1. Dummy Feature Placement for Chemical- mechanical Polishing Uniformity in a Shallow Trench Isolation Process Ruiqi Tian 1,2, Xiaoping Tang 1, D. F. Wong 1 1. Dept. of CS, University of Texas at Austin, Austin, TX 78712 2. Motorola Inc., 3501 Ed Bluestein Blvd., Austin, TX 78721 {ruiqi, tang, wong}@cs.utexas.edu

2. Outline  The STI Process  Derivations for CMP in STI  Models used (a review)  Assumptions and results  Dummy Feature Placement  Problem formulation  Iterative Approach  Computational Experience  Conclusion

3. Nitride Deposition The STI Process Etch Oxide Deposition Nitride Strip CMP CMP in STI is a dual-material polish

4. Models: Effective Density from Pad Bending Derivations for CMP in STI

5. Models: Local Pad Compression Derivations for CMP in STI  Polish rates of high and low areas are related by step height due to pressure re-distribution  Initial contact height decreases with increasing density, no consideration for spacing

6. Models: Dual-Material Polish Derivations for CMP in STI  Polish rates are similar to local pad compression  Different blanket polish rate for different materials  Intersection depends on contact height and density

7. Assumptions: Derivations for CMP in STI  Two stages identified for CMP in STI  Overburden oxide removal  Dual-material polish of nitride and oxide Results:

8. Dummy Feature Placement for STI Formulations as NLP Problems Min S.T. Min S.T.  Min-Fill Formulation  Min-Var Formulation

9. Dummy Feature Placement for STI Iterative Approaches

10. Computational Experience

11. Density and Post-CMP Topography Simulations for L3: Original Tiled Density Topography

12. Conclusion  Formulation for CMP in STI  Models for pad bending, pad compression, and dual- material polish are considered  Dummy feature placement as an NLP problem  Solution for dummy feature placement  Iterative approaches proposed  Experimental results are good  Future studies needed  Contact height dependence on feature spacing