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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 interatomic potential: Bridge the gap between small-scale models and realistic device-scale simulations
Guanjie Wang, Changrui Wang, Xuanguang Zhang, et al.
iScience (2024) Vol. 27, Iss. 5, pp. 109673-109673
Open Access | Times Cited: 21

Showing 21 citing articles:

A review of displacement cascade simulations using molecular dynamics emphasizing interatomic potentials for TPBAR components
Ankit Roy, Giridhar Nandipati, Andrew M. Casella, et al.
npj Materials Degradation (2025) Vol. 9, Iss. 1
Open Access | Times Cited: 1
Advancing Food Security: The Role of Machine Learning in Pathogen Detection
Helen Onyeaka, Adenike A. Akinsemolu, Taghi Miri, et al.
Applied Food Research (2024), pp. 100532-100532
Open Access | Times Cited: 4
Lattice dynamics modeling of thermal transport in solids using machine-learned atomic cluster expansion potentials: A tutorial
Liangshuai Guo, Yuanbin Liu, Lei Yang, et al.
Journal of Applied Physics (2025) Vol. 137, Iss. 8
Open Access
Application of Machine Learning Interatomic Potentials in Heterogeneous Catalysis
Gbolagade Olajide, Khagendra Baral, Sophia Ezendu, et al.
(2025)
Closed Access
Non-Nernstian Effects in Theoretical Electrocatalysis
Dipam Manish Patel, Georg Kastlunger
Chemical Reviews (2025)
Closed Access
Shadow Molecular Dynamics with a Machine Learned Flexible Charge Potential
Cheng-Han Li, Mehmet Cagri Kaymak, Maksim Kulichenko, et al.
Journal of Chemical Theory and Computation (2025)
Closed Access
Advances in high-pressure materials discovery enabled by machine learning
Zhenyu Wang, Xiaoshan Luo, Q. Wang, et al.
Matter and Radiation at Extremes (2025) Vol. 10, Iss. 3
Open Access
Applications of machine learning in surfaces and interfaces
Shaofeng Xu, Jing‐Yuan Wu, Ying Guo, et al.
Chemical Physics Reviews (2025) Vol. 6, Iss. 1
Open Access
Advances in modeling complex materials: The rise of neuroevolution potentials
Penghua Ying, Cheng Qian, Rui Zhao, et al.
Chemical Physics Reviews (2025) Vol. 6, Iss. 1
Open Access
On simulating thin-film processes at the atomic scale using machine-learned force fields
Suresh Kondati Natarajan, Jens Schneider, Neha Pandey, et al.
Journal of Vacuum Science & Technology A Vacuum Surfaces and Films (2025) Vol. 43, Iss. 3
Closed Access
Knowledge-guided large language model for material science
Guanjie Wang, Jingjing Hu, Jian Zhou, et al.
(2025), pp. 100007-100007
Open Access
The evolution of machine learning potentials for molecules, reactions and materials
Junfan Xia, Yaolong Zhang, Bin Jiang
Chemical Society Reviews (2025)
Open Access
Advancing electrocatalyst discovery through the lens of data science: State of the art and perspectives☆
Xue Jia, Tianyi Wang, Di Zhang, et al.
Journal of Catalysis (2025), pp. 116162-116162
Open Access
Review of External Field Effects on Electrocatalysis: Machine Learning Guided Design
Lei Wang, Xuyan Zhou, Zihan Luo, et al.
Advanced Functional Materials (2024)
Closed Access | Times Cited: 3
Sparse Gaussian process based machine learning first principles potentials for materials simulations: Application to batteries, solar cells, catalysts, and macromolecular systems
Soohaeng Yoo Willow, Amir Hajibabaei, Miran Ha, et al.
Chemical Physics Reviews (2024) Vol. 5, Iss. 4
Open Access | Times Cited: 3
Recent machine learning-driven investigations into high entropy alloys: a comprehensive review
Yonggang Yan, Xunxiang Hu, Yalin Liao, et al.
Journal of Alloys and Compounds (2024), pp. 177823-177823
Closed Access | Times Cited: 3
Critical review of high-entropy alloys for catalysts: Design, synthesis, and applications
Long Luo, Huimin Han, Liangpan Chen, et al.
International Journal of Hydrogen Energy (2024) Vol. 90, pp. 885-917
Closed Access | Times Cited: 2
Machine Learning-Driven Advances in Metal-Organic Framework Nanomaterials for Wastewater Treatment: Developments and Challenges
V. Godvin Sharmila, M. Dinesh Kumar, K. Tamilarasan
Separation and Purification Reviews (2024), pp. 1-21
Closed Access | Times Cited: 2
Diamond under extremes
Alex C. Li, Boya Li, Felipe González‐Cataldo, et al.
Materials Science and Engineering R Reports (2024) Vol. 161, pp. 100857-100857
Closed Access | Times Cited: 1
Recent progress in mechanistic insights into cation effects on electrochemical CO2 reduction reactions
Xueping Qin, Renata Sechi, Heine Anton Hansen
Current Opinion in Electrochemistry (2024), pp. 101614-101614
Closed Access | Times Cited: 1
Knowledge Graphs in Smart Digital Libraries
Phayung Meesad, Anirach Mingkhwan
Studies in big data (2024), pp. 327-389
Closed Access
Efficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks
Rui Wang, Hongyu Yu, Yang Zhong, et al.
Journal of Materials Informatics (2024)
Open Access
Is the Future of Materials Amorphous? Challenges and Opportunities in Simulations of Amorphous Materials
Ata Madanchi, Emna Azek, Karim Zongo, et al.
ACS Physical Chemistry Au (2024) Vol. 5, Iss. 1, pp. 3-16
Open Access
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