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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:

Deep learning-based phase prediction of high-entropy alloys: Optimization, generation, and explanation
Soo Young Lee, Seokyeong Byeon, Hyoung Seop Kim, et al.
Materials & Design (2020) Vol. 197, pp. 109260-109260
Open Access | Times Cited: 153

Showing 1-25 of 153 citing articles:

Machine learning for high-entropy alloys: Progress, challenges and opportunities
Xianglin Liu, Jiaxin Zhang, Zongrui Pei
Progress in Materials Science (2022) Vol. 131, pp. 101018-101018
Open Access | Times Cited: 188
Additive manufactured high entropy alloys: A review of the microstructure and properties
Wei Zhang, Ali Chabok, Bart J. Kooi, et al.
Materials & Design (2022) Vol. 220, pp. 110875-110875
Open Access | Times Cited: 141
Machine learning approach to predict new multiphase high entropy alloys
Yegi Vamsi Krishna, Ujjawal Kumar Jaiswal, M.R. Rahul
Scripta Materialia (2021) Vol. 197, pp. 113804-113804
Closed Access | Times Cited: 110
Machine-learning and high-throughput studies for high-entropy materials
E‐Wen Huang, Wen‐Jay Lee, Sudhanshu S. Singh, et al.
Materials Science and Engineering R Reports (2022) Vol. 147, pp. 100645-100645
Open Access | Times Cited: 91
Machine learning accelerates the materials discovery
Jiheng Fang, Ming Xie, Xingqun He, et al.
Materials Today Communications (2022) Vol. 33, pp. 104900-104900
Closed Access | Times Cited: 78
Comprehensive review on high entropy alloy-based coating
Santosh Kumar
Surface and Coatings Technology (2023) Vol. 477, pp. 130327-130327
Closed Access | Times Cited: 76
Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys
Guillermo Vazquez, Prashant Singh, Daniel Sauceda, et al.
Acta Materialia (2022) Vol. 232, pp. 117924-117924
Open Access | Times Cited: 70
A map of single-phase high-entropy alloys
Wei Chen, Antoine Hilhorst, Georgios Bokas, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 60
Recent applications of machine learning in alloy design: A review
Mingwei Hu, Qiyang Tan, Ruth Knibbe, et al.
Materials Science and Engineering R Reports (2023) Vol. 155, pp. 100746-100746
Closed Access | Times Cited: 57
The integral role of high‐entropy alloys in advancing solid‐state hydrogen storage
Zhao Ding, Yuting Li, Han Jiang, et al.
Interdisciplinary materials (2024)
Open Access | Times Cited: 18
A Comprehensive Review on Deep Learning Applications in Advancing Biodiesel Feedstock Selection and Production Processes
Olugbenga Akande, Jude A. Okolie, Richard Kimera, et al.
Green Energy and Intelligent Transportation (2025), pp. 100260-100260
Open Access | Times Cited: 2
High Entropy Alloy Coatings and Technology
Ashutosh Sharma
Coatings (2021) Vol. 11, Iss. 4, pp. 372-372
Open Access | Times Cited: 97
High‐Entropy Energy Materials in the Age of Big Data: A Critical Guide to Next‐Generation Synthesis and Applications
Qingsong Wang, Leonardo Velasco, Ben Breitung, et al.
Advanced Energy Materials (2021) Vol. 11, Iss. 47
Open Access | Times Cited: 76
Phase classification of multi-principal element alloys via interpretable machine learning
Kyungtae Lee, Mukil V. Ayyasamy, Paige Delsa, et al.
npj Computational Materials (2022) Vol. 8, Iss. 1
Open Access | Times Cited: 57
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
Phase formation prediction of high-entropy alloys: a deep learning study
Wenhan Zhu, Wenyi Huo, Shiqi Wang, et al.
Journal of Materials Research and Technology (2022) Vol. 18, pp. 800-809
Open Access | Times Cited: 45
Machine Learning–Assisted Design of Material Properties
Sanket Kadulkar, Zachary M. Sherman, Venkat Ganesan, et al.
Annual Review of Chemical and Biomolecular Engineering (2022) Vol. 13, Iss. 1, pp. 235-254
Open Access | Times Cited: 38
Phase prediction and experimental realisation of a new high entropy alloy using machine learning
Swati Singh, Nirmal Kumar Katiyar, Saurav Goel, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 38
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
Methods, progresses, and opportunities of materials informatics
Chen Li, Kun Zheng
InfoMat (2023) Vol. 5, Iss. 8
Open Access | Times Cited: 28
Design of high-performance high-entropy nitride ceramics via machine learning-driven strategy
Qian Zhou, Feng Xu, Chengzuan Gao, et al.
Ceramics International (2023) Vol. 49, Iss. 15, pp. 25964-25979
Open Access | Times Cited: 23
Machine Learning Design for High-Entropy Alloys: Models and Algorithms
S. Liu, Chao Yang
Metals (2024) Vol. 14, Iss. 2, pp. 235-235
Open Access | Times Cited: 15
High-throughput and data-driven machine learning techniques for discovering high-entropy alloys
Lu Zhichao, Dong Ma, Liu Xiongjun, et al.
Communications Materials (2024) Vol. 5, Iss. 1
Open Access | Times Cited: 13
Machine learning prediction and characterization of sigma-free high-entropy alloys
Mohammad Sajad Mehranpour, Ali Koushki, Seyed Soroush Karimi Madahi, et al.
Materials Characterization (2024) Vol. 212, pp. 113937-113937
Closed Access | Times Cited: 10
Explainable Machine Learning based approach for the design of new refractory high entropy alloys
Saswati Swateelagna, Manish Kumar Singh, M.R. Rahul
Intermetallics (2024) Vol. 167, pp. 108198-108198
Closed Access | Times Cited: 9
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