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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 Machine Learning for Understanding Surface Structures of Heterogeneous Catalysts
Haobo Li, Yan Jiao, Kenneth Davey, et al.
Angewandte Chemie International Edition (2022) Vol. 62, Iss. 9
Open Access | Times Cited: 69

Showing 26-50 of 69 citing articles:

Urea Electrosynthesis Accelerated by Theoretical Simulations
Junxian Liu, Xiangyu Guo, Thomas Frauenheim, et al.
Advanced Functional Materials (2023) Vol. 34, Iss. 14
Open Access | Times Cited: 21
Achieving Digital Catalysis: Strategies for Data Acquisition, Storage and Use
Clara Patricia Marshall, Julia Schumann, Annette Trunschke
Angewandte Chemie International Edition (2023) Vol. 62, Iss. 30
Open Access | Times Cited: 17
Toward Next-Generation Heterogeneous Catalysts: Empowering Surface Reactivity Prediction with Machine Learning
Xinyan Liu, Hong‐Jie Peng
Engineering (2024) Vol. 39, pp. 25-44
Open Access | Times Cited: 7
Machine Learning Big Data Set Analysis Reveals C–C Electro-Coupling Mechanism
Haobo Li, Xinyu Li, Pengtang Wang, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 32, pp. 22850-22858
Closed Access | Times Cited: 7
AI‐Driven Electrolyte Additive Selection to Boost Aqueous Zn‐Ion Batteries Stability
Haobo Li, Junnan Hao, Shi Zhang Qiao
Advanced Materials (2024)
Open Access | Times Cited: 7
Recent advances and applications of machine learning in electrocatalysis
You Hu, Junhua Chen, Zheng Wei, et al.
Journal of Materials Informatics (2023) Vol. 3, Iss. 3
Open Access | Times Cited: 15
Effect of temperature and pressure on electrochemical CO2 reduction: A mini review
Shuang Zong, Aibing Chen, Marek Wiśniewski, et al.
Carbon Capture Science & Technology (2023) Vol. 8, pp. 100133-100133
Open Access | Times Cited: 14
Cu7S4/MxSy (M=Cd, Ni, and Mn) Janus Atomic Junctions for Plasmonic Energy Upconversion Boosted Multi‐Functional Photocatalysis
Meijun Guo, Amin Talebian‐Kiakalaieh, Bingquan Xia, et al.
Advanced Functional Materials (2023) Vol. 33, Iss. 46
Closed Access | Times Cited: 13
Enhancing electrochemical methane coupling in solid oxide cells by tuning oxygen species in the catalyst
Xiaoyong Xu, Haobo Li, Xu Han, et al.
Journal of Materials Chemistry A (2024) Vol. 12, Iss. 9, pp. 5115-5123
Closed Access | Times Cited: 4
AI unveils metal-support interaction principle to optimize catalyst design
Haobo Li
Chem Catalysis (2025) Vol. 5, Iss. 1, pp. 101231-101231
Closed Access
Facing the “Cutting Edge:” Edge Site Engineering on 2D Materials for Electrocatalysis and Photocatalysis
Yiran Ying, Ke Fan, Zezhou Lin, et al.
Advanced Materials (2025)
Open Access
Harnessing Physics-inspired Machine Learning to Design Nanocluster Catalysts for Dehydrogenating Liquid Organic Hydrogen Carriers
Chuhong Lin, Bryan Lee, Uzma Anjum, et al.
Applied Catalysis B Environment and Energy (2025), pp. 125192-125192
Closed Access
Fine-Tuning Graph Neural Networks via Active Learning: Unlocking the Potential of Graph Neural Networks Trained on Nonaqueous Systems for Aqueous CO2 Reduction
Zihao Jiao, Yu Mao, Ruihu Lu, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
Revealing the reconstruction mechanism of AgPd nanoalloys under fluorination based on a multiscale deep learning potential
Longfei Guo, Shuang Shan, Xiaoqing Liu, et al.
The Journal of Chemical Physics (2024) Vol. 160, Iss. 17
Closed Access | Times Cited: 3
Revolution of Artificial Intelligence in Computational Chemistry Breakthroughs
Anjaneyulu Bendi, Sanchita Goswami, Prithu Banik, et al.
Chemistry Africa (2024) Vol. 7, Iss. 6, pp. 3443-3459
Closed Access | Times Cited: 3
Rational electrocatalyst design for selective nitrate reduction to ammonia
Zhaodong Niu, Guoxiong Wang
Chemical Physics Reviews (2025) Vol. 6, Iss. 1
Open Access
Machine-learning-assisted Design of Cathode Catalysts for Metal-Sulfur/Oxygen/Carbon Dioxide Batteries
Qi Zhang, Rui Yang, Zhengran Wang, et al.
Energy storage materials (2025), pp. 104261-104261
Closed Access
Finite difference model of electrostatic channeling in TCA cycle enzymes
Christina Wark, Yan Xie, Scott Calabrese Barton
Electrochimica Acta (2025), pp. 146131-146131
Closed Access
Data-driven discovery of Pt single atom embedded germanosilicate MFI zeolite catalysts for propane dehydrogenation
Qiancheng Zhao, Lin Chen, Sicong Ma, et al.
Nature Communications (2025) Vol. 16, Iss. 1
Open Access
Artificial intelligence for catalyst design and synthesis
Longhai Zhang, Qiming Bing, Qin Huang, et al.
Matter (2025) Vol. 8, Iss. 5, pp. 102138-102138
Closed Access
Active-learning accelerated computational screening of A2B@NG catalysts for CO2 electrochemical reduction
Xinyu Li, Haobo Li, Zhen Zhang, et al.
Nano Energy (2023) Vol. 115, pp. 108695-108695
Open Access | Times Cited: 8
Fundamentals, Applications, and Perspectives of Liquid Metals in Catalysis: An Overview of Molecular Simulations
Xing Zhi, Fangxi Xie, Ali Zavabeti, et al.
Energy & Fuels (2023) Vol. 37, Iss. 23, pp. 17875-17891
Closed Access | Times Cited: 8
Applications and training sets of machine learning potentials
Chang‐Ho Hong, Jaehoon Kim, Jaesun Kim, et al.
Science and Technology of Advanced Materials Methods (2023) Vol. 3, Iss. 1
Open Access | Times Cited: 8
Single‐Atom Heterogeneous Catalysts: Human‐ and AI‐Driven Platform for Augmented Designs, Analytics and Reality‐Enabled Manufacturing
Lei Cheng, Yawen Tang, Kostya Ostrikov, et al.
Angewandte Chemie International Edition (2023) Vol. 63, Iss. 5
Closed Access | Times Cited: 7
Metalloenzyme-inspired approach to the design and applications of phosphatase-mimetic nanozymes. Bridging the inorganic and organic worlds
Pavel Janoš, Pavel Janoš
Environmental Science Nano (2024) Vol. 11, Iss. 8, pp. 3268-3285
Closed Access | Times Cited: 2

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