modeling of cmp
DESCRIPTION
Modeling of CMP. David Dornfeld CMP researchers: Jihong Choi, Sunghoon Lee, Dr. Hyoungjae Kim, Dr. Dan Echizenya Department of Mechanical Engineering University of California Berkeley CA 94720-1740 http://lma.berkeley.edu. Overview. Background on modeling Review of work to date - PowerPoint PPT PresentationTRANSCRIPT
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Modeling of CMP
David Dornfeld
CMP researchers: Jihong Choi, Sunghoon
Lee, Dr. Hyoungjae Kim, Dr. Dan Echizenya
Department of Mechanical Engineering
University of California
Berkeley CA 94720-1740
http://lma.berkeley.edu
2
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Overview
• Background on modeling
• Review of work to date
• Some new developments• pattern/feature sensitivity• pad design
3
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
New Book on Modeling Chemical Mechanical Planarization (CMP)“Integrated Modeling of Chemical Mechanical Planarization for Sub-Micron IC Fabrication:
From Particle Scale to Feature, Die and Wafer Scales,” J. Luo and D. A. Dornfeld
For information:
www.springeronline.com/east/3-540-22369-X.
Written by researchers at UC-Berkeley, this monograph reviews CMP modeling literature (from Preston to present day efforts) and develops, with a strong emphasis on mechanical elements of CMP, an integrated model of CMP addressing wafer,die and particle scale mechanisms and features. Special emphasis is on abrasive sizes, distributions and resulting material removal rates and uniformity resulting over all scales.
175 Figures and 14 tables
ISBN 3-540-22369-x Springer-Verlag 2004
Or contact: [email protected]
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Chemical Mechanical Planarization
Mechanical Phenomena
Chemical Phenomena
Interfacial and Colloid
Phenomena
CMP Team in FLCCDornfeld, et alDoyle, et alTalbot, et al
5
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Scale Issues in CMP
From E. Hwang, 2004
Scale/sizenm µm mm
Material Removal
Mechanical particle forcesParticle enhanced chemistry
ChemicalReactions
ActiveAbrasives
Pores,Walls
Grooves
Tool mechanics,Load, Speed
critical features dies
Pad
Mechanism
Layoutwafer
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LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
w p :pad rotation
tablepad
slurry feedconditioner
head
w w : wafer rotationOscillation
F : down force
Backing film
Retainerring
Wafer
Wafer Carrier
Pad
Pore Wall
Abrasive particle
CMP Process Schematic
Electro plated diamond conditioner Typical pad
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Bulk Cu CMP Barrier polishing W CMP Oxide CMP Poly-Si CMP
Physical models of material removal mechanism in abrasive scale
Chemical reactions
Bulk Cu slurry Barrier slurry W slurry Oxide slurry Poly-Si slurry
Mechanical material removal mechanism in abrasive scale
Abrasive type, size and concentration
[oxidizer], [complexing agent], [corrosion inhibitor],
pH …
Pad asperity density/shape
Pad mechanical propertiesin abrasive scale
Pad properties in die scale
Slurry supply/ flow patternin wafer scale
Wafer scale pressure NU Models of WIWNU
Models ofWIDNU
Topography
Wafer scale velocity profile
Wafer bending with zone pressures
Better control of WIWNU
Reducing ‘Fang’
Small dishing & erosion
Ultra low-k integration
Smaller WIDNU
Reducing slurry usageUniform pad performance
thru it’s lifetimeLonger pad life time
Reducing scratch defects
Better planarization efficiency
E-CMPPad groove
Pad design
Fabrication
Test
Fabrication technique
Slurry supply/ flow pattern in die scale
Cu CMP
model
design goal
Pad development
PatternMIT model
Dornfeld modelDoyle
An overview of CMP research in FLCC
Talbot
8
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
The 4-component system
• Hypotheses: – all polishing processes can be described as a 4 component
system;– Understanding the components and their interactions (pair-wise,
triplets, etc) provides a structure to catalog our knowledge (and ignorance)
Lap (rigid)
Workpiece LapGranuleCarrier fluid
Platen Pad }
“Granule”?Deliberately sought a word that covers the range of particles used without implying anything about size, hardness, or removal mechanism: m to nm size range; from hard (diamond) to soft (rouge);
Source: 86. Evans, J., Paul, E., Dornfeld, D., Lucca, D., Byrne, G., Tricard, M., Klocke, F., Dambon, O., and Mullany, B.,“Material Removal Mechanisms in Lapping and Polishing,” STC “G” Keynote, CIRP Annals, 52, 2, 2003.
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LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Six possible pair-wise interactions
• Fluid-workpiece• Workpiece-pad• Workpiece-granule• Granule-pad• pad-fluid• Fluid-granule
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LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Three-way interactions (triplets)
• Workpiece-fluid-granule• Workpiece-fluid-pad• Workpiece-granule-pad• Fluid-pad-granule
11
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Stribeck Curve and Characteristics of slurry film thickness
Fric
t ion
coe
f fic
ien t
Film
thi
ckne
ss
Pressure
VelocityViscosity Hersey number(= )
Hydrodynamic
lubrication
Elasto-
hydrodynamic
lubrication
Boundary
lubrication
Direct
contact
Semi-direct
contact
Hydroplane
sliding
Stribeck curve
Polishing pad
Wafer Slurry
Direct contact
Semi-direct contact
Hydroplane sliding
12
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Gap effects on “mechanics”
Pad-based removal
Slurry-based removal
‘Small’ gap
‘Big’ gap
Silicon wafer
Polishing pad
Abrasive particle
Delaminated by brushing
Eroded surface by chemical reaction--- softening
Silicon wafer
Polishing pad
Abrasive particles
13
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Idealized CMP
Silicon wafer
Polishing pad
Abrasive particle
‘Softened’ surface by chemical reaction
Pad asperity
Mechanical Aspects of the Material Removal Mechanism in Chemical Mechanical Polishing (CMP)
14
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Interactions between Input Variables
Four Interactions: Wafer-Pad Interaction; Pad-Abrasive Interaction;
Wafer-Slurry Chemical Interaction; Wafer-Abrasive Interaction
Polishing pad
Abrasive particles in Fluid (All inactive)
Pad asperity
Active abrasives on Contact area
Vol Chemically Influenced Wafer Surface
Wafer
Abrasive particles on Contact area with number N
Source: J. Luo and D. Dornfeld, IEEE Trans: Semiconductor Manufacturing, 2001
Velocity V
15
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Framework Connecting Input Parameters with Material Removal Rate
Slurry Abrasive WeightConcentration C Fraction of Active
Abrasive: 1-((g-Xavg)/ ) where g is the minimum size of active abrasives
Force F & Velocity
Wafer Hardness Hw / Slurry Chemicals & Wafer Materials
Vol
Active Abrasive Size Xavg-a
Basic Equation of Material Removal: MRR= N Vol
Average Abrasive Size Xavg
Proportion of Active Abrasives
N
Pad Topography& Pad Material
Abrasive SizeDistribution
Down Pressure P0
gXavg
Fraction of Active Abrasives X avg-
a
16
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Ke1 (K1=84148,
K2= 0.137)
Experimental Verification of Pressure Dependence of Material Removal Rate
(MRR)
Advantage over Preston’s Eq. MRR= KePV+ MRR0:
What input variables and how they influence Ke is predicable
MRR= N Vol= K1 {1-
(1-K2P01/3)}P0
1/2.
Ke2(K1=8989, K2= 0.3698)
SiO2 CMP Experimental Data from Zhao and Shi, Proceedings of VMIC, 1999
17
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Abrasive Size Distribution Dependence of MRR:
Particle Size Distribution [1]Five Different Kinds of Abrasive (Alumina) Size Distributions for Tungsten CMP
1. Bielmann et. al., Electrochem. Letter, 1999
Abrasive Size X (Log Scale)
(%
) F
req
uen
cy
18
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
00.20.4
0.60.8
11.21.4
1.61.8
2
0 0.05 0.1 0.15 0.2 0.25 0.3
Standard Deviation (10-6m)
Nor
mal
ized
Mat
eria
l Rem
oval
Rat
e
Xavg= 0.29umXavg=0.38umXavg=0.60umXavg=0.88umXavg=2um
Relationship between Standard Deviation and MRR Based on Model Prediction
Std dev influenced
Size influenced
19
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Pattern-Density Dependency Model
InterLevel Dielectric Case (single material)
K
K/densityUp Area
0Down Area
Time
pad
oxide
pad
oxide
Same Pattern Density
Different Orientations
Source: MIT
MRR
20
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Framework of a CMP Topography Evolution Model
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Dishing and Erosion in Copper Damascene Process
Via
Trench
SiO2
SiN
(a) (b)
(c) (d)
Fabrication steps in dual damascene process (a) deposition of SiN, SiO2 and etching trenches and vias in
SiO2 (b) deposition of barrier layer (c) copper fill (d) CMP
and deposition of SiN (courtesy of Serdar Aksu)
22
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Definition of Feature-Scale Topography
(a) (b)
(a) Feature scale topography before dielectric material is exposed and (b) feature scale topography after dielectric
material is exposed
Wcu
S
H
Wox
Copper Dishing d = S
Oxide Erosion e
H= Hox
Hox=
Hox0
Hcu Copper Thinning
23
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Kd
Kf
(a) (b) (c) (d)
E E E1
1
E2 2
E
Models of Polishing Pad
Linear Elastic and Linear ViscoElastic Models
Separated Models of Pad Bulk and Asperities
24
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Dishing d
3
Erosion e
2
1
Df
S1=Df1
S=S0
H=Hcu0+Hox0 H= Hstage1
Hcu0
Hox0
Three Stages of Wafer-Pad Contact
Only upper part of step is in contact
Both upper and bottom parts of step is in contact
Two different materials are removed simultaneously
25
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
0 20 40 60 80 100 120 140 160 180 2000
50
100
150
200
250
300
350
400
450
500
Polishing Time t (second)
Ste
p H
eigh
t S (n
m)
PDi= 0.1PDi= 0.2PDi= 0.3PDi= 0.4PDi= 0.5PDi= 0.6PDi= 0.7PDi= 0.8PDi= 0.9
0 20 40 60 80 100 120 140 160 180 2000
50
100
150
200
250
300
350
400
450
500
Polishing Time t (second)
Ste
p H
eigh
t S
(nm
)
PDi= 0.1PDi= 0.2PDi= 0.3PDi= 0.4PDi= 0.5PDi= 0.6PDi= 0.7PDi= 0.8PDi= 0.9
Simulation Results of Step Height Evolution for Different Pattern
Density
Linear Elastic Pad Linear Viscoelastic Pad
Ste
p h
eig
ht
S (
nm
)
Ste
p h
eig
ht
S (
nm
)
Planarization time (sec) Planarization time (sec)
Wcu = 100 microns
26
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Copper Dishing as a Function of Pattern Density
using commercial pads
27
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Copper Dishing as a Function of Selectivity
28
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Effect of Pattern Density - Planarization Length (PL)
ILD
Metal lines
Planarization Length
High-density region
Low-density region
Global step
29
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Effective pattern density
a=320um
a=640um
a=1280um
< Effective density map >
< Test pattern >
< Post CMP film thickness prediction at
die-scale >
Modeling of pattern density effects in CMP
Planarization length (window size) effect on “Up area”
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Initial pressure distribution
Topography evolution
New pressure distribution
Contact wear model
Contact wear model
MRR model
Iteration
with time step
Die scale modeling of topography evolution during CMP
31
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
PAD
Z(x,y)
Reference height (z=0)
Z_pad
Z(x,y)
Z_padz
dz
padZyxZ
zyxZzPDFdzzPDFdensityasperityKpyxF_),(
0
)),(())()(()_(),(
Feature level interaction between pad asperities and pattern topography
die
dxdyyxFtentF ),(_
F_tent > F_die ? F_tent < F_die ?
++Z_pad --Z_pad
No
Yes
No
Yes
Z_pad
32
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
k1
k2
221
21k
kk
kkKpad
Chip level interaction between pad and pattern topography
rPL
w40um
40umPattern
40um x 40um cell
ji
ji
E jiw
jiPDjiwPD
,,
),(
),(),(
dPL
r
E
qrrw
2
0
22
22
sin1)1(4
)(
MIT model : approximation of contact wear model
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
100%
50%
33%
20%
50%33%20%
t=0 sec t=10 sec t=20 sec
t=30 sec t=40 sec t=50 sec
t=60 sec t=70 sec t=80 sec
Simulation result
34
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Pattern orientation effect on on copper dishingSiO2
Ti Cu
Si
Kinetic analysis of sliding direction during process time
pad rpm < wafer rpm
pad rpm = wafer rpm
35
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
• Ra = 12.5µm
• Rz = 96.7µm
• Pore diameter : 30~50 µm
• Peak to Peak : 200~300µm
100µm
45µm
-45µm100µm 300µm 500µm
(SEM, x150)
200~300µm
(White light Interferometer, x200)
Pad Characterization
36
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Asperity: Real contact area10~50 µm
Pores40~60µm
Simplified Pad Model
Peak to Peak200~300 µm
1. Reaction Region (10~15 µm)
2. Transition Region
3. Reservoir Region
Pad modeling
37
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
3 Dimensional analysisReaction region
Reservoir region
Transition region
38
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
2D and 3D image of reaction region
• Contact area : 10-50µm
• Ratio of real contact area : 10-15%
• Spherical or conical shape edge
• Stress concentration when compressed
2 dimensional image (w/o pressure) 3 dimensional image (w/o pressure)
39
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
10 – 50 µm
Reaction region (asperity)
Reaction region – ILD CMP
• Over polishing on recess area
• Smoothing, not planarization
Defects of a conventional pad
50 µm
Large asperity
wafer
ILDRounding
10 µm
Small asperity
wafer
ILD
Over polishing
40
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Reaction region – Cu CMP
wafer
Pressure
Position
Stress concentration
ErosionDishingFang
Cu-CMP defects (due to stress concentration in conventional pad)
Pad asperity
Nominal pressure
Avg. contact pressure
wafer
wafer
41
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
New In 3minutes
In 5minutes In 7minutes
Pad degradation
42
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Design rules for a pad
Macro scale Micro scale Nano scale
Stacked layer
(Hard/soft)
Slurry channel
Constant contact area
(width:10-50um)
The ratio of real contact area
(13-17%)
Conditioning-less CMP
High slurry efficiency
Compatible features to abrasive
Constant re-generation of nano
scale surface roughness
Design rules for a pad
43
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Soft Layer(i.e. low stiffness)
Hard Layer(i.e. high stiffness)
Channel Nano scale features
A pad design based on the rules
50-70µm
50-200µm
44
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Wafer
Pad
Wafer
Pad
• Conditioning-less process
• High planarity & good uniformity in ILD CMP
• Without stress concentration
• Less defects in Metal CMP
Advantages
ILD CMP
Cu CMP
Expectations
45
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Design of new pads Type 2 – With slurry guidance Type 1 – Without slurry guidance
50µm
Slurry flow direction20µm
46
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Type 1 Type 2
• Area : 4.294^-10 m2
• Flow rate : 3.24^-10 kg/sec• Area : 4.3^-10 m2
• Flow rate : 3.93^-11 kg/sec
8 times more flow rateOn contact area
Simulation result
47
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Pad fabrication
1. Master 2. Silicone Rubber Casting
3. Silicone Rubber Mold
4. Hard Layer Casting
5. Soft Layer Casting
6. Demolding
New pad
48
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Performance of a new pad – Planarity in ILD CMP
ILD pattern (MIT mask Version 1.0)
50%50um/50um
20%20um/80um
Si wafer
SiO2
0.77µm
1.7µm
PadIC1000/SUBA400 New pad
60rpm
Wafer
3inch wafer (12-100% density,1.7µm SiO2)
30rpm
SlurryD-7000 (Cabot Co.)
100ml/min
Pressure 1.6psi 1.6psi 2.7psi
Polishing machine
Experiment condition
49
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
Density 20% - under same pressure:1.6psi
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1000 1100 1200 1300 1400 1500
Position(um)
Rel
ativ
e S
tep
hei
gh
t (u
m)
New In 3min In 7min In 12min In 17min-0.4
-0.2
0
0.2
0.4
0.6
0.8
1000 1100 1200 1300 1400 1500
Position(um)
Rel
ativ
e S
tep
hei
gh
t(u
m)
New In 3min In 15min In 20min In 40min
• Time : 17minutes
• Over Polishing : 2200Å
• Time : 40minutes
• Over Polishing : 400Å
Good planarityHigh removal rate
IC1000/SUBA400 (1.6psi) New pad (1.6psi)
50
LMA
Laboratory for Manufacturing Automation, 2005
University of California at Berkeley
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1000 1100 1200 1300 1400 1500
Position(um)
Rel
ativ
e S
tep
hei
gh
t (u
m)
New In 3min In 7min In 12min In 17min-0.4
-0.2
0
0.2
0.4
0.6
0.8
1000 1100 1200 1300 1400 1500
Position(um)
Rel
ativ
e S
tep
Hei
gh
t(u
m)
New In 10min In 20min
IC1000/SUBA400 (1.6psi) New pad (2.7psi)
• Time : 17minutes
• Over Polishing : 2200Å
• Time : 20minutes
• Over Polishing : 800Å
Good planarity & removal rate
Density 20% - under different pressure:1.6psi &2.7psi