Background: Stochastic printing failures, manifested as random defects in a patterned photoresist image, result from statistical fluctuations in photon flux and resist components and are a key issue confronting extreme ultraviolet (EUV) lithography. Empirical data indicate that photoresist composition and processing influence stochastic printing failure rates.

Aim: To devise a simple and flexible model framework for assessing how changes in photoresist composition and imaging chemistry can be expected to impact the frequency of stochastic printing failures

Approach: A simple physicochemical description based solely on resist component and photon statistics is combined with combinatorial calculations of resist imaging chemistry and Monte Carlo analysis to estimate rates of random printing failures.

Results: This model yields results consistent with experimental observations. The method is applied to predict impacts of resist formulation, composition, and process changes on the rates of stochastic printing failures.

Conclusions: This approach provides rapid assessment of the relative impact of resist materials and process modifications and is useful as a tool to advance EUV photoresist design.