Development of an OPC compact model integrating underlayer effects in metal oxide resists

Metal oxide resists (MOR) are emerging as promising next-generation photoresists for extreme ultraviolet (EUV) lithography, offering distinct advantages over chemically amplified resists (CAR). The unique physical and chemical mechanisms involved in MOR photolithography necessitate the development of a new compact model for predicting afterdevelopment inspection (ADI) images in optical proximity correction (OPC). While many research groups have proposed numerical models to simulate the behavior of metal oxide particles and the development process, existing research has predominantly relied on stochastic models. These stochastic approaches, which require ensemble calculations, limit their feasibility for high-throughput OPC modeling. This paper introduces a deterministic approach to MOR modeling. We derive an average MOR cross-linked distribution from hypothetical chemical rate equations, leading to the formulation of a compact model analogous to those used for CAR. Furthermore, we demonstrate that the new model effectively accounts for the underlayer effect, specifically the exponential decrease in the dose-to-size (DtS) required for patterning as the thickness of the MOR underlayer increases.