Band Alignment of Oxides by Learnable Structural-Descriptor-Aided Neural Network and Transfer Learning-Reference-Cited by-同舟云学术

Band Alignment of Oxides by Learnable Structural-Descriptor-Aided Neural Network and Transfer Learning

Published:2024-03-28 Issue:14 Volume:146 Page:9697-9708
ISSN:0002-7863
Container-title:Journal of the American Chemical Society
language:en
Short-container-title:J. Am. Chem. Soc.

Author:

Kiyohara Shin¹²^ORCID,Hinuma Yoyo³^ORCID,Oba Fumiyasu¹⁴^ORCID

Affiliation:

1. Laboratory for Materials and Structures, Institute of Innovative Research, Tokyo Institute of Technology, R3-7, 4259 Nagatsuta, Midori-ku, Yokohama 226-8501, Japan

2. Institute for Materials Research, Tohoku University, 2-2-1 Katahira, Aoba-ku, Sendai 980-8577, Japan

3. Department of Energy and Environment, National Institute of Advanced Industrial Science and Technology (AIST), 1-8-31 Midorigaoka, Ikeda, Osaka 563-8577, Japan

4. MDX Research Center for Element Strategy, International Research Frontiers Initiative, Tokyo Institute of Technology, SE-6, 4259 Nagatsuta, Midori-ku, Yokohama 226-8501, Japan

Funder

Ministry of Education, Culture, Sports, Science and Technology

Kanagawa Institute of Industrial Science and Technology

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/jacs.3c13574

Reference88 articles.

1. Visible-light driven heterojunction photocatalysts for water splitting – a critical review

2. Band alignment of rutile and anatase TiO2

3. Band Bending in Semiconductors: Chemical and Physical Consequences at Surfaces and Interfaces

4. Photovoltaic materials: Present efficiencies and future challenges

5. Energy conversion approaches and materials for high-efficiency photovoltaics

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