A hybrid machine learning approach to predict and evaluate surface chemistries of films deposited via APPJ

Wang, Y. orcid.org/0009-0006-4353-9278, Ma, X. orcid.org/0009-0009-8746-656X, Robson, A.J. orcid.org/0000-0002-1449-9477 et al. (2 more authors) (2025) A hybrid machine learning approach to predict and evaluate surface chemistries of films deposited via APPJ. Plasma Processes and Polymers. ISSN 1612-8850

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Item Type: Article
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© 2025 The Author(s). Plasma Processes and Polymers published by Wiley-VCH GmbH. This is an open access article under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: deep learning; films; machine learning; plasma polymerization; TEMPO
Dates:
  • Accepted: 28 April 2025
  • Published (online): 11 May 2025
  • Published: 11 May 2025
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Science (Sheffield) > School of Mathematical and Physical Sciences
Depositing User: Symplectic Sheffield
Date Deposited: 19 May 2025 13:28
Last Modified: 19 May 2025 13:28
Status: Published online
Publisher: Wiley
Refereed: Yes
Identification Number: 10.1002/ppap.70035
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