Optimization from Design Rules, Source and Mask, to Full Chip with a Single Computational Lithography Framework: Level-Set-Methods-based Inverse Lithography Technology (ILT)

摘要

For semiconductor manufacturers moving toward advanced technology nodes -32nm, 22nm and below - lithography presents a great challenge, because it is fundamentally constrained by basic principles of optical physics. Because no major lithography hardware improvements are expected over the next couple years, Computational Lithography has been recognized by the industry as the key technology needed to drive lithographic performance. This implies not only simultaneous co-optimization of all the lithographic enhancement tricks that have been learned over the years, but that they also be pushed to the limit by powerful computational techniques and systems. In this paper a single computational lithography framework for design, mask, and source co-optimization will be explained in non-mathematical language. A number of memory and logic device results at the 32nm node and below are presented to demonstrate the benefits of Level-Set-Method-based ILT in applications covering design rule optimization, SMO, and full-chip correction.