Assessment of contour modeling readiness for curvilinear masks

Raewon Yi; Sukho Lee; Jin Choi; Eok Bong Kim; Sanghee Lee

doi:10.1117/12.2641692

1 December 2022 Assessment of contour modeling readiness for curvilinear masks

Raewon Yi, Sukho Lee, Jin Choi, Eok Bong Kim, Sanghee Lee

Proceedings Volume 12293, Photomask Technology 2022; 1229308 (2022) https://doi.org/10.1117/12.2641692
Event: SPIE Photomask Technology + EUV Lithography, 2022, Monterey, California, United States

Abstract

Curvilinear pattern has been introduced as one of solutions for complex and challenging next generation lithography. However mask process correction (MPC) has been developed originally for Manhattan pattern. MPC now is using only orthogonal CD measurement information (so-called conventional modeling) which is not sufficient to represent all information needed to curvilinear pattern. In this reason a new solution for MPC is required for curvilinear pattern. Contour modeling is one of the known modeling techniques, which uses information of many vertices along pattern contour instead of orthogonal CD values. However contour modeling has not been evaluated yet in mass production level. As an evaluating procedure, we introduce a quality assurance (QA) method using virtual SEM contour. By adopting this QA method, we can analyze errors only from modeling itself separated from process induced errors. Moreover, aspect of error budget can be estimated by adding various errors on purpose. In this paper, we present the QA results of contour modeling and the comparison to the conventional modeling. Some discussion and future works will be followed.

Citation Download Citation

Raewon Yi, Sukho Lee, Jin Choi, Eok Bong Kim, and Sanghee Lee "Assessment of contour modeling readiness for curvilinear masks", Proc. SPIE 12293, Photomask Technology 2022, 1229308 (1 December 2022); https://doi.org/10.1117/12.2641692

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KEYWORDS

Scanning electron microscopy

Data modeling

Photomasks

Process modeling

Error analysis

Image processing

Etching

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