In this paper, an efficient approach to mask optimization for digital micromirror device lithography is proposed, leveraging an enhanced particle swarm optimization algorithm, which significantly elevates the resolution and precision of lithography. Initially, chaos mapping is applied to the initial population to enhance particle diversity, thereby improving the optimization efficiency of the algorithm. Subsequently, self-adaptive parameter adjustments and simulated annealing are integrated to effectively avoid premature convergence and escape local optima. Numerical simulation results demonstrate a substantial reduction in pattern errors between the printed and the target images by 95.2%, 95.4%, and 89.2%. The proposed algorithm markedly surpasses conventional optimization methods, notably bolstered in optimization efficiency and pattern accuracy.
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January 2025
Research Article|
January 13 2025
Chaos-enhanced self-adaptive particle swarm optimization with simulated annealing for digital lithography mask optimization
Shengzhou Huang
;
Shengzhou Huang
a)
(Data curation, Formal analysis, Investigation, Methodology, Writing – original draft)
1
School of Artificial Intelligence, Anhui Polytechnic University
, Wuhu 241000, China
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
3
Anhui Province Wuhu Instrument Research Co., Ltd
, Wuhu 241006, China
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Dongjie Wu
;
Dongjie Wu
(Conceptualization, Funding acquisition, Supervision, Writing – review & editing)
1
School of Artificial Intelligence, Anhui Polytechnic University
, Wuhu 241000, China
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Yuanzhuo Tang;
Yuanzhuo Tang
(Conceptualization, Funding acquisition, Supervision)
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
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Bowen Ren;
Bowen Ren
(Data curation, Formal analysis, Investigation)
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
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Jiani Pan;
Jiani Pan
(Conceptualization, Supervision, Writing – original draft, Writing – review & editing)
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
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Zhaowei Tian;
Zhaowei Tian
(Data curation, Formal analysis, Investigation, Methodology)
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
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Yongkang Shao;
Yongkang Shao
(Conceptualization, Data curation, Investigation)
2
School of Mechanical Engineering, Anhui Polytechnic University
, Wuhu 241000, China
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Siwen He
Siwen He
(Supervision, Writing – review & editing)
1
School of Artificial Intelligence, Anhui Polytechnic University
, Wuhu 241000, China
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a)
Electronic mail: [email protected]
J. Vac. Sci. Technol. B 43, 012601 (2025)
Article history
Received:
September 27 2024
Accepted:
December 23 2024
Citation
Shengzhou Huang, Dongjie Wu, Yuanzhuo Tang, Bowen Ren, Jiani Pan, Zhaowei Tian, Yongkang Shao, Siwen He; Chaos-enhanced self-adaptive particle swarm optimization with simulated annealing for digital lithography mask optimization. J. Vac. Sci. Technol. B 1 January 2025; 43 (1): 012601. https://doi.org/10.1116/6.0004107
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