Collaborative platform, tool-kit, and physical models for DfM

Andy Neureuther; Wojtek Poppe; Juliet Holwill; Eric Chin; Lynn Wang; Jae-Seok Yang; Marshal Miller; Dan Ceperley; Chris Clifford; Koji Kikuchi; Jihong Choi; Dave Dornfeld; Paul Friedberg; Costas Spanos; John Hoang; Jane Chang; Jerry Hsu; David Graves; Alan C. F. Wu; Mike Lieberman

doi:10.1117/12.721199

28 March 2007 Collaborative platform, tool-kit, and physical models for DfM

Andy Neureuther, Wojtek Poppe, Juliet Holwill, Eric Chin, Lynn Wang, Jae-Seok Yang, Marshal Miller, Dan Ceperley, Chris Clifford, Koji Kikuchi, Jihong Choi, Dave Dornfeld, Paul Friedberg, Costas Spanos, John Hoang, Jane Chang, Jerry Hsu, David Graves, Alan C. F. Wu, Mike Lieberman

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Proceedings Volume 6521, Design for Manufacturability through Design-Process Integration; 652104 (2007) https://doi.org/10.1117/12.721199
Event: SPIE Advanced Lithography, 2007, San Jose, California, United States

Abstract

Exploratory prototype DfM tools, methodologies and emerging physical process models are described. The examples include new platforms for collaboration on process/device/circuits, visualization and quantification of manufacturing effects at the mask layout level, and advances toward fast-CAD models for lithography, CMP, etch and photomasks. The examples have evolved from research supported over the last several years by DARPA, SRC, Industry and the Sate of California U.C. Discovery Program. DfM tools must enable complexity management with very fast first-cut accurate models across process, device and circuit performance with new modes of collaboration. Collaborations can be promoted by supporting simultaneous views in naturally intuitive parameters for each contributor. An important theme is to shift the view point of the statistical variation in timing and power upstream from gate level CD distributions to a more deterministic set of sources of variations in characterized processes. Many of these nonidealities of manufacturing can be expressed at the mask plane in terms of lateral impact functions to capture effects not included in design rules. Pattern Matching and Perturbation Formulations are shown to be well suited for quantifying these sources of variation.

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Andy Neureuther, Wojtek Poppe, Juliet Holwill, Eric Chin, Lynn Wang, Jae-Seok Yang, Marshal Miller, Dan Ceperley, Chris Clifford, Koji Kikuchi, Jihong Choi, Dave Dornfeld, Paul Friedberg, Costas Spanos, John Hoang, Jane Chang, Jerry Hsu, David Graves, Alan C. F. Wu, and Mike Lieberman "Collaborative platform, tool-kit, and physical models for DfM", Proc. SPIE 6521, Design for Manufacturability through Design-Process Integration, 652104 (28 March 2007); https://doi.org/10.1117/12.721199

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