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:

Modeling of CO2 solubility in piperazine (PZ) and diethanolamine (DEA) solution via machine learning approach and response surface methodology
Zohreh Khoshraftar, Ahad Ghaemi
Case Studies in Chemical and Environmental Engineering (2023) Vol. 8, pp. 100457-100457
Open Access | Times Cited: 16

Showing 16 citing articles:

Modeling based on machine learning to investigate flue gas desulfurization performance by calcium silicate absorbent in a sand bed reactor
Kamyar Naderi, Mohammad Yazdi, Hanieh Jafarabadi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 13

Enhanced carbon dioxide adsorption using lignin-derived and nitrogen-doped porous carbons: A machine learning approaches, RSM and isotherm modeling
Zohreh Khoshraftar, Ahad Ghaemi
Case Studies in Chemical and Environmental Engineering (2024) Vol. 9, pp. 100668-100668
Open Access | Times Cited: 10

Comprehensive investigation of isotherm, RSM, and ANN modeling of CO2 capture by multi-walled carbon nanotube
Zohreh Khoshraftar, Ahad Ghaemi, Alireza Hemmati
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 10

Modeling of carbon dioxide absorption into aqueous alkanolamines using machine learning and response surface methodology
Hadiseh Masoumi, Ali Akbar Imani, A. Aslani, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 5

Mixed MDEA-PZ amine solutions for CO2 capture: Modeling and optimization using RSM and ANN approaches
Pedram Zafari, Ahad Ghaemi
Case Studies in Chemical and Environmental Engineering (2023) Vol. 8, pp. 100509-100509
Open Access | Times Cited: 12

Analysis of effective area and mass transfer in a structure packing column using machine learning and response surface methodology
Amirsoheil Foroughi, Kamyar Naderi, Ahad Ghaemi, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 4

Analysis of CO2 solubility in ionic liquids as promising absorbents using response surface methodology and machine learning
Alireza Rahimi, Fatemeh Bahmanzadegan, Ahad Ghaemi
Journal of CO2 Utilization (2025) Vol. 93, pp. 103043-103043
Open Access

Prediction of methane hydrate equilibrium in saline water solutions based on support vector machine and decision tree techniques
Chou‐Yi Hsu, Jorge Sebastián Buñay Guamán, Amit Ved, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

Optimization of CO2 absorption into MDEA-PZ-sulfolane hybrid solution using machine learning algorithms and RSM
Abolfazl Shokri, Sepehr Aarabi Dahej, Ahad Ghaemi
Environmental Science and Pollution Research (2025)
Closed Access

Maximizing Cyclone Efficiency: Innovating Body Rotation for Silica Particle Separation via RSM and ANNs Modeling
Zohreh Khoshraftar, Ahad Ghaemi
Arabian Journal for Science and Engineering (2024) Vol. 49, Iss. 6, pp. 8489-8507
Closed Access | Times Cited: 2

Polyethylenimine-functionalized halloysite nanotube as an adsorbent for CO2 capture: RSM and ANN methodology
Zohreh Khoshraftar, Ahad Ghaemi, Fatemeh S. Taheri
Current Research in Green and Sustainable Chemistry (2023) Vol. 7, pp. 100389-100389
Open Access | Times Cited: 4

Influence of Piperazine on CO2 Hydrate Dissociation Equilibrium Conditions
Jing Xia, Zhigao Sun
Journal of Chemical & Engineering Data (2024) Vol. 69, Iss. 11, pp. 4098-4103
Closed Access

Predictive modeling of CO2 capture efficiency using piperazine solutions: a comparative study of white-box algorithms
Fahimeh Hadavimoghaddam, Jianguang Wei, Alexei Rozhenko, et al.
Deleted Journal (2024) Vol. 6, Iss. 11
Open Access

Predictive Modeling of the Long-term Effects of Combined Chemical Admixtures on Concrete Compressive Strength Using Machine Learning Algorithms
S. Heidari, Majid Safehian, Faramarz Moodi, et al.
Case Studies in Chemical and Environmental Engineering (2024) Vol. 10, pp. 101008-101008
Open Access

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