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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:

Prediction of electrochemical corrosion behavior of magnesium alloy using machine learning methods
Atwakyire Moses, Ding Chen, Peng Wan, et al.
Materials Today Communications (2023) Vol. 37, pp. 107285-107285
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Enhancing wear and corrosion resistance of magnesium alloys through in-situ Al2O3 doping for plasma electrolytic oxidation coating
Yan Li, Chen Li, Quanfu Wang, et al.
Materials Today Communications (2024) Vol. 38, pp. 108234-108234
Closed Access | Times Cited: 11
Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications
Sreenivas Raguraman, Maitreyee Sharma Priyadarshini, Tram Nguyen, et al.
Journal of Magnesium and Alloys (2024) Vol. 12, Iss. 6, pp. 2267-2283
Open Access | Times Cited: 7
Prediction of creep rupture life of ODS steels based on machine learning
Tian-Xing Yang, Peng Dou
Materials Today Communications (2024) Vol. 38, pp. 108117-108117
Closed Access | Times Cited: 5
Prediction of hardness or yield strength for ODS steels based on machine learning
Tian-Xing Yang, Peng Dou
Materials Characterization (2024) Vol. 211, pp. 113886-113886
Closed Access | Times Cited: 4
Machine learning-assisted prediction and interpretation of electrochemical corrosion behavior in high-entropy alloys
Yun Zou, Jiahao Qian, Xu Wang, et al.
Computational Materials Science (2024) Vol. 244, pp. 113259-113259
Closed Access | Times Cited: 4
Construction of a time-frequency measurement system and its application in sensing biofilms based on XGBoost model
Boyu Guo, Jun Yu, Huiming Bao, et al.
Measurement (2025), pp. 116735-116735
Closed Access
Rapid prediction of the corrosion behaviour of coated biodegradable magnesium alloys using phase field simulation and machine learning
Songyun Ma, Dawei Zhang, Peilei Zhang, et al.
Computational Materials Science (2024) Vol. 247, pp. 113546-113546
Open Access | Times Cited: 3
State-of-the-art progress on artificial intelligence and machine learning in accessing molecular coordination and adsorption of corrosion inhibitors
Taiwo W. Quadri, Ekemini D. Akpan, Saheed E. Elugoke, et al.
Applied Physics Reviews (2025) Vol. 12, Iss. 1
Closed Access
Insights into the high-temperature oxidation and electrochemical corrosion behavior of Si alloyed TiAl alloys and the prediction of corrosion behavior using machine learning approaches
Y. Garip, O. Ozdemir
Journal of Alloys and Compounds (2025), pp. 179023-179023
Closed Access
Using Artificial Neural Networks in Designing and Developing Magnesium-Based Materials for Degradable Implant Applications
Manoj Kumar Elipey, P.S. Kishore, Ratna Sunil Buradagunta
Advances in chemical and materials engineering book series (2025), pp. 231-244
Closed Access
An intelligent screening for rare earth in Ni alloy based on machine learning and multi-objective optimisation
Zengyi Zhong, Xianggang Wu, Yongzhi Huang, et al.
The Philosophical Magazine A Journal of Theoretical Experimental and Applied Physics (2025), pp. 1-18
Closed Access
Comparative Study of Wear Behaviour of ZA37 Alloy, ZA37/SiC Composite, and Grey Cast Iron under Lubricated Conditions: Predictive Modeling by Machine Learning
Khursheed Ahmad Sheikh, Mohammad Mohsin Khan, Mohd Nadeem Bhat
Tribology International (2025), pp. 110623-110623
Closed Access
Modeling and analysis between texture evolution and mechanical properties of ZK60 magnesium alloy based on artificial neural network
Hongwei Yan, Qingshan Yang, Dan Zhang, et al.
Materials Today Communications (2025) Vol. 44, pp. 112150-112150
Closed Access
Unraveling the relationship between severe plastic deformation and corrosion responses of AZ31 Mg alloys
Yuming Xie, Jianing Dong, Lianmei Wu, et al.
Corrosion Science (2025), pp. 112881-112881
Closed Access
Fast screening of high anti-corrosion Ta ternary alloys by machine learning and electron-level descriptors
Yuanjiang Lv, Wenqian Sun, Qiaomei Luo, et al.
Materials Chemistry and Physics (2025), pp. 130820-130820
Closed Access
Accurate prediction of pitting corrosion in aluminum alloys via integrated multi-model methods
Zhenchang Xu, Xinliang Li, Baoyu Cai, et al.
Progress in Natural Science Materials International (2025)
Closed Access
Investigation of Microstructure, Corrosion Performance and Mechanical Properties of Mg- 6.5Zn- 7.24Sn- 1.22Ca Alloy
Md Nahid Rahman Nafi, Aninda Nafis Ahmed, Hossain M.M.A. Rashed
Applied Mechanics and Materials (2025) Vol. 925, pp. 59-75
Closed Access
Studying corrosion resistance of ODS steels in supercritical water by machine learning
Tian-Xing Yang, Peng Dou
Journal of Iron and Steel Research International (2025)
Closed Access
Corrosion modeling of Magnesium and its alloys: A short review
A. Ortiz-Ozuna, Marvin Montoya-Rangel, Homero Castaneda, et al.
Materials Today Communications (2025), pp. 112491-112491
Open Access
Machine learning-assisted prediction and interpretation of electrochemical corrosion behavior in Mg–Li alloys
Xu Wang, Yang Li, Jiahao Qian, et al.
Electrochimica Acta (2025), pp. 146426-146426
Closed Access
Unraveling Magnesium Alloy Corrosion Patterns Through Unsupervised Machine Learning: Exploring Clustering Techniques for Enhanced Insight
Atwakyire Moses, Peng Xie, Siyuan Wang, et al.
JOM (2024) Vol. 76, Iss. 8, pp. 4388-4403
Closed Access | Times Cited: 3
Machine learning-based predictive approach for pitting and uniform corrosion in geothermal energy systems
Pawan Bohane, Trushar B. Gohil, Ajeet K. Srivastav
Electrochimica Acta (2024) Vol. 504, pp. 144884-144884
Closed 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
Theoretical Screening of Transition Metal Alloys with High Corrosion Resistance: The Case of Ta-Based Alloys as an Example
Yuanjiang Lv, Jianping Gao, Qiaomei Luo, et al.
The Journal of Physical Chemistry C (2024) Vol. 128, Iss. 19, pp. 8123-8130
Closed Access | Times Cited: 2
An Efficient Corrosion Prediction Model Based on Genetic Feedback Propagation Neural Network
Ziheng Zhao, Elmi Bin Abu Bakar, Norizham Bin Abdul Razak, et al.
Arabian Journal for Science and Engineering (2024)
Closed Access | Times Cited: 2
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