electrode distance (1 mm),
the accuracy of the alignment must be better than 0.1◦ to assure measurements remain e.g.
in the center of the discharge cross-section while scanning from gas inlet to effluent. Hence,
even a slight misalignment occurring between actuator axis and µ-APPJ must be actively
compensated by the stepper motor control.
This is achieved by scanning the gas channel cross-section at different z values (e.g. z =
5 mm and z = 35 mm) to find the coordinates of the respective centers. For evaluation,
z axis is then accounted for as the interpolated line intersecting the centers of the channel
cross-sections.
3.4.2 Signal acquisition and evaluation
Figures 3.7, 3.8, and 3.9 show the TALIF signal acquisition and evaluation method applied
in this work. The reference signal for the laser intensity and the fluorescence signal from the
photo multiplier tube were recorded with a digital sampling oscilloscope (figure 3.7). Both
signals were averaged over at least 64 laser shots to account for a better signal to noise
ratio. As laser shots were not synchronized to the rf plasma excitation, a transient electron
excitation can thus be subtracted as background radiation. Two cursors (1 and 2) mark the
59
Chapter 3. Setup
3.4. Optical setup TALIF
iode
PMT (x50)
UV d
oscilloscope signal [V]
0.5
0.4
or 3
cursor 4
curs
0.3
0.2
0.1
0.0
-20
0
20
40
60
80
100
120
time [ns]
Figure 3.8: Signals shifted due to y0 (averaged outside cursor 1 and 2).
-4
ln ( PMT signal [V] )
-5
or 3
cursor 4
curs
-6
-7
-8
-9
-10
-20
0
20
40
60
80
100
120
time [ns]
Figure 3.9: PMT signal on logarithmic scale and decay-rate fit (Cursor 3 and 4
marking the fluorescence interval after laser excitation and before late
scattering reflexions).
60
8
-1 -1
normalized TALIF signal [10 V
s
]
Chapter 3. Setup
3.4. Optical setup TALIF
4
3
2
J=2
J=1
J=0
1
0
88630
O
(2p
4 3
88631
P - 3p
2
3
88632
P ) wavenumber [cm
J
88633
-1
]
Figure 3.10: Measured line profiles for the respective two-photon transition of
atomic oxygen incl. Voigt profile best fit.
interval to calculate the corresponding y0 offset for both signals from the signal level outside
these cursors.
For data evaluation the temporally integrated signals between cursor 1 and 2 were chosen
with respect to the calculated offset (figure 3.8).
For measurements of the total de-excitation rate, cursor three denotes the end of the laser
pulse, where no further excitation takes place. Cursor 4 is set 10 ns after cursor 1 before the
onset of late reflexions and noise. Between cursor 3 and 4 an automated exponential fit is
applied to evaluate the effective de-excitation time (figure 3.9).
3.4.3 Xenon calibration
For absolute calibration of the TALIF system, the µ-APPJ was operated at standard parameters of 1500 sccm helium flow with an admixture of 9 sccm O2 at an intermediate
generator power of 12 W. The µ-APPJ was moved within the vessel, until the foci of laser
and fluorescence imaging overlapped in the center of the discharge cross-section at z = 30
mm.
In this position, a wavelength scan of the dye laser was performed to find the resonance
wavelength of the two-photon excitation (figure 3.10). After the wavelength scan, the dye
61
Chapter 3. Setup
3.4. Optical setup TALIF
squared laser pulse energy [(µJ)
921
0
TALIF PMT Signal [10
-10
Vs]
4
2
]
1843
2764
0.4
0.6
O
Xe (0.65Pa)
3
Xe (1.1Pa)
Xe (3Pa)
2
1
0
0.0
0.2
squared UV d
iode signal [10-18 V2s2]
Figure 3.11: Variation of the laser intensity to validate the quadratic dependence
of the TALIF signal.
laser was set to the resonance wavelength and subsequently the quadratic dependence of the
fluorescence signal on the laser intensity was validated by a variation of the incident laser
intensity (figure 3.11).
For xenon calibration, the µ-APPJ was kept in the same position, the vessel was closed and
pumped down to 10−3 Pa. Subsequently it was filled with a controlled low pressure xenon
atmosphere of 3 Pa. The dye laser then scanned the respective two-photon transition (figure
3.12) and was set to the on-resonance wavelength. Here, the quadratic dependence on the
laser intensity was validated as well (figure 3.11).
Due to the pressure gauge accuracy of 5%, these measurements were repeated for two further
xenon fillings 0.65 and 1.1 Pa and the regression line of all three pressures was chosen for
reference (figure 3.13).
As the ratio of two-photon excitation cross-sections for oxygen and xenon was given only
for the spectrally integrated cross-sections, the ratio of on-resonance peak value and spectrally integrated signal –over the whole resonance– was obtained from figures 3.10 and 3.12.
Accordingly, following measurements were carried out by first finding the on-resonance and
subsequently measuring at the fixed on-resonance wavelength only.
62
8
-1 -1
normalized TALIF signal [10 V
s
]
Chapter 3. Setup
3.4. Optical setup TALIF
4
3
2
1
0
89161
Xe (5p
89162
6 1
89163
89164
89165
S - 6p'[3/2] ) wavenumber [cm
0
2
-1
]
Figure 3.12: Measured line profiles for the respective two-photon transition of
xenon incl. Voigt profile best-fit.
xenon density [1014 cm-3]
10
8
6
4
2
0
0
4
2
6
Xe TALIF signal / squared UV diode signal [10
8
8
-1 -1
V
s
]
Figure 3.13: Calibration signal for several xenon partial reference densities.
63
Chapter 3. Setup
3.5. Optical setup PROES
3.5 Optical setup PROES
The optical setup for phase resolved optical emission spectroscopy is shown in figure 3.14.
The µ-APPJ’s plasma channel is imaged onto the intensified CCD chip (ICCD) of a camera
(LaVision Picostar HR) via a cylindrical lens (f = 40 mm) and a commercial prime lens (f
= 50 mm). This setup ensures that both the electrode distance of 1 mm and the length of
the plasma channel of 40 mm can be imaged with sufficient resolution.
Due to the cylindrical lens, the image is smoothed out in the direction of the plasma channel
by a few millimeters. The electrode gap is imaged onto the ICCD chip with an effective
resolution of 48 pixel per millimeter, while the full electrode length is imaged onto the chip
with an effective resolution of 11 pixel per millimeter.
The ICCD chip consists of a commercial CCD chip (512x512 pixel) and a fast gated microchannel plate (MCP) as an intensifier. During the CCD’s integration time of several
milliseconds, the MCP is synchronized to the µ-APPJ driving rf voltage via a custom trigger
unit additionally applied to the rf signal and a PC controlled custom delay generator as can
be found in figure 3.3.
An interference filter of ∆λF W HM = 10 nm at the central wavelength of λ = 778 nm assured
only light of the 777 nm line to be recorded. The plasma operation parameters are 1500
sccm helium flow with an admixture of 9 sccm O2 . The insertion of the custom phase trigger
box caused an additional stray capacitance. Thus, the reference generator power is shifted
upwards to 15 W for ignition and to 40 W for the transition to arcing.
Figure 3.15 introduces the procedure how the phase resolved emission plots are generated.
For each transient position within the phase cycle (e.g. figure 3.15 a) and 3.15 b)), the
emission image of the complete discharge channel is recorded. The gate width is set to 1
ns while the phase-delay increase is 0.6 ns for each successive image (oversampling). The
rf cycle of 74 ns is thus resolved within 123 separate images. At a fixed position z of the
channel the horizontal cross-section is averaged over the nearby 20 pixels (i.e. 2 mm) in
horizontal direction and combined with the respective information from the other images to
form the phase resolved emission plots (figure 3.15 d)). The position of the electrode edges
is derived from a back light picture as indicated in figure 3.15 c).
64
Chapter 3. Setup
3.5. Optical setup PROES
Figure 3.14: Optical setup for phase resolved optical emission spectroscopy.
65
Chapter 3. Setup
3.5. Optical setup PROES
Figure 3.15: Evaluation of phase resolved optical emission data. a) Emission image
of the µ-APPJ discharge channel during operation at a fixed temporal
position within the excitation cycle. b) Emission image at a different
temporal position within the excitation cycle. Lateral position and
averaging spatial interval of evaluation is marked. c) Electrode reference position is derived from a back light image. d) Phase resolved
emission plot obtained from images at several temporal positions.
66
Chapter 3. Setup
3.6. Setup for temperature measurements
3.6 Setup for temperature measurements
To measure the gas temperature inside the µ-APPJ, two methods were applied: Optical
emission spectroscopy of nitrogen rotational emission bands and insertion of a fluorescence
fiber thermometer into the gas channel.
The optical emission spectroscopy was carried out by positioning the glass fiber of a USB high
resolution UV-spectrometer (OceanOptics, 325 - 420 nm, ≈0.05 nm resolution) perpendicular
to the gas channel close to the effluent at approximately z=32 mm. The distance between
gap and fiber of 2 cm ensures integrated light recording over the whole 1 mm discharge
gap.
For probe measurements the quartz panes have been replaced by ordinary glass panes with
a hole of 1 mm diameter drilled into one of the panes centrally at a position 8 mm before the
transition from electrodes to the effluent as shown in figure 3.16. The tip of the fluorescence
thermometers (LUXTRON I652, STF probe, outer diameter 0.8 mm) fiber was inserted into
the hole perpendicular to the glass pane until the tip reached half of the plasma channels
cross section. Hole and fiber were sealed by covering the hole with adhesive tape and pushing
the fiber through the tape.
67
Chapter 3. Setup
3.6. Setup for temperature measurements
Figure 3.16: Scheme of the setup for temperature measurements.
68
4 Results
4.1 Discharge characterization
To classify the results of TALIF and (PR)OES measurements it is first mandatory to analyze
the typical operation mode of the µ-APPJ and to span the interval of outer parameters in
terms of applicable gas mixtures and in coupled powers.
4.1.1 Operation range
For the electric characterization, the calibrated U-I probe measures total voltage and total
current at the insertion point under variation of the generator power. Due to the small
impedance of the µ-APPJ it is very difficult to measure the conduction current directly,
as the conduction current is dominated by the displacement current by far. However, the
voltage at the measuring points can be assumed to be the same as at the electrodes due to
the low resistivity of the BNC connecting cables.
The dependency of the rms voltage on the generator power can be seen in figure 4.1. Data
was recorded for the generator power interval from zero to close before arcing of the µ-APPJ
for various admixtures of oxygen to the 1500 sccm helium base gas flow at atmospheric
pressure (1000 mbar). One can see that from approximately 10 W on, a linear fit with a
slope of 3 V/W and an offset of 62.8 V describes the dependency well. This information is
valuable for comparison to measurements where only either generator power or voltage are
known.
The ignition of the plasma as well as the transition to the arcing mode occurs at different
voltage threshold values as measured in 4.2. The ignition voltage increases almost linearly
from 79 V at 0.2% oxygen admixture to 129 V at 1.6% oxygen admixture. The threshold
69
Chapter 4. Results
4.1. Discharge characterization
160
rms voltage [V]
140
120
0 sccm
100
6 sccm
80
O
O
O
O
O
2
2
12 sccm
60
18 sccm
40
24 sccm
0
10
20
2
2
2
30
generator power [W]
Figure 4.1: Dependency of the rms voltage on the generator output power.
160
rms voltage [V]
140
120
100
80
60
40
arcing
20
ignition
0
0.0
0.5
O
2
1.0
1.5
xture [%]
admi
Figure 4.2: Dependency of ignition voltage and arcing voltage on the admixture
of oxygen to the helium base gas flow of 1500 sccm at atmospheric
pressure
70
Chapter 4. Results
4.1. Discharge characterization
5
total current [A]
4
3
0 sccm
6 sccm
2
O
O
O
O
O
12 sccm
1
18 sccm
24 sccm
2
2
2
2
2
0
0
10
20
30
generator power [W]
Figure 4.3: Dependency of the total current on the generator output power.
voltage for arcing also increases from 127 V at 0.2% oxygen admixture to 150 V at 1.6%
oxygen admixture with a smaller slope than the ignition voltage.
A stronger fluctuation in the threshold voltage for the transition into the arcing mode is due
to the small differential resistance in that area (U-I characteristic measured for the APPJ
shows a maximum at the transition and thus a vanishing slope). Here minor fluctuations of
the applied voltage can easily cause an on-set of arcing.
It is further worth noting that for pure helium ignition voltage of 91 V and arcing threshold
of 161 V are higher than for a slight molecular admixture which may be attributed to the
higher ionization threshold of helium (25 eV) in comparison to molecular oxygen (12 eV).
For higher admixtures however, energy consumption in rotational and vibrational states as
well as formation of negative ions may cause both thresholds to increase again. Due to the
slightly different slope, ignition and arcing threshold tend to intersect for admixtures higher
than around 1.8% preventing a stable operation for higher admixtures.
Measured total currents are shown in figure 4.3 for generator powers from zero to close before
arcing for each admixture. From approximately 10 W on, a linear fit with a slope of 0.08
A/W and an offset of 1.73 A describes the dependency well.
Plotting the measured voltage against the total current (figure 4.4) we can find a constant
total impedance of |Z| = 36.5 Ω caused by the impedance matching, the connection cables,
the U-I probe and the µ-APPJ. Calculating the rf resistance χ = 1/(2πf C) of a vacuum
71
Chapter 4. Results
4.1. Discharge characterization
160
rms voltage [V]
140
ignition
120
100
arcing
80
1500 sccm He incl.
60
0.0%
40
0.6%
20
1.2 %
0
0
1
2
3
O
O
O
2
2
2
4
total rms current [A]
Figure 4.4: Rms voltage versus total rms current shows a linear dependence due
to the large stray capacitance of the system.
plate capacitor with an area of 40 mm2 and a distance of 1 mm, we end up with a capacitance
of ≈0.35 pF and thus with an rf resistance of χ = 33 kΩ. This indicates the presence of a
stray capacitance (cause by cables, µ-APPJ housing, the vessel transition, and the U-I probe
itself) orders of magnitude higher than that of the actual plasma channel (before plasma
ignition).
Under the assumption that no conduction current is present between the electrodes (here
the phase difference is assumed to be 90◦ ) close before ignition of the plasma, we may
attribute a change in the phase angle between total current and voltage to the appearance of
a conduction current within the plasma. The phase detector indicates the phase between two
signals as a DC voltage of 10 mV/◦ with an accuracy of 0.1◦ . Applying the phase detector
to the total current and voltage signal (figure 4.5), we obtain a total phase shift between
ignition and arcing of less than 3◦ which is less than 200 ps and thus not resolvable for our
oscilloscopes. At transition to the arcing mode however, the phase change of around 30◦ is
significantly higher due to the well conducting character of the arc discharge.
Due to different cable lengths and possible internal delay, we cannot obtain an absolute phase
difference between voltage and current but only the shift of the phase difference.
Assuming the conduction current Iplas within the plasma to be Iplas = Itotal · cos (π/2 − δφ),
we can find the U-I characteristic of our plasma as shown in figure 4.6 for four different gas
72
Chapter 4. Results
4.1. Discharge characterization
100
relative U-I phase shift [°]
1500 sccm He
9 sccm
O
2
10
arcing
ignition
1
0,1
0,01
0
10
20
30
generator power [W]
Figure 4.5: Dependency of the phase shift between total current and voltage under
variation of the generator power.
160
760 Torr
rms voltage [V]
140
120
0.4%
0.8%
100
1.2%
6
1. %
O
O
O
O
2
2
2
2
80
0
4
8
12
16
20
24
rms current [mA]
Figure 4.6: Rms voltage plot against the rms conduction current obtained from
the phase shift.
73
Chapter 4. Results
4.1. Discharge characterization
250
600 Torr
rms voltage [V]
200
150
100
6
He (1. mm)
He (2.4mm)
50
He + 1%
O
2
(2.4mm)
0
0
10
20
30
40
50
60
-2
rms current density [mA cm
]
Figure 4.7: U-I characteristic of the APPJ as measured by Park et al. in [25],
current normalized to electrode area of 100 cm2 .
admixtures.
A steep slope can be found for small currents below approximately 10 mA and low voltages
below approximately 130 V. Here the signal is very noisy due to the phase probe operating
below its accuracy limit. Towards higher currents and voltages a flattening of the slope
occurs. Further, one can observe the maximum measured current to increase for higher
admixtures of O2 . This agrees well with the expected U-I characteristic derived from the
larger APPJ.
Maximum powers are thus approximately 0.5 W for a 1500 sccm flow with an admixture of
0.4% of oxygen, approximately 1.5 W for an admixture of 0.8%, 2.6 W for an admixture
of 1.2%, and 3.0 W for an admixture of 1.4%. However, these data strongly rely on the
assumption of 90◦ phase shift shortly before ignition and a total phase shift only caused by
the conduction current within the plasma. Further considering the accuracy of the DC phase
signal output to be given as ”better than ±1◦ ” (but certainly not better than ±0.1◦ ), it must
be noted that the shown U-I graph must be seen as a rather qualitative graph.
Due to the flattening of the U-I characteristic, the plasma becomes highly sensitive to voltage
fluctuations in this regime. Hence, the transition into an arc-like discharge can easily occur
for small fluctuations of the generator’s voltage stability.
Park et al. measured the U-I characteristic for the larger APPJ [25] as partially shown in
74
Chapter 4. Results
4.1. Discharge characterization
250
760 Torr
rms voltage [V]
200
150
0.4%
100
0.8%
1.2%
50
6
1. %
O
O
O
O
2
2
2
2
0
0
10
20
30
40
50
60
-2
rms current density [mA cm
]
Figure 4.8: U-I characteristic of the µ-APPJ as measured in this work normalized
to electrode area of 0.4 cm2
figure 4.7 for larger gap sizes of 1.6 mm and 2.4 mm at a reduced pressure of 600 Torr. Park
et al. showed that the characteristic voltages decrease with the electrode distance (180 V
ignition voltage at 2.4 mm and 130 V at 1.6 mm for pure helium at 600 Torr), and increase
with pressure and admixture.
Currents measured for the APPJ are in the range of 1 to 6 A, however for an electrode area
of 100 cm2 .
Normalizing the current to the electrode area, we find typical current densities shortly before
transition into the arcing mode in the range of 50 mA cm−2 for both devices (figure 4.8).
This underlines the good comparability between APPJ and µ-APPJ. Powers coupled into
the µ-APPJ can thus be found to be in the order of one or two watts, increasing with the
amount of molecular admixture.
Calorimetric considerations
We can further estimate the power coupled into the plasma on a calorimetric base. Assuming,
that the majority of the input power causes gas heating (directly or indirectly) and formation
of reactive oxygen species, we can estimate the power necessary to heat a gas and to dissociate
molecular oxygen. Light emission is neglected here, as at atmospheric pressure collisional
de-excitation is supposed to dominate the radiative de-excitation.
75
Chapter 4. Results
4.1. Discharge characterization
We consider typical operation conditions of a gas flow of 1500 sccm helium with an admixture
of 9 sccm O2 (0.6%). As the majority of the gas consists of helium (heat capacitance 5193 J
kg−1 K−1 ) we end up with a heating power of 0.023 W/K. Thus, considering 1 W to only heat
the gas flow, we can obtain a temperature increase of around 43 K. Assuming that all charges
have recombined in the effluent and the dominant reactive oxygen species is atomic oxygen
(assuming ozone being created from this atomic oxygen later and neglecting meta-stables)
we can calculate the power to create a certain partial density of atomic oxygen.
A binding energy of 498 kJ/mole [69] for molecular oxygen leads to a dissociation power of
3.3 W/ admixed 9 sccm oxygen (partial pressure 1.6 × 1017 cm−3 ). As we gain two oxygen
atoms per dissociation, this leads to 1 W for the creation of 1017 cm−3 of atomic oxygen.
Due to the high uncertainty in the determination of power coupled into the plasma, in the
following only the rf generator power will be given as a reference. Parameter variations are
carried out from ignition to close to arcing thus spanning the range of operation.
Summary
The operation interval from ignition to arcing strongly varies with the gas mixture. The
higher the amount of admixed oxygen is, the higher the threshold values of voltage and generator power will be. The threshold interval between ignition and arcing decreases for higher
admixtures of oxygen. For admixtures of more than approximately 1.6%, no stable operation can be sustained. Within the interval between ignition and arcing, generator power and
measured voltage scale approximately linearly. Thus, threshold values of ignition and arcing
(either for measured voltage or generator power) are a good reference when comparing different electric setups. Due to the small but varying impedance of the µ-APPJ, measurements
of the discharge power are very difficult. Calculations of the plasma conduction current from
the phase shift of total voltage and current reveal powers in the order of one or two watts.
The obtained power densities are comparable with measurements on the APPJ (much higher
impedance) and agree well with calorimetric considerations.
4.1.2 Gas temperature
Another important parameter of operation is the gas temperature as most of the (heavy particle) reactions taking place inside the plasma more or less depend on the gas temperature.
The two most common temperature diagnostics are temperature probes and optical emission
diagnostics, both with their respective advantages and disadvantages.
76
Chapter 4. Results
4.1. Discharge characterization
6
measured emission
intensity [a.u.]
5
4
simulated emission
interval for least square fit:
335.4 - 336.8 nm
3
T
rot
=
320 K
2
1
0
335
336
337
338
wavelength [nm]
Figure 4.9: Sample measured spectrum and simulated emission spectrum best fitting for a temperature of 320 K.
Both methods were applied in this work. Firstly measuring the molecular emission spectra
of the nitrogen impurities’ rotational bands and comparing to simulations of the respective
spectra at varying temperatures, secondly the application of an optical fiber fluorescence
thermometer.
Due to a large pressure broadening of the lines at atmospheric pressure, temperature determination by means of Doppler-broadening is not applicable. Evaluating the temperature from
the emission spectrum of rotational bands has the advantage of being non-intrusive, but the
accuracy is usually limited to values of at least ±20 K, and measurements highly depend on
the assumption that rotational states are in an equilibrium with the gas temperature. The
evaluated emission spectra must not overlap with other atomic lines and there must not be
any additional excitation mechanisms such as energy transfer from meta-stables [70, 71].
Figure 4.9 shows the measured emission spectrum of the nitrogen N2 (C-B, ν’=0, ν”=0)
band as open squares, and the respective simulated emission of 320 K as a dashed line. The
emission spectrum was simulated under a variation of the gas temperature, while fitting to
the measured spectrum a least square fit. The wavelength interval for the spectrum fit was
chosen from 335.4 to 336.8 nm to avoid low signal noise for too small wavelengths and to
avoid outliers from the band head.
Figure 4.10 shows the temperature obtained from the emission spectra as open circles. Mea-
77
Chapter 4. Results
4.1. Discharge characterization
380
fluorescence fibre
T
temperature [K]
360
rot
N
2
(C-B, v'=
0 v''=0)
340
320
300
0
10
20
generator power [W]
Figure 4.10: Variation of the generator power at a helium flow of 1500 sccm with
an admixture of 0.6% of oxygen.
360
fluorescence fibre
temperature [K]
T
rot
N
2
(C-B, v'=
0 v''=0)
340
320
300
0.5
0.0
O
2
1.0
admixture [%]
Figure 4.11: Variation of the oxygen admixture at a power of 12 W for a gas flow
of 1500 sccm.
78
Chapter 4. Results
4.1. Discharge characterization
fluorescence fibre
temperature [K]
360
T
rot
N
2
(C-B, v'=
0 v''=0)
340
320
300
0.0
0.5
1.0
1.5
2.0
2.5
He flow [slm] incl.
3.0
3.5
4.0
4.5
5.0
0.6% O2 admixed
Figure 4.12: Variation of the total gas flow at an admixture of 0.6% and 16 W
generator power.
surements were carried out under variation of the generator power at a gas flow of 1500 sccm
He with an admixture of 0.6% O2 .
Measurements reveal a strong statistical spread within a temperature interval from 300 to
360 K. Due to this strong spread, no distinct trend can be observed. Figure 4.11 and figure
4.12 show a similar behavior for a variation of the admixed oxygen (to a constant flow of
1500 sccm He at a fixed generator power of 12 W), and a variation of the total gas flow at a
constant admixture of 0.6% O2 and a fixed generator power of 16 W.
In the low power operation regime as well as in the operation regime of high admixtures,
the total intensity of the plasma radiation decreases. Hence, the spread of OES temperature
measurements increases in these regions.
From the OES measurements it can be concluded, that the gas temperature remains close
to room temperature over a large interval of operation parameters. To gain a better understanding of temperature trends, a fluorescence fiber probe thermometer was subsequently
applied as an alternative diagnostic.
Probes, on the other hand, are intrusive to the system and thus may change the plasma
properties itself. Further it must be assumed that no additional surface heating occurs due
to charge fluxes to the probe’s surface.
79
Chapter 4. Results
4.1. Discharge characterization
Figure 4.10 shows the probe temperature’s dependence on the generator power for a helium
gas flow of 1500 sccm and an admixture of 0.6% of oxygen. Before ignition at 10 W temperature increases with a flat slope of 1/4 K/W from 298 K at 1 W to 300 K at 9 W probably
due to resistive electrode heating by the rf current. At ignition at 10 W temperature jumps
to 319 K and increases linearly to 359 K at 20 W shortly before transition to arcing. Here
the slope is much steeper with approximately 4 K/W. Measurements within the arcing mode
were not performed to prevent probe and µ-APPJ from damage.
Figure 4.11 shows the temperature in dependence of the oxygen admixture for a helium flow
of 1500 sccm. The relatively low generator power of 12 W was chosen to prevent transition
into arcing for low admixtures. An almost linear decrease of the temperature can be found
with a slope of approximately -13 K/vol.% O2 .
A slight deviation occurs for admixtures close to zero (the influence of possible further
impurities caused by the tape sealing may cause the deviation) and high admixtures, where
the plasma becomes instable and constricted at such low generator powers. The decrease
of power can be explained in the increased possibilities of power deposition (dissociation,
rotation, vibration) with the increased molecular admixture.
The dependence of the gas temperature on the total gas flow of helium with an admixture of
0.6% at 16 W generator power can be found in figure 4.12. For gas flows below 500 sccm the
plasma becomes contricted and thus the heating becomes smaller at constant power density.
From 335 K at 500 sccm temperature increases almost linearly to 349 K at 2000 sccm. For
higher gas flows the temperature remains constant.
As mentioned before, the applied TALIF diagnostics and calibration are only weakly dependent on the gas temperature within this range. Thus, for further measurement an overall
averaged temperature of 345 K will be assumed.
On the other hand, the gas temperature may significantly influence e.g. the reaction chemistry of ozone as shown in table 4.1, especially enhancing the thermal destruction of ozone
via heavy particle impact (O3 + M → O + O2 +M). Density measurements of ozone and
atomic oxygen in the effluent of the APPJ showed that close to the nozzle, ozone densities
are lower than atomic oxygen densities [73]. Ozone measurements inside the discharge area
of the APPJ show that ozone densities are another order of magnitude lower inside the discharge than in the effluent [35, 58]. Thus the temperature effect on the ozone chemistry may
only show a minor influence on the discharge chemistry of atomic oxygen.
80
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
reaction
O3 + M → O + O2 + M
O3 + O → 2 O2 + M
1
O2 ( ∆g ) + O3 → O + 2 O2 + M
O3 + O → O2 (1 ∆g ) + O2 + M
O + O2 + M → O3 + M
rate coefficient [cm3 /s]
7.2 × 10−10 exp (-11400/T )
1.8 × 10−11 exp (-2300/T )
5.2 × 10−11 exp (-2840/T )
1.01 × 10−11 exp (-2300/T )
6.4 × 10−35 exp (663/T ) (in cm6 /s)
370K
ratio 320K
123
2.6
3.3
2.6
0.76
Table 4.1: Ozone reactions and dependence on the gas temperature. The ratio of
the reaction rate coefficients is exemplified for 320 K and 370 K
Summary
Summarizing, temperatures inside the µ-APPJ remain slightly above room temperature and
never exceed the range of 360 K as long as the discharge is not operated in the arcing mode.
Temperatures increase linearly with the rf generator power between ignition and arcing and
weakly decrease with the amount of admixed oxygen. Further a weak decrease of temperature
was found for gas flows below 2000 sccm and a strong decrease was found for gas flows below
500 sccm which is probably due to constriction of the discharge.
The TALIF calibration and obtained absolute density data, however, are very robust against
temperature changes within this interval.
Regarding the gas heating to be proportional to the in-coupled power, figure 4.10 is an
indication for the plasma power to be linearly depending on the generator power within
the interval between ignition and arcing. Accordingly, the rf generator power remains an
adequate reference within this operation mode.
Spatial profiles of the gas temperature are difficult to obtain. The spread of the data obtained
from OES is much stronger than the expected spatial variations and the fiber probe is a too
strong local disturbance of the plasma.
4.2 Calibration and benchmarking of the TALIF system
As mentioned earlier, the TALIF calibration is very robust against variations of the gas
temperature, as the changes due to gas density, quenching rate and population of the lowest
ground state level mostly compensate each other.
To obtain absolute atomic oxygen densities from TALIF measurements, the system still
needs to be calibrated concerning possible vignetting (due to the small size and the observed
plasma volume) and collisional de-excitation.
81
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
Figure 4.13: Vignetting caused by imaged fluorescence light partially blocked in
the vicinity of the electrodes.
Vignetting
When the foci of the optical setup reach the vicinity of the electrodes, geometrical shadowing
may occur for the fluorescence imaging as shown in figure 4.13.
Due to the small width and distance of the µ-APPJs electrodes (1 mm) and the comparably
long focal length of the imaging lens (260 mm) and small lens radius (28 mm), this effect
can be supposed to be relatively small.
However, at an electrode distance of 1 mm, the radius of the exciting laser focus itself
may also be partially vignetted in the vicinity of the electrodes (figure 4.14). The resulting
reduction in obtained fluorescence light can be more crucial here.
Figure 4.15 shows the normalized TALIF signal of the homogeneously distributed xenon
reference measurement between the electrodes at low pressure (z = 35 mm, y = 0 mm)
as filled triangles. The actual xenon density distribution (dashed line) is one between the
electrodes ( -0.5 mm < x < 0.5 mm) and zero outside ( |x| > 0.5 mm). The measured
signal shows a blurring of this edge of ±0.2 mm which accordingly is attributed to the total
vignetting by fluorescence and laser.
In both cases circular segments of the imaging cross section are covered by the electrodes.
The function F of transmitted light can be described as noted in equation 4.1.
82
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
Figure 4.14: Vignetting caused by partially blocked laser focus in the vicinity of
the electrodes.
normalized TALIF signal [a.u.]
1.2
1.0
0.8
6
0.
0.4
xenon density distribution
xenon fluorescence signal
0.2
total vignetting
0.0
-
0.5
0.0
0.5
x axis [mm]
Figure 4.15: TALIF signal of a homogeneous low pressure xenon atmosphere between the electrodes at -0.5 and +0.5 mm.
83
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
1.2
1.0
signal [a.u.]
0.8
6
gap function
0.
laser radius function
imaging radius function
0.4
total vignetting
0.2
0.0
-
0.5
0.0
0.5
x axis [mm]
Figure 4.16: Composition of the total vignetting (solid line) as a convolution of
the gap profile (dashed line) with the radial functions of the laser
(dash-dot) and imaging (dot).
F =
(
1−
1
1
π
h
arccos y − y
i
p
1 − y 2 for 0 < y < 1
for y > 1
(4.1)
For the vignetting of the fluorescence from a punctual light source (as shown in 4.13), y
L
L
denotes yi = R
= xr R
where L = 260 mm is the distance and R = 28 mm the radius of the
imaging lens, r = 0.5 mm is the central position underneath the electrode.
For the vignetting of the laser light (as shown in 4.14), yL = RxL denotes the ratio of x to the
laser radius RL (estimated to be 200 µm) in the focal area. For simplicity, calculations of
the vignetting are based on the assumption of a homogeneous intensity distribution within
a cylindric focus.
The dotted line in figure 4.15 shows the vignetting function only considering the fluorescence
imaging and the dashed line shows the dominant vignetting only caused by the laser shadowing. The total vignetting of both, laser and fluorescence mostly overlaps with the laser
vignetting only (because of the small influence of imaging vignetting). This total vignetting
function (solid line) can be derived from the convolution of the gap function with the two
84
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
normalized radial functions of imaging fi =
figure 4.16.
p
p
1 − yi2 and laser fL = 1 − yL2 as shown in
For atomic oxygen measurements, this vignetting must be considered.
Collisional de-excitation
As collisional de-excitation (collisional quenching) becomes dominant at atmospheric pressure, one major issue for a reliable absolute calibration of the TALIF system is a reliable
knowledge of the respective quenching rate coefficients.
In non-equilibrium helium-oxygen plasmas, usually only helium atoms and di-atomic oxygen
molecules in the ground state are considered to contribute to quenching as they represent the
dominant species. Excited species and ions are neglected as their densities can be assumed to
be some orders of magnitude lower than the feed gas densities. The self-quenching coefficient
for atomic oxygen kO = 8.2 ± 8.2 × 10−11 cm3 s−1 is about one order of magnitude lower than
the coefficient for O2 [38]. As long as the degree of dissociation remains low (in the order
of 10%) the total de-excitation rate does not change much due to atomic oxygen and ozone
as plotted in figure 4.17. Atomic oxygen and ozone can thus be neglected for collisional
quenching as well.
The remaining coefficients for helium and O2 are known from low to mid pressure experiments
with small admixtures of the respective species. This assures the effective lifetime to remain
relatively long and thus measurable. Such measurements at medium pressures of some
hundred Pascals within a flow tube reactor can be found e.g. in [34] revealing kHe = 1.7±0.2×
10−12 cm3 s−1 for helium and kO2 = 9.4 ± 0.5 × 10−10 cm3 s−1 for O2 . Other sources however
report coefficients differing by up to one order of magnitude (e.g. kHe = 1.5 ± 0.5 × 10−11
cm3 s−11 and kO2 = 6.3 ± 0.1 × 10−10 cm3 s−1 [72]).
As three-body collisions may become important at atmospheric pressure, an extrapolation
of the coefficients to atmospheric pressure conditions must be validated.
To validate these assumptions and coefficients for the measurements at atmospheric pressure,
the total de-excitation was measured under variation of the admixed gas, for two feed gas
flows of 1500 sccm and 4500 sccm at two position inside the plasma (z = 35 mm) and in the
effluent (z = 42 mm) as shown in figures 4.18 and 4.19.
Within the bandwidth limit (250 MHz) of the oscilloscope, the measured values are in very
good agreement with the total de-excitation calculated from the named extrapolated mid
85
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
300
O
280
3P ) decay rate [MHz]
J
260
2
admixture:
0,1 %
0,2 %
220
0,
0,4 %
200
0,5 %
0,
240
3%
6%
180
160
140
120
p
100
80
60
(
O3
40
20
0
1
10
O
degree of
2
100
dissociation [%]
Figure 4.17: Calculated total O(3p3 PJ ) decay rate under variation of the degree
of O2 dissociation for several admixtures of O2 to one atmosphere of
helium.
300
oscilloscope 2
J) decay rate [MHz]
250
50 MHz bandwidth limit
200
150
z =
50
35 mm (plasma)
z = 42 mm (effluent)
(
O3
p
3P
100
extrapolated mid-pressure data
0
0
3
O
6
2
9
partial pressure [
12
15
Pa]
Figure 4.18: Measured de-excitation rate of O(3p3 PJ ) state for a helium base gas
flow of 1500 sccm at atmospheric pressure.
86
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
oscilloscope 2
250
50 MHz bandwidth limit
200
150
100
z =
50
35 mm (plasma)
z = 42 mm (effluent)
(
O3
p
3P
J) decay rate [MHz]
300
extrapolated mid-pressure data
0
0
9
18
O
2
36
27
partial pressure [
45
Pa]
Figure 4.19: Measured de-excitation rate of O(3p3 PJ ) state for a helium base gas
flow of 4500 sccm at atmospheric pressure.
pressure values from [34]. Further, no significant difference can be found, when these measurements are carried out in the charge free effluent or within the plasma.
It can thus be concluded, that ground state helium and O2 remain the only relevant species
for collisional de-excitation and rate coefficients of [34] can be extrapolated even to the
atmospheric pressure case.
From the measured total de-excitation rate, the given accuracy of the two-photon crosssections of 20% from [34], small dependance on the gas temperature and the vignetting, the
maximum error of the TALIF system absolute calibration can be estimated to be in the order
of 50%.
Benchmark against Molecular Beam Mass Spectrometry in the Effluent
Alternative methods to benchmark the system are rare. Rayleigh calibrated LIF e.g. relies
on UV photons which cannot be used due to atmospheric pressure condition. Actinometry
highly depends on the knowledge of the spatial and temporal behavior of the electron density
and mass spectrometry is limited by the small size of the confining structure and atmospheric
pressure.
87
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
power [W]
2
3
O
O3
O
1,8
1,6
5
6
7
8
9
10
11
(MBMS)
(MBMS)
(TALIF) x0.4
1,4
1,2
1,0
arcing
]
-3
cm
15
density [10
2,0
ignition
2,4
2,2
4
0,8
0,6
0,4
0,2
0,0
180
200
220
240
260
280
300
320
peak to peak rms voltage [V]
Figure 4.20: O density measured under variation of the applied voltage from ignition to arcing. Measured in the center of the effluent gas stream at
a distance of 3 mm to the nozzle. Helium flow is 1400 sccm with an
admixture of 0.6% O2 .
However, molecular beam mass spectroscopy (MBMS) can be applied to a freely expanding
effluent to compare results.
Thus, a slightly modified version of the µ-APPJ (reduced electrode length of 30 mm with
a freely expanding effluent) was built to fit the needs of MBMS. The same device was
investigated inside the TALIF vessel and subsequently in front of the mass spectrometer.
Mass spectrometer measurements were performed by D. Ellerweg and J. Benedikt at the
Ruhr-Universität Bochum. The results are published in [19] and thus only briefly discussed
here.
The atomic oxygen density was measured in the center of the effluent gas stream in a distance
of 3 mm to the µ-APPJ’s nozzle. Results for both techniques under variation of the applied
voltage are shown in figure 4.20. Attributing to a different stray capacitance in both experiments, measurements are shown for the voltage (generator power) interval from ignition to
arcing of the plasma.
Both measurements show an increase of the atomic oxygen density from ignition to arcing,
which is linear in good approximation. MBSM reveals an atomic oxygen density (open circles)
of 0.4×1015 cm−3 at ignition increasing to 2×1015 cm−3 before arcing. However, the absolute
values obtained from MBMS are 0.4 times smaller than those measured by TALIF.
88
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
1.2
1.1
15
-3
density [10
cm
]
1.0
0.9
0.8
0.7
0.6
0.5
0.4
O
O
O
0.3
0.2
3
0.1
0.0
0.0
(MBMS)
0.2
0.4
0.6
O
2
0.8
(MBMS)
(TALIF) x0.27
1.0
1.2
1.4
1.6
admixture [%]
Figure 4.21: Variation of the O2 admixture in a distance of 3 mm. Measured at a
peak to peak voltage of 230V at a helium flow of 1.4 slm.
The MBMS technique is capable to also measure other oxygen species such as ozone (open
triangles), which is found to be below the atomic oxygen density, in particular for higher
powers.
The difference in the absolute values can be attributed to both, the 50% uncertainty of the
TALIF calibration as well as the uncertainty of the MBMS which was assumed to be a factor
of two. The measured MBMS O2 depletion (not shown here) is higher than the sum of the
MBMS ozone and atomic oxygen signal and may indicate an underestimation of the oxygen
species in MBMS.
A further difference may occur from the different configurations during measurements: TALIF
measurements are performed in an undisturbed effluent, whereas the MBMS introduces a
metal plate with a sampling orifice into the gas flow.
Figure 4.21 shows the atomic oxygen density as a function of the molecular oxygen admixture.
A variation of the distance can be found in figure 4.22. These measurements were carried out
at a relatively low voltage of 230V to prevent an additional discharge between the powered
electrode and the mass spectrometer. In this regime, the absolute atomic oxygen densities
measured by the mass spectrometer are again lower than the TALIF measurements by a
factor of 0.27 which is still within the combined accuracy of both techniques. The relative
signal profiles agree perfectly.
89
Chapter 4. Results
4.2. Calibration and benchmarking of the TALIF system
1,5
1,4
1,3
density [10
15
cm
-3
]
1,2
1,1
1,0
0,9
O
O
O
0,8
0,7
0,6
0,5
0,4
(MBMS)
3
(MBMS)
(TALIF) x0.27
0,3
0,2
0,1
0,0
0
5
10
15
20
25
30
35
40
45
50
55
z axis [mm]
Figure 4.22: Variation of the distance at a fixed admixture of 0.6% O2 . Measured
at a peak to peak voltage of 230V at a helium flow of 1.4 slm
The variation of the admixed oxygen was performed in a distance of 3 mm (figure 4.21).
Here, the atomic oxygen density increases with the admixed O2 , peaking at around 0.6%
O2 admixture. For higher admixtures, the atomic oxygen density decreases again until the
plasma vanishes at higher admixtures of more than 1.6%. These results agree well to the
measured electric operation range shown in figure 4.2.
For an admixture of 0.6% O2 (figure 4.22), a steep decrease of the atomic oxygen density can
be found from 1 × 1015 cm−3 in 3 mm distance to below 1 × 1014 cm−3 in 30 mm distance
(MBMS). The ozone density increasing with distance indicates, that atomic oxygen is mostly
lost in a recombination with O2 by the formation of ozone. Extrapolating ozone and atomic
oxygen profiles to the plasma core, ozone densities within the plasma will be significantly
lower than the atomic oxygen densities.
Both techniques show difficulties to measure the atomic oxygen created closer than 3 mm to
the µ-APPJs nozzle due to different reasons. TALIF measurements cause laser stray light
in the vicinity of the nozzles edges, and MBMS causes an additional plasma between mass
spectrometer and powered electrode. In this area, the slope of the atomic oxygen decay is
steepest and difficult to extrapolate to the O densities in the plasma core.
Whereas density measurements within the freely expanding effluent are very valuable for
application, they only allow indirect access to the creation processes of the reactive oxygen
90
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
species within the plasma core. Density profiles within a freely expanding effluent can generally be described by gas kinetics and reactions [58, 73]. However, the resulting density
profiles highly depend on each initial species density close to the nozzle. These densities on
the other hand are the results of the complex processes inside the plasma core. Accordingly,
it is inevitable to determine the processes and densities inside the plasma core to understand
the subsequent processes inside the effluent.
As the benchmark in the effluent shows, the used TALIF system provides reliable data and
can therefore be applied to measure atomic oxygen densities inside the plasma core of the
extended µ-APPJ.
Summary
Vignetting for measurements in the vicinity of the electrodes was found mostly due to the size
of the laser focus. The total collisional de-excitation of O(3p3 PJ ) was measured for various
admixtures of oxygen and a very good agreement to extrapolated data from [34] was found.
To benchmark the complete TALIF setup, measurements in the effluent of a modified µ-APPJ
device were carried out and compared to molecular beam mass spectrometric measurements.
The relative density profiles for parameter variations agree perfectly, the absolute values
of MBMS are below the TALIF values by a factor of approximately three. However, the
difference is still well within the combined accuracy of both methods.
4.3 TALIF measurements in the plasma core.
To get an overview on the density distribution inside the plasma core, in a first step, a twodimensional map of the oxygen fluorescence signal is recorded in the central layer between
the quartz panes (y = 0) as shown in figure 4.23 as a false color map.
The TALIF signal map is recorded for a gas flow of 1500 sccm helium with an admixture of
9 sccm O2 at 12 W rf generator power. The signal map is obtained by scanning the stepper
motors in x direction from -0.5 mm to 0.5 mm in 0.1 mm intervals for each z position along
the gas channel from -3 to 55 mm in 0.5 mm steps.
From the beginning of the electrodes (at z = 0 mm), the signal increases within a few
millimeters to a constant equilibrium level along the gas flow. From the end of the electrodes
(at z = 40 mm) the signal rapidly decays within the effluent as expected from measurements
91
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
x [mm]
0.4
plasma
0.2
effluent
0.0
-0.2
-0.4
0
10
20
30
40
50
z [mm]
0
1
2
3
15
atomix oxygen density [10
4
-3
cm ]
Figure 4.23: TALIF signal map as obtained for a gas flow of 1500 sccm helium
with an admixture of 9 sccm O2 at 12 W rf generator power.
in the freely expanding effluent [16, 19]. Perpendicular to the gas flow, the signal decreases
towards the electrodes.
For a better analysis the transversal and longitudinal profiles as well as the amplitude value
in the plateau will be discussed separately.
4.3.1 Transversal profiles
The transversal signal profiles of the atomic oxygen fluorescence are shown in figure 4.24
measured at several longitudinal positions along the discharge channel (z = 0, 5, 10, 15, 20,
25, 30, 35, and 40 mm). In all positions the transversal profile is flat in the center of the
discharge channel and decreases in the vicinity of the electrodes. The noise to signal ratio
caused by the laser fluctuations can be identified to be in the order of 10%.
Calibrating these convex profiles with the total vignetting obtained from xenon calibration,
the actual atomic oxygen density profile can be found to be homogeneously distributed
between the electrodes in good approximation (figure 4.25).
This indicates, that if surface losses should appear at the electrodes (e.g. surface induced
recombination to molecular oxygen), they must be dominated or compensated by volume
processes.
92
normalized TALIF signal [a.u.]
1.2
1.0
electrode
4.3. TALIF measurements in the plasma core.
electrode
Chapter 4. Results
vignetting
00 mm
0.8
05 mm
0.6
15 mm
10 mm
20 mm
0.4
25 mm
0.2
35 mm
30 mm
40 mm
0.0
-0.5
0.0
0.5
x axis [mm]
15
atomic oxygen density [10
cm-3]
Figure 4.24: Transversal fluorescence signal profiles measured in various axial positions (z = 0, 5, 10, 15, 20, 25, 30, 35, and 40 mm) in comparison to
the vignetting obtained from xenon calibration.
3.0
lateral
position:
2.5
00 mm
05 mm
2.0
10 mm
15 mm
1.5
20 mm
25 mm
1.0
30 mm
35 mm
0.5
40 mm
0.0
-0.5
0.0
0.5
x axis [mm]
Figure 4.25: Transversal atomic oxygen density distributions at various axial positions after vignetting and xenon calibration applied.
93
15
-3
atomic oxygen density [10
cm
]
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0
10
20
30
40
50
z [mm]
Figure 4.26: Measured atomic oxygen density along the gas channel (z axis) measured in the center of the channel cross-section. Operation parameters are a helium flow of 1500 sccm with an admixture of 0.6% O2 a
generator power of 12 W calibrated to a gas temperature of 345 K.
On the other hand it should be mentioned, that the estimated radius of the laser focus of 200
µm blurs out structures of smaller sizes. Thus, a distinct profile resulting from wall losses
could not be identified if the characteristic size is significantly below 200 µm.
As with regards to vignetting, the transversal profiles are constant in good approximation,
we will further concentrate on the spatial atomic oxygen density profiles along the central z
axis of the gas channel.
4.3.2 Longitudinal profiles
Figure 4.26 shows the central longitudinal atomic oxygen profile obtained from the signal
map in figure 4.23 after xenon calibration and vignetting. Within the plasma from z = 0 to
z = 40 mm the atomic oxygen density increases with an asymptotic spatial convergence into
a plasma chemical equilibrium value of yp = 2.6 · 1015 cm−3 close to the electrode’s end i.e.
to the transition to the effluent at z = 40 mm.
To describe this asymptotic increase and to define a measure for the respective ascent length,
an analytical function is fitted to the measured values.
94
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
This ascent can be described best by fitting a function f (z) = −A · exp − Lz + yp where A
is an arbitrary proportionality constant attributing to a possible shift in z direction, A = yp
for f (0) = 0. yp is the equilibrium density in the plasma and L denoting an exponential
ascent length scale of 2 mm.
From the beginning of the effluent at z = 40 the density profile shows a descent behavior
which can be described best by fitting a similar function f (z) = +B · exp − zl + ye where
B is again an arbitrary proportionality constant, ye is an equilibrium density in the effluent
of 4.9 · 1014 cm−3 and l is the exponential decay distance of 2 mm.
The choice of these exponential analytical fit functions is motivated by a crude assumption
for production and losses: Production of atomic oxygen is assumed to be independent of the
local O density, whereas the loss term depends linearly on the local O density.
∂n(z)
= Production term (const) − Loss term (const) · n(z)
∂z
(4.2)
This corresponds to a zero dimensional continuity equation, substituting the position z along
the gas channel with the time of flight t times the gas velocity vgas (z = vgas ·t).
The used analytical functions are a solution of this differential equation. Here, the resulting equilibrium density is determined by the ratio of production term and loss term. The
resulting ascent length commensurates with the inverse of the loss term.
In the most simple model approach, atomic oxygen can be assumed to be created e.g. by
direct electron impact dissociation of O2 , and it is lost e.g. via recombination with O2
forming ozone in the volume. Both is reasonable for a low degree of dissociation.
For a simplified one dimensional fluid model, the information of a quickly reached equilibrium
state is a very valuable information, as the convective flow can possibly be neglected within
this equilibrium (convective flow of atomic oxygen into a transient volume is equal to the
flow out and thus canceling out).
To check, if the quick convergence into an equilibrium density remains true under variation
of the operation parameters, scans along the central axis of the µ-APPJ were performed. To
compensate for possible misalignment, the center of the gas channel was determined at the
beginning and at the end of the plasma channel, subsequently scanning the coordinates of
the interpolated line between them.
95
exponential ascent distance L [mm]
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
2,0
1,5
1,0
0,5
0,0
0
3
6
9
12
15
18
generator power [W]
exponential ascent distance L [mm]
Figure 4.27: Ascent distance L in respect to the rf generator power at 1.5 slm
helium gas flow and 0.6% oxygen admixture.
1,6
1,4
1,2
1,0
0,8
0,6
0,4
0,2
0,0
0,2
0,4
O
0,6
2
0,8
1,0
admixture [%]
Figure 4.28: Ascent distance L in respect to the oxygen admixture at 16 W rf
generator power at 1.5 slm helium gas flow.
96
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
The resulting exponential ascent lengths are plotted in figure 4.27 under a variation of the
generator power (fixed admixture of 0.6% O2 ). The ascent length slightly decreases with
elevated generator powers from 1.9 mm at 8 W to approximately 1.2 mm at 16 W. The
slightly faster convergence at higher powers can be explained e.g. with the onset of higher
order destruction processes. Recombination of two oxygen atoms forming O2 e.g. depends
quadratically on the O density and becomes more important for higher degrees of O2 dissociation. The exponential fit functions, however, are motivated by the assumption of primarily
first order destruction processes (depending linearly on the atomic oxygen density).
The indicated error bars in the order of 10% can thus only denote the statistical error deriving
from the least-square-fit of the analytical exponential functions. The appearance of outliers
due to fluctuations of the measuring signal in combination with the relatively steep ascent
causes the overall uncertainty in the ascent distance to be higher i.e. in the order of 30%.
Nevertheless, it is an important finding, that the exponential ascent distance is rather robust
to a variation of power and L remains within one to two millimeters which is much less than
the electrode length of 40 mm.
Operating the µ-APPJ at a fixed generator power of 12 W and a fixed helium base gas flux
of 1500 sccm, the ascent distance increases from 1 mm at an admixture of 0.2 vol.% to 1.4
mm at an admixture of 1.0 vol.% of O2 .
Again, the change in the ascent distance within the range of typical O2 admixtures of 0.0%
to 1.0% is rather small.
Summarizing, at standard operation parameters of 1500 sccm helium gas flow with an O2
admixture of 0.2 to 1.0 vol.%, the spatial atomic oxygen density increases within the first
few milimeters and quickly converges into an equilibrium density.
To understand the underlying processes of the atomic oxygen creation, a modeling approach
and a comparison of measurement and simulation results is useful.
State of the art models and numerical simulations are essentially limited to global or one
dimensional models. These models usually calculate dynamic (phase averaged) equilibrium
conditions, where the plasma chemistry has converged [4, 43].
A comparison of experiments to simulation results can thus only be performed in the area
where the dynamic equilibrium has been reached i.e. close before the transition to the effluent.
The dependence of this steady state values on the operation parameters will be studied in
the following.
97
10
25
generator power [W]
arcing
9
8
20
7
6
glow mode
15
5
4
10
3
2
5
plasma off
0,0
0,2
0,4
O
2
0,6
0,8
1,0
1,2
1,4
1
0
1015 cm-3]
4.3. TALIF measurements in the plasma core.
atomic oxygen density [
Chapter 4. Results
admixture [vol.%]
Figure 4.29: Atomic oxygen density at z = 35 mm under variation of rf generator
power and O2 admixture to a 1500 sccm helium gas flow.
4.3.3 Parameter variations in the dynamic equilibrium
The equilibrium density measured close to the transition to the effluent in a fixed position
z = 35 mm is shown in figure 4.29. Atomic oxygen density is plotted as gray scale values
under variation of the generator power for several O2 admixtures from 0.1 to 1.5 vol.%. The
map was recorded in one spatial position increasing the power from zero to arcing for each
mixture subsequently. When decreasing the power or increasing the O2 admixture at a fixed
power, the plasma can be sustained even for powers slightly below the ignition power, thus
bluring the graph in the lower left corner in figure 4.29.
Atomic oxygen densities increase from 5 × 1014 cm−3 at 4 W and 0.1 vol.% O2 to 1 × 1016
cm−3 at 25 W and 1.5 vol.% O2 .
For each set of admixture, the increase in the atomic oxygen equilibrium value commensurates
in good approximation to the generator power.
4.3.4 Comparison to numerical simulations
Due to the non-linear dependence of most collisional cross-sections (e.g. excitation and
dissociation) on the electron energy, global models only account for spatially and temporally
98
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
averaged values. The quick build-up of the measured dynamic equilibrium along the gas
channel motivates a one-dimensional model of the discharge gap.
Such a one dimensional model was developed by J. Waskönig et al.. As a detailed description
of the model can be found in [4], it is only briefly described here.
The model consists of a fluid approach, solving the continuity equation (equation 2.49)
for each species and a drift-diffusion approach for the momentum conservation (equation
2.50). Electrons are treated semi-kinetically by solving the electron energy conservation
(equation 2.51) and receiving the respective transport coefficients and reaction rates from a
zero-dimensional Boltzmann solver in two-term approximation (Bolsig+ [74]). The obtained
coefficients and rates are fitted to analytical functions of the mean electron energy, which
are solved within the model. The model is closed by Poisson’s equation (equation 2.52). The
boundary condition of Poisson’s equation incorporates the fact that one of the electrodes is
driven at a frequency of 13.56 MHz and the other is grounded. To account for the different
time scales of electron dynamics and chemistry, both are decoupled: Firstly the complete
set of partial differential equations is solved for several rf-cycles, secondly only the neutral
species reactions are solved on a much longer timescale. These two steps are performed iteratively until convergence is reached. The simulation domain is set-up within the commercial
FEM solver COMSOL Multiphysics [75] using a time-dependent solver.
The feed gas mixture of He and O2 (1000:5) is fixed at atmospheric pressure and a temperature of 345 K. 16 species are considered, namely electrons, helium meta-stables He∗ ,
ions He+ , excimers He∗2 , molecular ions He+
2 , oxygen ground state atoms O, atomic meta1
∗
+
stables O( D)=O , positive atomic ions O , negative atomic ions O− , molecular meta-stables
−
−
O2 (1 ∆)=O∗2 , positive molecular ions O+
2 , negative molecular ions O2 and O3 , ozone O3 .
Ground state helium and ground state O2 are treated as background gas with a fixed density
(no significant depletion). Among those species, 116 reactions are considered, which are
compiled from references [27, 58, 76, 77, 78] and found to be the most important reactions
within the investigated parameter regime. Due to a low sticking coefficient for ground state
atomic oxygen, which is in the order of 10−4 at atmospheric pressure (surface coverage [46]),
zero surface loss is assumed for atomic oxygen.
Figure 4.30 shows the atomic oxygen density in the discharge center under variation of the
power obtained from the TALIF measurements at z = 35 mm and the numerical results,
both shown from ignition to arcing. For TALIF measurements, the generator power is
plotted. For simulation data, the calculated power dissipated in the plasma is plotted which
is significantly lower than the generator power due to reasons discussed earlier. Arcing in the
simulation is defined as the maximum in the calculated U-I characteristic. The calculated
99
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
atomic oxygen density [
1015 cm-3]
simulation power [W]
0.0
5
0.2
0.4
0.6
0.8
1.0
1.2
4
3
2
1
TALIF measurements
7
numerical simulation x 0.3
0
0
5
10
15
20
25
generator power [W]
Figure 4.30: Comparison of the measured atomic oxygen densities to numerical
simulation data from [4].
maximum power before mode transition fits nicely to the plasma power of one or two watts
obtained from the U-I measurements in figure 4.6.
TALIF measurements reveal an increase of the atomic oxygen density from 2 × 1015 cm−3
at ignition to 4.5 × 1015 cm−3 close to arcing which is linear in good approximation. The
simulation results perfectly overlap with the measured data, the absolute values however
are higher than the measured values by a factor of 2.7. Besides the overall uncertainty of
the TALIF setup of 50%, the model depends on a variety of cross-section data and rate
coefficients, each with an uncertainty of at least 30% [79].
The simulation results for the phase- and space-averaged (averaged over the electrode gap)
production processes of atomic oxygen are shown in figure 4.31 and the loss processes are
shown in figure 4.32 .
The main atomic oxygen producing processes are direct electron impact dissociation of O2
and de-excitation of meta-stable O∗ which was created previously by direct electron impact.
Plotting the phase averaged spatial profile of the total atomic oxygen production rate, as
shown in figure 4.33, one can see that the production mainly occurs within the ”plasma bulk”
from x = -0.3 to 0.3 mm. Model results on the plasma parameters such as electron density
profiles and electron energy distribution function are not shown or discussed here as they
can be found in [4, 45].
100
4.3. TALIF measurements in the plasma core.
5.0
4.5
O*
4.0
e +
3.5
3.0
2.5
O
+ He
O
O
+
O
2
O
+ He
2
e +
2
O*
+
O
O*
+
O
3
2
O
+ e
+ e
+ 2
2
O
O*
O
O
+
2
2.0
O
1.5
1.0
0.5
avg.
1
1
24
-3 production rate [ 0
m
s
]
Chapter 4. Results
0.0
0.0
0.2
0.4
0.6
0.8
1.0
simulation power [W]
Figure 4.31: Phase and space averaged production processes of atomic oxygen obtained from the numerical simulation.
7
6
5
O
+
2
O
O
+
O
2
O
+ He
O
+ He
O
3
3
2
2
+ He
+ He
O
2
4
3
2
avg.
O
1
1
24
-3 loss rate [ 0
m
s
]
8
1
0
0.0
0.2
0.4
0.6
0.8
1.0
simulation power [W]
Figure 4.32: Phase and space averaged loss processes of atomic oxygen obtained
from the numerical simulation.
101
4.3. TALIF measurements in the plasma core.
2.5
1.0W
0. 5W
0.5W
0.25W
7
2.0
1.5
1.0
0.5
total
O
production rate [
1025 m-3s-1]
Chapter 4. Results
0.0
-0.4
-0.2
0.0
0.2
0.4
x axis [mm]
2.0
1.0W
0. 5W
0.5W
0.25W
7
1.5
1.0
0.5
total
O
destruction rate [
1025 m-3s-1]
Figure 4.33: Simulation results for the spatial profile of the phase averaged atomic
oxygen total production rate.
0.0
-0.4
-0.2
0.0
0.2
0.4
x axis [mm]
Figure 4.34: Simulation results for the spatial profile of the phase averaged atomic
oxygen total destruction rate.
102
Chapter 4. Results
4.3. TALIF measurements in the plasma core.
relative ratio of losses
1.0
0.8
2
O
O
+
O
O
O
+
O
2
O
+
O
+ He
+ He
2
+ He /
2
O
+ He
3
+ He
0.6
0.4
0.2
0.0
0.0
3
2
0.2
O
2
/
O
3
+ He
0.4
0.6
0.8
1.0
simulation power [W]
Figure 4.35: Ratio of the three main loss processes under variation of the power.
From this bulk region, the atomic oxygen density expands due to diffusion. The total atomic
oxygen destruction rate, as plotted in figure 4.34, shows a more uniform profile. However,
for higher powers, still a maximum of atomic oxygen destruction can be found for the bulk
region.
The main loss processes are recombination of atomic oxygen and O2 forming ozone and the
recombination of two oxygen atoms forming O2 . The latter one (higher order recombination)
becomes more important with increasing power as shown in figure 4.35. This corresponds
well to the measured decrease of the typical ascent length with elevated powers.
The resulting phase-averaged atomic oxygen density profiles, as shown in figure 4.36, reveal
a very homogeneous distribution of atomic oxygen within the discharge gap, which agrees
well with the measured transversal profiles shown in figure 4.24.
Summary
Spatially resolved TALIF measurements revealed a fast build up of atomic oxygen within
the first few millimeters of the µ-APPJ with an adjacent plateau value. From the end of
the electrodes, the atomic oxygen density quickly decreases within the effluent. Within
the accuracy of the TALIF system, the transversal density distribution shows a flat profile
all along the plasma channel. Plateau values increase linearly with the sender power and
103
4.3. TALIF measurements in the plasma core.
1.0
calculated atomic
O
density [
1016 cm-3]
Chapter 4. Results
0.5
1.0W
0. 5W
7
0.5W
0.25W
0.0
-0.4
-0.2
0.0
0.2
0.4
x axis [mm]
Figure 4.36: Simulation results for the spatial profile of the steady state atomic
oxygen density.
increase with the admixed O2 . Densities are found to be in the order of 1015 to 1016 cm−3
according to generator power and O2 admixture.
In the plateau region, a one-dimensional fluid model with a semi kinetic treatment of the
electrons can reproduce the linear increase of atomic oxygen with power. The absolute
values of the model are about 2.5 times higher than the measured values. This can either be
attributed to the combined uncertainty of measurement and simulation (each cross section
has an uncertainty of at least 30%), or may indicate an additional loss process not considered
in the simulation (e.g. non-zero surface quenching or effective reactions with unconsidered
impurities such as nitrogen or hydrogen species).
According to the model, the main production processes of atomic oxygen are direct electron
impact dissociation of O2 and stepwise production of meta-stable O∗ from O2 with an adjacent de-excitation. These processes predominantly take place in the plasma bulk. Major
loss processes are found to be recombination with O2 forming ozone and recombination with
atomic oxygen forming O2 . The latter becomes more important with increasing power.
104
1.0
2.6
electrode distance [mm]
2.3
0.8
1
II
I
2.
1.8
1.6
1.3
1.0
0.6
0.4
0.8
I
II
0.2
0.5
0.3
777 exc. rate [1021 m-3 s-1]
4.4. PROES measurements to benchmark the simulation
O
Chapter 4. Results
0.0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.37: Simulation of the excitation of the 5 So state for a power of 0.25 W.
4.4 PROES measurements to benchmark the simulation
Due to the multitude of assumptions in the modeling and simulation, further experimental
evidence is necessary to validate the model. Phase resolved charge dynamics are difficult
to measure directly. The plasma light emission however can be detected by phase resolved
emission spectroscopy with a high temporal resolution. It must be noted here, that each
spectral emission line may show a distinct spatial and transient emission behavior due to different excitation energy thresholds and lifetimes. The atomic oxygen λ = 777 nm (5 P−5 S0 )
line represents the dominant emission line of the µ-APPJ. A direct comparison of the measured transient emission profiles to simulated transient excitation profiles is motivated by
the short effective lifetime (few nanoseconds due to quenching) which is much shorter than
the rf excitation period [80].
4.4.1 Model predictions
The excitation of the atomic oxygen λ = 777 nm line is simulated by applying the respective excitation cross-sections for direct and dissociative electron impact excitation [56] to
the plasma parameters of the converged one dimensional fluid model. The resulting total
excitation into the 5 So state is shown in figures 4.37, 4.38, 4.39, and 4.40 for a variation of
the power.
105
electrode distance [mm]
1.0
7.5
6.7
0.8
II
I
6.0
5.2
0.6
4.5
III
7
3.
0.4
3.0
III
2.2
I
II
0.2
1.5
0.7
777 exc. rate [1021 m-3 s-1]
4.4. PROES measurements to benchmark the simulation
O
Chapter 4. Results
0.0
0.0
0
10
20
30
40
50
60
70
time [ns]
11.7
10.6
II
0.8
9.4
I
8.2
0.6
7.0
III
5.9
0.4
7
4.
III
0.2
3.5
I
II
2.3
1.2
O
electrode distance [mm]
1.0
777 exc. rate [1021 m-3 s-1]
Figure 4.38: Simulation of the excitation of the 5 So state for a power of 0.5 W.
0.0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.39: Simulation of the excitation of the 5 So state for a power of 0.75 W.
106
electrode distance [mm]
1.0
14.5
13.0
11.6
10.1
8.7
7.2
II
0.8
I
0.6
III
0.4
5.8
III
0.2
4.3
2.9
I
II
1.5
777 exc. rate [1021 m-3 s-1]
4.4. PROES measurements to benchmark the simulation
O
Chapter 4. Results
0.0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.40: Simulation of the excitation of the 5 So state for a power of 1.00 W
(transition to arcing).
The axis of the abscissae shows the time of one rf cycle while the ordinate shows the spatial
distance between the electrodes. The upper electrode is the powered electrode (ordinate = 1
mm), the lower one is the grounded electrode (ordinate = 0 mm). The potential of the upper
electrode is modulated with the cosine rf frequency of 13.56 MHz with maximum potential
at t=0 s. Excitation rate is plotted in false colors.
For the lowest power of 0.25 W (figure 4.37), two excitation structures can be observed in
the time interval of 30 to 38 ns which repeat in the next half-cycle from 66 to 74 ns. This
appears shortly before the potential is at maximum or minimum voltage respectively. These
structures marked I and II can be attributed to sheath expansion (I) and collapse (II). The
sheath expansion structure I appears in a distance of 0.4 mm from the electrode, while the
sheath collapse pattern appears closer to the electrodes at 0.25 mm. At low powers, both
structures overlap vertically forming a bar shaped structure across the plasma bulk.
At an increased power of 0.5 W (figure 4.38), the overlap of structure I and II decreases and
the separate structures become more distinct. The overall excitation rate increases, while
the excitation rate of the sheath collapse increases more than the sheath expansion. At
t=7 ns and t=44 ns an additional excitation structure III occurs in the vicinity (0.2 mm)
of the electrodes where the sheath has collapsed. This third pattern can be attributed to
excitation from secondary electrons created from penning ionization and ion impact onto the
electrode.
107
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
1.0
I
0.8
II
1,980
1,
760
1,540
320
1,100
0.6
1,
0.4
880
660
intensity [a.u.]
electrode distance [mm]
2,200
440
0.2
220
I
II
0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.41: Phase resolved emission plot of the 777 nm atomic oxygen line at a
generator power of 20 W (close to ignition).
A further increase of power to 0.75 W (figure 4.39) and 1.0 W (figure 4.40), leads to a further
increase of the overall excitation, while the increase is strongest for the secondary electron
induced structure III and least for the sheath expansion structure I. The overlap of structures
I and II further decreases and both become more distinct.
The resulting emission can be obtained by a convolution of the excitation pattern with the
effective lifetime of the 5 So state [81]. In case of a short effective lifetime (which is the
case due to collisional quenching at atmospheric pressure), the excitation can directly be
compared to the observed emission pattern for simplicity.
4.4.2 PROES emission results
To validate these predictions, the emission of the 777 nm line was recorded via phase resolved
emission spectroscopy. The fluorescence light was recorded according to the setup introduced
in the previous chapter.
Figure 4.41 shows the phase resolved emission plots recorded for a helium flow of 1500 sccm
He with an admixture of 9 sccm O2 at a low generator power of 20 W (close to ignition).
Figure 4.42 shows a similar measurement for a medium generator power of 30 W and figure
108
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
1.0
I
0.8
706
5,072
II
5,
4,438
0.6
3,804
70
2,536
3,1
0.4
1,902
intensity [a.u.]
electrode distance [mm]
6,340
1,268
0.2
634
I
II
0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.42: Phase resolved emission plot of the 777 nm atomic oxygen line at a
generator power of 30 W.
1.0
10,100
II
9,090
0.8
8,080
7,070
0.6
III
6,060
5,050
III
0.4
4,040
3,030
intensity [a.u.]
electrode distance [mm]
I
2,020
0.2
1,010
I
II
0
0.0
0
10
20
30
40
50
60
70
time [ns]
Figure 4.43: Phase resolved emission plot of the 777 nm atomic oxygen line at a
generator power of 40 W (close to arcing).
109
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
M
10
ax. intensity
I
II
intensity [a.u.]
8
III
6
4
2
0
0
5
10
15
20
25
30
35
40
45
generator power [W]
Figure 4.44: Increase of the three observed PROES emission structures with
power.
4.43 for a higher power of 40 W (close to arcing). These phase plots were derived from a
lateral position close to the discharge end at z=38 mm.
The observed emission structures I and II agree very well with the predicted excitation
structures from the numerical simulation in spatial and temporal position. At low powers,
the two structures overlap vertically forming the predicted bar-shaped structure, while they
become more distinct at elevated powers. Further, the appearance of the third emission
structure can be found at the predicted spatial and temporal position for higher powers.
Figure 4.44 shows the increase of the three emission structures at z=38 mm. Figure 4.45
shows the same increase of the respective simulated excitation structures.
The recorded PROES emission shows an increase of emission structures I and II which is
linear in very good approximation, whereas the simulated excitation structures I and II show
a slightly sub linear increase (structure I is more sub linear than structure II). Structure III
shows a strongly over-linear dependence on the power for both, the recorded emission and the
simulated excitation, which is a strong support for the predicted secondary electron origin.
Accordingly, one can attribute structures I and II to the discharge α-mode, which represents
the linear region in the U-I characteristic (figure 1.5), and structure III to the γ-mode, which
represents the onset of flattening in the U-I characteristic. Hence, the discharge always
operates in a hybrid mode of α- and γ-processes. While α processes dominate in the low-
110
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
8
7
M
ax. excitation
I
intensity [a.u.]
6
5
II
III
4
3
2
1
0
0,0
0,2
0,4
0,6
0,8
1,0
1,2
calculated power [W]
Figure 4.45: Increase of the three simulated excitation structures with power.
and mid-power operation regime, the influence of the γ-processes strongly increases towards
elevated powers. The transition to the arcing mode can be found close to the point where
γ-processes exceed α-processes in magnitude (e.g. represented by measured intensities).
The same qualitative emission behavior is found at any lateral position as shown in a logarithmic scale in figures 4.46, 4.47, and 4.48. Intensities of all three structures show a build-up
within the first few millimeters and are then forming a plateau. A slight increase of the
intensity towards the nozzle can be found which may be attributed to the camera imaging.
However, the intensity ratio of the three emission structures remains the same for all lateral
positions and only varies with the generator power.
Even an increase of the O2 admixture and an increase of the gas flow to 4500 sccm, as
shown in figure 4.49, shows structures I and II to find an equilibrium density within the
first few millimeters of the discharge. Now, structure III, on the other hand, shows a much
longer spatial ascent than before, which strongly supports the thesis of secondary electrons
originating from penning-ionization.
In conclusion, the (primary) electron dynamics represented by structures I and II find a
steady state equilibrium quickly, while the secondary electrons show a slower build up which
can be related to the supposed slower build up of reactive heavy particles such as metastables.
Thus, the good qualitative agreement of the measured atomic oxygen equilibrium densities
111
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
4
3
intensity [a.u.]
2
1
M
ax. intensity
I
II
III
-5
0
5
10
15
20
25
30
35
40
45
z [mm]
Figure 4.46: Spatial ascent of the three observed emission structures along the
discharge channel at 20 W generator power.
7
6
5
intensity [a.u.]
4
3
2
M
ax. intensity
I
1
II
III
-5
0
5
10
15
20
25
30
35
40
45
z [mm]
Figure 4.47: Spatial ascent of the three observed emission structures along the
discharge channel at 30 W generator power.
112
Chapter 4. Results
4.4. PROES measurements to benchmark the simulation
10
9
8
7
6
intensity [a.u.]
5
4
3
M
2
ax. intensity
I
II
III
1
-5
0
5
10
15
20
25
30
35
40
45
z [mm]
Figure 4.48: Spatial ascent of the three observed emission structures along the
discharge channel at 40 W generator power.
10
9
8
7
6
intensity [a.u.]
5
4
3
M
2
ax. intensity
I
II
III
1
-5
0
5
10
15
20
25
30
35
40
z axis [mm]
Figure 4.49: Spatial ascent of the three observed emission structures along the
discharge channel at 45 W generator power for an elevated gas flow
of 4500 sccm helium with an elevated admixture of 1% O2 .
113
Chapter 4. Results
4.5. Dependence on the gas flow
by TALIF and the phase resolved emission of atomic oxygen measured by PROES strongly
support the proposed one dimensional model.
Summary
The spatially and phase resolved transient dynamics of the one-dimensional simulation predicts the occurrence of two excitation structures per half-cycle and the appearance of a third
structure at higher powers. The first two structures could be attributed to sheath expansion
and collapse, while the third structure could be attributed to secondary electron induced
processes due to Penning-ionization and surface-impact. For the case of excitation into the
atomic oxygen 5 So state, the 777 nm line emission was recorded via PROES and a good
agreement of the transient and spatial positions between predicted excitation and measured
emission was found. The observed emission structures I and II could be attributed to an
α-mode operation, while structure III could be attributed to a γ-mode operation. Thus,
the µ-APPJ usually operates in a hybrid mode of both excitation mechanisms, while the
α-mode remains dominant. The transition into an arc-like discharge appears close to the
power value, where observed γ-mode emission structures reached intensities similar to the
α-mode emission structures. The intensity ratio of structures I and II does not vary much
along the plasma channel, the total intensity was found to quickly increase within the first
few millimeters of the discharge channel. Towards the effluent only a slight increase of the
total intensity was found. Structure III shows a slower spatial convergence, which could be
observed only at high gas flows.
4.5 Dependence on the gas flow
What recent modeling and simulations cannot describe yet, is the explicit dependence on
the gas flow. To investigate whether there is an explicit dependence of the discharge on the
convective gas flow, the atomic oxygen density was recorded for the same generator power
of 16 W and a constant mixture of one atmosphere He with an admixture of 0.6 vol.% of O2 .
The results are shown in figure 4.50
The ascent distance increases almost linearly from 0.7 mm at a gas flow of 750 sccm to 4.4
mm at a gas flow of 4500 sccm as shown in figure 4.51. As the ratio of ascent length and
gas velocity does not change much, this indicates that the transient behavior of production
and loss rates does not change much with the total gas flow. Considering the average gas
velocity, it corresponds to an average exponential reaction time of approximately 60 µs.
114
Chapter 4. Results
4.5. Dependence on the gas flow
-3
cm
]
7
c oxygen density [10
15
6
5
4
3
2
atomi
1
4500 sccm
3000sccm
750 sccm
2000 sccm
0
0
20
40
z axis [mm]
exponential ascent distance L [mm]
Figure 4.50: Spatial atomic oxygen density profile at different total gas flows at a
fixed generator power of 16 W and a fixed O2 admixture of 0.6 vol.%.
5.0
4.5
4.0
3.5
3.0
2.5
2.0
.5
.0
0.5
0.0
1
1
0
1000
2000
3000
4000
5000
gas flow [sccm]
Figure 4.51: Ascent distance L in respect to the total gas flow at a fixed generator
power of 16 W and a fixed O2 admixture of 0.6 vol.%.
115
g
atomic oxy en density [
1015 cm-3]
Chapter 4. Results
4.5. Dependence on the gas flow
6
5
4
3
2
1
0
0
1000
H
e
2000
3000
4000
gas flow [sccm] incl. 0.6% O2
5000
Figure 4.52: Plateau atomic oxygen density in dependence of the total gas flow.
Astonishingly, an additional increase of the maximum atomic oxygen density can be observed
for higher gas flows as shown in figure 4.50. The atomic oxygen density increases from
2.3 × 1015 cm−3 at 750 sccm total gas flow to more than 5 × 1015 cm−3 at a total gas flow of
4500 sccm. At these high fluxes, the measured absolute values agree much better with the
values obtained from simulation. Accordingly, a decrease of atomic oxygen loss processes
for higher gas flows can be assumed. Possible explanations may be additional loss processes
originating from higher impurities at low gas flows (back diffusion or leaks), a shift of the
drift-diffusion-convection-reaction balance in the plasma dynamics, or a shift in temperature
balance leading to a change in the reaction coefficients and species densities.
Density profiles at low gas flows further show an influence also on the profile shape. Whereas
for higher gas flows, a continuous increase and convergence into an equilibrium density is
found, for low gas flows of e.g. 750 sccm a maximum density is reached early (z = 2 mm)
with a subsequent linear decrease towards the effluent. The slope of this decrease is relatively
small. For higher gas flows, this effect vanishes.
To study the possible influence of nitrogen, the emission spectrum at several operational
parameters was recorded using a broadband USB spectrometer (OceanOptics, 194-1120 nm,
0.25 nm resolution). The setup was similar to the OES temperature measurements.
For a low gas flow rate of 0.5 slm He with 0.6% of O2 admixed, the typical emission spectrum
of the µ-APPJ at z=39 mm can be seen in figure 4.53. The most dominant radiation derives
116
Chapter 4. Results
4.5. Dependence on the gas flow
0
12
2
N (C-B,v'=
0)
-v''=
Bandhead:
intensity [a
.u.
]
10
33
7nm
8
6
4
2
0
200
S°- P)
5
O (
5
777nm
H
3
° S)
3
O (
844
706nm
400
3
nm
600
wavelen
S°- P)
3
e ( P -
800
gth [nm]
Figure 4.53: Spectrum (z=39 mm) at a total gas flow of 0.5 slm.
12
S°- P)
5
O (
777nm
.u.
]
10
intensity [a
5
8
6
2
4 7
2
0
200
0
N (C-B,v'=
0)
H
-v''=
° S)
706nm
Bandhead:
33
3
3
e ( P -
S°- P)
3
O (
844
3
nm
nm
400
600
wavelen
gth [nm]
800
Figure 4.54: Spectrum (z=39 mm) at a total gas flow of 3.0 slm.
117
Chapter 4. Results
4.5. Dependence on the gas flow
20
18
N
33
7 nm
H
O
777 nm
706 nm
O
nm
2
16
e
844
intensity [a
.u.
]
14
12
10
8
6
4
2
0
0
u
heli
1
m
2
3
4
gas flow incl. 0.6% O2 admixed [slm]
Figure 4.55: Emission intensity of helium oxygen and nitrogen impurities as a
function of the total gas flow.
from nitrogen molecules in the spectral range around 300-400 nm, the atomic lines of helium
at 706 nm, and atomic oxygen at 777 nm and 844 nm. Recording the emission at the same gas
mixture and generator power (figure 4.54), with the only difference of an elevated total gas
flow of 3 slm, one can see that the nitrogen emission has disappeared almost completely.
Figure 4.55 shows the emission of the second positive N2 system band head at 337 nm as a
representative for the dominant nitrogen emission. Further it shows the respective emission
of the atomic helium and atomic oxygen lines under variation of the total gas flow.
The atomic oxygen lines at 777 nm and 844 nm reveal a similar behavior as the TALIF
signal in figure 4.52 with an exponential convergence increasing with the gas flow, while the
N2 emission decreases exponentially with the gas flow. For total gas flows higher than 3 slm
or average gas velocities higher than 50 m/s respectively, the emission of the nitrogen is no
longer detected by OES
The decreasing nitrogen emission with elevated gas velocities may have two different origins.
Either mainly the nitrogen density decreases or the excitation mechanisms for nitrogen become less effective for higher gas velocities i.e. the plasma dynamics themselves change with
the flow.
118
4.5. Dependence on the gas flow
7
1
5
05
2
gas flow [slm]
6
6
,
1
W
0 5
15
,7
,
3
4
3
2
1
33
g
7 nm nitro en : 7
06
intensity ratio [a
.u.
]
u
nm heli m
Chapter 4. Results
0
0
20
40
z axis [mm]
Figure 4.56: Ratio of nitrogen to helium emission along the discharge channel.
Firstly, assuming that the nitrogen density is affected by the gas flow, several sources must be
considered. Nitrogen impurities originating directly from the feed gases (e.g. purity inside the
gas supply bottles) can be neglected as their partial pressure remains the same for each gas
flow. To further distinguish whether the nitrogen flows back through the extended effluent
or leaks in before or inside the jet, the spatial development of the nitrogen emission was
investigated. Figure 4.56 e.g. shows the ratio of the 337 nm nitrogen emission in comparison
to the 706 nm helium line.
The contribution of the nitrogen emission increases towards the effluent for lower gas flows
of 0.5 slm or 0.75 slm. For gas flows higher than 2 slm the relative nitrogen emission even
decreases towards the effluent. This rather indicates a nitrogen back diffusion. Leveille et al.
and Sun et al. found a similar behavior for similar atmospheric pressure discharges operating
under a flow of the feed gas. Here, a change of the plasma at low gas velocities is supposed
to be caused by back-flowing outer atmosphere [82, 83].
The behavior also corresponds very well with the observed density profiles as displayed in
figure 4.50. For low flows of 0.5 slm a maximum in the atomic oxygen density at z = 5 mm
is observed, then slightly decaying again towards the effluent. This directly corresponds to
the spatial minimum of N2 emission in figure 4.56 at z = 5 mm and then increasing nitrogen
emission towards the effluent.
Nitrogen might suppress the production of O either by consuming parts of the supplied power
119
Chapter 4. Results
4.5. Dependence on the gas flow
.0
2
4
2
1
5
7
4
36
0.6
31
26
0.4
21
16
0.2
0.0
0.0
10
0.2
0.4
0.6
0.8
.0
5
0
gas velocity [m/s]
y [mm]
0.8
1
x [mm]
Figure 4.57: Distribution of the gas velocity in laminar helium flow at atmospheric
pressure inside a rectangular channel of 1x1 mm2 cross-section.
or by processes such as NO production. Sousa et al. proposed the effective atomic oxygen
destruction inside a micro hollow cathode discharge even by small admixtures of reactive
nitrogen species [23].
On the other hand, assuming the gas velocity v = 25 m/s, a binary diffusion coefficient
D = 7 · 10−5 m2 s−1 and a typical length of one millimeter, the resulting Peclet number
P e = v·l
is 357, which is significantly larger than 1. This indicates that feed gas convection
D
dominates over possible back-diffusion. Thus, nitrogen back flow should be negligibly small
for the plasma itself.
This consideration, however is only valid for a laminar gas flow without any vortex formation.
below 2100, a turbulent flow can be disqualified. Here
For a Reynolds number Re = d·ρ·v̄
µ
d denotes the typical length scale (usually tube diameter, here 1 mm assumed), ρ = 0.16
kg · m−3 the helium density (at room temperature), µ = 2 · 10−5 P a · s the dynamic viscosity
of helium, and v̄ the average gas velocity [84, 85]. Even for the highest average gas velocity of
75 m/s (4500 sccm), the resulting Reynolds number of 600 is well below the critical value.
In a stable laminar flow, the velocity field develops a parabola-shaped distribution, as e.g.
shown for an average gas velocity of 25 m/s in figure 4.57. Here the gas velocity in the
vicinity of the walls is much lower than the average gas velocity, while in the center it is
much higher.
120
0
0.8
-
0.6
1
-2
-3
-4
gas flow
-
0.4
-
5
6
-7
0.2
-
0.0
39.0 39.2 39.4 39.6 39.8 40.0
-
8
9
10
g
x [mm]
.0
1
g10 scale]
4.5. Dependence on the gas flow
nitro en concentration [lo
Chapter 4. Results
z [mm]
Figure 4.58: Calculated spatial nitrogen concentration (back diffusion) against a
laminar helium flow with parabola-shaped velocity profile.
To investigate a possible back diffusion of nitrogen, in the vicinity of the walls, a numerical two dimensional diffusion-convection calculation was performed using the pre-defined
diffusion-convection module within the program COMSOL Multiphysics (atmospheric pressure, 300 K, diffusion coefficient D = 7 · 10−5 m2 s−1 )[75]. The simulation domain covers a
channel of 1 mm width (x direction) and 40 mm length (z direction). Nitrogen diffuses from
the right (concentration set to one at the right boundary at z = 40 mm and to zero at the
left boundary at z = 0 mm) against a helium flow from the left with a velocity distribution
according to figure 4.57. The resulting nitrogen concentration is shown in gray values on a
logarithmic scale in figure 4.58. It can be found that nitrogen back-diffusion in the vicinity
of the walls is indeed more pronounced than in the center of the gas channel. However, even
close to the confining walls the nitrogen concentration decreases below 10−10 within less than
one millimeter.
Macroscopic vortexes, on the other hand may appear due to possible edges appearing at the
transition between electrodes and guided effluent or due to the electro hydrodynamic forces
of the plasma. The formation of a vortex at the tip of a plasma needle discharge (operated at
13.56 MHz under a helium gas flow) e.g. was found in [86]. Such vortexes may significantly
enhance the mixture of gases.
If, on the other hand, the partial density of nitrogen does not change at all within the gas
channel, the plasma dynamics themselves might be depending on the gas velocity. An actual
121
Chapter 4. Results
4.5. Dependence on the gas flow
change is highly depending on the balance of drift, diffusion, convection and reactions and
hence can only be addressed by much more complex models which include the convective
gas flow explicitly.
Summary
A variation of the feed gas velocity revealed a slightly over-linear increase of the atomic
oxygen density build-up length. Astonishingly, even the plateau-density itself increases with
the gas flow showing a converging behavior towards higher gas velocities. Here, the measured
atomic oxygen densities agree better with the numerical predictions. A possible origin for this
dependence on the gas flow might be the back-diffusion of nitrogen species or other impurities
from the surrounding atmosphere. Accordingly, a significant decrease of nitrogen emission
was found for elevated gas velocities. Under the assumption of an undisturbed laminar flow,
possible back-diffusion should be dominated by the convective feed gas flow. These findings
were found to be reasonable even for a non-uniform laminar velocity distribution within the
gas flow. However, the possibility of vortex occurrence was discussed, which may significantly
enhance gas mixture.
From the observed flow dependence further consequences can be drawn. According to the applied gas flow, a further shortening of the electrodes length can lead to a not fully established
and equilibrated oxygen chemistry at the nozzle and thus to lower density values within the
effluent. On the basis of these findings, the gas flow rate is found to be an important parameter for plasmas operating under a convective gas flow. It must be explicitly addressed when
such discharges are characterized and compared to each other or to numerical simulations.
122
5 Summary and outlook
Within this work, it was achieved to quantitatively investigate atomic oxygen density profiles inside a micro-scaled atmospheric pressure plasma jet (µ-APPJ) under a variation of
the operation parameters such as rf generator power, gas mixture and gas flow. To measure
these densities within the 1 x 1 x 40 mm3 discharge core, two-photon laser induced fluorescence spectroscopy was applied. Atomic oxygen is supposed to be one of the key agents
for the various surface modifying effects. The presented measurements are valuable data to
benchmark numerical simulations of proposed models.
The range of operation parameters such as generator power and gas mixture was determined
by electric measurements of the U-I characteristics. Increasing the oxygen admixture, the
generator power threshold values for ignition and arcing were found to shift to higher power
values. Additionally, for admixtures higher than 1.0%, the power interval from ignition
to arcing tends to shrink. Stable operation becomes impossible for admixtures higher than
approximately 1.6%. Despite the advantage of enhanced optical access, the reduced electrode
size of the µ-APPJ is a challenge for electric diagnostics due to the low impedance of the
discharge. Deriving the plasma conduction current from the phase shift of total current and
voltage, a good comparability to the larger APPJ and to numerical simulations was found.
Those measurements revealed the powers coupled into the µ-APPJ to be significantly lower
than the generator output powers due to large stray capacitances.
Since the measurement of absolute atomic oxygen density values critically depends on the
knowledge of competitive collisional de-excitation, and available data for the respective rate
coefficients shows a large spread, the total de-excitation rate of the atomic oxygen fluorescence signal was measured explicitly and compared to extrapolated data from mid pressure
experiments. The measured total de-excitation rates agree very well with extrapolated midpressure data from [34] (within an accuracy of below 10% up to the 250 MHz bandwidth limit
of the recording oscilloscope). Ground state helium atoms and O2 molecules were found to
123
Chapter 5. Summary and outlook
be the only relevant species for collisional quenching in the effluent and also in the discharge
core.
According to the small sizes of the discharge structure in comparison to the typical sizes
of the optical setup, the influence of vignetting was investigated. In the vicinity of the
discharge boundaries, the partial ”cut-off” of the laser focus was found to cause the dominant
vignetting of the fluorescence signal. Gas temperatures within the discharge core represent
another important parameter for the calibration of the applied TALIF diagnostics and for
numerical simulations. They were measured independently by optical emission spectroscopy
of the rotational spectrum of nitrogen impurities and by a fluorescence fiber probe. Both
techniques found the temperature to remain below 360 K. In this range the TALIF calibration
was found to be very insensitive towards fluctuations of the gas temperature.
The calibrated TALIF system was benchmarked against independent molecular beam mass
spectrometry in a freely expanding effluent. Both independent diagnostics show a very good
qualitative agreement for variations of generator power, gas mixture, and distance from the
discharge nozzle. The quantitative data agree within the combined accuracy range of both
techniques. However, TALIF measurements systematically revealed slightly higher absolute
density values than MBMS.
With the calibrated and benchmarked system, subsequent measurements in the discharge
core were performed. The spatial ascent of atomic oxygen densities inside the plasma core
shows a fast asymptotic convergence into a dynamic equilibrium density which is reached
within a few millimeters along the gas stream. The equilibrium densities were found to last
until the end of the electrodes and quickly decay within the adjacent effluent.
The finding of a developed dynamic equilibrium of the oxygen chemistry is further valuable
information. Many numerical simulations reveal steady state conditions and can only be
compared to experimental results where the chemistry has converged.
The measured density within the dynamic equilibrium increases almost linearly with increased generator power and molecular oxygen admixture. Atomic oxygen densities up to
1016 cm−3 were found e.g. for 25 W generator power, 1.5 slm He and 22.5 sccm O2 . Under a variation of generator power and oxygen admixture, the spatial ascent was found to
remain within the first few millimeters. This quick convergence into a dynamic equilibrium
density motivates a comparison to the numerical results of a one-dimensional fluid model
(only resolving the gap between the electrodes). The simulation results could reproduce the
linear increase of atomic oxygen equilibrium densities with incoupled power. The model
revealed atomic oxygen to be produced mainly by electron impact dissociation of O2 forming
124
Chapter 5. Summary and outlook
either two ground state oxygen atoms or meta-stable atomic oxygen as a precursor. These
processes predominantly occur within the ”plasma bulk” which can roughly be considered as
the central 60% of the discharge gap. Loss processes were identified to be volume dominated
(zero surface loss assumed in simulation) which agrees well with the measured flat transversal
density profile. The absolute density values predicted by the model, however, were found
to be higher than the measured ones by a factor of 2.7. This can either be attributed to
the uncertainties in each of the utilized cross-sections or it can be attributed to additional
atomic oxygen loss processes, which are not covered by the model.
To investigate the spatial and transient charge dynamics, the emission of the dominant
atomic oxygen 777 nm line was investigated by phase resolved optical emission spectroscopy
(PROES). Comparing the observed emission profiles to the numerically predicted spatial
and transient excitation profiles, these measurements represent an additional benchmark of
the proposed model. Simulated spatial and transient positions of the oxygen 5 So excitation
structures were found to agree well with the measured emission structures from that level. A
variation of generator power and simulated power identified the observed emission structures
to be similar to sheath expansion and collapse. A third emission structure appearing for
higher powers could be attributed to secondary electron emission. The observed distinct
spatial ascent behavior of this structure along the gas channel supports the model prediction
of penning ionization as an origin for these secondary electrons. Still further measurements
of species such as ozone, helium and oxygen meta-stables and possibly electrons, ions and
electric fields are desired to further benchmark the modeled discharge dynamics.
Finally, the explicit dependence of the atomic oxygen density profile on the gas velocity, which
is not modeled, was studied. An increase towards higher gas velocities revealed an almost
linear increase of the typical ascent length of the atomic oxygen density which indicates a
typical reaction time of 60 µs. Astonishingly, an increase of the equilibrium density value
with the applied gas velocity was found as well. From a gas flow of 750 sccm to a gas flow
of 4500 sccm, the atomic oxygen density in the dynamic equilibrium was found to increase
by more than a factor of two.
A simultaneous observation of decreasing nitrogen emission with higher gas velocities led
to the assumption of impurities transported back into the discharge from the outer atmosphere. A spatial increase of the nitrogen emission in the vicinity of the nozzle motivated
the assumption of a back-diffusion from the surrounding against the gas stream. Considerations on the nitrogen diffusion against the convective laminar helium flow however revealed
back-diffusion to be compensated within one millimeter from the nozzle. Other explanations
such as a shift in the balance of drift, diffusion, convection, and reactions are still difficult to
125
Chapter 5. Summary and outlook
access by simulation and diagnostics and thus require further investigations. The influence
of impurities can be studied e.g. by a controlled varying admixture to the feed gas.
In particular for the µ-APPJ, for gas flows lower than 3 slm, or a velocity lower than 60 m/s
respectively, the influence of the gas velocity cannot be neglected and must be considered
when comparing experimental data to analytical models and simulations.
Since the mentioned influence of the gas velocity was found even for the extended jet design,
it can possibly be even higher –or more probable– for other jet-like discharge designs with
freely expanding effluents. Increasing the gas velocity may thus also increase the atomic
oxygen densities created in such devices.
126
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131
Curriculum Vitae
Name: Nikolas Knake
Geburtsdatum: 15. März 1982
Geburtsort: Bottrop
Schulausbildung
1988 – 1992 Rheinbaben-Grundschule Bottrop
1992 – 2001 Josef-Albers-Gymnasium Bottrop
Juni 2001 Abschluss : Allgemeine Hochschulreife
2001 – 2002 Zivildienst bei der evangelischen Sozialberatung Bottrop
Hochschulausbildung
2002 – 2007 Studium der Physik an der Universität Duisburg-Essen
06 – 08 2006 IAESTE Praktikum an der University of Tokyo
August 2007 Abschluss: Diplom Physiker,
Schwerpunkt Plasmaphysik
seit 2006 Studentische Hilfskraft
am Institut für Experimentalphysik II,
Ruhr-Universität Bochum
Promotionsvorhaben
2007 – 2010 Wissenschaftlicher Mitarbeiter am
Institut für Experimentalphysik II,
Ruhr-Universität Bochum
seit 2007 Stipendiat im DFG Graduiertenkolleg 1051
2008-2009 Vize-Sprecher der Doktoranden des GK 1051
04 –05 2008 Research Student
an der University of Nagoya
gefördert durch das GK 1051
seit 2008 Fellow der RUB Research School
2008-2009 Vize-Sprecher der Doktoranden
der Sektion Naturwissenschaftler und Ingenieure
Publications
Parts of this work have already been published. The respective papers are marked with ⋄.
• ”Gas flow dependence of ground state atomic oxygen in plasma needle discharge at atmospheric pressure”
Y. Sakiyama, N. Knake, D. Schröder, J. Winter, V. Schulz-von der Gathen, and D.B. Graves
Appl. Phys. Lett. 97 (2010) 151501
• ”Phase resolved optical emission spectroscopy of coaxial microplasma jet operated with He
and Ar”
J. Benedikt, S. Hofmann, N. Knake, H. Böttner, R. Reuter, A. von Keudell, and V. Schulzvon der Gathen
Eur. Phys. J. D 60 (2010) 539
⋄ ”Investigations of the spatio-temporal build-up of atomic oxygen inside the micro-scaled atmospheric pressure plasma jet”
N. Knake and V. Schulz-von der Gathen
Eur. Phys. J. D 60 (2010) 645
⋄ ”Atomic oxygen formation in a radio-frequency driven micro atmospheric pressure plasma
jet”
J. Waskoenig, K. Niemi, N. Knake, L. M. Graham, S. Reuter, V. Schulz-von der Gathen, and
T. Gans
Plasma Sources Sci. Technol. 19, (2010) 045018
⋄ ”Investigations on the generation of atomic oxygen inside a capacitively coupled atmospheric
pressure plasma jet”
N. Knake, D. Schröder, J. Winter, and V. Schulz-von der Gathen
J. Phys.: Conf. Ser. 227, (2010) 012020
• ”Diagnostic based modelling on a micro-scale atmospheric pressure plasma jet”
J. Waskoenig, K. Niemi, N. Knake, L. M. Graham, S. Reuter, V. Schulz- von der Gathen,
and T. Gans
Pure and Applied Chemistry 82 (2010) 1209-1222
⋄ ”Characterization of the effluent of a He/O2 microscale atmospheric pressure plasma jet by
quantitative molecular beam mass spectrometry”
D. Ellerweg, J. Benedikt, A. von Keudell, N. Knake, and V. Schulz-von der Gathen
New Journal of Physics 12, (2010) 013021
• ”Diagnostic based modelling of radio-frequency driven atmospheric pressure plasmas”
K. Niemi, S. Reuter, L. M. Graham, J. Waskoenig, N.Knake, V. Schulz-von der Gathen, and
T. Gans
J. Phys. D: Appl. Phys. 43, (2010) 124006
• ”Absolute atomic oxygen density profiles in the discharge core of a micro scale atmospheric
pressure plasma jet”
N. Knake, K. Niemi, St. Reuter, V. Schulz-von der Gathen, and J. Winter
Appl. Phys. Lett. 93, (2008) 131503
• ”Spatially resolved diagnostics on a micro atmospheric pressure plasma jet”
V. Schulz-von der Gathen, L. Schaper, N. Knake, St. Reuter, K. Niemi, T. Gans, and J.
Winter
J. Phys. D: Appl. Phys. 41, (2008) 194004
• ”Absolute atomic oxygen density distributions in the effluent of a micro scale atmospheric
pressure plasma jet”
N. Knake, St. Reuter, K. Niemi, V. Schulz-von der Gathen, and J. Winter
J. Phys. D: Appl. Phys. 41, (2008) 194006
• ”Optical Diagnostics of Micro Discharge Jets”
V. Schulz-von der Gathen, V. Buck, T. Gans, N. Knake, K. Niemi, St. Reuter, L. Schaper,
and J. Winter
Contr. Plasma Phys. 47, (2007) 510-519
• ”Diagnostics on an atmospheric pressure plasma jet”
K. Niemi, St. Reuter, L. Schaper, N. Knake, V. Schulz-von der Gathen, and T. Gans
Institute of Physics - Journal of Physics Conference Series 71 (2007) 012012
Danksagung
An dieser Stelle möchte ich mich noch einmal ganz herzlich bei allen Personen bedanken, die durch
ihre freundliche Unterstützung zum Gelingen dieser Arbeit beigetragen haben.
Mein Dank gilt Herrn Prof. Dr. J. Winter, der mir durch seine intensive und fortwährende
Förderung ermöglicht hat, diese Dissertation an der Ruhr-Universität Bochum im Bereich der
Plasmaphysik durchzuführen.
Herrn Prof. Dr. U. Czarnetzki möchte ich für die kurzfristige Übernahme des Zweitgutachtens
danken. Ich möchte ihm und Herrn Prof. K. Sasaki ebenfalls dafür danken, dass sie mir den Gastaufenthalt an der Universität Nagoya ermöglicht haben und mich während dessen fortwährend
unterstützt haben.
Herrn Dr. Volker Schulz-von der Gathen danke ich für die fortwährende hervorragende Betreuung,
Unterstützung und Förderung während meiner Promotion und darüber hinaus. Ihm, Herrn Dr. M.
Böke und Frau V. Scharf danke ich ebenfalls für das Korrekturlesen meiner Arbeit.
Herrn D. Ellerweg und Herrn Dr. J. Benedikt danke ich für die hilfreiche Zusammenarbeit und
Durchführung der Molecular Beam Mass Spectroscopy Messungen.
Herrn J. Waskönig danke ich für die vielen hilfreichen Diskussionen und Kooperationen bezüglich
der von ihm entwickelten Computersimulationen. Für die Einführung in die Phasenwinkel-Messungen
möchte ich Herrn Dr. P. Kempkes danken.
Ebenfalls bedanken möchte ich mich bei den technischen Mitarbeitern des Lehrstuhls, den Herren
K. Fiegler, B. Redeker, A. Lang, M. Konkowski, K. Brinkhoff und W. Winterhalder und den Mitarbeitern der zentralen Werkstatt insbesondere Herrn G. Schäfer und C. Vilter für Konstruktionen,
Ratschläge und die sofortige Hilfe auch bei zeitkritischen Problemen. Frau M. Ocklenburg danke
ich ebenso für ihre Unterstützung.
Ein großes Dankeschön noch einmal an meine Büronachbarn, Laborkollegen und Freunde H. Böttner und J. Waskönig für die großartige Zeit an der Universität und darüber hinaus. Gleiches gilt
für unsere Diplomanden D. Schröder, A. Greb und H. Bahre.
Sämtlichen Mitarbeiter der Gruppen EP II und AG Reaktive Plasmen und allen hier ungenannten
Kolleginnen und Kollegen danke ich für das angenehme Arbeitsklima und die freundliche Unterstützung. Ich werde die gemeinsame Zeit vermissen.
Ich möchte mich bei den Mitarbeitern und Kollegiaten der Research-School der Ruhr-Universität
136
Bochum für die außerfachliche Förderung bedanken. Ferner bedanke ich mich bei der Deutschen
Forschungsgemeinschaft für die Förderung im Rahmen des Graduiertenkollegs 1051, der Forschergruppe 1123, und des Projekts SCHU-2353.
Nicht zu vergessen danke ich meinen Eltern und Geschwistern für ihren Rückhalt und ihre Unterstützung.
Vielen Dank!