Fast lithography aerial image calculation method based on machine learning

被引:29
作者
Ma, Xu [1 ]
Zhao, Xuejiao [1 ]
Wang, Zhiqiang [1 ]
Li, Yanqiu [1 ]
Zhao, Shengjie [2 ]
Zhang, Lu [3 ]
机构
[1] Beijing Inst Technol, Sch Optoelect, Key Lab Photoelect Imaging Technol & Syst, Minist Educ China, Beijing 100081, Peoples R China
[2] Tongji Univ, Sch Software Engn, Shanghai 201804, Peoples R China
[3] Nokia Shanghai Bell Co Ltd, China Off 5G, Mobile Networks Business Grp, Shanghai 201206, Peoples R China
基金
中国国家自然科学基金;
关键词
SOURCE MASK OPTIMIZATION; COUPLED-WAVE ANALYSIS; OPTICAL LITHOGRAPHY; IMMERSION LITHOGRAPHY; SIMULATION; MODEL; DIFFRACTION; EFFICIENT;
D O I
10.1364/AO.56.006485
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Aerial image calculation for thick masks is an indispensable but time-consuming step in most lithography simulations. This paper develops a fast thick-mask aerial image calculation method based on machine learning for partially coherent lithography systems. First, some sparse sampling points are chosen from the source plane to represent the partially coherent illumination. Then, the training libraries of thick-mask diffraction near-fields are built up for all sampling points based on a set of representative mask features. For an arbitrary thick mask, we calculate its aerial image using the nonparametric kernel regression technique and the pre-calculated training libraries. Subsequently, a post-processing method is applied to compensate for the estimation error and improve the computational accuracy. In addition, this paper also studies the impacts of several key factors on the accuracy and efficiency of the proposed method. Finally, the proposed method is verified by the simulations at 45 nm and 14 nm technology nodes. (C) 2017 Optical Society of America
引用
收藏
页码:6485 / 6495
页数:11
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