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:
Insights into metal glass forming ability based on data-driven analysis
Tinghong Gao, Yong Ma, Yutao Liu, et al.
Materials & Design (2023) Vol. 232, pp. 112129-112129
Open Access | Times Cited: 8
Tinghong Gao, Yong Ma, Yutao Liu, et al.
Materials & Design (2023) Vol. 232, pp. 112129-112129
Open Access | Times Cited: 8
Showing 8 citing articles:
Prediction of mechanical properties of high entropy alloys based on machine learning
Tinghong Gao, Qingqing Wu, Lei Chen, et al.
Physica Scripta (2025) Vol. 100, Iss. 4, pp. 046013-046013
Closed Access
Tinghong Gao, Qingqing Wu, Lei Chen, et al.
Physica Scripta (2025) Vol. 100, Iss. 4, pp. 046013-046013
Closed Access
Research on glass-forming ability based on transformer and tabular data transformation
Yuancheng Lin, Yongchao Liang, Qian Chen
Journal of Non-Crystalline Solids (2025) Vol. 652, pp. 123416-123416
Closed Access
Yuancheng Lin, Yongchao Liang, Qian Chen
Journal of Non-Crystalline Solids (2025) Vol. 652, pp. 123416-123416
Closed Access
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
Guiyang Liu, Qingqing Wu, Yong Ma, et al.
Journal of Materials Science (2025)
Closed Access
Uncovering metallic glasses hidden vacancy-like motifs using machine learning
Suyue Yuan, Aoyan Liang, Chang Liu, et al.
Materials & Design (2023) Vol. 233, pp. 112185-112185
Open Access | Times Cited: 5
Suyue Yuan, Aoyan Liang, Chang Liu, et al.
Materials & Design (2023) Vol. 233, pp. 112185-112185
Open Access | Times Cited: 5
An end-to-end explainable graph neural networks-based composition to mechanical properties prediction framework for bulk metallic glasses
Tao Long, Zhilin Long, Bo Pang
Mechanics of Materials (2024) Vol. 191, pp. 104945-104945
Closed Access | Times Cited: 1
Tao Long, Zhilin Long, Bo Pang
Mechanics of Materials (2024) Vol. 191, pp. 104945-104945
Closed Access | Times Cited: 1
Data-driven glass-forming ability for Fe-based amorphous alloys
Yicheng Wu, Lei Yan, Jinfeng Liu, et al.
Materials Today Communications (2024) Vol. 40, pp. 109440-109440
Closed Access | Times Cited: 1
Yicheng Wu, Lei Yan, Jinfeng Liu, et al.
Materials Today Communications (2024) Vol. 40, pp. 109440-109440
Closed Access | Times Cited: 1
Machine learning-enabled design of Fe-based bulk metallic glasses for superior thermal neutron absorption properties
Jin Gao, Jianxin Hou, Yuting Wu, et al.
Journal of Alloys and Compounds (2024), pp. 177595-177595
Closed Access
Jin Gao, Jianxin Hou, Yuting Wu, et al.
Journal of Alloys and Compounds (2024), pp. 177595-177595
Closed Access
Ensemble learning predicts glass-forming ability under imbalanced datasets
Dehua Cheng, Yongchao Liang, Yuanwei Pu, et al.
Computational Materials Science (2024) Vol. 248, pp. 113601-113601
Closed Access
Dehua Cheng, Yongchao Liang, Yuanwei Pu, et al.
Computational Materials Science (2024) Vol. 248, pp. 113601-113601
Closed Access
