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Characterization of descriptors in machine learning for data-based sputtering yield prediction

  • Published:2021-01 Issue:1 Volume:28 Page:013504
  • ISSN:1070-664X
  • Container-title:Physics of Plasmas
  • language:en
  • Short-container-title:Physics of Plasmas

Author:

Kino Hiori1ORCID,Ikuse Kazumasa2ORCID,Dam Hieu-Chi3ORCID,Hamaguchi Satoshi2ORCID

Affiliation:

1. MaDIS, National Institute for Materials Science (NIMS), Namiki 1-1, Tsukuba, Ibaraki 305-0044, Japan

2. Center for Atomic and Molecular Technologies, Osaka University, Suita, Osaka 565-0871, Japan

3. Japan Advanced Institute of Science and Technology, 1-1 Asahidai, Nomi, Ishikawa 923-1292, Japan

Funder

Japan Society for the Promotion of Science

Japan Science and Technology Agency

Publisher

AIP Publishing

Subject

Condensed Matter Physics

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1. Sputtering of silver nanoparticles bombarded with 3–100 keV Ar ions;Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms;2024-07

2. Future of plasma etching for microelectronics: Challenges and opportunities;Journal of Vacuum Science & Technology B;2024-06-07

3. Plasma-Driven Sciences: Exploring Complex Interactions at Plasma Boundaries;Plasma;2024-02-27

4. 2022 Review of Data-Driven Plasma Science;IEEE Transactions on Plasma Science;2023-07

5. Deep neural network-based reduced-order modeling of ion–surface interactions combined with molecular dynamics simulation;Journal of Physics D: Applied Physics;2023-06-22
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