Lithography

Efficient source mask optimization method for reduction of computational lithography cycles and enhancement of process-window predictability

[+] Author Affiliations
Moran Guo, Zhiyang Song, Yayi Wei

Chinese Academy of Sciences, Institute of Microelectronics, Laboratory of Microelectronics Devices and Integrated Technology, 3 Beitucheng West Road, Chaoyang, Beijing 100029, China

Yaobin Feng, Zhengguo Tian, Qingchen Cao

Xinxin Semiconductor Manufacturing Corporation, 18 Gaoxin 4TH Road, Wuhan, Hubei 430205, China

J. Micro/Nanolith. MEMS MOEMS. 14(4), 043507 (Nov 23, 2015). doi:10.1117/1.JMM.14.4.043507
History: Received August 10, 2015; Accepted October 22, 2015
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Abstract.  Source-mask optimization (SMO) is used in advanced computational lithography to further enlarge the process margin. SMO provides the source for subsequent optical proximity correction (OPC) to generate the mask with reasonable manufacturability and functionality. Little attention is paid to the mask optimization procedure of SMO. The procedure may potentially cause significant mismatch between a source-mask optimized mask (SMOed mask) and an optical proximity-corrected mask (OPCed mask), which affects the efficiency of the optimization. We investigate and report a specific example of an efficient method to align the SMOed mask to the OPCed mask so as to reduce the cycles of computational lithography and improve the predictability of SMO. This method incorporates techniques of retargeting and manipulating the cost function (CF) into SMO to modify the CF and eventually change the mask shapes. Various defects can also be corrected to minimize the needed number of hotspots, which also improves the effectiveness of SMO and decreases the cycles of computational lithography. Our sample simulations performed on a metal layer with both diffractive optical element (DOE) and freeform illumination demonstrate that the proposed SMO further enhances the process window (PW) by more than 30% compared with conventional SMO. The optimized mask shape is also more similar to OPCed mask. Experimental verification is also performed to validate the proposed method.

Figures in this Article
© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Moran Guo ; Zhiyang Song ; Yaobin Feng ; Zhengguo Tian ; Qingchen Cao, et al.
"Efficient source mask optimization method for reduction of computational lithography cycles and enhancement of process-window predictability", J. Micro/Nanolith. MEMS MOEMS. 14(4), 043507 (Nov 23, 2015). ; http://dx.doi.org/10.1117/1.JMM.14.4.043507


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