Label-free neural networks-based inverse lithography technology

Neural network-based inverse lithography technology (NNILT) has been used to improve the computational efficiency of large-scale mask optimization for advanced photolithography. NNILT is now mostly based on labels, and its performance is affected by the quality of labels. It is difficult for NNILT t...

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Bibliographic Details
Published in:Optics express 2022-12, Vol.30 (25), p.45312-45326
Main Authors: Chen, Jing-Tao, Zhao, Yuan-Yuan, Zhang, Yang, Zhu, Jian-Xin, Duan, Xuan-Ming
Format: Article
Language:English
Subjects:
Neural Networks, Computer
Printing
Technology
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Summary:Neural network-based inverse lithography technology (NNILT) has been used to improve the computational efficiency of large-scale mask optimization for advanced photolithography. NNILT is now mostly based on labels, and its performance is affected by the quality of labels. It is difficult for NNILT to achieve high performance and extrapolation ability for mask optimization without using labels. Here, we propose a label-free NNILT (LF-NNILT), which is implemented completely without labels and greatly improves the printability of the target layouts and the manufacturability of the synthesized masks compared to the traditional ILT. More importantly, the optimization speed of LF-NNILT is two orders of magnitude faster than the traditional ILT. Furthermore, LF-NNILT is simpler to implement and can achieve better solvers to support the development of advanced lithography.
ISSN:1094-4087
1094-4087
DOI:10.1364/OE.472495