Automated defect severity analysis for binary and PSM mask defects

Lynn Cai; Jiunn-Hung Chen; Lin-Hsin Tu; Brian Chu; Noah Chen; Te Yang Fang; W. B. Shieh

doi:10.1117/12.467436

27 December 2002 Automated Defect Severity Analysis for Binary and PSM Mask Defects

Lynn Cai, Jiunn-Hung Chen, Lin-Hsin Tu, Brian Chu, Noah Chen, Te Yang Fang, W. B. Shieh

Author Affiliations +

Proceedings Volume 4889, 22nd Annual BACUS Symposium on Photomask Technology; (2002) https://doi.org/10.1117/12.467436
Event: Photomask Technology 2002, 2002, Monterey, CA, United States

Abstract

Traditionally, mask defect analysis has been done through a visual inspection review. As the semiconductor industry moves into smaller process generations and the complexity of mask exponentially increases, the traditional mask defect analysis method becomes very time consuming. The Automatic Defect Severity Scoring (ADSS) module of i-Virtual Stepper System from Numerical Technologies offers an extremely fast and highly accurate software solution for defect printability analysis of advanced masks such as OPC and phase-shifting masks in a real production environment. In a previous paper [1], we have introduced the ADSS concept and discussed some results for line-space patterns on OPC and non-OPC masks. In this paper, we will discuss the ADSS results for both line-space and contact patterns on attenuated phase-shifting masks (ATTPSM), together with some ADSS results for line-space patterns on binary masks. The ADSS results are compared to wafer results. The wafer exposures were performed using 248 nm imaging technology and inspection images were generated on a KLA-Tencor’s SLF27 system.

Citation Download Citation

Lynn Cai, Lynn Cai, Jiunn-Hung Chen, Jiunn-Hung Chen, Lin-Hsin Tu, Lin-Hsin Tu, Brian Chu, Brian Chu, Noah Chen, Noah Chen, Te Yang Fang, Te Yang Fang, W. B. Shieh, W. B. Shieh, } "Automated Defect Severity Analysis for Binary and PSM Mask Defects", Proc. SPIE 4889, 22nd Annual BACUS Symposium on Photomask Technology, (27 December 2002); doi: 10.1117/12.467436; https://doi.org/10.1117/12.467436

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