Model-based DRC for design and process integration

Chi-Yuan Hung; Andrew M. Jost; Qingwei Liu

doi:10.1117/12.631505

8 November 2005 Model-based DRC for design and process integration

Chi-Yuan Hung, Andrew M. Jost, Qingwei Liu

Proceedings Volume 5992, 25th Annual BACUS Symposium on Photomask Technology; 59923M (2005) https://doi.org/10.1117/12.631505
Event: SPIE Photomask Technology, 2005, Monterey, California, United States

Abstract

Accurately and efficiently verifying the device layout is a crucial step in semiconductor manufacturing. A single missed design violation carries the potential for a disastrous and avoidable yield loss. Typically, design rule checking (DRC) is accomplished by validating drawn layout geometries against pre-determined rules, the specifics of which are derived empirically or from lithographic first principles. These checks are intrinsically rigid, and, taken together, a set of DRC rules only approximate the manufacturable design space in the crudest manner. Process-specific effects are entirely neglected. But for leading-edge technologies, process variations significantly impact the manufacturability of a design, so traditional DRC becomes increasingly difficult to implement, or worse, speciously inaccurate. Fortunately, the rise of Optical Proximity Correction (OPC) has given manufacturers a means to accurately model optical and process effects, and, therefore, an opportunity to introduce this information into the layout validation flow. We demonstrate an enhanced, full-chip DRC technique, which utilizes process models to locate marginal or bad design features and classify them according to severity.

Citation Download Citation

Chi-Yuan Hung, Andrew M. Jost, and Qingwei Liu "Model-based DRC for design and process integration", Proc. SPIE 5992, 25th Annual BACUS Symposium on Photomask Technology, 59923M (8 November 2005); https://doi.org/10.1117/12.631505

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available