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.

Overview Why is CMP important for MEMS? Characterization test mask CMP modeling Results Current work Conclusions 4/14/2004

Why is CMP important to MEMS? Multilevel surface processes Inlaid MEMS materials Multilevel wafer bonding roughness reduction Feature sizes can be 10-100x bigger than for circuits 4/14/2004 C. M. Spadaccini et al. MIT 2002

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 4/14/2004

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

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 4/14/2004

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 4/14/2004

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 4/14/2004

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

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 4/14/2004

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

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 4/14/2004

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

Experimental Parameters 6 inch wafers polished at 10, 20, 30, 40 and 50 secs Strasbaugh 6EC Chemical Mechanical Polisher Down force of 68.95 kPa (10 psi); back pressure of 55.16 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 4/14/2004

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 4/14/2004

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 4/14/2004

Die Topography – 10 sec 3D Mesh Contour Plot 4/14/2004

Die Topography – 20 sec 3D Mesh Contour Plot 4/14/2004

Die Topography – 30 sec 3D Mesh Contour Plot 4/14/2004

Die Topography – 40 sec 3D Mesh Contour Plot 4/14/2004

Die Topography – 50 sec 3D Mesh Contour Plot 4/14/2004

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 4/14/2004

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 4/14/2004

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 4/14/2004

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 4/14/2004

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 4/14/2004

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 4/14/2004