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Related Experiment Video

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Fast extreme ultraviolet lithography mask near-field calculation method based on machine learning.

Jiaxin Lin, Lisong Dong, Taian Fan

    Applied Optics
    |April 1, 2020
    PubMed
    Summary

    This study introduces a fast machine learning method for calculating near fields in extreme ultraviolet (EUV) lithography masks. The approach significantly enhances computational efficiency and accuracy for 3D mask simulations.

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    Area of Science:

    • Computational physics
    • Applied electromagnetics
    • Semiconductor manufacturing technology

    Background:

    • Accurate near-field calculation is critical for simulating extreme ultraviolet (EUV) lithography masks.
    • Traditional methods face challenges in computational efficiency for complex 3D mask structures.

    Purpose of the Study:

    • To develop a computationally efficient and accurate method for 3D mask near-field calculations in EUV lithography.
    • To leverage machine learning for accelerating complex electromagnetic simulations.

    Main Methods:

    • Training rigorous mask near-field libraries using representative mask samples and source points.
    • Segmenting masks into patches and calculating local near fields via non-parametric regression and data fusion.
    • Synthesizing the full near field using image stitching and data fitting techniques.

    Main Results:

    • The proposed machine learning method achieves higher accuracy than traditional domain decomposition methods.
    • Computational efficiency is improved by up to an order of magnitude compared to rigorous electromagnetic field simulators.
    • Demonstrated feasibility of fast and accurate 3D mask near-field calculations for EUV lithography.

    Conclusions:

    • Machine learning offers a powerful approach to accelerate near-field calculations in EUV lithography.
    • The developed method provides a significant speedup without compromising accuracy for 3D mask simulations.
    • This advancement can benefit the design and optimization of EUV lithography processes.