Fast and accurate lithography simulation using cluster analysis in resist model building

被引:10
作者
Kumar, Pardeep [1 ]
Srinivasan, Babji [1 ]
Mohapatra, Nihar R. [1 ]
机构
[1] Indian Inst Technol Gandhinagar, Dept Elect Engn, Ahmadabad 382424, Gujarat, India
来源
JOURNAL OF MICRO-NANOLITHOGRAPHY MEMS AND MOEMS | 2015年 / 14卷 / 02期
关键词
lithography simulation; compact model; optical proximity correction; clustering algorithm; K-means clustering; density peak clustering; randomization; empirical resist model; AERIAL IMAGE; OPC; PERFORMANCE;
D O I
10.1117/1.JMM.14.2.023506
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As technology nodes continue to shrink, optical proximity correction (OPC) has become an integral part of mask design to improve the subwavelength printability. The success of lithography simulation to perform OPC on an entire chip relies heavily on the performance of lithography process models. Any small enhancement in the performance of process models can result in a valuable improvement in the yield. We propose a robust approach for lithography process model building. The proposed scheme uses the clustering algorithm for model building and thereby improves the accuracy and computational efficiency of lithography simulation. The effectiveness of the proposed method is verified by simulating some critical layers in 14- and 22-nm complementary metal oxide semiconductor technology nodes. Experimental results show that compared with a conventional approach, the proposed method reduces the simulation time by 50x with similar to 5% improvement in accuracy. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)
引用
收藏
页数:6
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