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Journal of Micro/Nanolithography, MEMS, and MOEMS • Open Access

Co-optimization of the mask, process, and lithography-tool parameters to extend the process window
Author(s): Xuejia Guo; Yanqiu Li; Lisong Dong; Lihui Liu

Paper Abstract

Optimization technologies have been widely applied to improve lithography performance, such as optical proximity correction and source mask optimization (SMO). However, most published optimization technologies were performed under fixed process conditions, and only a few parameters were optimized. A method for mask, process, and lithography-tool parameter co-optimization (MPLCO) is developed to extend the process window. A normalized conjugate gradient algorithm is proposed to improve the convergence efficiency of the MPLCO when optimizing different scale parameters. In addition, a parametric mask and source are used in the MPLCO that could obtain exceedingly low mask and source complexity compared with a traditional SMO.

Paper Details

Date Published: 18 March 2014
PDF: 8 pages
J. Micro/Nanolith. MEMS MOEMS 13(1) 013015 doi: 10.1117/1.JMM.13.1.013015
Published in: Journal of Micro/Nanolithography, MEMS, and MOEMS Volume 13, Issue 1
Show Author Affiliations
Xuejia Guo, Beijing Institute of Technology (China)
Yanqiu Li, Beijing Institute of Technology (China)
Lisong Dong, Beijing Institute of Technology (China)
Lihui Liu, Beijing Institute of Technology (China)

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