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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

AI-based optimization of PEM fuel cell catalyst layers for maximum power density via data-driven surrogate modeling
Bowen Wang, Biao Xie, Jin Xuan, et al.
Energy Conversion and Management (2020) Vol. 205, pp. 112460-112460
Open Access | Times Cited: 159

Showing 1-25 of 159 citing articles:

Fundamentals, materials, and machine learning of polymer electrolyte membrane fuel cell technology
Yun Wang, Bongjin Seo, Bowen Wang, et al.
Energy and AI (2020) Vol. 1, pp. 100014-100014
Open Access | Times Cited: 350
Multi-physics-resolved digital twin of proton exchange membrane fuel cells with a data-driven surrogate model
Bowen Wang, Guobin Zhang, Huizhi Wang, et al.
Energy and AI (2020) Vol. 1, pp. 100004-100004
Open Access | Times Cited: 158
Multi-objective optimization of PEM fuel cell by coupled significant variables recognition, surrogate models and a multi-objective genetic algorithm
LI Hong-we, Boshi Xu, Guolong Lu, et al.
Energy Conversion and Management (2021) Vol. 236, pp. 114063-114063
Closed Access | Times Cited: 157
Performance prediction of proton-exchange membrane fuel cell based on convolutional neural network and random forest feature selection
Weiwei Huo, Weier Li, Zehui Zhang, et al.
Energy Conversion and Management (2021) Vol. 243, pp. 114367-114367
Closed Access | Times Cited: 145
Porous Flow Field for Next-Generation Proton Exchange Membrane Fuel Cells: Materials, Characterization, Design, and Challenges
Guobin Zhang, Zhiguo Qu, Wen‐Quan Tao, et al.
Chemical Reviews (2022) Vol. 123, Iss. 3, pp. 989-1039
Closed Access | Times Cited: 124
Towards ultralow platinum loading proton exchange membrane fuel cells
Linhao Fan, Hao Deng, Yingguang Zhang, et al.
Energy & Environmental Science (2023) Vol. 16, Iss. 4, pp. 1466-1479
Closed Access | Times Cited: 112
A survey of Digital Twin techniques in smart manufacturing and management of energy applications
Yujie Wang, Xu Kang, Zonghai Chen
Green Energy and Intelligent Transportation (2022) Vol. 1, Iss. 2, pp. 100014-100014
Open Access | Times Cited: 97
Application of Machine Learning in Optimizing Proton Exchange Membrane Fuel Cells: A Review
Rui Ding, Shiqiao Zhang, Yawen Chen, et al.
Energy and AI (2022) Vol. 9, pp. 100170-100170
Open Access | Times Cited: 96
A systematic review of machine learning methods applied to fuel cells in performance evaluation, durability prediction, and application monitoring
Wuyi Ming, Peiyan Sun, Zhen Zhang, et al.
International Journal of Hydrogen Energy (2022) Vol. 48, Iss. 13, pp. 5197-5228
Closed Access | Times Cited: 96
Machine learning modeling for proton exchange membrane fuel cell performance
Adithya Legala, Jian Zhao, Xianguo Li
Energy and AI (2022) Vol. 10, pp. 100183-100183
Open Access | Times Cited: 78
Synergetic effect of N/O functional groups and microstructures of activated carbon on supercapacitor performance by machine learning
Mohammad Rahimi, Mohammad Hossein Abbaspour‐Fard, Abbas Rohani
Journal of Power Sources (2022) Vol. 521, pp. 230968-230968
Closed Access | Times Cited: 68
Integration of multi-physics and machine learning-based surrogate modelling approaches for multi-objective optimization of deformed GDL of PEM fuel cells
Jiankang Wang, Hai Jiang, Gaojian Chen, et al.
Energy and AI (2023) Vol. 14, pp. 100261-100261
Open Access | Times Cited: 48
Investigation of optimization and evaluation criteria for flow field in proton exchange membrane fuel cell: A critical review
Yu Zhou, Ben Chen
Renewable and Sustainable Energy Reviews (2023) Vol. 185, pp. 113584-113584
Closed Access | Times Cited: 46
Advancing next-generation proton-exchange membrane fuel cell development in multi-physics transfer
Guobin Zhang, Zhiguo Qu, Wen‐Quan Tao, et al.
Joule (2023) Vol. 8, Iss. 1, pp. 45-63
Closed Access | Times Cited: 42
Application of artificial intelligence techniques for modeling, optimizing, and controlling desalination systems powered by renewable energy resources
Enas Taha Sayed, A.G. Olabi, Khaled Elsaid, et al.
Journal of Cleaner Production (2023) Vol. 413, pp. 137486-137486
Closed Access | Times Cited: 39
Hydrogen fuel cell electric trains: Technologies, current status, and future
Daniel Z. Ding, Xiaoyu Wu
Applications in Energy and Combustion Science (2024) Vol. 17, pp. 100255-100255
Open Access | Times Cited: 23
Recent advances in artificial intelligence boosting materials design for electrochemical energy storage
X.-B. Liu, Kexin Fan, Xinmeng Huang, et al.
Chemical Engineering Journal (2024) Vol. 490, pp. 151625-151625
Open Access | Times Cited: 20
Machine learning and Bayesian optimization for performance prediction of proton-exchange membrane fuel cells
Soufian Echabarri, Phuc Do, Hai Canh Vu, et al.
Energy and AI (2024) Vol. 17, pp. 100380-100380
Open Access | Times Cited: 15
A review of machine learning applications in hydrogen electrochemical devices
Nikola Franić, Ivan Pivac, Frano Barbir
International Journal of Hydrogen Energy (2025) Vol. 102, pp. 523-544
Open Access | Times Cited: 1
Machine learning toward advanced energy storage devices and systems
Tianhan Gao, Wei Lu
iScience (2020) Vol. 24, Iss. 1, pp. 101936-101936
Open Access | Times Cited: 128
A Review of physics-based and data-driven models for real-time control of polymer electrolyte membrane fuel cells
Jian Zhao, Xianguo Li, Chris Shum, et al.
Energy and AI (2021) Vol. 6, pp. 100114-100114
Open Access | Times Cited: 99
Optimization of blocked channel design for a proton exchange membrane fuel cell by coupled genetic algorithm and three-dimensional CFD modeling
Wei-Zhuo Li, Weiwei Yang, Ning Wang, et al.
International Journal of Hydrogen Energy (2020) Vol. 45, Iss. 35, pp. 17759-17770
Closed Access | Times Cited: 96
Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation
Haoran Xu, Jingbo Ma, Peng Tan, et al.
Energy and AI (2020) Vol. 1, pp. 100003-100003
Open Access | Times Cited: 85
Current density and temperature distribution measurement and homogeneity analysis for a large-area proton exchange membrane fuel cell
Tianwei Miao, Chasen Tongsh, Jianan Wang, et al.
Energy (2021) Vol. 239, pp. 121922-121922
Closed Access | Times Cited: 71
Improvement of the three-dimensional fine-mesh flow field of proton exchange membrane fuel cell (PEMFC) using CFD modeling, artificial neural network and genetic algorithm
Zeting Yu, Lei Xia, Guoping Xu, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 82, pp. 35038-35054
Closed Access | Times Cited: 63
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