In applying EUV lithography to 5-nm technology node and beyond, stochastic defect issues have arisen, seriously affecting manufacturing yield and/or limiting applicable minimum device sizes. To develop materials/processes with suppressing such defects and to bring them under control, we discuss a probabilistic model for stochastic defect generation processes. To deal with extremely low probability (typically 10^-4~10-¹²⁾ while being based on physics and chemistry of resist exposure, our model combines Monte Carlo method with probabilistic models. We focus on two mechanisms as causes of stochastic defects, (A) accidental connections of photon shot noises enhanced by densely localized secondary electron (SE) generation and (B) cascading SE generations along photoelectron trajectories. Our analyses show significantly higher defect probabilities in EUV than in ArF and their strong dependences on patterns sizes and process conditions, which is attributed to a wider spatial inhomogeneity in SE generation. Material parameter optimization by combining the model with the multi-objective genetic algorithm shows a trilemma among defect probability, target size, and required exposure dosage to size. It also shows necessity of scaling material parameters with shrinking target design rules. Guidelines for defect suppression are also suggested.

Date Published: 26 March 2019
PDF: 12 pages
Proc. SPIE 10957, Extreme Ultraviolet (EUV) Lithography X, 109570G (26 March 2019); doi: 10.1117/12.2514018

Published in SPIE Proceedings Vol. 10957:
Extreme Ultraviolet (EUV) Lithography X
Kenneth A. Goldberg, Editor(s)