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RESEARCH PAPER · Catalysts · 2024

Prediction of Oxygen Evolution Activity for FeCoMn Oxide Catalysts via Machine Learning

Lei Zhang, Jinfei Hou, Honglin Ji, Dan Meng, Jian Qi, Xiaoguang San

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9 direct citing papers in this saved network. Explore the next layer with second-order citations.

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Prediction of Oxygen Evolution Activity for FeCoMn Oxide Catalysts via Machine LearningOriginalAI and ML for selecting viable electrocatalysts: progress and perspectives51Machine learning-assisted optimization design for enhanced oxygen evolution reaction based on vanadium-doped nickel–cobalt layered double hydroxides34Machine Learning Optimized FeCoMn‐Trimetallic MOF‐Decorated Nanofibers for Enhanced OER Catalysis14Accelerating development of hydriodic acid decomposition catalysts for hydrogen production in thermochemical sulfur-iodine cycle via machine learning4Data-driven optimisation of more sustainable high-to-medium entropy Perovskites for oxygen evolution catalysts0Enhancement Strategies in Transition Metal Oxides as Efficient Electrocatalysts for the Oxygen Evolution Reaction10From prediction to materials design: machine learning in electrocatalytic water splitting1Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications4Natural light driven high concentration 5-hydroxymethylfurfural oxidation coupled with 4-nitrophenol reduction by machine learning-optimized Cu0.46-Ni3S2@NF1

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  1. AI and ML for selecting viable electrocatalysts: progress and perspectives

    Journal of Materials Chemistry A · 2024-01-01

    Anastasiia Pavlovna Dmitrieva, Anna Fomkina, Chantal Tracey, Elizaveta A. Romanenko, Ali Ayati, Pavel V. Krivoshapkin, Elena Fedorovna Krivoshapkina

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  2. Machine learning-assisted optimization design for enhanced oxygen evolution reaction based on vanadium-doped nickel–cobalt layered double hydroxides

    Journal of Materials Chemistry A · 2025-01-01

    Pitchai Chandrasekaran, Ting-Yu Lo, Hou-Chien Chang, Hung‐Chung Li, Ming-Der Yang, Chih‐Ming Chen

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  3. Machine Learning Optimized FeCoMn‐Trimetallic MOF‐Decorated Nanofibers for Enhanced OER Catalysis

    Advanced Sustainable Systems · 2025-03-17

    Farhan Zafar, Muhammad Ali Khan, Mohamed M. El-Toony, Naeem Akhtar, Sadaf Ul Hassan, Rana Abdul Shakoor, Cong Yu

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  4. Accelerating development of hydriodic acid decomposition catalysts for hydrogen production in thermochemical sulfur-iodine cycle via machine learning

    Journal of environmental chemical engineering · 2025-08-18

    Muyang Zhao, Zhi Ying, Yongbao Chen, Xinao Xie, Xiaoyuan Zheng

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  5. Data-driven optimisation of more sustainable high-to-medium entropy Perovskites for oxygen evolution catalysts

    Materials Horizons · 2026-01-01

    Anis Arisa Roslan, Jack J. Quayle, Yuankai Zhao, Thomas Edward Ashton, Jiacheng Wang, Stuart A. Bateman, Tu C. Le, Jawwad Arshad Darr

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  6. Enhancement Strategies in Transition Metal Oxides as Efficient Electrocatalysts for the Oxygen Evolution Reaction

    Molecules · 2026-01-01

    Pengxin Li, Song Ng, Naxiang Wang, Yan Qiong He, Zhi Wen Zhu, Yongsheng Yan

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  7. From prediction to materials design: machine learning in electrocatalytic water splitting

    Chemical Communications · 2026-01-01

    Pitchai Chandrasekaran, Ting-Yu Lo, Yu-Ting Hsu, I Chen, Hung‐Chung Li, Chih‐Ming Chen

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  8. Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications

    Advanced Powder Materials · 2026-05-21

    Ziwei Liu, Hanqing Gu, Liwei Yang, Wengcheng Wu, Zhong Huang, Haozhi Wang, Yang Wang, Yida Deng

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  9. Natural light driven high concentration 5-hydroxymethylfurfural oxidation coupled with 4-nitrophenol reduction by machine learning-optimized Cu0.46-Ni3S2@NF

    Applied Catalysis B: Environmental · 2026-05-31

    Xuxia Chen, Hao Feng, Liying Fu, J. Li, Shunxin Shao, Xueying Cheng, Guangbo Che, Yonghui Gao, Renquan Guan, Chunbo Liu

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