ruiqi tian 1,2 , xiaoping tang 1 , d. f. wong 1
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
Dummy Feature Placement for Chemical-mechanical Polishing Uniformity in a Shallow Trench Isolation Process
Ruiqi Tian1,2, Xiaoping Tang1, D. F. Wong1
1. Dept. of CS, University of Texas at Austin, Austin, TX 787122. Motorola Inc., 3501 Ed Bluestein Blvd., Austin, TX 78721
{ruiqi, tang, wong}@cs.utexas.edu
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
Nitride Deposition
The STI Process
Etch
Oxide Deposition
Nitride Strip
CMP
CMP in STI is a dual-material polish
Models: Effective Density from Pad Bending
Derivations for CMP in STI
Li
Lii
Lj
Ljj
jjiifjidji' '
)','()','(),(
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
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
Assumptions:
Derivations for CMP in STI
Two stages identified for CMP in STI Overburden oxide removal Dual-material polish of nitride and oxide
Results:
)',',,(0),( jijiHtHd xx
Dummy Feature Placement for STI
jijixjixjijijijit
jijiHjijiHjijitjiHjijitjiH
a
M
ni
ox
,),,(),(0',',,),',',,(0
',',,,)',',,(,,0)),(),,((,,0)),(),,((
2
1
MH
Formulations as NLP Problems
Min
S.T.ji
jix,
),(Min
S.T.
jijixjixjijijijitjijijijiHjijitjiHjijitjiH
a
ni
ox
,),,(),(0',',,),',',,(0',',,,)',',,(,,0)),(),,((,,0)),(),,((
2
1
Min-Fill Formulation Min-Var Formulation
Dummy Feature Placement for STI
Iterative Approaches
Computational Experience
Computational ExperienceDensity and Post-CMP Topography Simulations for L3:
Original Tiled
Density
Topography
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