Large scale thin film thickness uniformity extraction based on dynamic spectroscopic ellipsometry

  • Daesuk Kim*
  • , Gukhyeon Hwang
  • , Gukhyeon Hwang
  • , Sukhyun Choi
  • , Vamara Dembele
  • , Saeid Kheiryzadehkhanghah
  • , Inho Choi
  • , Chung Song Kim
  • , Daesuk Kim*
  • *Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

Abstract

This paper describes a new approach for large-scale thin film thickness mapping based on dynamic spectroscopic ellipsometry. The proposed system can provide a real time thin film uniformity measurement capability with high precision. We expect the proposed scheme can be applied for various large-scale thin film deposition process applications such as roll to roll manufacturing where real time process uniformity monitoring becomes crucial.

Original languageEnglish
Title of host publicationOptical Technology and Measurement for Industrial Applications Conference 2021
EditorsTakeshi Hatsuzawa, Rainer Tutsch, Toru Yoshizawa
PublisherSPIE
ISBN (Electronic)9781510647220
DOIs
StatePublished - 2021
EventOptical Technology and Measurement for Industrial Applications Conference 2021 - Virtual, Online, Japan
Duration: 2021.04.202021.04.22

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11927
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceOptical Technology and Measurement for Industrial Applications Conference 2021
Country/TerritoryJapan
CityVirtual, Online
Period21.04.2021.04.22

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • Imaging spectroscopic ellipsometry
  • Large-scale
  • Snapshot
  • Thin film thickness

Quacquarelli Symonds(QS) Subject Topics

  • Materials Science
  • Computer Science & Information Systems
  • Mathematics
  • Engineering - Electrical & Electronic
  • Engineering - Petroleum
  • Data Science
  • Physics & Astronomy

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