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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:

Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures
Florence H. Vermeire, Yunsie Chung, William H. Green
Journal of the American Chemical Society (2022) Vol. 144, Iss. 24, pp. 10785-10797
Open Access | Times Cited: 55

Showing 1-25 of 55 citing articles:

Chemprop: A Machine Learning Package for Chemical Property Prediction
Esther Heid, Kevin P. Greenman, Yunsie Chung, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 1, pp. 9-17
Open Access | Times Cited: 140
Characterizing Uncertainty in Machine Learning for Chemistry
Esther Heid, Charles J. McGill, Florence H. Vermeire, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 13, pp. 4012-4029
Open Access | Times Cited: 38
An integrated high-throughput robotic platform and active learning approach for accelerated discovery of optimal electrolyte formulations
Juran Noh, Hieu A. Doan, Heather Job, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 15
Frontiers of molecular crystal structure prediction for pharmaceuticals and functional organic materials
Gregory J. O. Beran
Chemical Science (2023) Vol. 14, Iss. 46, pp. 13290-13312
Open Access | Times Cited: 34
Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models
Arash Tayyebi, Ali Alshami, Zeinab Rabiei, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 21
Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates
Yunsie Chung, William H. Green
Chemical Science (2024) Vol. 15, Iss. 7, pp. 2410-2424
Open Access | Times Cited: 11
When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties?
Shih‐Cheng Li, Haoyang Wu, Angiras Menon, et al.
Journal of the American Chemical Society (2024) Vol. 146, Iss. 33, pp. 23103-23120
Closed Access | Times Cited: 7
Recovery of Carbon Fibres From Aged Epoxy Matrix Composites Using H2O2 as an Oxidant: A Thermodynamic and Technoeconomic Analysis
Paul Njeni Mabalane, Kristóf Molnár, Philani Thembelihle Mazibuko, et al.
Journal of Engineering (2025) Vol. 2025, Iss. 1
Open Access
Solution Processing of Cross-Linked Porous Organic Polymers
Lingling Wang, Yan Su, Cheng Gu
Accounts of Materials Research (2022) Vol. 3, Iss. 10, pp. 1049-1060
Closed Access | Times Cited: 28
Predicting Critical Properties and Acentric Factors of Fluids Using Multitask Machine Learning
Sayandeep Biswas, Yunsie Chung, Josephine Ramirez, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 15, pp. 4574-4588
Closed Access | Times Cited: 17
Gibbs–Duhem-informed neural networks for binary activity coefficient prediction
Jan G. Rittig, Kobi Felton, Alexei A. Lapkin, et al.
Digital Discovery (2023) Vol. 2, Iss. 6, pp. 1752-1767
Open Access | Times Cited: 15
Extrapolation validation (EV): a universal validation method for mitigating machine learning extrapolation risk
Mengxian Yu, Yin‐Ning Zhou, Qiang Wang, et al.
Digital Discovery (2024) Vol. 3, Iss. 5, pp. 1058-1067
Open Access | Times Cited: 6
Solubility of dapsone in deep eutectic solvents: Experimental analysis, molecular insights and machine learning predictions
Tomasz Jeliński, Maciej Przybyłek, Rafał Różalski, et al.
Polymers in Medicine (2024) Vol. 54, Iss. 1, pp. 15-25
Open Access | Times Cited: 5
Bayesian Optimization over Multiple Experimental Fidelities Accelerates Automated Discovery of Drug Molecules
Matthew A. McDonald, Brent A. Koscher, Richard B. Canty, et al.
ACS Central Science (2025) Vol. 11, Iss. 2, pp. 346-356
Open Access
Opportunities for Machine Learning and Artificial Intelligence to Advance Synthetic Drug Substance Process Development
Daniel J. Griffin, Connor W. Coley, Scott A. Frank, et al.
Organic Process Research & Development (2023) Vol. 27, Iss. 11, pp. 1868-1879
Open Access | Times Cited: 13
Predicting drug solubility in organic solvents mixtures: A machine-learning approach supported by high-throughput experimentation
Francesca Cenci, Samir Diab, Paola Ferrini, et al.
International Journal of Pharmaceutics (2024) Vol. 660, pp. 124233-124233
Open Access | Times Cited: 4
High-Energy and Long-Lasting Organic Electrode for a Rechargeable Aqueous Battery
Myeong Hwan Lee, Giyun Kwon, Hyuntae Lim, et al.
ACS Energy Letters (2022) Vol. 7, Iss. 10, pp. 3637-3645
Closed Access | Times Cited: 21
Self-assembly of an amino acid derivative as an anode interface layer for advanced alkaline Al–air batteries
Lei Guo, Lei Zhu, Yue Huang, et al.
Physical Chemistry Chemical Physics (2024) Vol. 26, Iss. 14, pp. 10892-10903
Closed Access | Times Cited: 3
ConfSolv: Prediction of Solute Conformer-Free Energies across a Range of Solvents
Lagnajit Pattanaik, Angiras Menon, Volker Settels, et al.
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 47, pp. 10151-10170
Closed Access | Times Cited: 9
Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
Piotr Cysewski, Tomasz Jeliński, Maciej Przybyłek, et al.
Pharmaceutics (2022) Vol. 14, Iss. 12, pp. 2828-2828
Open Access | Times Cited: 15
Vapor-liquid phase equilibria behavior prediction of binary mixtures using machine learning
Guanlun Sun, Zhenyu Zhao, Shengjie Sun, et al.
Chemical Engineering Science (2023) Vol. 282, pp. 119358-119358
Closed Access | Times Cited: 8
A hybrid modelling approach to compare chemical separation technologies in terms of energy consumption and carbon dioxide emissions
Gergő Ignácz, Aron K. Beke, Viktor Tóth, et al.
Nature Energy (2024)
Open Access | Times Cited: 2
Uncovering the Molecular Mechanisms of Cosolvency and Predicting the Cosolvency Phenomenon by Molecular Simulations: A Case Study of Amino Acids
Dongbo Wang, Ying Wang, Fan Li, et al.
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 26, pp. 6143-6150
Closed Access | Times Cited: 7
Intermolecular Interactions as a Measure of Dapsone Solubility in Neat Solvents and Binary Solvent Mixtures
Piotr Cysewski, Maciej Przybyłek, Tomasz Jeliński
Materials (2023) Vol. 16, Iss. 18, pp. 6336-6336
Open Access | Times Cited: 7
Predicting the Solubility of Organic Energy Storage Materials Based on Functional Group Identity and Substitution Pattern
Madison R. Tuttle, Emma Brackman, Farshud Sorourifar, et al.
The Journal of Physical Chemistry Letters (2023) Vol. 14, Iss. 5, pp. 1318-1325
Closed Access | Times Cited: 6
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