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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:

Modeling of CO2 capture ability of [Bmim][BF4] ionic liquid using connectionist smart paradigms
Bahador Daryayehsalameh, Miralireza Nabavi, Behzad Vaferi
Environmental Technology & Innovation (2021) Vol. 22, pp. 101484-101484
Closed Access | Times Cited: 97

Showing 26-50 of 97 citing articles:

Multi-layer perceptron's neural network with optimization algorithm for greenhouse gas forecasting systems
Ashok Kumar Nanda, S. Neelakandan, Sachi Gupta, et al.
Environmental Challenges (2023) Vol. 11, pp. 100708-100708
Open Access | Times Cited: 17
Mapping the application research on machine learning in the field of ionic liquids: A bibliometric analysis
Ze Wei, Fei Chen, Hui Liu, et al.
Fluid Phase Equilibria (2024) Vol. 583, pp. 114117-114117
Closed Access | Times Cited: 6
Experimental investigation and artificial intelligent estimation of thermal conductivity of nanofluids with different nanoparticles shapes
Wei Cui, Zehan Cao, Xinyi Li, et al.
Powder Technology (2021) Vol. 398, pp. 117078-117078
Closed Access | Times Cited: 40
Determination of Methanol Loss Due to Vaporization in Gas Hydrate Inhibition Process Using Intelligent Connectionist Paradigms
Saleh Hosseini, Behzad Vaferi
Arabian Journal for Science and Engineering (2021) Vol. 47, Iss. 5, pp. 5811-5819
Closed Access | Times Cited: 37
Potential application of metal-organic frameworks (MOFs) for hydrogen storage: Simulation by artificial intelligent techniques
Yan Cao, Hayder A. Dhahad, Sara Ghaboulian Zare, et al.
International Journal of Hydrogen Energy (2021) Vol. 46, Iss. 73, pp. 36336-36347
Closed Access | Times Cited: 35
RETRACTED: Hybrid Application of Nanoparticles and Polymer in Enhanced Oil Recovery Processes
Yanqiu Hu, Zeyuan Zhao, Huijie Dong, et al.
Polymers (2021) Vol. 13, Iss. 9, pp. 1414-1414
Open Access | Times Cited: 33
Hydrogen solubility in furfural and furfuryl bio-alcohol: Comparison between the reliability of intelligent and thermodynamic models
Juanjuan Xie, Xiaoqing Liu, Xiaodong Lao, et al.
International Journal of Hydrogen Energy (2021) Vol. 46, Iss. 73, pp. 36056-36068
Closed Access | Times Cited: 33
The role of surface and structural functionalisation on graphene adsorbent nanomaterial for CO2 adsorption application: Recent progress and future prospects
Amirul Hafiiz Ruhaimi, C.N.C. Hitam, M.A.A. Aziz, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 167, pp. 112840-112840
Closed Access | Times Cited: 24
Ce(III) and La(III) ions adsorption using Amberlite XAD-7 resin impregnated with DEHPA extractant: response surface methodology, isotherm and kinetic study
Azadeh Yarahmadi, Mohammad Hassan Khani, Masoud Nasiri, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 13
CARBON CAPTURE USING IONIC LIQUIDS: AN EXPLICIT DATA DRIVEN MODEL FOR CARBON (IV) OXIDE SOLUBILITY ESTIMATION
Okorie E. Agwu, Saad Alatefi, Ahmad Alkouh, et al.
Journal of Cleaner Production (2024) Vol. 472, pp. 143508-143508
Closed Access | Times Cited: 5
Petroleum and oil industries
Suryapratap Ray, Sanjana Thanjan Shaju, Chitra Jangid
Green Chemistry (2025), pp. 293-327
Closed Access
Smart tracking of the influence of alumina nanoparticles on the thermal coefficient of nanosuspensions: application of LS-SVM methodology
Miralireza Nabavi, Vesal Nazarpour, Ali Hosin Alibak, et al.
Applied Nanoscience (2021) Vol. 11, Iss. 7, pp. 2113-2128
Closed Access | Times Cited: 31
On the application of surfactant and water alternating gas (SAG/WAG) injection to improve oil recovery in tight reservoirs
Xiao Sun, Jia Liu, Xiaodong Dai, et al.
Energy Reports (2021) Vol. 7, pp. 2452-2459
Open Access | Times Cited: 27
Predicting the hydrogen uptake ability of a wide range of zeolites utilizing supervised machine learning methods
Seyed Mehdi Alizadeh, Zahra Parhizi, Ali Hosin Alibak, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 51, pp. 21782-21793
Closed Access | Times Cited: 21
Developing an accurate empirical correlation for predicting anti-cancer drugs’ dissolution in supercritical carbon dioxide
Fardad Faress, Amin Yari, Fereshteh Rajabi Kouchi, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 20
The Electrical Conductivity of Ionic Liquids: Numerical and Analytical Machine Learning Approaches
Theodoros E. Karakasidis, Filippos Sofos, Christos Tsonos
Fluids (2022) Vol. 7, Iss. 10, pp. 321-321
Open Access | Times Cited: 19
Investigation of the solubility of anticancer drugs in the supercritical solvent for development of innovative drug delivery systems; artificial intelligence paradigms (MLP-ANN) and thermodynamic correlations
Mitra Amani, Nedasadat Saadati Ardestani
Journal of Molecular Liquids (2023) Vol. 394, pp. 123701-123701
Closed Access | Times Cited: 12
A critical review on machine-learning-assisted screening and design of effective sorbents for carbon dioxide (CO2) capture
Zequn Yang, Chen Bo-shi, Hongmei Chen, et al.
Frontiers in Energy Research (2023) Vol. 10
Open Access | Times Cited: 11
A laboratory approach to enhance oil recovery factor in a low permeable reservoir by active carbonated water injection
Xinxiao Chen, Aminsadegh Paprouschi, Marischa Elveny, et al.
Energy Reports (2021) Vol. 7, pp. 3149-3155
Open Access | Times Cited: 24
A modeling approach for estimating hydrogen sulfide solubility in fifteen different imidazole-based ionic liquids
Jafar Abdi, Masoud Hadipoor, Seyyed Hamid Esmaeili-Faraj, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 18
Applying the wavelet neural network to estimate hydrogen dissolution in underground sodium chloride solutions
Yinuo Zhu, Hongda Wang, Keya Vano
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 54, pp. 22720-22730
Closed Access | Times Cited: 17
Relying on machine learning methods for predicting hydrogen solubility in different alcoholic solvents
Zongming Zhou, Pejman Nourani, Mehdi Karimi, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 9, pp. 5817-5827
Closed Access | Times Cited: 16
Utilizing fly ash from a power plant company for CO2 capture in a microchannel
Kaveh Nejati, Babak Aghel
Energy (2023) Vol. 278, pp. 128005-128005
Closed Access | Times Cited: 9
A comprehensive thermodynamic modeling of the solubility of sugar alcohols in ionic liquids
Ali Bakhtyari, Khayyam Mehrabi, Ali Rasoolzadeh, et al.
Separation and Purification Technology (2024) Vol. 338, pp. 126308-126308
Open Access | Times Cited: 3
Mathematical modeling of dispersed CO2 dissolution in ionic liquids: Application to carbon capture
Parsa Amin, Alireza Memarian, Eveliina Repo, et al.
Journal of Molecular Liquids (2024) Vol. 402, pp. 124486-124486
Open Access | Times Cited: 3

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