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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:

Automatic Prediction of Band Gaps of Inorganic Materials Using a Gradient Boosted and Statistical Feature Selection Workflow
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 4, pp. 1187-1200
Open Access | Times Cited: 11

Showing 11 citing articles:

Automatic Prediction of Peak Optical Absorption Wavelengths in Molecules Using Convolutional Neural Networks
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 5, pp. 1486-1501
Open Access | Times Cited: 7
Machine-Learning Prediction of Curie Temperature from Chemical Compositions of Ferromagnetic Materials
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 16, pp. 6388-6409
Open Access | Times Cited: 3
Machine-Learning Predictions of Critical Temperatures from Chemical Compositions of Superconductors
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024)
Open Access | Times Cited: 3
Applications of Long Short-Term Memory (LSTM) Networks in Polymeric Sciences: A Review
Ivan Malashin, В С Тынченко, Andrei Gantimurov, et al.
Polymers (2024) Vol. 16, Iss. 18, pp. 2607-2607
Open Access | Times Cited: 3
Predictive Modeling of High-Entropy Alloys and Amorphous Metallic Alloys Using Machine Learning
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024)
Open Access | Times Cited: 1
Interpretable machine learning boosting the discovery of targeted organometallic compounds with optimal bandgap
Taehyun Park, Junho Song, Jinyoung Jeong, et al.
Materials Today Advances (2024) Vol. 23, pp. 100520-100520
Open Access
Enhancing photovoltaic cell design with multilayer sequential neural networks: a study on Neodymium-doped ZnO nanoparticles
Rogelio A. Léon-García, Ernesto Rojas-Pablos, Jorge L. Mejía-Méndez, et al.
Chemical Engineering Journal Advances (2024), pp. 100669-100669
Open Access
Perovskite Solar Cell Stability Analysis Using Entropy‐Based Support Vector Machines Learning
R. K. Bhaduri, S. Manasa
Progress in Photovoltaics Research and Applications (2024)
Closed Access
Matini-Net: Versatile Material Informatics Research Framework for Feature Engineering and Deep Neural Network Design
Myeonghun Lee, Taehyun Park, Kyoungmin Min
Journal of Chemical Information and Modeling (2024)
Closed Access
Machine learning prediction of materials properties from chemical composition: Status and prospects
Mohammed Alghadeer, Nyimas Aisyah, Mahmoud Hezam, et al.
Chemical Physics Reviews (2024) Vol. 5, Iss. 4
Open Access
Automatic Prediction of Molecular Properties Using Substructure Vector Embeddings within a Feature Selection Workflow
Son Gyo Jung, Guwon Jung, Jacqueline M. Cole
Journal of Chemical Information and Modeling (2024)
Open Access
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