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:
Property Prediction and Structural Feature Extraction of Polyimide Materials Based on Machine Learning
Han Zhang, Haoyuan Li, Hanshen Xin, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 17, pp. 5473-5483
Closed Access | Times Cited: 7
Han Zhang, Haoyuan Li, Hanshen Xin, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 17, pp. 5473-5483
Closed Access | Times Cited: 7
Showing 7 citing articles:
Application of machine learning in polyimide structure design and property regulation
Wenjia Huo, Haiyue Wang, Liying Guo, et al.
High Performance Polymers (2025)
Closed Access
Wenjia Huo, Haiyue Wang, Liying Guo, et al.
High Performance Polymers (2025)
Closed Access
Practical Machine Learning Model Selection and Interpretation for Organophosphorus Flame Retardancy in Epoxy Resin
Jiajun Li, Bin Zou, Amirbek Bekeshev, et al.
Polymer Degradation and Stability (2025) Vol. 234, pp. 111209-111209
Closed Access
Jiajun Li, Bin Zou, Amirbek Bekeshev, et al.
Polymer Degradation and Stability (2025) Vol. 234, pp. 111209-111209
Closed Access
Clustering method for the construction of machine learning model with high predictive ability
Hiromasa Kaneko
Chemometrics and Intelligent Laboratory Systems (2024) Vol. 246, pp. 105084-105084
Closed Access | Times Cited: 3
Hiromasa Kaneko
Chemometrics and Intelligent Laboratory Systems (2024) Vol. 246, pp. 105084-105084
Closed Access | Times Cited: 3
Prediction and Interpretability Study of the Glass Transition Temperature of Polyimide Based on Machine Learning with Quantitative Structure–Property Relationship (Tg-QSPR)
Tianyong Zhang, Suisui Wang, Yamei Chai, et al.
The Journal of Physical Chemistry B (2024) Vol. 128, Iss. 36, pp. 8807-8817
Closed Access | Times Cited: 1
Tianyong Zhang, Suisui Wang, Yamei Chai, et al.
The Journal of Physical Chemistry B (2024) Vol. 128, Iss. 36, pp. 8807-8817
Closed Access | Times Cited: 1
Multi-property prediction and high-throughput screening of polyimides: an application case for interpretable machine learning
Bo Zhang, Xueqing Li, Xinxin Xu, et al.
Polymer (2024) Vol. 312, pp. 127603-127603
Closed Access | Times Cited: 1
Bo Zhang, Xueqing Li, Xinxin Xu, et al.
Polymer (2024) Vol. 312, pp. 127603-127603
Closed Access | Times Cited: 1
Machine Learning-Based High-Throughput Screening for High-Stability Polyimides
Gaoyang Luo, Feicheng Huan, Yuwei Sun, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access | Times Cited: 1
Gaoyang Luo, Feicheng Huan, Yuwei Sun, et al.
Industrial & Engineering Chemistry Research (2024)
Closed Access | Times Cited: 1
Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties
Hajime Shimakawa, Akiko Kumada, Masahiro Sato
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 9, pp. 3621-3629
Closed Access
Hajime Shimakawa, Akiko Kumada, Masahiro Sato
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 9, pp. 3621-3629
Closed Access
