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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:

Machine learning: Accelerating materials development for energy storage and conversion
An Chen, Xu Zhang, Zhen Zhou
InfoMat (2020) Vol. 2, Iss. 3, pp. 553-576
Open Access | Times Cited: 283

Showing 1-25 of 283 citing articles:

“More is Different:” Synergistic Effect and Structural Engineering in Double‐Atom Catalysts
Yiran Ying, Xin Luo, Jinli Qiao, et al.
Advanced Functional Materials (2020) Vol. 31, Iss. 3
Open Access | Times Cited: 278
Machine Learning: An Advanced Platform for Materials Development and State Prediction in Lithium‐Ion Batteries
Chade Lv, Xin Zhou, Lixiang Zhong, et al.
Advanced Materials (2021) Vol. 34, Iss. 25
Open Access | Times Cited: 260
Lithium lanthanum titanate perovskite as an anode for lithium ion batteries
Lu Zhang, Xiaohua Zhang, Guiying Tian, et al.
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 191
2D Materials Bridging Experiments and Computations for Electro/Photocatalysis
Xu Zhang, An Chen, Letian Chen, et al.
Advanced Energy Materials (2021) Vol. 12, Iss. 4
Closed Access | Times Cited: 184
Electrochemical reduction of carbon dioxide to multicarbon (C2+) products: challenges and perspectives
Bin Chang, Hong Pang, Fazal Raziq, et al.
Energy & Environmental Science (2023) Vol. 16, Iss. 11, pp. 4714-4758
Open Access | Times Cited: 168
A Machine Learning Model on Simple Features for CO2 Reduction Electrocatalysts
An Chen, Xu Zhang, Letian Chen, et al.
The Journal of Physical Chemistry C (2020) Vol. 124, Iss. 41, pp. 22471-22478
Closed Access | Times Cited: 162
Machine learning for advanced energy materials
Liu Yun, Oladapo Christopher Esan, Zhefei Pan, et al.
Energy and AI (2021) Vol. 3, pp. 100049-100049
Open Access | Times Cited: 151
CHAIN: Cyber Hierarchy and Interactional Network Enabling Digital Solution for Battery Full-Lifespan Management
Shichun Yang, Rong He, Zhengjie Zhang, et al.
Matter (2020) Vol. 3, Iss. 1, pp. 27-41
Open Access | Times Cited: 142
Effect of pore structure and doping species on charge storage mechanisms in porous carbon-based supercapacitors
Lijing Xie, Fangyuan Su, Longfei Xie, et al.
Materials Chemistry Frontiers (2020) Vol. 4, Iss. 9, pp. 2610-2634
Open Access | Times Cited: 139
Unravelling the origin of bifunctional OER/ORR activity for single-atom catalysts supported on C2N by DFT and machine learning
Yiran Ying, Ke Fan, Xin Luo, et al.
Journal of Materials Chemistry A (2021) Vol. 9, Iss. 31, pp. 16860-16867
Open Access | Times Cited: 139
Reviewing machine learning of corrosion prediction in a data-oriented perspective
Leonardo Bertolucci Coelho, Dawei Zhang, Yves Van Ingelgem, et al.
npj Materials Degradation (2022) Vol. 6, Iss. 1
Open Access | Times Cited: 138
Prospective Methodologies in Hybrid Renewable Energy Systems for Energy Prediction Using Artificial Neural Networks
Md. Mijanur Rahman, Mohammad Shakeri, Tiong Sieh Kiong, et al.
Sustainability (2021) Vol. 13, Iss. 4, pp. 2393-2393
Open Access | Times Cited: 128
Polymer‐/Ceramic‐based Dielectric Composites for Energy Storage and Conversion
Hong‐Hui Wu, Fangping Zhuo, Huimin Qiao, et al.
Energy & environment materials (2021) Vol. 5, Iss. 2, pp. 486-514
Open Access | Times Cited: 126
The role of artificial intelligence in the mass adoption of electric vehicles
Moin Ahmed, Yun Zheng, Anna Amine, et al.
Joule (2021) Vol. 5, Iss. 9, pp. 2296-2322
Closed Access | Times Cited: 110
Advanced Cathode Materials for Protonic Ceramic Fuel Cells: Recent Progress and Future Perspectives
Ning Wang, Chunmei Tang, Lei Du, et al.
Advanced Energy Materials (2022) Vol. 12, Iss. 34
Closed Access | Times Cited: 108
Data‐Driven Materials Innovation and Applications
Zhuo Wang, Zhehao Sun, Hang Yin, et al.
Advanced Materials (2022) Vol. 34, Iss. 36
Closed Access | Times Cited: 106
Intelligent disassembly of electric-vehicle batteries: a forward-looking overview
Kai Meng, Guiyin Xu, Xianghui Peng, et al.
Resources Conservation and Recycling (2022) Vol. 182, pp. 106207-106207
Closed Access | Times Cited: 103
Theory-guided experimental design in battery materials research
Alex Yong Sheng Eng, Chhail Bihari Soni, Yanwei Lum, et al.
Science Advances (2022) Vol. 8, Iss. 19
Open Access | Times Cited: 95
Catalytic Hydrogenation of CO2 to Methanol: A Review
Menghao Ren, Yanmin Zhang, Xuan Wang, et al.
Catalysts (2022) Vol. 12, Iss. 4, pp. 403-403
Open Access | Times Cited: 90
Overview on Theoretical Simulations of Lithium‐Ion Batteries and Their Application to Battery Separators
D. Miranda, Renato Gonçalves, Stefan Wuttke, et al.
Advanced Energy Materials (2023) Vol. 13, Iss. 13
Open Access | Times Cited: 89
Emerging Trends in Sustainable CO2‐Management Materials
Zhen Zhang, Yun Zheng, Lanting Qian, et al.
Advanced Materials (2022) Vol. 34, Iss. 29
Closed Access | Times Cited: 88
Toward Excellence of Electrocatalyst Design by Emerging Descriptor‐Oriented Machine Learning
Jianwen Liu, Wenzhi Luo, Lei Wang, et al.
Advanced Functional Materials (2022) Vol. 32, Iss. 17
Closed Access | Times Cited: 77
Machine Learning: A New Paradigm in Computational Electrocatalysis
Xu Zhang, Yun Tian, Letian Chen, et al.
The Journal of Physical Chemistry Letters (2022) Vol. 13, Iss. 34, pp. 7920-7930
Closed Access | Times Cited: 74
Atomic‐Level Design of Active Site on Two‐Dimensional MoS2 toward Efficient Hydrogen Evolution: Experiment, Theory, and Artificial Intelligence Modelling
Chunwen Sun, Longlu Wang, Weiwei Zhao, et al.
Advanced Functional Materials (2022) Vol. 32, Iss. 38
Closed Access | Times Cited: 73
Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics
Hong Zhou, Liangge Xu, Zhihao Ren, et al.
Nanoscale Advances (2022) Vol. 5, Iss. 3, pp. 538-570
Open Access | Times Cited: 73
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