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Choosing objective functions for inverse lithography patterning

dc.citation.volume7973en_US
dc.contributor.authorYu, Jue-Chinen_US
dc.contributor.authorYu, Peichenen_US
dc.contributor.department光電工程學系zh_TW
dc.contributor.departmentDepartment of Photonicsen_US
dc.date.accessioned2014-12-08T15:03:14Z
dc.date.available2014-12-08T15:03:14Z
dc.date.issued2011en_US
dc.description.abstractInverse lithography which generates model-based patterns theoretically has superior patterning fidelity comparing to conventional rule-based technique. Cost functions are the determinant of performance inverse lithography that is also an optimization problem. However, the design and know-how of cost functions have rarely been discussed. In this paper, we investigate the impacts of various cost functions and their superposition for inverse lithography patterning exploiting a steepest descent algorithm. We research the most generally used objective functions, which are the resist and aerial images, and also deliver a derivation for the aerial image contrast. We then discuss the pattern fidelity and final mask characteristics for simple layouts with a single isolated contact and two nested contacts. Moreover, the convergences which are expressed by edge-placement error (EPE) and contrast versus iteration numbers rapidly attain to steady sate in most hybrid cost functions. All in all, we conclude that a cost function composed of a dominant resist-image component and a minor aerial-image or image-contrast component can carry out a good mask correction and contour targets when using inverse lithography patterning.en_US
dc.identifier.doi10.1117/12.879440en_US
dc.identifier.isbn978-0-81948-532-8en_US
dc.identifier.issn0277-786Xen_US
dc.identifier.journalOPTICAL MICROLITHOGRAPHY XXIVen_US
dc.identifier.urihttp://dx.doi.org/10.1117/12.879440en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/1796
dc.identifier.wosnumberWOS:000294216100052
dc.language.isoen_USen_US
dc.subjectMicrolithographyen_US
dc.subjectInverse lithographyen_US
dc.subjectModel-based patteringen_US
dc.subjectGradient descenten_US
dc.subjectComputational imagingen_US
dc.titleChoosing objective functions for inverse lithography patterningen_US
dc.typeArticleen_US

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