Review highlights machine learning applications in computational lithography, addressing resolution limitations in semiconductor manufacturing.
As semiconductor manufacturing technology advances, lithography faces increasingly severe challenges from resolution limitations and process variability. Computational lithography has become a critical technology that ensures manufacturability and yield in advanced semiconductor nodes. This paper comprehensively reviews recent advancements in computational lithography, focusing on three core areas: lithography modeling, hotspot detection, and mask optimization. Particular attention is given to innovative applications of machine learning in these domains, along with an analysis of the technical challenges in full-chip optimization. By summarizing the latest technologies and applications, this paper aims to offer valuable insights into the trends and future directions of computational lithography in advanced semiconductor manufacturing.
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Jin et al. (2025) studied this question.
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