A novel pre-processing approach for OPC using LSMR

In the integrated circuit manufacturing process, particularly in lithography, resolution enhancement techniques, such as optical proximity correction(OPC), are extremely important. To improve pattern fidelity and CD uniformity in lithography, it is necessary to generate appropriate sub-resolution assist feature(SRAF) and an initial mask as a pre-processing step for OPC. In this paper, we propose a novel method for generating an appropriate initial mask and SRAF, which we refer to as Quasi-Inverse Lithography Technique(QILT). The optical image intensity is expressed as a linear combination of the squares of the convolutions of the sum of coherent systems(SOCS) kernel and the mask function. Although solving this inverse problem directly is challenging, it can be reduced to a linear equation and solved approximately. To address this linear problem, we adopt the LSMR method, a conjugate residual method applied to the normal equation. This paper provides a detailed description of our method and demonstrates its effectiveness.

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Publication Details

Published
2025-04-22
DOI
https://doi.org/10.1117/12.3050121
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
1.24
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article

A novel pre-processing approach for OPC using LSMR

J. Inoue, Taiki Kimura, Kinji Kimura, Masafumi Suzuki
1 citations
Industrial Vision Systems and Defect Detection
1.24
article

A novel pre-processing approach for OPC using LSMR

J. Inoue, Taiki Kimura, Kinji Kimura, Masafumi Suzuki
article en
1 citations

Abstract

In the integrated circuit manufacturing process, particularly in lithography, resolution enhancement techniques, such as optical proximity correction(OPC), are extremely important. To improve pattern fidelity and CD uniformity in lithography, it is necessary to generate appropriate sub-resolution assist feature(SRAF) and an initial mask as a pre-processing step for OPC. In this paper, we propose a novel method for generating an appropriate initial mask and SRAF, which we refer to as Quasi-Inverse Lithography Technique(QILT). The optical image intensity is expressed as a linear combination of the squares of the convolutions of the sum of coherent systems(SOCS) kernel and the mask function. Although solving this inverse problem directly is challenging, it can be reduced to a linear equation and solved approximately. To address this linear problem, we adopt the LSMR method, a conjugate residual method applied to the normal equation. This paper provides a detailed description of our method and demonstrates its effectiveness.

University of Fukui (JP)
Openalex Percentile: Top 20%
Industrial Vision Systems and Defect Detection
1.24
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