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![Page 1: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/1.jpg)
Feature-scale to wafer-scale modelling and simulation of physical vapor deposition
Peter O’Sullivan
Funded by an NSF/DARPA VIP grant through the University of Illinois
In collaboration with: I. Petrov, C.-S. Shin and T.-Y. Lee
Materials Research Lab,U. of Illinois, Urbana-Champaign
work done with: Frieder Baumann, George Gilmer & Jacques Dalla Torre, Bell Labs., Lucent Technologies,
Murray Hill, NJ
![Page 2: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/2.jpg)
Background
![Page 3: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/3.jpg)
Multi-level interconnects / metallization for ICs
Tungsten (W) deposited incircular “vias” (plugs) usingCVD
Al lines (Cu electro-deposited in long trenches)
![Page 4: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/4.jpg)
Thin Films for Metalization
Cu TaSiO2
Si
• WF6 + 3H2O W + 3O + 6 HF etches SiO2
during CVD fill of vias
• Cu diffuses into Si short circuit
Must use “barrier” layers of Ti, TiN, Ta, TaN to
to prevent diffusion or etch-damage
2m
![Page 5: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/5.jpg)
Simulation of PVD into trench
Low bottomcoverage
Keyhole formation
Low side-wall coverage
![Page 6: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/6.jpg)
Barrier failure
• Metallic films are polycrystalline
Micro-voids and grain boundaries
Columnar (rough) growth and pores more likely because of oblique incidence & lowsurface diffusivity
10nm
impinging atoms
~ 0.25m
( Monte Carlo simulations by Jacques Dalla Torre & George Gilmer )
![Page 7: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/7.jpg)
Objectives: 1. Predict film coverage across wafer 2. Optimize deposition process
![Page 8: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/8.jpg)
Talk Outline
• Physical model of low pressure PVD:• Feature-scale + reactor-scale (continuum) (atomistic)
• Axisymmetric vias:• Validation + analytic scaling with AR• Different angular distributions• Comparison with experiment (Ti and Ta)
• Summary & conclusions
• General 3D:• Across-wafer non-uniformity
• Modelling issues• Problems, challenges
• Numerics for moving interface:• Level sets
![Page 9: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/9.jpg)
Low pressure PVD—DC magnetron sputtering
Rotating magnetic field “traps” electrons => non-uniform target erosion
sputter target
Ti, Ta, Al, Cu, ....
+V
S N SN
wafer
-V
Ar+
ArP ~ 1 - 20 mTorr
+V
plasma
30 cm
![Page 10: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/10.jpg)
Target
Feature on wafer
Sputter
L Rn
• Need to know: Size and distance of target Target erosion pattern (relative sputter rate across target) Angular distribution of atoms from target, f()
• Must calculate flux at each surface point Target visibility/shadowing.................Ray tracing
• Current assumption / applicability: Sticking coeff. = 1 ..................... Ti, Ta
• More complex surface kinetics under development (reflection, resputtering etc.)
Physical Model of Sputter Deposition
Advance usinglevel sets
![Page 11: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/11.jpg)
• Objectives:
• Compute bottom / sidewall step coverage in high aspect ratio trenches, vias, etc.
• Predict across-wafer non-uniformity of coverage — Simulate feature-scale film profile evolution in 3D
• Study effects of macroscopic reactor variables on coverage — target erosion — angular distribution of different materials — gas pressure
• Incorporate important physical effects as determined from complementary Monte Carlo simulators and experimental data
• Develop efficient algorithms for O(N4—5) ray-tracing codes
Continuum Modeling
![Page 12: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/12.jpg)
Low pressure PVD — Monte Carlo vapor transport code
S N SN
wafer
sputter target
Rotating magnetic field “traps” electrons
-V
Ar+
Ar
Ti, Ta, Al, Cu, ....
P ~ 1 - 20 mTorr
+V
plasma +VBinary collision MC code gives resultant angular distribution, f(), just above wafer
f() then used in level set code
“virtual” target
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Computation of geometric 3D material flux
0
0.2
0.4
0.6
0.8
1
1.2
0 10 20 30 40 50 60 70 80 90
(deg)
3D MD data for Al
Nonlinear curve fit
Equivalent 2D flux
Cos
f(
A
r
discrete surfaceelement on target
discrete surfaceelement on substrate
n
Deposition rate given by:
w() f() cos r 2dA
visibleregion
F3D(substrate) =
w() = weight function from target erosion profile
f(cos((isotropic emission from target)
f(
f(
cosA kk
k ......from molecular dynamics calculations
Can use differentangular distibutions:
......Monte Carlo vapor transport code
![Page 14: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/14.jpg)
Code / model validation
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Via Geometry
• 3D flux• finite target
• 3D line-of-
sight model
• Axisymmetric, but with 3D shadowing
AR = h / w Q = Z / R
2R
h
w
Zwafer
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Step coverage vs. AR : Circular Via
Side-wall coverage
Analytic
Bottom coverage
22
AR41Q1
100)BC(
0t
AR = h / wQ = Z / R
Analytic
Field = 250 Å }
} Field = 1250 Å
bs
t
BC = 100 b / tSWB = 100 s / t
~AR–3
~AR–2
![Page 17: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/17.jpg)
Ti deposition into vias (which angular distribution?)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 20 40 60 80 (deg)
Polar plot:cosine
Subcosine (ellipse) *
Ti at 2mTorr (Varian M2000)MC vapor transport code
dNd—
* suggested by Malaurie & Bessaudou (Thin Solid Films v. 286, 1996)
![Page 18: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/18.jpg)
Deposition
Start End
HRSEM
Ti into vias
cosine
f() from gas transport code
Experimental data
Subcosine (ellipse)
BC vs AR for several angular distributions
• Subcosine shows best agreement subcosine + scattering
![Page 19: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/19.jpg)
Full 3D — Across-wafer non-uniformity
![Page 20: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/20.jpg)
20cm wafer; 30cm target; depth = 0.8m; AR = 2;deposited 0.4m
cut-away side view
cut-away viewfrom below
Complex 3D features
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Off-axis circular via, depth = 0.85m, aspect ratio, AR = 2.0,deposited 0.3m
z (
m)
m
yx
Plan view
x
y
Target
wafer
xoff
z
LHS: Sees less of target
RHS: Shadowed by overhang
LHS
Asymmetry in minimum step coverage ~ 10%
Off-Axis Deposition
![Page 22: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/22.jpg)
More experimental validation — long-throw deposition (similar to ionized PVD)
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0.0
0.2
0.4
0.6
0.8
1.0
1.2
0.0 0.5 1.0 1.5 2.0 2.5 3.0
w()
(cm)
Low pressure Ta PVD (circular via)
• Simulation takes angular distribution from vapor transport code
• Measured target erosion profile modelled by w()
ZT = 10 cm
R 3 cm
P=1mTorr
1.0
0.0
dN —d
20 40 60 80
cosine
![Page 24: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/24.jpg)
Low pressure Ta PVD (circular via)
Cosine (no erosion) Experimental Erosion + scattering
ZT = 10 cm
R 3 cm
P = 1mTorr
![Page 25: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/25.jpg)
Columnar growth / roughness
ZT = 10 cm
R 3 cm
P = 1mTorr
Amplitude = 8 Amplitude = 4
m (400 X 400)
![Page 26: Feature-scale to wafer-scale modelling and simulation of physical vapor deposition Peter O’Sullivan Funded by an NSF/DARPA VIP grant through the University.](https://reader036.fdocuments.us/reader036/viewer/2022070412/5697bf881a28abf838c89229/html5/thumbnails/26.jpg)
Conclusions
• Level set code fast, accurate, predictive model for PVD of refractory metals
• Validated LS code using analytic formulae — Step coverage ~ AR–2 (trench)
— Step coverage ~ AR–3 (via)
• LS code coupled to MC code through f() and “virtual” target
• Full 3D code• Strong non-uniformity in coverage across wafer
• Quantitative comparison w/ experiment
• Ti data: Subcosine distribution improves agreement — Need more data for ang. dist. + vapor transport
• Ta data: Can predict bottom coverage— Need to incorporate more physics to predict closing of feature (breadloafing)