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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:

Predicting the wettability rocks/minerals-brine-hydrogen system for hydrogen storage: Re-evaluation approach by multi-machine learning scheme
Hung Vo Thanh, Mohammad Rahimi, Zhenxue Dai, et al.
Fuel (2023) Vol. 345, pp. 128183-128183
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Machine-learning models to predict hydrogen uptake of porous carbon materials from influential variables
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, et al.
Separation and Purification Technology (2023) Vol. 316, pp. 123807-123807
Closed Access | Times Cited: 43
Machine learning - based shale wettability prediction: Implications for H2, CH4 and CO2 geo-storage
Bin Pan, Tianru Song, Ming Yue, et al.
International Journal of Hydrogen Energy (2024) Vol. 56, pp. 1384-1390
Closed Access | Times Cited: 26
Exploring hydrogen geologic storage in China for future energy: Opportunities and challenges
Zhengyang Du, Zhenxue Dai, Zhijie Yang, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 196, pp. 114366-114366
Closed Access | Times Cited: 20
A critical review of physics-informed machine learning applications in subsurface energy systems
Abdeldjalil Latrach, Mohamed Lamine Malki, Misael M. Morales, et al.
Geoenergy Science and Engineering (2024) Vol. 239, pp. 212938-212938
Open Access | Times Cited: 17
Prediction of hydrogen−brine interfacial tension at subsurface conditions: Implications for hydrogen geo-storage
Mostafa Hosseini, Yuri Leonenko
International Journal of Hydrogen Energy (2024) Vol. 58, pp. 485-494
Open Access | Times Cited: 16
Low-Carbon Advancement through Cleaner Production: A Machine Learning Approach for Enhanced Hydrogen Storage Predictions in Coal Seams
Yongjun Wang, Hung Vo Thanh, Hemeng Zhang, et al.
Renewable Energy (2025), pp. 122342-122342
Closed Access | Times Cited: 1
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: 38
Modelling underground hydrogen storage: A state-of-the-art review of fundamental approaches and findings
Motaz Saeed, Prashant Jadhawar
Gas Science and Engineering (2023) Vol. 121, pp. 205196-205196
Open Access | Times Cited: 28
Yield prediction and optimization of biomass-based products by multi-machine learning schemes: Neural, regression and function-based techniques
Mohammad Rahimi, Hossein Mashhadimoslem, Hung Vo Thanh, et al.
Energy (2023) Vol. 283, pp. 128546-128546
Closed Access | Times Cited: 27
Recent progress on advanced solid adsorbents for CO2 capture: From mechanism to machine learning
Mobin Safarzadeh Khosrowshahi, Amirhossein Afshari Aghajari, Mohammad Rahimi, et al.
Materials Today Sustainability (2024) Vol. 27, pp. 100900-100900
Closed Access | Times Cited: 12
Molecular Insights into the Impact of Surface Chemistry and Pressure on Quartz Wettability: Resolving Discrepancies for Hydrogen Geo-storage
Ruyi Zheng, Timothy C. Germann, Michael R. Gross, et al.
ACS Sustainable Chemistry & Engineering (2024) Vol. 12, Iss. 14, pp. 5555-5563
Closed Access | Times Cited: 11
Enhancing carbon sequestration: Innovative models for wettability dynamics in CO2-brine-mineral systems
Hung Vo Thanh, Hemeng Zhang, Mohammad Rahimi, et al.
Journal of environmental chemical engineering (2024) Vol. 12, Iss. 5, pp. 113435-113435
Closed Access | Times Cited: 9
Integrating Capacity and Efficiency for Optimal Hydrogen Storage Site Selection in Saline Aquifers
Fangxuan Chen, Bailian Chen, Shaowen Mao, et al.
Energy & Fuels (2024) Vol. 38, Iss. 5, pp. 4733-4742
Closed Access | Times Cited: 8
Investigation of Wettability and IFT Alteration during Hydrogen Storage Using Machine Learning
Mehdi Maleki, Mohammad Rasool Dehghani, Ali Akbari, et al.
Heliyon (2024) Vol. 10, Iss. 19, pp. e38679-e38679
Open Access | Times Cited: 7
Long-term stability forecasting for energy storage salt caverns using deep learning-based model
Kai Zhao, Shinong Yu, Louis Ngai Yuen Wong
Energy (2025), pp. 134854-134854
Closed Access
Estimating the hydrogen adsorption in depleted shale gas reservoirs for kerogens in underground hydrogen storage using machine learning algorithms
Grant Charles Mwakipunda, Mouigni Baraka Nafouanti, AL-Wesabi Ibrahim, et al.
Fuel (2025) Vol. 388, pp. 134534-134534
Closed Access
Artificial intelligence in geoenergy: bridging petroleum engineering and future-oriented applications
Sungil Kim, Tea-Woo Kim, Suryeom Jo
Journal of Petroleum Exploration and Production Technology (2025) Vol. 15, Iss. 2
Open Access
Application of Ensemble Learning Paradigms in Predicting Interfacial Tension of H2/Cushion Gas Systems and the Implications on Subsurface H2 Storage
Joshua Nsiah Turkson, Muhammad Aslam Md Yusof, Bennet Nii Tackie-Otoo, et al.
International Petroleum Technology Conference (2025)
Closed Access
Data-Driven Prediction of Storage Column Height for H2-Brine Systems: Accelerating Underground Hydrogen Storage
Aneeq Nasir Janjua, Zeeshan Tariq, Muhammad Ali, et al.
International Petroleum Technology Conference (2025)
Closed Access
Technical challenges and opportunities of hydrogen storage: A comprehensive review on different types of underground storage
Guangyao Leng, Wei Yan, Zhangxin Chen, et al.
Journal of Energy Storage (2025) Vol. 114, pp. 115900-115900
Closed Access
Improving wettability estimation in carbonate formation using machine learning algorithms: Implications for underground hydrogen storage applications
Grant Charles Mwakipunda, AL-Wesabi Ibrahim, Allou Koffi Franck Kouassi, et al.
International Journal of Hydrogen Energy (2025) Vol. 111, pp. 781-797
Closed Access
Hydrogen production and pollution mitigation: Enhanced gasification of plastic waste and biomass with machine learning & storage for a sustainable future
Abu Danish Aiman Bin Abu Sofian, Hooi Ren Lim, Kit Wayne Chew, et al.
Environmental Pollution (2023) Vol. 342, pp. 123024-123024
Closed Access | Times Cited: 10
Prediction of interfacial wetting behavior of H2/mineral/brine; implications for H2 geo-storage
Kamyab Kohzadvand, Maryam Mahmoudi Kouhi, Ali Akbar Barati, et al.
Journal of Energy Storage (2023) Vol. 72, pp. 108567-108567
Closed Access | Times Cited: 8
Reservoir rock typing for optimum permeability prediction of Nubia formation in October Field, Gulf of Suez, Egypt
Mohamed A. Kassab, Ali Abbas, Ihab Abdel Latif Osman, et al.
Journal of Petroleum Exploration and Production Technology (2024) Vol. 14, Iss. 6, pp. 1395-1416
Open Access | Times Cited: 2
Dynamics of hydrogen storage in subsurface saline aquifers: A computational and experimental pore-scale displacement study
Rajat Dehury, Satyajit Chowdhury, Jitendra S. Sangwai
International Journal of Hydrogen Energy (2024) Vol. 69, pp. 817-836
Closed Access | Times Cited: 2
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