Distribution of defective sub-cluster formation probability for stochastic hotspot prediction

Hiroshi Fukuda

doi:10.1117/12.2655317

28 April 2023 Distribution of defective sub-cluster formation probability for stochastic hotspot prediction

Hiroshi Fukuda

Author Affiliations +

Proceedings Volume 12494, Optical and EUV Nanolithography XXXVI; 1249403 (2023) https://doi.org/10.1117/12.2655317
Event: SPIE Advanced Lithography + Patterning, 2023, San Jose, California, United States

Abstract

In applying EUV lithography to fine-pitch random logic ICs, systematic defects and EPEs take on stochastic nature, and stochastic hot spot predictions are desired. This is challenging, however, since those defects generate probabilistic because of strong correlations. This paper analyzes and predicts stochastic hot spots in arbitrary patterns. We describe the formation of patterns and their anomalies as the probability of molecular sub-cluster generation, based on the 1st principle Monte Carlo simulation and the discrete dev/etch model. The sub-cluster generation well describes correlated pattern/anomaly formation. Correlation is squeezed in the direction normal to pattern edges and spreads as the image slope is relaxed. It is independent of pattern size but dependent on materials, and thus its impact increases with shrinking pattern sizes. Pattern polarity changing probability rises unexpectedly when the reaction in a shallow image slope area enters a certain reaction density range. This is because the inter-molecular correlation range approaches optical image size, and it can be the origin of stochastic hot spots. A deep neural network effectively predicts this phenomenon and infers the probabilities of stochastic EPEs and hot spots.

Conference Presentation

Citation Download Citation

Hiroshi Fukuda "Distribution of defective sub-cluster formation probability for stochastic hotspot prediction", Proc. SPIE 12494, Optical and EUV Nanolithography XXXVI, 1249403 (28 April 2023); https://doi.org/10.1117/12.2655317

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