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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:

Data-driven design of double-atom catalysts with high H2 evolution activity/CO2 reduction selectivity based on simple features
Chenyang Wei, Dingyi Shi, Zhaohui Yang, et al.
Journal of Materials Chemistry A (2023) Vol. 11, Iss. 34, pp. 18168-18178
Closed Access | Times Cited: 11

Showing 11 citing articles:

Theoretical Calculation Assisted by Machine Learning Accelerate Optimal Electrocatalyst Finding for Hydrogen Evolution Reaction
Yue‐Fei Zhang, Xuefei Liu, Wentao Wang
ChemElectroChem (2024) Vol. 11, Iss. 13
Open Access | Times Cited: 4
Mechanical Reversal in the Catalytic Capability of Monolayer Transition Metal Dichalcogenides for Hydrogen Evolution Reaction: An Explicit First-Principles Study
Jing Xu, Wanlin Guo, Yufeng Guo
ACS Applied Materials & Interfaces (2025)
Closed Access
Computational Approaches for Designing Heterostructured Electrocatalysts
Miyeon Kim, Kyu In Shim, Jeong Woo Han
Small Science (2025)
Open Access
Interpretable physics-informed machine learning approaches to accelerate electrocatalyst development
Hao Wu, Mingxuan Chen, Hao Cheng, et al.
Journal of Materials Informatics (2025) Vol. 5, Iss. 2
Open Access
Large Language Models Assisted Materials Development: Case of Predictive Analytics for Oxygen Evolution Reaction Catalysts of (Oxy)hydroxides
Chenyang Wei, Yutong Shi, Wenbo Mu, et al.
ACS Sustainable Chemistry & Engineering (2025)
Closed Access
Revolutionizing heterogeneous catalysis: Dual-atom catalysts as the next frontier in green chemistry
Wen Jiang, Qiang Xiao, Weidong Zhu, et al.
Fuel (2025) Vol. 396, pp. 135262-135262
Closed Access
A machine learning model with minimize feature parameters for multi-type hydrogen evolution catalyst prediction
Chao Wang, Bing Wang, Changhao Wang, et al.
npj Computational Materials (2025) Vol. 11, Iss. 1
Open Access
An environmental corrected descriptor based on d‐orbital spin states for atomically dispersed dual‐metal catalysts
Linkai Han, Wenhao Qiu, Zhonghua Xiang
AIChE Journal (2024) Vol. 70, Iss. 8
Closed Access | Times Cited: 2
Harnessing the Potential of Machine Learning to Optimize the Activity of Cu-Based Dual Atom Catalysts for CO2 Reduction Reaction
A. Das, Diptendu Roy, Souvik Manna, et al.
ACS Materials Letters (2024), pp. 5316-5324
Closed Access | Times Cited: 2
Highly selective electrosynthesis of 3,4-dihydroisoquinoline accompanied with hydrogen production over three-dimensional hollow CoNi-based microarray electrocatalysts
Xin Yu, Liyu Chen, Yingwei Li, et al.
Nano Research (2023) Vol. 17, Iss. 4, pp. 2509-2519
Closed Access | Times Cited: 6
Machine learning-assisted the Ag/Ni(OH)2 heterostructure design for boosting electrocatalytic hydrogen evolution through charge redistribution
Yangshuo Liu, Keke Huang, Yao Meng, et al.
Fuel (2024) Vol. 381, pp. 133593-133593
Closed Access | Times Cited: 1
A supported Ni2 dual-atoms site hollow urchin-like carbon catalyst for synergistic CO2 electroreduction
Jianhua Shen, Zhenping Pan
Journal of Colloid and Interface Science (2024) Vol. 673, pp. 486-495
Closed Access
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