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Pattern Dependent Modeling for CMP Optimization and Control

Published online by Cambridge University Press:  10 February 2011

D. Boning,
B. Lee,
C. Oji,
D. Ouma,
T. Park,
T. Smith and
T. Tugbawa
D. Boning
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
B. Lee
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
C. Oji
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
D. Ouma
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
T. Park
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
T. Smith
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
T. Tugbawa
Affiliation:
Massachusetts Institute of Technology, Microsystems Technology Laboratories, EECS, Room 39–567, Cambridge, MA 02139
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Abstract

In previous work, we have formalized the notions of “planarization length” and “planarization response function” as key parameters that characterize a given CMP consumable set and process. Once extracted through experiments using carefully designed characterization mask sets, these parameters can be used to predict polish performance in CMP for arbitrary product layouts. The methodology has proven effective at predicting oxide interlevel dielectric planarization results.

In this work, we discuss extensions of layout pattern dependent CMP modeling. These improvements include integrated up and down area polish modeling; this is needed to account for both density dependent effects, and step height limits or step height perturbations on the density model. Second, we discuss applications of the model to process optimization, process control (e.g. feedback compensation of equipment drifts), and shallow trench isolation (STI) polish. Third, we propose a framework for the modeling of pattern dependent effects in copper CMP. The framework includes “removal rate diagrams” which concisely capture dishing height and step height dependencies in dual material polish processes.

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References

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