MPC model sensitivity analysis: model ambit vs. correction runtime

Alex Zepka; John Valadez; Parikshit Kulkarni; Kohei Yanagisawa; Kota Kobayashi; Kiyoshi Kageyama

doi:10.1117/12.2535707

27 June 2019 MPC model sensitivity analysis: model ambit vs. correction runtime

Alex Zepka, John Valadez, Parikshit Kulkarni, Kohei Yanagisawa, Kota Kobayashi, Kiyoshi Kageyama

Author Affiliations +

Proceedings Volume 11178, Photomask Japan 2019: XXVI Symposium on Photomask and Next-Generation Lithography Mask Technology; 1117808 (2019) https://doi.org/10.1117/12.2535707
Event: Photomask Japan 2019, 2019, Yokohama, Japan

Abstract

Mask Process Correction (MPC) is becoming increasingly relevant as the industry moves toward more challenging technology nodes. Because running MPC on large layouts can be extremely resource intensive, it is important to strike a balance between the quality of the correction and the total turnaround time (TAT). This paper describes the results of applying a geometry-based MPC solution to a mask lithography process created at Toppan where the model is calibrated from AEI metrology data of patterns that accounts for beam blur, etch, and proximity effects present in the etched mask up to ~1 um. In this solution, the model calibration can result in different but equivalent predictors, i.e., the model parameters can differ while the overall error residuals (model RMS) can be nearly identical. The following sections probe a possible trade-off between correction quality and speed by testing how an MPC software based on edge movement behaves as the effective range of an enhanced multi-Gaussian mask model template is constrained.

Citation Download Citation

Alex Zepka, John Valadez, Parikshit Kulkarni, Kohei Yanagisawa, Kota Kobayashi, and Kiyoshi Kageyama "MPC model sensitivity analysis: model ambit vs. correction runtime", Proc. SPIE 11178, Photomask Japan 2019: XXVI Symposium on Photomask and Next-Generation Lithography Mask Technology, 1117808 (27 June 2019); https://doi.org/10.1117/12.2535707

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