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RESEARCH PAPER · Journal of Materials Informatics · 2023

Recent advances and applications of machine learning in electrocatalysis

You Hu, Junhua Chen, Zheng Xi Wei, Qiu He, Yan Zhao

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Recent advances and applications of machine learning in electrocatalysisOriginalComputational design of spatially confined triatomic catalysts for nitrogen reduction reaction19Theoretical design of dendrite-free zinc anode through intrinsic descriptors from symbolic regression10Critical review of high-entropy alloys for catalysts: Design, synthesis, and applications27Prediction of holey graphyne-supported single atom catalyst for nitrogen reduction reaction by interpretable machine learning and first-principles calculations8Rational modulate the coordination environment of FeMoNx-G electrocatalysts to boost nitrogen reduction reaction activity2Machine learning guided tuning of metal precursors and solvent pH for superior OER performance of ZnO-Co3O4/C electrocatalysts31Transformative strategies in photocatalyst design: merging computational methods and deep learning39Large Language Model-Driven Knowledge Discovery for Designing Advanced Micro/Nano Electrocatalyst Materials4Transforming Carbon-Based Material: The Role of AI and ML Regression Techniques in Material Science0Weak Sunlight Responsive Photocatalytic Degradation Via Synergy of Oxygen Vacancies and S-Type Heterojunctions in G-C3n4-Zn2sno40Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective23Unveiling the potential of high-entropy materials toward high-energy metal batteries based on conversion reactions: Synthesis, structure, properties, and beyond11Advanced theoretical modeling methodologies for electrocatalyst design in sustainable energy conversion28Electrochemical CO 2 Reduction on SnO: Insights into C 1 Product Dynamic Distribution and Reaction Mechanisms40Parametric Optimization of Transition Metal-Based Nanocomposite Electrocatalysts for Oxygen Evolution Reaction in Alkaline Media4Accelerating the screening of catalysts for hydrogen evolution reaction in graphene materials based on DFT calculations and machine learning5Weak sunlight responsive photocatalytic degradation via synergy of oxygen vacancies and S-scheme heterojunctions in g-C3N4-Zn2SnO47Design and Application of Electrocatalyst Based on Machine Learning33Machine Learning-Assisted Design of Transition-Metal-Doped Cobalt Phosphide Electrocatalysts for Hydrogen Evolution10Machine learning-enabled optoelectronic material discovery: a comprehensive review31Artificial intelligence-driven catalyst design for electrocatalytic hydrogen production: Paradigm innovation and challenges in material discovery14Enhanced extrapolative machine learning for designing high‐performance multi‐principal‐element superalloys9Light-Driven Enhancement of Oxygen Evolution for Clean Energy Conversion: Co3O4-TiO2/CNTs P-N Heterojunction Catalysts Enabling Efficient Carrier Separation and Reduced Overpotential2Review of Artificial Intelligence Applications in Performance Prediction of Advanced Energy Materials2Multi-feature deep learning framework for predicting CO adsorption mechanisms at metal oxide interfaces: a transformer-based approach1Decoupling mass transport from spin chemistry in the electro-fenton process under magnetic fields0Predicting Activation Energy of Hydrocarbon Dehydrogenation on Au(111) via Machine Learning0Machine learning-accelerated transition state prediction for strain-engineered high-entropy alloy catalysts2Data-Driven Electrocatalyst Discovery: Recent Trends in Machine Learning Approaches and Descriptor-Based Design Principles20Recent Advances in Nano‐Microstructured Catalysts for Electrochemical Seawater Electrocatalysis9Machine learning-driven light-assisted electrocatalytic conversion of methane to alcohols using Pt-Co/TiO₂/g-C₃N₄ nanohybrids under ambient conditions0Integrating machine learning in catalyst design for sustainable hydrogen from plastic waste4Energetically Anchored Machine-Learning Interatomic Potential Embeddings for Reliable Hydrogen Evolution Electrocatalyst Prediction0Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production1Tutorials on Machine Learning Tools for Simulations in Electrocatalysis1

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  1. Computational design of spatially confined triatomic catalysts for nitrogen reduction reaction

    Journal of Materials Informatics · 2023-12-21

    Wei Pei, Wenya Zhang, Xueke Yu, Lei Hou, Weizhi Xia, Zi Wang, Yongfeng Liu, Si Zhou, Yusong Tu, Jijun Zhao

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  2. Theoretical design of dendrite-free zinc anode through intrinsic descriptors from symbolic regression

    Journal of Materials Informatics · 2024-05-27

    Mengde Kang, Kai Huang, Jiahui Li, Honglai Liu, Cheng Lian

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  3. Critical review of high-entropy alloys for catalysts: Design, synthesis, and applications

    International Journal of Hydrogen Energy · 2024-10-09

    Long Luo, Huimin Han, Liangpan Chen, Dianchen Feng, Lirong Li, Lirong Li, Tingting Zhai, Zhiwei Chen, Rihao Gao, Haibin Wu, Suxia Liu, Wenli Pei, Yongzhi Li

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  4. Prediction of holey graphyne-supported single atom catalyst for nitrogen reduction reaction by interpretable machine learning and first-principles calculations

    Surfaces and Interfaces · 2024-11-06

    Dian Zheng, Fei Yan Deng, Jing Xu, Wei Liu

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  5. Rational modulate the coordination environment of FeMoNx-G electrocatalysts to boost nitrogen reduction reaction activity

    Molecular Catalysis · 2024-12-06

    Yuwen Cheng, Cuiping Shao, Wenjie Wang

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  6. Machine learning guided tuning of metal precursors and solvent pH for superior OER performance of ZnO-Co3O4/C electrocatalysts

    International Journal of Hydrogen Energy · 2024-12-10

    Farhan Zafar, Muhammad Asad, Wajid Sajjad, Muhammad Ali Khan, Naeem Akhtar, Sadaf Ul Hassan, Cong Yu

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  7. Transformative strategies in photocatalyst design: merging computational methods and deep learning

    Journal of Materials Informatics · 2024-12-31

    Jianqiao Liu, Liqian Liang, Boru Su, Di Wu, Yuequ Zhang, Jianzhao Wu, Ce Fu

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  8. Large Language Model-Driven Knowledge Discovery for Designing Advanced Micro/Nano Electrocatalyst Materials

    Computers, materials & continua/Computers, materials & continua (Print) · 2025-01-01

    Ying Shen, Shichao Zhao, Yanfei Lv, Fei Chen, Li Fu, Hassan Karimi‐Maleh

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  9. Transforming Carbon-Based Material: The Role of AI and ML Regression Techniques in Material Science

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  10. Weak Sunlight Responsive Photocatalytic Degradation Via Synergy of Oxygen Vacancies and S-Type Heterojunctions in G-C3n4-Zn2sno4

    SSRN Electronic Journal · 2025-01-01

    Di Wu, Di Wu, Zhicong Huang, Linna Qiao, Chuqiao Hu, Peilun Qiu, Ce Fu, Junsheng Wang

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  11. Superior single-atom and single-cluster catalysts towards electrocatalytic nitrogen reduction reactions: a theoretical perspective

    Journal of Materials Informatics · 2025-01-13

    Haihong Meng, Yinghe Zhao, Fengyu Li, Zhongfang Chen

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  12. Unveiling the potential of high-entropy materials toward high-energy metal batteries based on conversion reactions: Synthesis, structure, properties, and beyond

    Energy storage materials · 2025-01-23

    Mingyu Lian, Weihao Gong, Shaofei Guo, Ying Jiang, Zhengqing Ye

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  13. Advanced theoretical modeling methodologies for electrocatalyst design in sustainable energy conversion

    Applied Physics Reviews · 2025-02-06

    Tianyi Wang, Qilong Wu, Yun Han, Zhongyuan Guo, Jun Chen, Chuangwei Liu

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  14. Electrochemical CO 2 Reduction on SnO: Insights into C 1 Product Dynamic Distribution and Reaction Mechanisms

    ACS Catalysis · 2025-02-06

    Zhongyuan Guo, Tianyi Wang, Heng Liu, Xue Jia, Di Zhang, Wei Li, Jiang Xu, Hao Li

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  15. Parametric Optimization of Transition Metal-Based Nanocomposite Electrocatalysts for Oxygen Evolution Reaction in Alkaline Media

    Electrocatalysis · 2025-04-11

    Vedasri Bai Khavala, Abhijai Velluva, Adhithyan Kathiravan, Harish Kuruva, Chandan Singh Khavala, Budaraju Srinivasa Murty, Tiju Thomas

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  16. Accelerating the screening of catalysts for hydrogen evolution reaction in graphene materials based on DFT calculations and machine learning

    Molecular Catalysis · 2025-04-25

    Zikai Xiong, Shengjun Huo, Wanglai Cen, Jikun Feng, Jiahao Zeng, Meiling Hou, Yu Liu

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  17. Weak sunlight responsive photocatalytic degradation via synergy of oxygen vacancies and S-scheme heterojunctions in g-C3N4-Zn2SnO4

    Journal of Photochemistry and Photobiology A Chemistry · 2025-04-27

    Di Wu, Zhicong Huang, Linna Qiao, Chuqiao Hu, Peilun Qiu, Jianqiao Liu, Ce Fu, Junsheng Wang

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  18. Design and Application of Electrocatalyst Based on Machine Learning

    Interdisciplinary materials · 2025-05-01

    Yulan Gu, Hailong Zhang, Zhen Xu, Rui Ren, Xiangyi Kong, Yafu Wang, Houen Zhu, Dongdong Xue, Yali Zhang, Yuzhu Ma, Dongyuan Zhao, Jiangwei Zhang

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  19. Machine Learning-Assisted Design of Transition-Metal-Doped Cobalt Phosphide Electrocatalysts for Hydrogen Evolution

    ACS Applied Nano Materials · 2025-05-01

    Sihan Fan, Yang Gao, Min Wu, Xinjuan Liu, Jianwei Li, Likun Pan, Fuzhen Xuan

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  20. Machine learning-enabled optoelectronic material discovery: a comprehensive review

    Journal of Materials Informatics · 2025-05-28

    Yu Shu, Naihua Miao, Rize Li, Yucheng Lin, Siyu Han, Jian Xin Zhou, Zhimei Sun

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  21. Artificial intelligence-driven catalyst design for electrocatalytic hydrogen production: Paradigm innovation and challenges in material discovery

    Sustainable Chemistry for Energy Materials · 2025-06-21

    Zhaoyong Jin, Dongxu Gu, Panpan Li, Guilin Ye, Heru Zhu, Kailun Wei, Chunxiang Li, Wenhui Zhong, Wenjie Du, Qing Jun Zhu

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  22. Enhanced extrapolative machine learning for designing high‐performance multi‐principal‐element superalloys

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  23. Light-Driven Enhancement of Oxygen Evolution for Clean Energy Conversion: Co3O4-TiO2/CNTs P-N Heterojunction Catalysts Enabling Efficient Carrier Separation and Reduced Overpotential

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  24. Review of Artificial Intelligence Applications in Performance Prediction of Advanced Energy Materials

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  25. Multi-feature deep learning framework for predicting CO adsorption mechanisms at metal oxide interfaces: a transformer-based approach

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  26. Decoupling mass transport from spin chemistry in the electro-fenton process under magnetic fields

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  27. Predicting Activation Energy of Hydrocarbon Dehydrogenation on Au(111) via Machine Learning

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  28. Machine learning-accelerated transition state prediction for strain-engineered high-entropy alloy catalysts

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  29. Data-Driven Electrocatalyst Discovery: Recent Trends in Machine Learning Approaches and Descriptor-Based Design Principles

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  30. Recent Advances in Nano‐Microstructured Catalysts for Electrochemical Seawater Electrocatalysis

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  31. Machine learning-driven light-assisted electrocatalytic conversion of methane to alcohols using Pt-Co/TiO₂/g-C₃N₄ nanohybrids under ambient conditions

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  32. Integrating machine learning in catalyst design for sustainable hydrogen from plastic waste

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  33. Energetically Anchored Machine-Learning Interatomic Potential Embeddings for Reliable Hydrogen Evolution Electrocatalyst Prediction

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  34. Machine learning approaches for electrocatalyst design in water splitting: a review for green hydrogen production

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  35. Tutorials on Machine Learning Tools for Simulations in Electrocatalysis

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