Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 driven rationally design of amorphous alloy with improved elastic models
Zhuang Li, Zhilin Long, Shan Lei, et al.
Materials & Design (2022) Vol. 220, pp. 110881-110881
Open Access | Times Cited: 16

Showing 16 citing articles:

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
Prediction of Vickers hardness of amorphous alloys based on interpretable machine learning
Xiaowei Liu, Zhilin Long, Peng Li
Journal of Non-Crystalline Solids (2022) Vol. 602, pp. 122095-122095
Closed Access | Times Cited: 24
Alloys innovation through machine learning: a statistical literature review
Alireza Valizadeh, Ryoji Sahara, Maaouia Souissi
Science and Technology of Advanced Materials Methods (2024) Vol. 4, Iss. 1
Open Access | Times Cited: 4
Predictor−corrector inverse design scheme for property−composition prediction of amorphous alloys
Long Tao, Zhilin Long, Bo Pang
Transactions of Nonferrous Metals Society of China (2025) Vol. 35, Iss. 1, pp. 169-183
Open Access
Accelerated discovery of Fe-based amorphous/nanocrystalline alloy through explicit expression and interpretable information based on machine learning
Bo Pang, Zhilin Long, Tao Long, et al.
Materials & Design (2023) Vol. 231, pp. 112054-112054
Open Access | Times Cited: 11
Interpretable machine learning methods to predict the mechanical properties of ABX3 perovskites
Shittu B. Akinpelu, Simeon A. Abolade, Emmanuel Okafor, et al.
Results in Physics (2024), pp. 107978-107978
Open Access | Times Cited: 3
Machine learning aided prediction of martensite transformation temperature of NiTi-based shape memory alloy
Chengcheng Liu, Hang Su
Materials Today Communications (2024), pp. 110720-110720
Closed Access | Times Cited: 3
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: 7
Prediction of magnetocaloric properties of Fe-based amorphous alloys based on interpretable machine learning
Chengcheng Liu, Xuandong Wang, Weidong Cai, et al.
Journal of Non-Crystalline Solids (2023) Vol. 625, pp. 122749-122749
Closed Access | Times Cited: 7
Prediction and customized design of Curie temperature of Fe-based amorphous alloys based on interpretable machine learning
Chengcheng Liu, Yongchao Lu, Jianfa Feng, et al.
Materials Today Communications (2023) Vol. 38, pp. 107667-107667
Closed Access | Times Cited: 6
The effect of ultrasonic field on the microstructure and corrosion behavior of Fe-based amorphous coating applied to selective laser melting
Morteza Taheri, Mansour Razavi
Materials Research Express (2023) Vol. 10, Iss. 7, pp. 076508-076508
Open Access | Times Cited: 5
A simple, quantitative expression for understanding and evaluating the yield strength of amorphous alloys based on symbolic regression and dimensional calculation
Zhuang Li, Zhilin Long, Shan Lei, et al.
Journal of Non-Crystalline Solids (2023) Vol. 614, pp. 122409-122409
Closed Access | Times Cited: 4
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
MonteCat: A Basin-Hopping-Inspired Catalyst Descriptor Search Algorithm for Machine Learning Models
Fernando García-Escobar, Toshiaki Taniike, Keisuke Takahashi
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 5, pp. 1512-1521
Closed Access | Times Cited: 1
A Review of the Preparation and Prospects of Amorphous Alloys by Mechanical Alloying
Xianjie Yuan, Y. D. Zhang, Xuanhui Qu, et al.
Journal of Materials Research and Technology (2024) Vol. 33, pp. 3117-3143
Open Access | Times Cited: 1
Composition optimization of cobalt-free Fe-Cr-Ni-Al/Ti multi-principal element alloys for strength-ductility trade-off based on machine learning
Kang Xu, Jin-hua An, Li Zhang, et al.
Materials Today Communications (2023) Vol. 36, pp. 106498-106498
Closed Access | Times Cited: 2
Page 1

Scroll to top