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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:

Computing Kinetic Solvent Effects and Liquid Phase Rate Constants Using Quantum Chemistry and COSMO-RS Methods
Yunsie Chung, William H. Green
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 27, pp. 5637-5651
Closed Access | Times Cited: 16

Showing 16 citing articles:

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: 16
Synergistic impact of organic and inorganic features in carborane hybrids for nonlinear optics and solvent-tunable properties
Iqra Kaifi, Shabbir Muhammad, Adan Ahmad, et al.
Dalton Transactions (2025)
Closed Access
The Effect of Microsolvation on the Mechanism, Kinetics and Energetics of a Reductive Amination Reaction
Aikaterini Diamanti, Amparo Galindo, Claire S. Adjiman
Industrial & Engineering Chemistry Research (2025)
Open Access
New modified Arrhenius equation to describe the temperature dependence of liquid phase reaction rates
Yunsie Chung, William H. Green
Chemical Engineering Journal (2025), pp. 163300-163300
Closed Access
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
Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates
Yunsie Chung, William H. Green
(2023)
Open Access | Times Cited: 5
Perspective on Automated Predictive Kinetics using Estimates derived from Large Datasets
William H. Green
(2024)
Open Access | Times Cited: 1
Widespread Misinterpretation of pKa Terminology for Zwitterionic Compounds and Its Consequences
Jonathan W. Zheng, Ivo Leito, William H. Green
Journal of Chemical Information and Modeling (2024)
Closed Access | Times Cited: 1
Beyond the Landfill: A critical review of techniques for End-of-Life Polyvinyl chloride (PVC) valorization
Mohammadhossein Havaei, Oğuzhan Akin, Andrea Locaspi, et al.
Waste Management (2024) Vol. 193, pp. 105-134
Open Access | Times Cited: 1
Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates
Yunsie Chung, William H. Green
(2023)
Open Access | Times Cited: 1
Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates
Yunsie Chung, William H. Green
(2024)
Open Access
New functional form to describe the temperature dependence of liquid phase reaction rates
Yunsie Chung, William H. Green
(2024)
Open Access
Dynamic Modeling for Synthesis of Tailored Microgels with Charged Domains
Luise F. Kaven, Jan Keil, Nadja Wolter, et al.
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 17, pp. 7727-7742
Closed Access
Perspective on automated predictive kinetics using estimates derived from large datasets
William H. Green
International Journal of Chemical Kinetics (2024)
Open Access
Widespread misinterpretation of pKa terminology and its consequences
Jonathan W. Zheng, Ivo Leito, William H. Green
(2024)
Open Access
Widespread misinterpretation of pKa terminology and its consequences
Jonathan W. Zheng, Ivo Leito, William H. Green
(2024)
Open Access
On the design of optimal computer experiments to model solvent effects on reaction kinetics
Lingfeng Gui, Alan Armstrong, Amparo Galindo, et al.
Molecular Systems Design & Engineering (2024)
Open Access
Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks
Kevin Spiekermann, Xiaorui Dong, Angiras Menon, et al.
The Journal of Physical Chemistry A (2024)
Closed Access
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