Simulation-based verification for MPC corrected mask designs

Nezih Unal; John Duff; Michael Krueger; Ulrich Hofmann; Dmitri Titko

doi:10.1117/12.2640513

15 September 2022 Simulation-based verification for MPC corrected mask designs

Nezih Unal, John Duff, Michael Krueger, Ulrich Hofmann, Dmitri Titko

Proceedings Volume 12325, Photomask Japan 2022: XXVIII Symposium on Photomask and Next-Generation Lithography Mask Technology; 123250N (2022) https://doi.org/10.1117/12.2640513
Event: Photomask Japan 2022, 2022, Online Only

Abstract

In this work we describe a new simulation-based verification technology that delivers improvement in verification capability for model-based MPC. This technology incorporates the same physics-based process model that is used in the model-based MPC. The input for this simulation-based verification is the target design, the MPC corrected design, and the mask process model parameters that were used for the correction. Verification is accomplished by performing a simulation that applies the process model to the corrected design, thereby predicting the contours on the mask after exposure and processing using the corrected design. This predicted lithographic result, i.e., the predicted design representation on the mask, is then compared to the target design. Differences are analyzed relative to a user-defined tolerance and, if in violation, are subsequently flagged with the option of being classified in user-defined categories. This new verification technology can also be used to analyze critical regions of the design (“hotspots”) defined by the user, enabling a more design-specific analysis. Note that the simulation algorithm is essentially different from the correction algorithm, so that potential algorithmic issues of the MPC correction are captured by the verification.

Citation Download Citation

Nezih Unal, John Duff, Michael Krueger, Ulrich Hofmann, and Dmitri Titko "Simulation-based verification for MPC corrected mask designs", Proc. SPIE 12325, Photomask Japan 2022: XXVIII Symposium on Photomask and Next-Generation Lithography Mask Technology, 123250N (15 September 2022); https://doi.org/10.1117/12.2640513

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KEYWORDS

Photomasks

Calibration

Lithography

Model-based design

Process modeling

Data modeling

Performance modeling

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