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    This study introduces an edge-based optical proximity correction (OPC) method using a vector imaging model. The novel approach achieves high accuracy in integrated circuit manufacturing with fewer iterations.

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    Area of Science:

    • Integrated Circuit Manufacturing
    • Computational Lithography

    Background:

    • Optical proximity correction (OPC) is crucial for integrated circuit (IC) manufacturing.
    • Traditional OPC methods require extensive computations for accurate modeling and pattern correction.

    Purpose of the Study:

    • To propose an efficient and accurate edge-based OPC method.
    • To reduce computational load in OPC by downsampling mask patterns.
    • To establish an analytical correlation between cost function and edge segment movement.

    Main Methods:

    • Developed an edge-based OPC method utilizing a vector imaging model.
    • Segmented and downsampled mask patterns to reduce data.
    • Employed the chain rule to derive the differential relation between cost value and segment movement.
    • Utilized a quasi-Newton method for determining segment adjustments.

    Main Results:

    • The proposed method establishes an analytical correlation using the chain rule.
    • Mask patterns are processed efficiently through segmentation and downsampling.
    • Demonstrated good OPC accuracy within a few iterations compared to commercial software.

    Conclusions:

    • The novel edge-based OPC method offers high accuracy and efficiency.
    • This approach simplifies the complex calculations involved in integrated circuit manufacturing.
    • The vector imaging model and chain rule application are key to the method's success.