A Fast Imaging Model of Plasmonic Lithography for Line/space Patterns Based on Parameter Sweep

As a new and alternative lithography technology, plasmonic lithography can break through the diffraction limit of traditional lithography by exciting the surface plasmon polaritons (SPPs) to make the evanescent wave at the mask participate in imaging. The photoresist aerial image distribution of different mask patterns can be calculated by establishing an imaging model, which is the basis for understanding and further optimizing imaging. Based on the idea of machine learning and parameter sweep, a fast imaging model for plasmonic lithography is established, including periodic line/space patterns. Compared with the rigorous numerical method, the fast imaging model can greatly improve the calculation speed with high accuracy, which creates conditions for the development of computational lithography technology.