Engineered Excellence
A Journal for Process and Device Engineers
Simulation of Ion Beam Etching of Patterned Nanometer-scale
Magnetic Structures for High-Density Storage Applications
Introduction
Fabrication of various nano-structures often requires
mask controlled or patterned etching of materials. The
chemical or wet etch methods cannot be used for nanoscale
geometries due to the substantial isotropic component of
etch rate. Therefore, various plasma or reactive ion etching
method are typically used. Unfortunately, some materials do not easily form volatile reaction products and all
types of chemically assist etching becomes problematic.
Among those materials are elements such as Co, Ni, Fe,
Pt, and Cr which are usually used in magnetic nanostructure technologies. Therefore, ion beam etching or
ion milling is the most suitable method to pattern these
materials [1].
that the selectivity ratio decreases with ion beam energy, and therefore a typical energy used for this process
is in the interval of 200 – 500 eV. The only real challenge
in controlling the ion etching of the Nanostructures is
the effect of redeposition [2]. The atoms removed (sputtered) from the surface of material being etched will
either escape back to the process chamber or collide
with sidewalls of the structure. Since the majority of
these sputtered atoms collide with the walls at very low
energies there is high probability for them to stick to
the wall and form a new layer. The redeposited layer is
an amorphous mixture of the particles sputtered from
different materials in the structure. For simplicity, we
will call this newly formed material “alloy”. In the case
where the substrate is a single material layer the alloy
will consist mostly of the substrate material atoms but
should have lower density.
The most promising magnetic nano-technology application is the Bit Pattern Media (BPM). The BPM technology
has a potential to manufacture Hard Drive Discs (HDD)
with density of up to few terabytes per square inch. To
achieve such high density, huge arrays of single domain
magnetic islands of ~10 nm diameter must be formed.
Other essential requirements for manufacturing of highdensity BPM are as small as possible distance between
these magnetic islands and as vertical as possible sidewalls of the islands.
Redeposition Effect
Redeposition considerably changes the geometrical dynamics of the ion etching process. Without redeposition
the etch rates would be nearly constant across the bottom
of the trench being etched because the ion beam is usually tilted by just few degrees and is constantly rotated.
The only variable geometrical characteristics would be
a faceted top corner of the mask which could result in a
very slight change in ion beam visibility on the trench
bottom. However, the picture is considerably different
Ion Milling
Ion milling is the leading candidate among etching
techniques capable of meeting the requirements above
[2]. No chemical process is involved and therefore the
geometry of etched structure is determined mainly by
mask geometry (thickness and slope), by parameters
of the ion beam (energy, direction, rotation, density)
and by the sputtering characteristics of the magnetic
and mask material. The successful use of ion milling
requires considerable etch rate selectivity between
mask and magnetic materials. Fortunately, carbon hard
masks typically have 3-5 times smaller ion etch rate
then most magnetic materials. It is important to note
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are key capabilities of Victory Process and auxiliary Silvaco tools which allow accurate simulation of ion milling
as well as process calibration and optimization:
• Accounting for ion beam tilt, rotation and divergence
• Full 3D visibility calculation for ion beam and sputtered fluxes
• Experimental tables or semi-empirical models for
angle dependency of etch rate
• Alloy redeposition model which takes into account
the secondary fluxes of sputtered particles
• The secondary particle fluxes are proportional to local etch rate and can have specific spatial distribution
(emission characteristic function). We use isotropic
emission function in simulations presented in this
paper
• Capability to take into account redeposition contribution from secondary fluxes generated within adjacent
domains
• Material-dependent redeposition efficiency allows us
to account for the fact that some secondary flux particles may not contribute to redeposited layer formation even if they reach its surface
Figure 1. Structure evolution during Ion Milling process. Green
is etched material, violet is mask material, red is alloy. (the
HTML version of this article includes more detailed animation).
• Automatic extraction of 2D cut planes for direct comparison with SEM pictures
when redeposition takes place. This is illustrated in
Figure 1, which shows the etch dynamics in a 2D section of a line pattern. The dynamically formed alloy layer decreases the ion beam visibility at the bottom of the
trench. Consequently, the effective etch area decreases
when the trench becomes deeper. Simultaneously, particles sputtered from the bottom of the deeper trench
have a lower probability to escape back to the process
chamber and therefore the alloy layer keeps growing on
the sidewalls. As this process continues the redeposited
layer is also getting etched by the incoming ion beam
flux and, depending on the stage of the process, the balance between etching and redeposition rate is changing.
• Extraction of key geometrical parameters from simulated structures: layer thickness, angles etc.
• Capability to setup designs of experiment with variation of process conditions, material parameters as
well as geometrical parameters of initial structure
and masks
Typical Example – Densely Packed
Magnetic Bits
Structures with densely packed features are most challenging for Ion Milling simulation. At the same time the large
matrix of small magnetic islands as shown in Figure 2 is
the ultimate goal of this technology. To demonstrate that
Victory Process can handle such dense structures we performed an ion milling simulation within a simulation domain indicated by the yellow box in the mask layout shown
in Figure 3. The area outside the yellow box demonstrates
8 reflective/symmetric domains which are taken into account only for redeposition. This means that the local etch
rates in these domains are the same as in the main simulation domain but some portion of sputtered particles may
reach the main domain and participate in redeposition.
Ion Milling Simulation
The complex dynamics and strong geometrical dependency of the redeposition effect make it almost impossible to develop a reliable and optimized ion milling
based process without extensive simulation. Experimental test structures may help to determine some parameters of the process, particularly the etching rates
as a function of beam characteristics and incident angle. However, without detailed simulation it is impossible to predict how redeposition dynamics will express
itself in real 3D structures.
The following settings were used for all simulations in
this paper. The ion milling was performed with 250 eV Ar
and a current density of 1.5 pA/μm2. The constantly rotated ion beam was tilted by 5° from surface normal and
To our knowledge, the Ion Milling module of Victory Process
is the only tool capable of predictive 3D simulation of ion
beam etching on a nanometer scale level. The following
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April, May, June 2013
Figure 2. Top-down image of dense pack of ion milled magnetic
islands arranged in hexagonal formation. The pitch or distance
between centers of the islands was ~20 nm. This is a fragment
of the SEM picture from [2] reprinted with permission from the
author Dan Kercher (HGST).
Figure 4. Ion etch rate dependence on incident ion angle for
three materials used in structures simulated in this paper.
Figure 3. Mask layout with 10 nm islands and 15nm pitch.
Figure 5. The final structure after 5 minutes ion milling. Yellow
is chromium, blue regions are hard masks and red layers are
redeposited “alloy”.
had flux divergence of 5°. The etched structure consisted
of two layers: Chromium substrate material and the 20
nm hard Carbon mask. The etch rate versus angle function for this simulation was obtain by the semi-empirical
Yamanura model [3] using above ion beam settings and
default values for these materials. Also, all parameters
of “alloy” were the same as for Chromium except the
density which was set to 80% of Chromium density. The
milling rates as a function of incidence angle for all three
materials are shown in Figure 4.
of the ion milling process in 3D: faceting of hard mask,
alloy thickness variation due to different proximity of
neighboring island, and shallower etch depth in directions toward closest neighbors (0, 60, 120,.. degrees).
Calibration of Ion Milling Simulation and
Process Optimization
The example in the previous section clearly shows that
the Ion Milling model of Victory Process can be successfully used for simulation of complex ion etching processes in Nanostructures. However, by no means is it a
“push-button” solution, because some important material parameters are not known apriori and would require
The result of ion milling simulation for the densely packed
magnetic islands is shown in Figure 5. This picture confirms that the simulator can capture main characteristics
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Figure 6. Example of experimental extraction which can be use for calibration and process optimization. This is a SEM picture from [2]
reprinted with permission from the author Dan Kercher (HGST).
to measure the etch rates and secondary efficiency for redeposited “alloy”. These parameters can be estimated by
varying them in simulation and comparing results with
experiments on simple test structures.
some calibration. First of all, the built-in etch rate model
may not match with experimental data for very low ion
beam energies used in this application. Therefore, accurate measurements of etch rates at several angles for each
material are usually required. However, it is impossible
The natural choices for tests structures are lines with
varying spaces between them. The depth and angle of
the resulting groove could serve as figures of merit. The
SEM picture measurements can be done at several etching times (see Figure 6).
Simulations with the goal of calibration and optimization could be efficiently performed within a narrow slice
of the structure consisting of two mask lines. The width
of the window between masks could be varied. Despite
this the simulation effectively uses a quasi-3D structure,
and the redepostion effect is considered in full 3D because four reflection domains are taken into account as
shown in Figure 3.
Figure 7. Extract process parameters used in analysis of the
redeposition effect. The etch depth and average sidewall angle
were obtained using Extract capability of DeckBuild. The 2D
cut plane structures were automatically exported from 3D structures (see [4]).
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Figure 8. The etch depth after 5 minutes ion milling versus redeposition efficiency for different window widths.
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April, May, June 2013
Figure 10. Sidewall slope angles versus mask window width for
deposition efficiencies from 40% to 100%.
Figure 9. The etch depth after ion milling for 2, 3, 4 and 5 minutes versus mask window width. The green lines are obtained
with 100% redeposition efficiency, while the red lines correspond to 80% redeposition efficiency.
Conclusions
It appears that Ion Beam Etching/Milling is emerging as
a viable tool for several nanoscale technologies including high-density magnetic storage applications. This article demonstrates that the Silvaco Victory Process simulator together with interactive and design of experiment
tools could be very useful in design and optimization of
this very advanced technology. The simulations in this
article show that the Ion Milling models can successfully
predict the key effects of the process including 3D redeposition of sputtered material.
The simulation conditions, materials, etch rates and mask
thickness were exactly the same as in the 3D test case
described in the previous section. A simple Design of
Experiment (DOE) was setup using the DBInternal tool
of DeckBuild in which the window width was varied
from 8 to 16 nm and redeposition efficiency was varied
from 25% to 100%. The 3D structures were saved after 2,
3,4, and 5 minutes of ion milling. The etch depth and the
average slope angle were extracted automatically from a
2D cut plane as shown in Figure 7.
The simulation results shown in Figure 8 could be used
for calibration of the important secondary efficiency parameter for redeposited alloy material. By measuring the
etch depth in the test structure with mask windows of
varying widths, one can easily find an optimum value
for this parameter.
Acknowledgment
We would like to express our gratitude to researchers at
San Jose Research Center HGST, a Western Digital company, for their valuable suggestions which help us to improve the code and to expand our understanding of Ion
Milling Process application to magnetic nanostructures.
The results shown in Figure 9 highlight that the etch
depth is not simply proportional to etch time. Moreover,
if redeposition efficiency is high the ion milling effectively stops after approximately 4 minutes.
References
1. D. Kercher, Pattering Magnetic Nanostructures with Ions,
in Nanofabrication Handbook, editors S. Cabrini and S. Kawata, CRC Press, p. 421 (2012).
The sidewall slope angle could serve as another figure of
merit for ion milling test structure simulation. These angle also depends on process conditions and structure geometry. The sidewall slopes can be extracted from DOE
simulations and compared with experimental angles
obtained from the SEM pictures (see Figure 6). In our
simulations these angles vary from 68° to 78° depending
on conditions. The sidewall angles considerably depend
on redeposition efficiency and less on the mask window
width (see Figure 10). We believe that sidewall slopes can
be more effectively controlled by other process parameters, e.g. ion beam angle, the mask widow thickness and
slope or even etch rate of redeposited alloy.
April, May, June 2013
2. D.Kercher, Geometrical Limitations of Ar Ion Beam Etching, EIPBN-2010.
3. A Semi-Empirical Model for the Simulation of Ion Milling in VICTORY Process, Simulation Standard, October,
November, December 2012. http://www.silvaco.com/
tech_lib_TCAD/simulationstandard/2012/oct_nov_dec/a2/
a-semi-empirical-model-for-the-simulation-of-Ion-millingin-victory-process_a2.html.
4. Syntax Driven 2D Structure Export from 3D Structures and
Extraction of 2D Volume Data Maps, Simulation Standard,,
April, May, June 2012. http://www.silvaco.com/tech_lib_
TCAD/simulationstandard/2012/apr_may_ jun/a3/Syntax_
Driven_2D_Structure_Export_from_3D_Structures_and_
Extraction_of_2D_Volume_Data_Maps_a3.html.
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