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

嵌段共聚物定向自组装（DSA）光刻技术是一种很有前途的下一代芯片制造技术，有可能生产最小特征尺寸低至7nm或以下的芯片。本项目将进行研究工作，以解决开发基于DSA的芯片设计自动化的复杂计算机软件的挑战，从而使DSA成为未来大规模芯片设计的可行方法，从而以更低的成本生产更复杂的芯片。在整个项目中，广泛的学生和PI交流和访问有望为两所PI的学生教育灌输更广阔的知识视角。大学（斯坦福大学和伊利诺伊大学）。拟议研究的多学科和创新性质将使研究生和本科生在芯片制造领域开展成功的职业生涯。为此目的，该项目相当重视本科生的研究和教育，包括妇女和少数民族。由于DSA技术的高通量和低工艺成本，它已成为下一代互补光刻技术中最有前途的均匀尺寸密集图案（如接触，过孔，切口等）的候选。DSA技术的开发和实现需要过程研究和电子设计自动化（EDA）算法开发之间的深度协作。由于DSA技术对模式的形状和分布非常敏感，因此EDA软件有必要了解DSA过程的模式偏好，以便不允许禁用模式，并使用更多的首选模式。本项目提出了DSA工艺研究与EDA软件开发之间的协同优化流程，并根据协同优化流程，针对DSA技术中最迫切的模式问题，提出了开发支持DSA的EDA软件。

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.