期刊
APPLIED SCIENCES-BASEL
卷 13, 期 9, 页码 -出版社
MDPI
DOI: 10.3390/app13095708
关键词
optical lithography; source optimization; genetic algorithm; resolution enhancement technology
In this study, a source optimization method based on a hybrid genetic algorithm is proposed to achieve an acceptable source shape in the imaging process for optical lithography. The method utilizes particle swarm optimization and the tabu list method from the tabu search algorithm to overcome the problems of local optima and small search scope, enhancing the optimization performance. Different feature patterns are employed as the input of the optimization model. Simulation results show that the proposed method exhibits dominant optimization performance for source optimization in optical lithography.
As an effective resolution enhancement technology, source optimization (SO) is considered key for significantly improving the image quality of optical lithography at advanced nodes. To solve the problem of unsatisfactory SO performance, it is necessary to combine it with optimization algorithms. In this study, an SO method based on a hybrid genetic algorithm is proposed to achieve an acceptable source shape in the imaging process for optical lithography. To overcome the problems of local optima and the small search scope, an update strategy that uses particle swarm optimization and the tabu list method from the tabu search algorithm are utilized to enhance the optimization performance. Meanwhile, different feature patterns were employed as the input of the optimization model. These simulation results show that the proposed SO method exhibits dominant optimization performance for SO in optical lithography.
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