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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:

SPT-NRTL: A physics-guided machine learning model to predict thermodynamically consistent activity coefficients
Benedikt Winter, Clemens Winter, Timm Esper, et al.
Fluid Phase Equilibria (2023) Vol. 568, pp. 113731-113731
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Applications of machine learning in supercritical fluids research
Lucien Roach, Gian‐Marco Rignanese, Arnaud Erriguible, et al.
The Journal of Supercritical Fluids (2023) Vol. 202, pp. 106051-106051
Open Access | Times Cited: 24
Challenges and opportunities for computer-aided molecular and process design approaches in advancing sustainable pharmaceutical manufacturing
Claire S. Adjiman, Amparo Galindo
Current Opinion in Chemical Engineering (2025) Vol. 47, pp. 101073-101073
Open Access | Times Cited: 1
Understanding the language of molecules: predicting pure component parameters for the PC-SAFT equation of state from SMILES
Benedikt Winter, Philipp Rehner, Timm Esper, et al.
Digital Discovery (2025)
Open Access | Times Cited: 1
Capturing molecular interactions in graph neural networks: a case study in multi-component phase equilibrium
Shiyi Qin, Shengli Jiang, Jianping Li, et al.
Digital Discovery (2022) Vol. 2, Iss. 1, pp. 138-151
Open Access | Times Cited: 29
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: 21
ML-SAFT: A machine learning framework for PCP-SAFT parameter prediction
Kobi Felton, Lukas Raßpe-Lange, Jan G. Rittig, et al.
Chemical Engineering Journal (2024) Vol. 492, pp. 151999-151999
Open Access | Times Cited: 8
Thermodynamics-consistent graph neural networks
Jan G. Rittig, Alexander Mitsos
Chemical Science (2024)
Open Access | Times Cited: 7
HANNA: Hard-constraint Neural Network for Consistent Activity Coefficient Prediction
Thomas Specht, Mayank Nagda, Sophie Fellenz, et al.
Chemical Science (2024) Vol. 15, Iss. 47, pp. 19777-19786
Open Access | Times Cited: 7
Working fluid and system optimisation of organic Rankine cycles via computer-aided molecular design: A review
Christos N. Markides, André Bardow, Michel De Paepe, et al.
Progress in Energy and Combustion Science (2024) Vol. 107, pp. 101201-101201
Open Access | Times Cited: 4
Assessment of Nylon-66 Depolymerization for Circular Economy: Kinetic Modeling, Purification, and Sustainable Design
Adam McNeeley, Y. A. Liu
Industrial & Engineering Chemistry Research (2025)
Closed Access
Similarity-Informed Matrix Completion Method for Predicting Activity Coefficients
Nicolas Hayer, Thomas Specht, Justus Arweiler, et al.
The Journal of Physical Chemistry A (2025)
Closed Access
Pooling solvent mixtures for solvation free energy predictions
Roel J. Leenhouts, Nathan Morgan, Emad Al Ibrahim, et al.
Chemical Engineering Journal (2025), pp. 162232-162232
Open Access
Physics-Informed Multifidelity Gaussian Process: Modeling the Effect of Water and Temperature on the Viscosity of a Deep Eutectic Solvent
Maximilian Fleck, Samir Darouich, Jürgen Pleiss, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
Thermophysical Properties of Surface Seawater for Sustainability in Estuarine Systems
Nishaben Desai Dholakiya, Ranjan Dey, Anirban Roy
Journal of Chemical & Engineering Data (2025)
Closed Access
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: 9
The artificial neural network-based two-phase equilibrium calculation framework for fast compositional reservoir simulation of CO2 EOR
Liang-nan Li, Hongbin Jing, Jianqiao Liu, et al.
Fluid Phase Equilibria (2024) Vol. 585, pp. 114151-114151
Closed Access | Times Cited: 3
Synthesis and design methods for energy-efficient distillation processes
Mirko Skiborowski
Current Opinion in Chemical Engineering (2023) Vol. 42, pp. 100985-100985
Open Access | Times Cited: 9
Predicting Temperature‐Dependent Activity Coefficients at Infinite Dilution Using Tensor Completion
Julie Damay, Gleb Ryzhakov, Fabian Jirasek, et al.
Chemie Ingenieur Technik (2023) Vol. 95, Iss. 7, pp. 1061-1069
Open Access | Times Cited: 8
Outlook: How I Learned to Love Machine Learning (A Personal Perspective on Machine Learning in Process Systems Engineering)
Ví­ctor M. Zavala
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 23, pp. 8995-9005
Open Access | Times Cited: 8
PUFFIN: A path-unifying feed-forward interfaced network for vapor pressure prediction
Vinícius V. Santana, Carine M. Rebello, Luana P. Queiroz, et al.
Chemical Engineering Science (2023) Vol. 286, pp. 119623-119623
Open Access | Times Cited: 7
Indirect Electrochemical Cooling: Model-Based Performance Analysis and Working Fluid Selection
Lana Liebl, André Bardow, Dennis Roskosch
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 2, pp. 1055-1065
Open Access | Times Cited: 2
Solubility, Thermodynamic Parameters, and Dissolution Properties of 17-α Hydroxyprogesterone in 13 Pure Solvents
Qi Zhao, Yinhu Pan, Yankai Xiong, et al.
ACS Omega (2024) Vol. 9, Iss. 14, pp. 16106-16117
Open Access | Times Cited: 2
Predicting the microalgae lipid profile obtained by supercritical fluid extraction using a machine learning model
Juan J. Pinto, J. Luis Guerrero, L. Niño de Rivera, et al.
Frontiers in Chemistry (2024) Vol. 12
Open Access | Times Cited: 2
Gibbs–Helmholtz Graph Neural Network for the Prediction of Activity Coefficients of Polymer Solutions at Infinite Dilution
Edgar Iván Sánchez Medina, Sreekanth Kunchapu, Kai Sundmacher
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 46, pp. 9863-9873
Open Access | Times Cited: 6
Integrating molecular dynamics simulations and experimental data for azeotrope predictions in binary mixtures
Xiaoyu Wang, Bingqing Cheng
The Journal of Chemical Physics (2024) Vol. 161, Iss. 3
Open Access | Times Cited: 1
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