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Machine-learning-driven design of TMCs heterojunctions with dual-single-atom synergy for efficient photocatalytic hydrogen evolution

Jie Yang, Peilin Huang, Hanwen Zhang, Hongyang Ren, Jie Zhang, Hong Chen, Xiaotian Wang, Hongkuan Yuan, Jianping Xie, Biao Wang

2025Applied Surface Science5 citationsDOI

Topics & Concepts

HeterojunctionPhotocatalysisMaterials scienceSemiconductorNanotechnologyOptoelectronicsComputer scienceBand gapHydrogenVisible spectrumAnataseCrystal structureAbsorption (acoustics)Hydrogen productionWater splittingElectronic band structureGrapheneCrystal (programming language)GraphMachine Learning in Materials Science2D Materials and ApplicationsAdvanced Photocatalysis Techniques
Machine-learning-driven design of TMCs heterojunctions with dual-single-atom synergy for efficient photocatalytic hydrogen evolution | Litcius