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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:

Hydrogen solubility in aromatic/cyclic compounds: Prediction by different machine learning techniques
Yongchun Jiang, Guang-Fen Zhang, Juanjuan Wang, et al.
International Journal of Hydrogen Energy (2021) Vol. 46, Iss. 46, pp. 23591-23602
Closed Access | Times Cited: 59

Showing 1-25 of 59 citing articles:

Role of metal-organic framework in hydrogen gas storage: A critical review
A. R. Yuvaraj, A. Jayarama, Deepali Sharma, et al.
International Journal of Hydrogen Energy (2024) Vol. 59, pp. 1434-1458
Closed Access | Times Cited: 31
Advancing hydrogen storage predictions in metal-organic frameworks: A comparative study of LightGBM and random forest models with data enhancement
Masoud Seyyedattar, Sohrab Zendehboudi, Ali Ghamartale, et al.
International Journal of Hydrogen Energy (2024) Vol. 69, pp. 158-172
Open Access | Times Cited: 16
Electrical efficiency of the photovoltaic/thermal collectors cooled by nanofluids: Machine learning simulation and optimization by evolutionary algorithm
Yan Cao, Elham Kamrani, Saeid Mirzaei, et al.
Energy Reports (2021) Vol. 8, pp. 24-36
Open Access | Times Cited: 100
Estimating the density of deep eutectic solvents applying supervised machine learning techniques
Mohammad Javad Abdollahzadeh, Marzieh Khosravi, Behnam Hajipour Khire Masjidi, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 68
Application of machine learning methods for estimating and comparing the sulfur dioxide absorption capacity of a variety of deep eutectic solvents
Xiaolei Zhu, Marzieh Khosravi, Behzad Vaferi, et al.
Journal of Cleaner Production (2022) Vol. 363, pp. 132465-132465
Closed Access | Times Cited: 62
Simulation the adsorption capacity of polyvinyl alcohol/carboxymethyl cellulose based hydrogels towards methylene blue in aqueous solutions using cascade correlation neural network (CCNN) technique
Ali Hosin Alibak, Mohsen Khodarahmi, Pooya Fayyazsanavi, et al.
Journal of Cleaner Production (2022) Vol. 337, pp. 130509-130509
Closed Access | Times Cited: 60
Machine learning analysis of alloying element effects on hydrogen storage properties of AB2 metal hydrides
Suwarno Suwarno, Ghazy Dicky, Abdillah Suyuthi, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 23, pp. 11938-11947
Closed Access | Times Cited: 54
Machine learning approaches for predicting arsenic adsorption from water using porous metal–organic frameworks
Jafar Abdi, Golshan Mazloom
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 44
Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage
Hung Vo Thanh, Hemeng Zhang, Zhenxue Dai, et al.
International Journal of Hydrogen Energy (2023) Vol. 55, pp. 1422-1433
Closed Access | Times Cited: 40
Employing Deep Learning Neural Networks for Characterizing Dual-Porosity Reservoirs Based on Pressure Transient Tests
Rakesh Kumar Pandey, Anil Kumar, Ajay Mandal, et al.
Journal of Energy Resources Technology (2022) Vol. 144, Iss. 11
Closed Access | Times Cited: 39
Real-time data-driven fault diagnosis of proton exchange membrane fuel cell system based on binary encoding convolutional neural network
Su Zhou, Yanda Lu, Datong Bao, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 20, pp. 10976-10989
Closed Access | Times Cited: 38
Prediction of hydrogen solubility in aqueous solution using modified mixed effects random forest based on particle swarm optimization for underground hydrogen storage
Grant Charles Mwakipunda, Norga Alloyce Komba, Allou Koffi Franck Kouassi, et al.
International Journal of Hydrogen Energy (2024) Vol. 87, pp. 373-388
Closed Access | Times Cited: 9
Robust intelligent topology for estimation of heat capacity of biochar pyrolysis residues
Mohsen Karimi, Elnaz Aminzadehsarikhanbeglou, Behzad Vaferi
Measurement (2021) Vol. 183, pp. 109857-109857
Closed Access | Times Cited: 49
Intelligent modeling for considering the effect of bio-source type and appearance shape on the biomass heat capacity
Mohsen Karimi, Ali Hosin Alibak, Seyed Mehdi Alizadeh, et al.
Measurement (2021) Vol. 189, pp. 110529-110529
Closed Access | Times Cited: 48
Estimating the Relative Crystallinity of Biodegradable Polylactic Acid and Polyglycolide Polymer Composites by Machine Learning Methodologies
Jing Wang, Mohamed Arselene Ayari, Amith Khandakar, et al.
Polymers (2022) Vol. 14, Iss. 3, pp. 527-527
Open Access | Times Cited: 37
Determination of the heat capacity of cellulosic biosamples employing diverse machine learning approaches
Mohsen Karimi, Marzieh Khosravi, Reza Fathollahi, et al.
Energy Science & Engineering (2022) Vol. 10, Iss. 6, pp. 1925-1939
Open Access | Times Cited: 33
Numerical investigating the effect of Al2O3-water nanofluids on the thermal efficiency of flat plate solar collectors
Xu Lan, Aboozar Khalifeh, Amith Khandakar, et al.
Energy Reports (2022) Vol. 8, pp. 6530-6542
Open Access | Times Cited: 29
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
Application of robust machine learning methods to modeling hydrogen solubility in hydrocarbon fuels
Mohammad-Reza Mohammadi, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.
International Journal of Hydrogen Energy (2021) Vol. 47, Iss. 1, pp. 320-338
Closed Access | Times Cited: 39
Hybrid boosting algorithms and artificial neural network for wind speed prediction
Ayşe Tuğba Dosdoğru, Aslı Boru
International Journal of Hydrogen Energy (2021) Vol. 47, Iss. 3, pp. 1449-1460
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
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
A universal methodology for reliable predicting the non-steroidal anti-inflammatory drug solubility in supercritical carbon dioxide
Tahereh Rezaei, Vesal Nazarpour, Nahal Shahini, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 26
Application of computational fluid dynamics for detection of high risk region in middle cerebral artery (MCA) aneurysm
Ali Rostamian, Keivan Fallah, Yasser Rostamiyan, et al.
International Journal of Modern Physics C (2022) Vol. 34, Iss. 02
Closed Access | Times Cited: 26
Combined septum and chamfer fins on threated stretching surface under the influence of nanofluid and the magnetic parameters for rotary seals in computer hardware
Paria Shadman, Zahra Parhizi, Reza Fathollahi, et al.
Alexandria Engineering Journal (2022) Vol. 62, pp. 489-507
Open Access | Times Cited: 25
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