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Related Concept Videos

Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

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Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
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Updated: Jul 1, 2025

Design and Development of a Three-Dimensionally Printed Microscope Mask Alignment Adapter for the Fabrication of Multilayer Microfluidic Devices
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Linearized EUV mask optimization based on the adjoint method.

Pinxuan He, Jiamin Liu, Honggang Gu

    Optics Express
    |March 5, 2024
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a fast EUV mask optimization method using the adjoint method to address thick mask effects in semiconductor manufacturing. The linearized gradient significantly improves efficiency for advanced production nodes.

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    Area of Science:

    • Photolithography
    • Semiconductor Manufacturing
    • Computational Lithography

    Background:

    • Mask optimization is crucial for advanced EUV lithography, but faces challenges due to high computational costs and the thick mask effect.
    • Existing methods struggle to efficiently optimize EUV masks while rigorously accounting for the thick mask effect and optical proximity effect.

    Purpose of the Study:

    • To propose a linearized EUV mask optimization method using the adjoint method for fast and effective optimizations.
    • To address the computational challenges and improve the accuracy of EUV mask optimization under rigorous thick mask effect considerations.

    Main Methods:

    • Introduced the adjoint method to calculate the gradient of the EUV mask model.
    • Developed a linearized gradient to efficiently compensate for wafer pattern distortion caused by the thick mask effect.
    • Implemented a two-step strategy for EUV mask optimization.

    Main Results:

    • The adjoint method enables gradient calculation for EUV mask models.
    • The linearized gradient demonstrated an approximate 40% efficiency improvement in the coarse optimization step.
    • The proposed method showed promise for accurate full-chip EUV mask optimization.

    Conclusions:

    • The linearized EUV mask optimization method based on the adjoint method offers a fast and effective solution.
    • This approach successfully mitigates challenges associated with the thick mask effect in EUV lithography.
    • The method is a promising advancement for accurate full-chip EUV mask optimization in semiconductor production.