1. Characterization and Modeling of Chemical-Mechanical Polishing for Polysilicon Microstructures
Brian Tang and Duane Boning
MIT Microsystems Technology Laboratories
Cambridge, MA 02139
Good afternoon, ladies and gentlemen.
My name is Xiaolin, currently a graduate student at MIT and my advisor is Professor Duane Boning.
Today I am going to talk about the relationship we found between Patterned Wafer Topography evolution and the STI CMP endpoint signals.
This work is done with collaboration with U. of Arizona, and Sandia National Lab.

2. Overview Why is CMP important for MEMS? Characterization test mask
CMP modeling
Results
Current work
Conclusions
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3. Why is CMP important to MEMS?
Multilevel surface processes
Inlaid MEMS materials
Multilevel wafer bonding roughness reduction
Feature sizes can be x bigger than for circuits
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C. M. Spadaccini et al. MIT 2002

4. Characterization Test Mask
Test mask incorporates MEMS features
Large feature dimensions, from 50 to 500 microns
Large open field regions
Die repeated across 6 inch wafer
Film stack with polysilicon structural material being polished 0% 0% 0% 0%
0.5 μm 0%
500/500
50%
50/50
50% 0%
1.0 μm
20mm 0%
150/150
50%
300/300
50% 0%
0.5 μm 0% 0% 0% 0%
5mm
Silicon
Polysilicon
Oxide
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5. Overview Why is CMP important for MEMS? Characterization test mask
CMP modeling
Effective pattern density and planarization length
Pattern density step height model
Updated pattern density step height model
Results
Current work
Conclusions
4/14/2004

6. Pattern Density Preston’s equation for blanket wafer polishing:
Removal Rate = KpPV
P is pressure, V is relative velocity, and Kp empirical
A patterned wafer has pattern density:
ρ = Areaup/Areatotal
For an infinitely rigid pad, force contacts “UP” parts only:
Removal Rate = KpPV(Areatotal/Areaup) = KpPV/ ρ
160 μm
2.56 mm
80 μm
up area
ρcell = 25%
ρblock = 25%
80 μm
160 μm
2.56 mm
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7. Effective Pattern Density
Real pads are not infinitely rigid
Filter function smoothes the pattern density around a point to get the location’s effective pattern density
Smoothing represents a real pad bending across features
Test Die
Effective Pattern Density
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8. Filter Size Filter size is defined by planarization length.
Planarization length (PL) is the distance we average over to get the effective pattern density
Removal rate depends on the smoothed effective pattern density, not local pattern density
Filter shape is Gaussian, which approximates how a pad deforms over a raised feature
Use a spatial convolution between local pattern density and filter function to create the effective pattern density
Planarization Length
Local Pattern Density
Filter Function
Effective Pattern Density
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9. Overview Why is CMP important for MEMS? Characterization test mask
CMP modeling
Effective density and planarization length
Density step height model
Updated density step height model
Results
Current work
Conclusions
4/14/2004

10. Density/Step Height Model
Phase I: Large step height
Pad held up by large step height
Down areas are not polished.
Phase II: Small step height
At and below contact height, pad can make contact with down areas
Both up and down areas are polished.
When step height is removed, the wafer is polished at the blanket rate RR
Large Step Height
Small Step Height
CMP Pad
Up Area
K/ K
Phase II
Phase I
Down Area hc
Phase I
Phase II
Steady State: K everywhere
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11. Overview Why is CMP important for MEMS? Characterization test mask
CMP modeling
Effective density and planarization length
Density step height model
Updated density step height model
Results
Current work
Conclusions
4/14/2004

12. Updated Density Step Height Model
Modification: continuous RR vs. step height relationship (Xie et al., MRS 2003)
Eliminate discontinuity between distinct regimes
Adapted from contact wear pressure dependence on step height
Up Area
Down Area
Old step height model
Updated step height model
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13. Overview Why is CMP important for MEMS? Characterization test mask
CMP modeling
Effective density and planarization length
Density step height model
Updated density step height model
Results
Current work
Conclusions
4/14/2004

14. Experimental Parameters
6 inch wafers polished at 10, 20, 30, 40 and 50 secs
Strasbaugh 6EC Chemical Mechanical Polisher
Down force of kPa (10 psi); back pressure of kPa (8 psi)
Table speed of 28 rpm; quill speed set to 20 rpm
Semisphere SS-25 silica slurry introduced at a rate of 200 mL/min
Polysilicon optical film thickness measurements with a Tencor UV1280
Line scan
Field points 1 2 3 4 5 6 7 9 10 8 15 11 14 16 13 12 17 18 19 20 21 22 23 24 26 25 28 27
500/500
1-5
6-16
17-22
23-28
50/50
150/150
300/300
500/500 1 2 3 4 5 6 7 9 10 8 15 11 14 16 13 12 17 19 20 21 22 23 24 25 27 26 28 18 29 30 31 32 33 34 36 37 38 39 40 41
1-6
7-17
18-24
25-29
50/50
150/150
300/300 35
Up measurement points
Down measurement points
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15. Results Up area polishing
Measurement of poly film thickness remaining at each time slice
Large features have film thickness larger than model prediction
Up areas have less pressure than expected. 1 2 3 4 5 6 7 9 10 8 15 11 14 16 13 12 17 18 19 20 21 22 23 24 26 25 28 27
500/500
1-5
6-16
17-22
23-28
50/50
150/150
300/300
10 sec
+ model
o actual
20 sec
30 sec
40 sec
50 sec
500/500
50/50
150/150
300/300
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16. Results – cont. Down area polishing
Measurement of poly film thickness remaining at each time slice
Larger feature size down areas polish more than smaller feature size down areas
More pressure put on down area big features than small features
500/500 1 2 3 4 5 6 7 9 10 8 15 11 14 16 13 12 17 19 20 21 22 23 24 25 27 26 28 18 29 30 31 32 33 34 36 37 38 39 40 41
1-6
7-17
18-24
25-29
50/50
150/150
300/300 35
10 sec
20 sec
30 sec
40 sec
50 sec
+ model
o actual
500/500
50/50
150/150
300/300
field
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17. Die Topography – 10 sec
3D Mesh
Contour Plot
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18. Die Topography – 20 sec
3D Mesh
Contour Plot
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19. Die Topography – 30 sec
3D Mesh
Contour Plot
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20. Die Topography – 40 sec
3D Mesh
Contour Plot
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21. Die Topography – 50 sec
3D Mesh
Contour Plot
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22. Model Results & Limitations
Planarization length (PL) = 3.2 mm
Total RMS error of 255 Å
All arrays have 50% local pattern density, but polish differently
Limitations in the model
Model captures general trend but has trouble with 500 μm and 50 μm feature size line trace
PL handles these big features poorly
As feature size increases, PL no longer averages together the density of a large number of features
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23. Model Limitations
Model captures general trend but has trouble with 500 μm and 50 μm feature size line trace
PL handles these big features poorly
As feature size increases, PL no longer averages together the density of a large number of features 1 2 3 4 5 6 7 9 10 8 15 11 14 16 13 12 17 18 19 20 21 22 23 24 26 25 28 27
500/500
1-5
6-16
17-22
23-28
50/50
150/150
300/300
10 sec
20 sec
30 sec
40 sec
50 sec
+ model
o actual
500/500
50/50
150/150
300/300
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24. Model Limitations – cont.
PL approximation averages contact pressures over millimeter scale
Averaging removes dependence on specific configuration
Both regions have same pattern density, but different configurations
Different configuration on scale of pad (up areas grouped into large features) will polish differently
Pad can bend and contact down areas more on right than on left
2.56 mm
2.56 mm
ρblock = 25%
2.56 mm
2.56 mm
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25. Current Work Explore feature size dependence
Exploring alternative models (i.e. integrated contact wear and density step-height)
Examine realistic MEMS structures
Explore overburden polishing for inlaid materials
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26. Conclusions
Pattern density/step-height CMP model captures primary trends in MEMS polishing
MEMS designs have additional characteristics that need to be modeled
pattern dependencies reliant on not only density but configuration of the density
Problem occurs when density configured into large blocks (e.g. big features)
As feature sizes approach planarization length, model no longer accurately predicts polishing
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27. Acknowledgements
The Singapore-MIT Alliance for providing financial support for our research
X. Xie, H. Cai, T. Park, and all the members of the Statistical Metrology Group
The Staff of the MIT Microsystems Technologies Laboratories
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