Pix2PixHD-Based Generation of SEM Image in the ETCH Domain by SEM Image of LITHO Domain

Botong Zhao, Jiwei Shen, Hu Lu, Pengjie Lou, Wenzhan Zhou, Kan Zhou, Xintong Zhao, Shujing Lyu, Yue Lu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In semiconductor manufacturing, a forward etching process model that can accurately predict the pattern transformation from post-lithography (ADI) to post-etch (AEI) is greatly desired. However, current etching model is etch bias based, it is unable to offer rich information as the SEM image does for engineers to do wafer disposition. We propose an AEI image generation model using the Pix2PixHD. It can generate AEI images corresponding to ADI images. Experimental results demonstrate that our generated images achieve a SSIM of 96.7% and a MSSIM of 94.2% when compared to AEI images. Therefore, Our method can generate AEI images with a high resolution of (1024, 1024) and meet the requirements of applications.

Original languageEnglish
Title of host publicationIWAPS 2023 - 2023 7th International Workshop on Advanced Patterning Solutions
EditorsYayi Wei, Tianchun Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350344547
DOIs
StatePublished - 2023
Event7th International Workshop on Advanced Patterning Solutions, IWAPS 2023 - Lishui, Zhejiang Province, China
Duration: 26 Oct 202327 Oct 2023

Publication series

NameIWAPS 2023 - 2023 7th International Workshop on Advanced Patterning Solutions

Conference

Conference7th International Workshop on Advanced Patterning Solutions, IWAPS 2023
Country/TerritoryChina
CityLishui, Zhejiang Province
Period26/10/2327/10/23

Keywords

  • deep learning
  • image generation
  • post-etch
  • post-lithography

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