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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:

Phase prediction and effect of intrinsic residual strain on phase stability in high-entropy alloys with machine learning
Huinan Chang, Yiwen Tao, Peter K. Liaw, et al.
Journal of Alloys and Compounds (2022) Vol. 921, pp. 166149-166149
Open Access | Times Cited: 38

Showing 1-25 of 38 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: 45
Predict the phase formation of high-entropy alloys by compositions
Qingwei Guo, Xiaotao Xu, Xiaolong Pei, et al.
Journal of Materials Research and Technology (2022) Vol. 22, pp. 3331-3339
Open Access | Times Cited: 63
Molecular dynamics simulation and machine learning-based analysis for predicting tensile properties of high-entropy FeNiCrCoCu alloys
Omarelfarouq Elgack, Belal Almomani, Junaidi Syarif, et al.
Journal of Materials Research and Technology (2023) Vol. 25, pp. 5575-5585
Open Access | Times Cited: 32
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: 31
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: 24
Fatigue life prediction of the FCC-based multi-principal element alloys via domain knowledge-based machine learning
Xiao Lu, Gang Wang, Weimin Long, et al.
Engineering Fracture Mechanics (2024) Vol. 296, pp. 109860-109860
Closed Access | Times Cited: 13
Machine learning studies for magnetic compositionally complex alloys: A critical review
Xin Li, C.H. Shek, Peter K. Liaw, et al.
Progress in Materials Science (2024) Vol. 146, pp. 101332-101332
Closed Access | Times Cited: 9
Overview: recent studies of machine learning in phase prediction of high entropy alloys
Yonggang Yan, Dan Lü, Kun Wang
Tungsten (2022) Vol. 5, Iss. 1, pp. 32-49
Closed Access | Times Cited: 33
Microstructure and mechanical property of Al,Ti co-adding L21-strengthened NiCrFe-based HEAs
Hanqing Xu, Mengdi Zhang, Gaimei Zhang, et al.
Materials Characterization (2023) Vol. 207, pp. 113516-113516
Closed Access | Times Cited: 17
Machine learning-based prediction of pitting corrosion resistance in stainless steels exposed to chloride environments
C. F. Qiao, Hong Luo, Xuefei Wang, et al.
Colloids and Surfaces A Physicochemical and Engineering Aspects (2023) Vol. 676, pp. 132274-132274
Closed Access | Times Cited: 15
Data-driven analysis and prediction of stable phases for high-entropy alloy design
Iman Peivaste, Ericmoore Jossou, Ahmed A. Tiamiyu
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 15
Multi-component thin films and coatings
Yunlong Zhu, Junzhi Cui, Xiaoxiang Guo, et al.
Materials & Design (2024), pp. 112664-112664
Open Access | Times Cited: 6
Sparse identification-assisted exploration of the atomic-scale deformation mechanism in multiphase CoCrFeNi high-entropy alloys
Xiao Lu, Xiaoxiang Guo, YuTong Sun, et al.
Science China Technological Sciences (2024) Vol. 67, Iss. 4, pp. 1124-1132
Closed Access | Times Cited: 4
Machine learning accelerated design of a family of AlxCrFeNi medium entropy alloys with superior high temperature mechanical and oxidation properties
Ling Qiao, R.V. Ramanujan, Jingchuan Zhu
Corrosion Science (2022) Vol. 211, pp. 110805-110805
Open Access | Times Cited: 18
A multimodal data-driven design of low pressure die casting gating system for aluminum alloy cabin
Zhiqiang Duan, Weipeng Chen, Xiao-long Pei, et al.
Journal of Materials Research and Technology (2023) Vol. 27, pp. 2723-2736
Open Access | Times Cited: 11
Machine learning aided high-throughput first-principles calculations to predict the formation enthalpy of σ phase
Yue Su, Jiong Wang
Calphad (2023) Vol. 82, pp. 102599-102599
Closed Access | Times Cited: 10
Machine learning-based phase prediction in high-entropy alloys: further optimization of feature engineering
Guiyang Liu, Qingqing Wu, Yong Ma, et al.
Journal of Materials Science (2025)
Closed Access
Developing new high-entropy alloys with enhanced hardness using a hybrid machine learning approach: integrating interpretability and NSGA-II optimization
Debsundar Dey, Anik Pal, P. Biyani, et al.
Journal of Materials Science (2025)
Closed Access
Phase Stability and Transitions in High-Entropy Alloys: Insights from Lattice Gas Models, Computational Simulations, and Experimental Validation
Łukasz Łach
Entropy (2025) Vol. 27, Iss. 5, pp. 464-464
Open Access
Machine-Learning-Assisted Phase Prediction in High-Entropy Alloys Using Two-Step Feature Selection Strategy
Jiayu Wang, Ke Liu, Lei Zhao, et al.
Acta Metallurgica Sinica (English Letters) (2025)
Closed Access
Criteria of predicting phase formation for MSi2-Type High-Entropy refractory metal silicides
Laiqi Zhang, Huicong Li, Zepeng Xiao
Materials & Design (2023) Vol. 231, pp. 112060-112060
Open Access | Times Cited: 9
Machine learning – informed development of high entropy alloys with enhanced corrosion resistance
H.C. Ozdemir, A. Nazarahari, Bengisu Yılmaz, et al.
Electrochimica Acta (2023) Vol. 476, pp. 143722-143722
Closed Access | Times Cited: 9
Phase prediction of high-entropy alloys based on machine learning and an improved information fusion approach
Cun Chen, Xiaoli Han, Yong Zhang, et al.
Computational Materials Science (2024) Vol. 239, pp. 112976-112976
Open Access | Times Cited: 3
Data extension-based analysis and application selection of process-composition-properties of die casting aluminum alloy
Jian Yang, Bo Liu, Yunbo Zeng, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108514-108514
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
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