Machine-learning prediction of metal sulfide photocatalysts for sacrificial hydrogen evolution under visible light irradiation

Journal of Materials Chemistry A 2026 Open access

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Authors: Yuichi Yamaguchi, Fuga Kakami, Ryuto Baba, Wataru Takahara, Yosuke Harashima, Tomoaki Takayama, Mikiya Fujii, Akihiko Kudo
DOI: 10.1039/d5ta06041a
Cited by: 3
References: 76

Abstract

Ag 2 CdGeS 4 and Cu 2 CdMS 4 (M = Ge and Sn) predicted by machine learning were experimentally developed for sacrificial hydrogen evolution under visible light.

Fields of Study & Subjects

Chalcogenide Semiconductor Thin Films Advanced Photocatalysis Techniques Quantum Dots Synthesis And Properties

Publication details

Journal / source
Journal of Materials Chemistry A
Publisher
Royal Society of Chemistry (RSC)
Volume
14
Issue
17
Pages
9956–9965
Publication date
1 January 2026
Language
EN