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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:

Toward Physics-Based Solubility Computation for Pharmaceuticals to Rival Informatics
Daniel J. Fowles, David Scott Palmer, Rui Guo, et al.
Journal of Chemical Theory and Computation (2021) Vol. 17, Iss. 6, pp. 3700-3709
Open Access | Times Cited: 22

Showing 22 citing articles:

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
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
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
Pixel calculations using Orca or GAUSSIAN for electron density automated within the Oscail package
Patrick McArdle
Journal of Applied Crystallography (2021) Vol. 54, Iss. 5, pp. 1535-1541
Open Access | Times Cited: 47
Blinded Predictions and Post Hoc Analysis of the Second Solubility Challenge Data: Exploring Training Data and Feature Set Selection for Machine and Deep Learning Models
Jonathan G. M. Conn, James W. Carter, Justin J. A. Conn, et al.
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 4, pp. 1099-1113
Open Access | Times Cited: 13
Computational insights into the rational design of organic electrode materials for metal ion batteries
Xinyue Zhu, Youchao Yang, Xipeng Shu, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2023) Vol. 13, Iss. 5
Closed Access | Times Cited: 12
Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process
Christopher L. Burcham, Michael F. Doherty, Baron Peters, et al.
Crystal Growth & Design (2024) Vol. 24, Iss. 13, pp. 5417-5438
Open Access | Times Cited: 4
Free Energy Perturbation Approach for Accurate Crystalline Aqueous Solubility Predictions
Richard S. Hong, Ana V. Rojas, Rajni M. Bhardwaj, et al.
Journal of Medicinal Chemistry (2023) Vol. 66, Iss. 23, pp. 15883-15893
Closed Access | Times Cited: 10
Sublimation – a green route to new solid-state forms
Patrick McArdle, Andrea Erxleben
CrystEngComm (2021) Vol. 23, Iss. 35, pp. 5965-5975
Closed Access | Times Cited: 23
CrystalClear: an open, modular protocol for predicting molecular crystal growth from solution
Peter R. Spackman, Alvin J. Walisinghe, Michael W. Anderson, et al.
Chemical Science (2023) Vol. 14, Iss. 26, pp. 7192-7207
Open Access | Times Cited: 8
Pharmaceutical Digital Design: From Chemical Structure through Crystal Polymorph to Conceptual Crystallization Process
Christopher L. Burcham, Michael F. Doherty, Baron Peters, et al.
(2024)
Open Access | Times Cited: 2
Predicting Solubility Limits of Organic Solutes for a Wide Range of Solvents and Temperatures
Florence H. Vermeire, Yunsie Chung, William H. Green
(2022)
Open Access | Times Cited: 13
High-Throughput Virtual Screening of Quinones for Aqueous Redox Flow Batteries: Status and Perspectives
Abhishek Khetan
Batteries (2022) Vol. 9, Iss. 1, pp. 24-24
Open Access | Times Cited: 10
When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties?
Shih‐Cheng Li, Haoyang Wu, Angiras Menon, et al.
(2024)
Open Access | Times Cited: 1
Solvation entropy, enthalpy and free energy prediction using a multi-task deep learning functional in 1D-RISM
Daniel J. Fowles, David Scott Palmer
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 9, pp. 6944-6954
Open Access | Times Cited: 4
When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties?
Shih‐Cheng Li, Haoyang Wu, Angiras Menon, et al.
(2024)
Open Access
Solubility prediction and interaction mechanism of FOX-7 in ten solvents by molecular and thermodynamic modeling
Zejun Wu, Yuchuan Shi, Yongjie Li, et al.
Chemical Engineering Journal (2024) Vol. 501, pp. 157241-157241
Closed Access
Machine Learning for Solubility Prediction
Tianyuan Zheng, John B. O. Mitchell, Simon Dobson
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
Advancing energy storage through solubility prediction: leveraging the potential of deep learning
Mesfin Diro Chaka, Yedilfana Setarge Mekonnen, Qin Wu, et al.
Physical Chemistry Chemical Physics (2023) Vol. 25, Iss. 46, pp. 31836-31847
Open Access | Times Cited: 1
Determination of the Cohesive Properties and Sublimation Temperatures of Glycine Polymorphs
Neubi Francisco Xavier, Glauco F. Bauerfeldt
Crystal Growth & Design (2021) Vol. 21, Iss. 11, pp. 6266-6275
Closed Access | Times Cited: 3
Accurately predicting solvation free energy in aqueous and organic solvents beyond 298 K by combining deep learning and the 1D reference interaction site model
Daniel J. Fowles, Rose G. McHardy, Abdullah Ahmad, et al.
Digital Discovery (2022) Vol. 2, Iss. 1, pp. 177-188
Open Access | Times Cited: 2
Sublimation and Vaporization Enthalpies of Niclosamide: Application of Transpiration Method and Thermogravimetric Analysis
Svetlana V. Blokhina, Angelica Sharapova, Marina V. Ol’khovich
Journal of Chemical & Engineering Data (2023) Vol. 68, Iss. 10, pp. 2547-2553
Closed Access
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