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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-based intelligent framework for discovering refractory high-entropy alloys with improved high-temperature yield strength
Stephen A. Giles, Debasis Sengupta, Scott Broderick, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 46

Showing 1-25 of 46 citing articles:

Interpretable hardness prediction of high-entropy alloys through ensemble learning
Yifan Zhang, Wei Ren, Weili Wang, et al.
Journal of Alloys and Compounds (2023) Vol. 945, pp. 169329-169329
Closed Access | Times Cited: 43
A neural network model for high entropy alloy design
Jaemin Wang, Hyeonseok Kwon, Hyoung Seop Kim, et al.
npj Computational Materials (2023) Vol. 9, Iss. 1
Open Access | Times Cited: 33
Machine Learning Paves the Way for High Entropy Compounds Exploration: Challenges, Progress, and Outlook
Xuhao Wan, Zeyuan Li, Wei Yu, et al.
Advanced Materials (2023)
Closed Access | Times Cited: 30
Prediction of the yield strength of as-cast alloys using the random forest algorithm
Wei Zhang, Peiyou Li, Lin Wang, et al.
Materials Today Communications (2024) Vol. 38, pp. 108520-108520
Closed Access | Times Cited: 13
Data-driven design of novel lightweight refractory high-entropy alloys with superb hardness and corrosion resistance
Tianchuang Gao, Jianbao Gao, Shenglan Yang, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 9
Prediction and design of high hardness high entropy alloy through machine learning
Wei Ren, Yifan Zhang, Weili Wang, et al.
Materials & Design (2023) Vol. 235, pp. 112454-112454
Open Access | Times Cited: 21
Data‐Driven Materials Research and Development for Functional Coatings
Kai Xu, Xuelian Xiao, Linjing Wang, et al.
Advanced Science (2024)
Open Access | Times Cited: 7
Predictive analytics of wear performance in high entropy alloy coatings through machine learning
S. Sivaraman, N. Radhika
Physica Scripta (2024) Vol. 99, Iss. 7, pp. 076014-076014
Closed Access | Times Cited: 6
Unraveling dislocation-based strengthening in refractory multi-principal element alloys
T. Wang, Jiuyin Li, Mian Wang, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 6
Machine learning-assisted design of high-entropy alloys with superior mechanical properties
Jianye He, Zezhou Li, Pingluo Zhao, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 260-286
Open Access | Times Cited: 6
A novel tetragonal T-C2N supported transition metal atoms as superior bifunctional catalysts for OER/ORR: From coordination environment to rational design
Zhe Xue, Rui Tan, Hongxia Wang, et al.
Journal of Colloid and Interface Science (2023) Vol. 651, pp. 149-158
Closed Access | Times Cited: 16
Explainable AI for Material Property Prediction Based on Energy Cloud: A Shapley-Driven Approach
Faiza Qayyum, Murad Ali Khan, Do‐Hyeun Kim, et al.
Materials (2023) Vol. 16, Iss. 23, pp. 7322-7322
Open Access | Times Cited: 13
Machine Learning-Assisted Design of High-Entropy Alloys for Optimal Strength and Ductility
Shailesh K. Singh, Bashista Kumar Mahanta, Pankaj Rawat, et al.
Journal of Alloys and Compounds (2024) Vol. 1007, pp. 176282-176282
Closed Access | Times Cited: 5
Data-driven design of high bulk modulus high entropy alloys using machine learning
Sandeep Jain, Reliance Jain, Vinod Kumar, et al.
Journal of Alloys and Metallurgical Systems (2024) Vol. 8, pp. 100128-100128
Open Access | Times Cited: 5
Data mining accelerated the design strategy of high‐entropy alloys with the largest hardness based on genetic algorithm optimization
Xianzhe Jin, Hong Luo, Xuefei Wang, et al.
Materials Genome Engineering Advances (2024) Vol. 2, Iss. 2
Open Access | Times Cited: 4
Machine Learning-Assisted Investigation of Anisotropic Elasticity in Metallic Alloys
Weimin Zhang, Hamzah Ali Alkhazaleh, Majid Samavatian, et al.
Materials Today Communications (2024) Vol. 40, pp. 109950-109950
Closed Access | Times Cited: 4
Synergistic strength-ductility enhancement of AlNbTiVZr lightweight refractory high entropy alloys with regulated Laves distribution morphology: network-to-dispersed transformation
Yiqing Zhao, Longxiang Sun, Leilei Wang, et al.
Materials Science and Engineering A (2025), pp. 148001-148001
Closed Access
Elemental numerical descriptions to enhance classification and regression model performance for high-entropy alloys
Yan Zhang, Cheng Wen, Pengfei Dang, et al.
npj Computational Materials (2025) Vol. 11, Iss. 1
Open Access
Effects of Changing Atomic Concentration of a Single Element on the Yield Strength of High-Entropy Alloys: A Causal Inference Study
Nguyen Hai Chau, Tomoyuki Yamamoto
Journal of Electronic Materials (2025)
Closed Access
Design strategies and mechanical behaviour of high-strength eutectic high-entropy alloys: A comprehensive review
Sandeep Jain, Reliance Jain, Vinod Kumar, et al.
Journal of Alloys and Compounds (2025), pp. 180000-180000
Closed Access
Development of linear structure property relationship for energetic materials using machine learning
David A. Newsome, Ghanshyam L. Vaghjiani, Steven D. Chambreau, et al.
Journal of Molecular Liquids (2025), pp. 127480-127480
Closed Access
Introduction to Materials Informatics
M.R. Rahul
Challenges and advances in computational chemistry and physics (2025), pp. 3-12
Closed Access
Predictive and heuristic framework for high entropy alloys design: Integrating solid solution strengthening with machine learning
Zheng Zhang, Yuanpei Meng, Zongyu Zhang, et al.
Journal of Alloys and Compounds (2025), pp. 180484-180484
Closed Access
Data science and material informatics in physical metallurgy and material science: An overview of milestones and limitations
Desmond Klenam, T.K. Asumadu, Mobin Vandadi, et al.
Results in Materials (2023) Vol. 19, pp. 100455-100455
Open Access | Times Cited: 10
Transfer learning enables the rapid design of single crystal superalloys with superior creep resistances at ultrahigh temperature
Fan Yang, Wenyue Zhao, Yi Ru, et al.
npj Computational Materials (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 3
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