Sub-resolution assist feature printability prediction using machine learning = 기계학습을 이용한 해상도 이하 보조형상의 인쇄가능성 예측

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Sub-resolution assist feature (SRAF) is a mask pattern nearby main feature to promote pattern fidelity of main feature but should not be printed on wafer. SRAFs are sometimes unintentionally printed and the printed SRAFs are critical defects in semiconductor manufacturing. To prevent the accident, the SRAF printabiltiy check is essential before mask tapeout. A conventional SRAF printability check method has large false alarm error because the method does not consider surrounding mask patterns, which effects on SRAF printability. Another conventional SRAF printability check is accurate but time-consuming so it is used only in small layout. We propose new SRAF printability check using machine learning and achieve 12%false alarm error and 69% runtime reduction.
Advisors
Shin, Youngsooresearcher신영수researcher
Description
한국과학기술원 :전기및전자공학부,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2019.8,[ii, 27 p. :]

Keywords

Sub-resolution assist feature▼aprintability▼amachine learning; 해상도 이하 보조형상▼a인쇄가능성; 기계학습

URI
http://hdl.handle.net/10203/283046
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=875340&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
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