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RESEARCH PAPER · Electroanalysis · 2021

Accelerating Optimizing the Design of Carbon‐based Electrocatalyst via Machine Learning

Zhuochen Yu, Weimin Huang

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

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Accelerating Optimizing the Design of Carbon‐based Electrocatalyst via Machine LearningOriginalMachine learning for design principles for single atom catalysts towards electrochemical reactions116Machine Learning Utilized for the Development of Proton Exchange Membrane Electrolyzers51Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery552Tuning OER Electrocatalysts toward LOM Pathway through the Lens of Multi-Descriptor Feature Selection by Artificial Intelligence-Based Approach51Application of Machine Learning for the Determination of Damaged Starch Ratio as an Alternative to Medcalf and Gilles Principle5Application of machine learning approach for green hydrogen2The Defect Chemistry Study of Single Transition-Metal Atoms Anchored on Ptse2 Monolayer for the Rational Design of Bifunctional Oer/Orr Electrocatalysts0Fine-structure sensitive deep learning framework for predicting catalytic properties with high precision9Explainable machine-learning predictions for catalysts in CO 2 -assisted propane oxidative dehydrogenation25Rational design of single transition-metal atoms anchored on a PtSe 2 monolayer as bifunctional OER/ORR electrocatalysts: a defect chemistry and machine learning study62High throughput screening for electrocatalysts for nitrogen reduction reaction using metal-doped bilayer borophene: A combined approach of DFT and machine learning17Prediction and evaluation of multiple output machine learning methods for ethylene oligomerization and aromatization kinetics modeling0Computational condensed matter science contributions to addressing water emerging contaminant pollution: a comprehensive review6Advanced theoretical modeling methodologies for electrocatalyst design in sustainable energy conversion28Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories33AILD: An Interpretable AI Framework for Designing Logical Descriptors in Predicting CO Adsorption on Catalysts0Machine learning-optimized bioinspired N-doped carbon-wrapped trimetallic oxides for an efficient oxygen evolution reaction0Machine-learning-aided predicting and engineering of hydrochar nitrogen-containing functional groups1High-Throughput Electrochemistry Using Scanning Electrochemical Cells4Data-driven design of electrocatalysts: Machine learning workflows, paradigm shifts, and applications4Carbonaceous catalysts for the hydrolysis of cellulose0

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  1. Machine learning for design principles for single atom catalysts towards electrochemical reactions

    Journal of Materials Chemistry A · 2022-01-01

    Mohsen Tamtaji, Hanyu Gao, Md Delowar Hossain, Patrick Ryan Galligan, Hoilun Wong, Zhenjing Liu, Hongwei Liu, Yuting Cai, William A. Goddard, Zhengtang Luo

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  2. Machine Learning Utilized for the Development of Proton Exchange Membrane Electrolyzers

    Journal of Power Sources · 2022-01-01

    Rui Fang Ding, Yawen Chen, Zhiyan Rui, Kang Hua, Yongkang Wu, Xiaoke Li, Xiao Duan, Jia Li, Xuebin Wang, Jianguo Liu

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  3. Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

    Chemical Reviews · 2022-07-21

    Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler, Rachel A. Caruso

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  4. Tuning OER Electrocatalysts toward LOM Pathway through the Lens of Multi-Descriptor Feature Selection by Artificial Intelligence-Based Approach

    ACS Materials Letters · 2022-12-27

    Haruna Adamu, Sani Isah Abba, Paul Betiang Anyin, Yusuf Sani, Zain Hassan Yamani, Mohammad Qamar

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  5. Application of Machine Learning for the Determination of Damaged Starch Ratio as an Alternative to Medcalf and Gilles Principle

    Food Analytical Methods · 2022-12-30

    N. Alper Tapan, Mehmet Erdem Günay, Nilüfer Yıldırım

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  6. Application of machine learning approach for green hydrogen

    Elsevier eBooks · 2023-01-01

    Amit Kumar Verma, Kanchan Rathore, Rohit Srivastava

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  7. The Defect Chemistry Study of Single Transition-Metal Atoms Anchored on Ptse2 Monolayer for the Rational Design of Bifunctional Oer/Orr Electrocatalysts

    SSRN Electronic Journal · 2023-01-01

    Shijiao Yue, Dongying Li, Aodi Zhang, Yu-Li Yan, Hongxia Yan, Zhenzhen Feng, Wentao Wang

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  8. Fine-structure sensitive deep learning framework for predicting catalytic properties with high precision

    CHINESE JOURNAL OF CATALYSIS (CHINESE VERSION) · 2023-07-01

    Yuzhuo Chen, Hao Wang, Bing Lu, Yi Qing Ni, Liang Cao, Yong Wang, Shanjun Mao

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  9. Explainable machine-learning predictions for catalysts in CO 2 -assisted propane oxidative dehydrogenation

    RSC Advances · 2024-01-01

    Hongyu Liu, Kang-Yu Liu, Hairuo Zhu, Weiqing Guo, Yuming Li

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  10. Rational design of single transition-metal atoms anchored on a PtSe 2 monolayer as bifunctional OER/ORR electrocatalysts: a defect chemistry and machine learning study

    Journal of Materials Chemistry A · 2024-01-01

    Shijiao Yue, Dongying Li, Aodi Zhang, Yuli Yan, Hongxia Yan, Zhenzhen Feng, Wentao Wang

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  11. High throughput screening for electrocatalysts for nitrogen reduction reaction using metal-doped bilayer borophene: A combined approach of DFT and machine learning

    Molecular Catalysis · 2024-02-28

    Chen Chen, Bo Xiao, Zhongwei Li, Wenzuo Li, Qingzhong Li, Xue-fang Yu

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  12. Prediction and evaluation of multiple output machine learning methods for ethylene oligomerization and aromatization kinetics modeling

    Reaction Chemistry & Engineering · 2025-01-01

    Bingbing Luo, Fang Jin

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  13. Computational condensed matter science contributions to addressing water emerging contaminant pollution: a comprehensive review

    Journal of Physics Condensed Matter · 2025-01-06

    José Rafael Bordin, Carolina Ferreira de Matos Jauris, Patrick Ruam Bredow Côrtes, Wanderson Souza Araújo, Luana S. Moreira, A. Santos, Mayara Bitencourt Leão, Elizane Efigenia de Moraes, Maurício J. Piotrowski, Mateus Henrique Köhler

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  14. 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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  15. Artificial intelligence in materials science and engineering: Current landscape, key challenges, and future trajectories

    Composite Structures · 2025-07-05

    Iman Peivaste, Salim Belouettar, Francesco Mercuri, Nicholas Fantuzzi, Hamidreza Dehghani, Razie Izadi, Halliru Ibrahim, Jakub Lengiewicz, Mael Belouettar-Mathis, Kouider Bendine, Ahmed Makradi, Martin Horsch, Peter Klein, M. Hachemi, Heinz A. Preisig, Yacine Rezgui, Natalia Konchakova, Ali Daouadji

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  16. AILD: An Interpretable AI Framework for Designing Logical Descriptors in Predicting CO Adsorption on Catalysts

    The Journal of Physical Chemistry A · 2025-12-23

    Yushun Chen, Zhiyong Xu, Tan Li, Wenbo Zhao

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  17. Machine learning-optimized bioinspired N-doped carbon-wrapped trimetallic oxides for an efficient oxygen evolution reaction

    Nanoscale · 2026-01-01

    Farhan Zafar, Hamdy Khamees Thabet, Muhammad Asad, Mehar Muhammad Hamza Maqbool, Muhammad Ali Khan, Naeem Akhtar, Sadaf Ul Hassan, Muhammad Shahid Nazir

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  18. Machine-learning-aided predicting and engineering of hydrochar nitrogen-containing functional groups

    Bioresource Technology · 2026-01-02

    Ning Liu, Jiefeng Chen, Xinni Lei, Weijin Zhang, Jia Feng, Hao Zhan, Lijian Leng, LI Hai-long

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  19. High-Throughput Electrochemistry Using Scanning Electrochemical Cells

    ACS electrochemistry. · 2026-03-13

    Joanna Magdalena Przybysz, Ken J. Jenewein, Serhiy Cherevko

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  20. 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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  21. Carbonaceous catalysts for the hydrolysis of cellulose

    Carbon letters · 2026-09-13

    Enoch Iraianbu, Mula Spurthy, Somak Chatterjee, Banasri Roy

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