Reactor- and Feature-Scale Simulations for Semiconductor...
Transcript of Reactor- and Feature-Scale Simulations for Semiconductor...
G. Schulze-IckingMP PDT CS SIM2003-05-15 Page 1
Reactor- and Feature-Scale Simulationsfor Semiconductor Manufacturing
- an excursion into different scales & complexities -
Dr. Georg Schulze-Icking
Infineon Technologies AG
G. Schulze-IckingMP PDT CS SIM2003-05-15 Page 2
Content
! equipment + feature ⇔ process + device simulation
! motivation
! equipment & feature scale simulation at IFX
� overview
� computational fluid dynamics
� coupling of scales
� feature scale simulation
! summary & outlook
! acknowledgement
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Difference to Prozess & Device Simulation
! process & device (bulk):� dopant concentrations, (crude) topography,...� electrical behaviour (e.g. I-V curves),...
! equipment & feature scale (gas phase + surface):� dep/etch uniformity, precursor depletion, T distribution,... (wafer scale)� step coverage, selectivity, microtrenching,... (sub-µ scale)
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Motivation
! production issues:� shrinking structures ⇒ more stringent specifications
! dep/etch uniformity across wafer, high aspect ratios,...� novel production processes
! high-k materials, atomic layer deposition,...� tough competition and timelines...
! simulation support:� allows separation of competing effects� helps understanding of complex processes → improvement of recipes� fast optimization cycles (after calibration)� cheap...
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Equipment & Feature Scale Simulation at IFX
! equipment simulation:� reaction kinetics (Chemkin)� fluid dynamics & radiation (CFD-ACE)� plasma & sheath (several)� molecular dynamics (custom)� quantum chemistry (Material Studio)� ...
! feature scale simulation:� AP-CVD, electroplating (Evolve)� LP-CVD, plasma etch,... (Topsi, custom)� �
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Computational Fluid Dynamics
! simulation of thermal processes (e.g. CVD) needs to account for several effects:
� gas flux (Navier-Stokes)� gas phase & surface chemistry� heat (convection, conduction, radiation, and reaction enthalpy)
! simulation yields e.g. dep/etch rate on wafer, bulk stoichiometry! issues: availability of models, breakdown at low-p (Knudsen limit),...
0.05 0.10 0.15
1.0
1.1
1.2
D [a
.u.]
r [m]
⇒
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CFD: Chamber Clean
! CVD chambers need to be cleaned frequently to avoid particles� for SiO2, NF3 clean (with in- or ex-situ plasma) common� NF3 most expensive process gas → large gain from optimizing clean
! example: impact of gas inlet on clean time (transient):
original inlet modified inlet
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CFD: HDP-CVD
! deposition across wafer needs to be very uniform (typically <2%)! issues becomes worse for larger wafers (12'' vs. 8'')! example: impact of reactor conditions on deposition uniformity
experiment simulationpres [SiH2]
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Coupling of Scales: IPVD
! for plasma processes, effects on very different scales need to be considered:
Plasma Model
Sheath Model
Feature Model
Molecular Dynamics Model
M+
M
Plasma
Angular andEnergy Distribution
Transportof M, M+,Ar+
and Deposition
Reaction RatesM, Ar =>Surface
Wafer
1 mm
<1 µ
1 nm
Plasma
Pkap
Pind
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Plasma Simulation
! plasma simulation (cont. or MC) yields e.g. plasma density, electron temperature, and bias voltage. Has to account for:
� coupling of different phases (neutrals, ions, electrons), each with separate T� complex chemistry (Tgas ≤ 1000 K; Tel ≈ 5⋅104 K)� self-consistent solving of charge distribution and E-fields (incl. external)� ...
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Plasma Sheath
! existence of a plasma sheath (e- depletion zone):� electron are orders of magnitude faster than ions
→ e- depletion at surfaces (similar to diode...)→ strong electric field, acceleration of ions towards surface (increased by
external RF bias)→ deceleration of e-
� in steady state ion and electron flux is equal!
∆t ≈ 10-8 s
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Plasma Sheath Simulation
! sheath important, determines ion energy & angle distribution on substrate. Hybrid FD-MC sheath simulator
� solves E-field and charge distribution self-consistently� accounts for gas phase collisions incl. charge exchange� applied RF bias,...
0.002
0.006
0.01
0.014
200 600 1000
Ion Energy [eV]
IED
[a.u
.]
5 mTorr; nPlasma=1010 cm-3
eion+
neutral
plasma
substrate
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Molecular Dynamics
! ions sputter surface, depending on energy and angle of incidence.! experimentally hard to access (low E) → obtain probability & yield from MD,
"simple" Newtonian dynamics but with� complex multi-body potentials� vastly different timescales btw. events: O(ns) for impact, O(s) for diffusion
many!
⇒
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Feature Scale Simulation
! using the above results, e.g gap fill or sputter damage can be studied (details of simulator below):
Ti+Ti+ / Ar+
Ti
Ti / Ti+
deposition
sputteringreflection
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Feature Scale Simulator: Motivation & Requirements
! motivation� extreme geometries → transport important� processes increasingly complex (plasma, superfill,�)� more stringent specifications with decreasing groundrule
! requirements� high accuracy (processes already good�)� higher order reactions� transient surface chemistry� 2D, 2.5D, and 3D� speed�
! currently no simulator available that fulfills above requirements...
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Topsi Feature Scale Simulator: Structure
! goal: temporal evolution of sub-µ structure subject to process:
! program structure:� flux calculation� surface chemistry� front propagation
time
front propagation
flux calculation
surface chemistryfront
local dep/etch rate
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Level Set Front Propagation: Basic Idea
� represent front as zero level of the distance function φ(x,y)� calculate normal velocity FN at front and extend to grid� evolve φ(x,y) (instead of front itself�)� extract new front from φ�(x,y)
φ(x,y)
front (φ=0)front (φ=0)
φ<0: insideφ<0: inside
φ>0: outsideφ>0: outside distancesdistances
FNFN
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Level Set Front Propagation: Equation
for every point at the front holds:
0ty
ytx
xt=
∂∂
∂φ∂+
∂∂
∂φ∂+
∂φ∂
0vt
=φ∇+∂φ∂ r
0NF||t
=φ∇+∂φ∂
0)t),t(y),t(x( =φ
total derivative wrt. t:
with normal velocity: vNFr
φ∇φ∇=
NFtttt ⋅φ∇⋅∆−φ=∆+φ→
φ<0: inside
φ>0: outside
tt ∆+φ
tφ
� LS equation is solved on grid points for time-step ∆t.
� after time-step a new front is extracted as zero level of φt+∆t(x,y).
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Level Set Front Propagation: Advantages
shock front topology Change accuracy
readily extended to 3D!
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Monte Carlo Transport: Motivation
transport effects important: - precursor depletion in structure- energetic sputtering of material- Reactive Ion Etch (RIE) lag...
tracing of particles (MC) accounts for these and...- is applicable to high aspect ratios (DT)- is easily extented to 3D- has no principal errors, only statistical...
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Monte Carlo Transport: Efficiency
desired accuracy requires many MC particles (≥105 per step)
MC flux calculation in Topsi is accelerated using:- adaptive quad-/octtrees- parallelization using MPI- several statistical enhancements
growingfront
initialfront
quadtree
particle
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Chemistry Solver: Requirements
! common processes exhibit:� higher order reactions� energetic reactions (plasma processes)� chemi- & physisorbed layers (e.g. ALD and DT etch)� complex surface chemistry (stiff ODE) � transient surface quantities (e.g. ALD)
! chemistry solver needs to account for these...
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Simple CVD
! precursor depletion results in non-conformal deposition. Gap fill improves with decreasing taper & sticking coefficient:
taper
a=85°s=10-2
a=87.5°s=10-2
a=90°s=10-2
a=87.5°s=10-3
stick
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HDP-CVD: Impact of Bias
! energetic ions from plasma:� sputter surface (high bias only)� activate surface� both yields depends on ion angle & energy
! neutrals deposit on active sites! re-deposition of sputtered material
high bias: low bias:
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HDP-CVD : Impact of Environment
! ideal CVD process:� fills structures of different AR void-free� has deposition height which is independent of design (for CMP)
! however, reality is not ideal...
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ALD: Transient Coverage
! Transport effect in (ideal) ALD� steady state obvious� study temporal evolution
DR=0
DR=0
DR=x
S=1
S=0
S=x
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Simple CVD 3D
! simple CVD (s=0.02) into comb-like structure. 3D geometry introduces complex shadowing effects (visualization with vtk).
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Summary & Outlook
! summary� equipment & feature scale simulation support unit process development � overview of IFX simulation activities� coupling of scales important (e.g. plasma)� computational fluid dynamics (briefly)� custom feature scale simulator Topsi� versatile problems...
! outlook� develop new chemistry models (bottleneck!)� improve support for current processes� develop support for future processes� ...
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Acknowledgement
! thanks to my colleagues who performed most of the presented simulations:
� Gerd Enders� Dr. Werner Jacobs� Dr. Alfred Kersch� Dr. Gerhard Prechtl� Dr. Winfried Sabisch