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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:

Can Machine Learning Predict the Phase Behavior of Surfactants?
Joseph C. R. Thacker, David J. Bray, Patrick B. Warren, et al.
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 16, pp. 3711-3727
Open Access | Times Cited: 10

Showing 10 citing articles:

From composite molecular structures to a multiplicity of supramolecular aggregates: The role of intermolecular interactions in biosurfactant self-assembly
Irene Russo Krauss, Rodolfo Esposito, Luigi Paduano, et al.
Current Opinion in Colloid & Interface Science (2024) Vol. 70, pp. 101792-101792
Open Access | Times Cited: 10
Applications of Artificial Intelligence and Machine Learning on Critical Materials Used in Cosmetics and Personal Care Formulation Design
Hai Xin, Akashdeep Singh Virk, Sabitoj Singh Virk, et al.
Current Opinion in Colloid & Interface Science (2024) Vol. 73, pp. 101847-101847
Closed Access | Times Cited: 7
Predicting the firefighting efficacy of surfactants prior to synthesis via ensemble artificial neural network modeling of a foam performance database
Jeffrey A. Cramer, Caleb M. Bunton, Matthew C. Davis, et al.
Journal of Surfactants and Detergents (2025)
Closed Access
Surfactants produced from carbohydrate derivatives: Part 2. A review on the value chain, synthesis, and the potential role of artificial intelligence within the biorefinery concept
Ronald Márquez, Maria Soledad Ortiz, Nelson Barrios, et al.
Journal of Surfactants and Detergents (2024)
Open Access | Times Cited: 4
Ionic surfactants critical micelle concentration prediction in water/organic solvent mixtures by artificial neural network
Anton Soria-López, Maria Garcia‐Marti, Enrique Barreiro, et al.
Tenside Surfactants Detergents (2024)
Closed Access | Times Cited: 2
Dynamic diffusive interfacial transport (D-DIT): A novel quantitative swelling technique for developing binary phase diagrams of aqueous surfactant systems
Parth U. Kelkar, Kendra A. Erk, Seth Lindberg
Review of Scientific Instruments (2024) Vol. 95, Iss. 3
Open Access | Times Cited: 1
Data-Driven Imputation of Miscibility of Aqueous Solutions via Graph-Regularized Logistic Matrix Factorization
Diba Behnoudfar, Cory M. Simon, Joshua Schrier
The Journal of Physical Chemistry B (2023) Vol. 127, Iss. 37, pp. 7964-7973
Open Access | Times Cited: 3
Evaluation of Machine Learning Assisted Phase Behavior Modelling of Surfactant–Oil–Water Systems
Daulet Magzymov, Meruyert Makhatova, Zhassulan Dairov, et al.
Applied Sciences (2024) Vol. 15, Iss. 1, pp. 100-100
Open Access
Accelerating Multicomponent Phase-Coexistence Calculations with Physics-informed Neural Networks
Satyen Dhamankar, Shengli Jiang, Michael Webb
Molecular Systems Design & Engineering (2024) Vol. 10, Iss. 2, pp. 89-101
Open Access
Data-driven imputation of miscibility of aqueous solutions via graph-regularized logistic matrix factorization
Diba Behnoudfar, Cory M. Simon, Joshua Schrier
(2023)
Open Access
Data-driven imputation of miscibility of aqueous solutions via graph-regularized logistic matrix factorization
Diba Behnoudfar, Cory M. Simon, Joshua Schrier
(2023)
Open Access
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