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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:

Physics-informed machine learning for battery degradation diagnostics: A comparison of state-of-the-art methods
Sina Navidi, Adam Thelen, Tingkai Li, et al.
Energy storage materials (2024) Vol. 68, pp. 103343-103343
Open Access | Times Cited: 13

Showing 13 citing articles:

A battery capacity trajectory prediction framework with mileage correction for electric buses
Yifei Xu, Hengzhao Yang
Journal of Energy Storage (2025) Vol. 110, pp. 115301-115301
Closed Access | Times Cited: 1
Application of physics-informed neural networks in fault diagnosis and fault-tolerant control design for electric vehicles: A review
Arslan Ahmed Amin, Amir Zaki Mubarak, Saba Waseem
Measurement (2025), pp. 116728-116728
Closed Access | Times Cited: 1
Interpretable Learning of Accelerated Aging in Lithium Metal Batteries
Xinyan Liu, Bobo Zou, Ya-Nan Wang, et al.
Journal of the American Chemical Society (2024)
Closed Access | Times Cited: 8
Insight Understanding of External Pressure on Lithium Plating in Commercial Lithium‐Ion Batteries
Hanqing Yu, Li Wang, Zhiguo Zhang, et al.
Advanced Functional Materials (2024)
Closed Access | Times Cited: 7
Integration of lithium-ion battery recycling into manufacturing through digitalization: A perspective
Imelda Cardenas-Sierra, Utkarsh Vijay, Frédéric Aguesse, et al.
Journal of Power Sources (2025) Vol. 631, pp. 236158-236158
Open Access
A hybrid methodology for assessing hydropower plants under flexible operations: Leveraging experimental data and machine learning techniques
Ali Amini, S Rey-Mermet, Steve Crettenand, et al.
Applied Energy (2025) Vol. 383, pp. 125402-125402
Open Access
Battery health prognosis in data-deficient practical scenarios via reconstructed voltage-based machine learning
Wu Wei, Zhen Chen, Weijie Liu, et al.
Cell Reports Physical Science (2025), pp. 102442-102442
Open Access
Battery fault diagnosis methods for electric vehicle Lithium-ion batteries: correlating codes and battery management system
G. Naresh, T. Praveenkumar, Dinesh Kumar Madheswaran, et al.
Process Safety and Environmental Protection (2025), pp. 106919-106919
Closed Access
Artificial Intelligence-Driven Electric Vehicle Battery Lifetime Diagnostics
Jingyuan Zhao, Andrew Burke
IntechOpen eBooks (2025)
Closed Access
Method for Evaluating Degradation of Battery Capacity Based on Partial Charging Segments for Multi-Type Batteries
Yujuan Sun, Hao Tian, Fangfang Hu, et al.
Batteries (2024) Vol. 10, Iss. 6, pp. 187-187
Open Access | Times Cited: 2
Forecasting battery degradation trajectory under domain shift with domain generalization
Ruifeng Tan, Xibin Lu, Minhao Cheng, et al.
Energy storage materials (2024) Vol. 72, pp. 103725-103725
Open Access | Times Cited: 1
A facile physics-based model for non-destructive diagnosis of battery degradation
Zhenya Wang, Dmitri L. Danilov, Zhiqiang Chen, et al.
Journal of Energy Storage (2024) Vol. 101, pp. 113819-113819
Open Access | Times Cited: 1
Decoding degradation: The synergy of partial differential equations and advanced predictive models for lithium-ion battery
Sahil Kadiwala, Prince Savsaviya, Siddhi Vinayak Pandey, et al.
Journal of Power Sources (2024) Vol. 627, pp. 235771-235771
Closed Access | Times Cited: 1
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