SHF: Small: Collaborative Research: Design Automation for Block Copolymer Directed Self-Assembly (DSA) Lithography Patterning

Stanford University, Stanford CA

Investigators

Abstract

Block-copolymer Directed Self-Assembly (DSA) lithography is a promising next-generation chip manufacturing technology which has the potential to produce chips with minimum feature size down to 7nm or below. This project will undertake research efforts to address the challenges in developing complex computer software for the design automation of DSA-based chips so as to enable DSA as a viable approach for large-scale chip design of the future, and thus more complex chips may be produced at a much lower cost. Extensive student and PI exchange and visits throughout the program is expected to instill a broader intellectual perspective on the student education at both PIs? universities (Stanford and University of Illinois). The multidisciplinary and innovative nature of the proposed research will position the graduate and undergraduate students involved to launch successful careers in the area of chip manufacturing. To this end, the project has substantial emphasis on undergraduate research and education, including women and minorities. Due to the high throughput and low process cost of the DSA technology, it has become the most promising candidate patterning the uniform sized dense patterns (e.g. contacts, vias, cuts, etc.) for the next generation complementary lithography technology. The development and implementation of DSA technology require deep collaboration between process research and Electronic Design Automation (EDA) algorithm development. Since the DSA technology is very sensitive to the shapes and distributions of patterns, it is necessary for the EDA software to understand the patterning preferences of the DSA process, such that forbidden patterns will be disallowed and more preferred patterns will be used. The project proposes a co-optimization flow between DSA process research and EDA software development, and following the co-optimization flow, it proposes to develop DSA aware EDA software targeting the most urgent patterning problems for the DSA technology.