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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:

Exploring the power of machine learning to predict carbon dioxide trapping efficiency in saline aquifers for carbon geological storage project
Majid Safaei-Farouji, Hung Vo Thanh, Zhenxue Dai, et al.
Journal of Cleaner Production (2022) Vol. 372, pp. 133778-133778
Closed Access | Times Cited: 62

Showing 1-25 of 62 citing articles:

Machine-learning predictions of solubility and residual trapping indexes of carbon dioxide from global geological storage sites
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, et al.
Expert Systems with Applications (2023) Vol. 222, pp. 119796-119796
Closed Access | Times Cited: 58
Prospects of carbon capture, utilization and storage for mitigating climate change
Poritosh Roy, Amar K. Mohanty, Manjusri Misra
Environmental Science Advances (2023) Vol. 2, Iss. 3, pp. 409-423
Open Access | Times Cited: 47
Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and storage
Hemeng Zhang, Hung Vo Thanh, Mohammad Rahimi, et al.
The Science of The Total Environment (2023) Vol. 877, pp. 162944-162944
Closed Access | Times Cited: 45
Selecting Geological Formations for CO2 Storage: A Comparative Rating System
Muhammad Hammad Rasool, Maqsood Ahmad, Muhammad Ayoub
Sustainability (2023) Vol. 15, Iss. 8, pp. 6599-6599
Open Access | Times Cited: 40
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
Reservoir Quality Prediction of Gas-Bearing Carbonate Sediments in the Qadirpur Field: Insights from Advanced Machine Learning Approaches of SOM and Cluster Analysis
Muhammad Rashid, Miao Luo, Umar Ashraf, et al.
Minerals (2022) Vol. 13, Iss. 1, pp. 29-29
Open Access | Times Cited: 52
A Novel Machine Learning Approach for Detecting Outliers, Rebuilding Well Logs, and Enhancing Reservoir Characterization
Muhammad Ali, Peimin Zhu, Huolin Ma, et al.
Natural Resources Research (2023) Vol. 32, Iss. 3, pp. 1047-1066
Closed Access | Times Cited: 37
Combined machine-learning and optimization models for predicting carbon dioxide trapping indexes in deep geological formations
Shadfar Davoodi, Hung Vo Thanh, David A. Wood, et al.
Applied Soft Computing (2023) Vol. 143, pp. 110408-110408
Closed Access | Times Cited: 34
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
A comparative study of statistical and machine learning models on carbon dioxide emissions prediction of China
Xiangqian Li, Xiaoxiao Zhang
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 55, pp. 117485-117502
Open Access | Times Cited: 26
A review of risk and uncertainty assessment for geologic carbon storage
Ting Xiao, Ting Chen, Zhiwei Ma, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 189, pp. 113945-113945
Closed Access | Times Cited: 26
Hydrogen Storage on Porous Carbon Adsorbents: Rediscovery by Nature-Derived Algorithms in Random Forest Machine Learning Model
Hung Vo Thanh, Sajad Ebrahimnia Taremsari, Benyamin Ranjbar, et al.
Energies (2023) Vol. 16, Iss. 5, pp. 2348-2348
Open Access | Times Cited: 23
New-generation machine learning models as prediction tools for modeling interfacial tension of hydrogen-brine system
Afeez Gbadamosi, Haruna Adamu, Jamilu Usman, et al.
International Journal of Hydrogen Energy (2023) Vol. 50, pp. 1326-1337
Closed Access | Times Cited: 23
Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning
Nianyin Li, Wentao Feng, Jiajie Yu, et al.
Energy & Fuels (2023) Vol. 37, Iss. 14, pp. 10087-10111
Closed Access | Times Cited: 21
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: 14
Data driven simulations for accurately predicting thermodynamic properties of H2 during geological storage
Mohamad Reza Soltanian, Amin Bemani, Farzad Moeini, et al.
Fuel (2024) Vol. 362, pp. 130768-130768
Closed Access | Times Cited: 12
An ensemble-based strategy for robust predictive volcanic rock typing efficiency on a global-scale: A novel workflow driven by big data analytics
Umar Ashraf, Hucai Zhang, Aqsa Anees, et al.
The Science of The Total Environment (2024) Vol. 937, pp. 173425-173425
Closed Access | Times Cited: 11
An application of a genetic algorithm in co-optimization of geological CO2 storage based on artificial neural networks
Pouya Vaziri, Behnam Sedaee
Clean Energy (2024) Vol. 8, Iss. 1, pp. 111-125
Open Access | Times Cited: 9
Reviewing direct air capture startups and emerging technologies
Eryu Wang, Rahul Navik, Yihe Miao, et al.
Cell Reports Physical Science (2024) Vol. 5, Iss. 2, pp. 101791-101791
Open Access | Times Cited: 9
Comparing the performance of machine learning methods in estimating the shear wave transit time in one of the reservoirs in southwest of Iran
MohammadRasool Dehghani, Shahryar Jahani, A.A. Ranjbar
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Sub-surface geospatial intelligence in carbon capture, utilization and storage: A machine learning approach for offshore storage site selection
Mehdi Nassabeh, Zhenjiang You, Alireza Keshavarz, et al.
Energy (2024) Vol. 305, pp. 132086-132086
Open Access | Times Cited: 8
Hydrocarbon Potential Assessment of Carbonate-Bearing Sediments in a Meyal Oil Field, Pakistan: Insights from Logging Data Using Machine Learning and Quanti Elan Modeling
Jawad Ali, Umar Ashraf, Aqsa Anees, et al.
ACS Omega (2022) Vol. 7, Iss. 43, pp. 39375-39395
Open Access | Times Cited: 29
A multi-criteria decision-making (MCDM) approach to determine the synthesizing routes of biomass-based carbon electrode material in supercapacitors
Mohammad Rahimi, Hung Vo Thanh, Iman Ebrahimzade, et al.
Journal of Cleaner Production (2023) Vol. 397, pp. 136606-136606
Closed Access | Times Cited: 19
Exploring the Potential of Carbon Capture, Utilization, and Storage in Baltic Sea Region Countries: A Review of CCUS Patents from 2000 to 2022
Mayur Pal, Viltė Karaliūtė, Shruti Malik
Processes (2023) Vol. 11, Iss. 2, pp. 605-605
Open Access | Times Cited: 16
A review of microfluidic technology for CO2 sequestration in saline aquifers
Yiyan Zhong, Qi Li, Wenbin Gao, et al.
Journal of Rock Mechanics and Geotechnical Engineering (2025)
Open Access
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