Optimization of Work Function via Bayesian Machine Learning Combined with First-Principles Calculation
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- Wataru Hashimoto
- Institute for Materials Chemistry and Engineering and IRCCS, Kyushu University, Nishi-ku, Fukuoka 819-0395, Japan
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- Yuta Tsuji
- Institute for Materials Chemistry and Engineering and IRCCS, Kyushu University, Nishi-ku, Fukuoka 819-0395, Japan
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- Kazunari Yoshizawa
- Institute for Materials Chemistry and Engineering and IRCCS, Kyushu University, Nishi-ku, Fukuoka 819-0395, Japan
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説明
Work function is one of the most fundamental and important physical quantities in surface science. Materials with either lower work function or higher work function would find various applications,...
収録刊行物
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- The Journal of Physical Chemistry C
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The Journal of Physical Chemistry C 124 (18), 9958-9970, 2020-04-14
American Chemical Society (ACS)
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詳細情報 詳細情報について
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- CRID
- 1360572092880336256
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- ISSN
- 19327455
- 19327447
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- 資料種別
- journal article
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- データソース種別
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- Crossref
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