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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:

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

Showing 24 citing articles:

A Comprehensive Review on Advanced Extraction Techniques for Retrieving Bioactive Components from Natural Sources
Yogesh A. Bhadange, Jitendra Carpenter, Virendra Kumar Saharan
ACS Omega (2024) Vol. 9, Iss. 29, pp. 31274-31297
Open Access | Times Cited: 32
Real-time concentration detection of Al dust using GRU-based Kalman filtering approach
Fengyu Zhao, Wei Gao, Jianxin Lu, et al.
Process Safety and Environmental Protection (2024) Vol. 189, pp. 154-163
Closed Access | Times Cited: 19
Recent Advances in Conventional and Innovative Extraction Techniques for Recovery of High-Added Value Compounds for Food Additives and Nutraceuticals
Abhishek Bisht, Snehalata Sahu, Anand Kumar, et al.
Food Physics (2025), pp. 100047-100047
Open Access | Times Cited: 2
Novel method for temperature prediction in rotary kiln process through machine learning and CFD
Yaozu Wang, Yue Xu, Xiaoran Song, et al.
Powder Technology (2024) Vol. 439, pp. 119649-119649
Closed Access | Times Cited: 11
Prediction of Drug-like Compounds Solubility in Supercritical Carbon Dioxide: A Comparative Study between Classical Density Functional Theory and Machine Learning Approaches
Dmitriy M. Makarov, Nikolai N. Kalikin, Yury A. Budkov
Industrial & Engineering Chemistry Research (2024) Vol. 63, Iss. 3, pp. 1589-1603
Closed Access | Times Cited: 8
Supercritical water gasification for hospital wastewater
Rich Jhon Paul Latiza, Rugi Vicente C. Rubi, Armando T. Quitain
Journal of Hazardous Materials Advances (2025), pp. 100651-100651
Open Access | Times Cited: 1
Design of Molecularly Imprinted Polymers Using Supercritical Carbon Dioxide Technology
Ana I. Furtado, Vasco D. B. Bonifácio, Raquel Viveiros, et al.
Molecules (2024) Vol. 29, Iss. 5, pp. 926-926
Open Access | Times Cited: 7
Heat transfer analysis in the engine‐based oil‐based hybrid nanofluid flow between two spinning disks: Probed by artificial neural network
Shahzad Khattak, Waseem Waseem, Asad Ullah, et al.
ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik (2025) Vol. 105, Iss. 2
Closed Access
Open-loop linear modeling method for unstable flow utilizing built-in data-driven feedback controllers
Chuanqiang Gao, Xinyu Yang, Kai Ren, et al.
Physical Review Fluids (2025) Vol. 10, Iss. 3
Closed Access
Improved Solubility Predictions in scCO2 Using Thermodynamics-Informed Machine Learning Models
Dmitriy M. Makarov, Nikolai N. Kalikin, Yury A. Budkov, et al.
Journal of Chemical Information and Modeling (2025)
Closed Access
A deep-learning model for predicting spatiotemporal evolution in reactive fluidized bed reactor
Chenshu Hu, Xiaolin Guo, Yuyang Dai, et al.
Renewable Energy (2024) Vol. 225, pp. 120245-120245
Closed Access | Times Cited: 3
Predicting the solubility of solids in supercritical carbon dioxide using the Chrastil equation with parameters estimated from a group contribution method
Clara García-Samino, Eva M. Martín del Valle, Antonio Tabernero
Journal of Molecular Liquids (2024) Vol. 403, pp. 124890-124890
Open Access | Times Cited: 3
Optimal transonic buffet aerodynamic noise PSD predictions with Random Forest: modeling methods and feature selection
Qiao Zhang, Dangguo Yang, Weiwei Zhang
Aerospace Science and Technology (2024) Vol. 150, pp. 109245-109245
Closed 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
A Three-Pronged Computational Approach for Evaluating Density Based Semi Empirical Equations of Supercritical Extraction Process and Data
FNU Srinidhi
(2024)
Open Access | Times Cited: 1
A Three-Pronged Computational Approach for Evaluating Density Based Semi Empirical Equations of Supercritical Extraction Process and Data
FNU Srinidhi
(2024)
Open Access | Times Cited: 1
A Three-Pronged Computational Approach for Evaluating Density Based Semi Empirical Equations of Supercritical Extraction Process and Data
FNU Srinidhi
(2024)
Open Access | Times Cited: 1
Artificial neural network aided vapor–liquid equilibrium model for multi-component high-pressure transcritical flows with phase change
Navneeth Srinivasan, Suo Yang
Physics of Fluids (2024) Vol. 36, Iss. 8
Closed Access | Times Cited: 1
Microfluidic supercritical CO2 applications: Solvent extraction, nanoparticle synthesis, and chemical reaction
Junyi Yang, Peichun Amy Tsai
Biomicrofluidics (2024) Vol. 18, Iss. 5
Closed Access | Times Cited: 1
Enhancing the interface stability of Li/NCM622 batteries by adding 3-Trifluoromethyl pyrazole
Fangfang Shang, Hengdao Quan, Xiaoxun Ma
Surfaces and Interfaces (2024) Vol. 54, pp. 105249-105249
Closed Access | Times Cited: 1
A systematic review of flow instability influencing factors and mechanisms in supercritical fluids
Attiq Ur Rehman, Xiaocheng Du, Hassaan Ahmad, et al.
International Journal of Heat and Fluid Flow (2024) Vol. 112, pp. 109677-109677
Closed Access | Times Cited: 1
20th European Meeting on Supercritical Fluids: Book of Abstracts
Željko Knez, Milica Pantić, Darija Cör
(2024)
Open Access
Conversion of soybean oil under subcritical water conditions into liquid biofuels with low oxygen contents
Jong-Ho Choi, JoYong Park, Aye Aye Myint, et al.
Fuel (2024) Vol. 378, pp. 132772-132772
Closed Access
Capabilities of Machine Learning Methods in Prediction of Solubility of Substances in Supercritical Carbon Dioxide
D. A. Lavrukhina, А. Д. Павлов, М. П. Шлеймович, et al.
Russian Journal of Physical Chemistry B (2024) Vol. 18, Iss. 8, pp. 1815-1820
Closed Access
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