Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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:

Robust smart schemes for modeling carbon dioxide uptake in metal − organic frameworks
Menad Nait Amar, Hocine Ouaer, Mohammed Abdelfetah Ghriga
Fuel (2021) Vol. 311, pp. 122545-122545
Closed Access | Times Cited: 31

Showing 1-25 of 31 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: 45
Modeling interfacial tension of the hydrogen-brine system using robust machine learning techniques: Implication for underground hydrogen storage
Cuthbert Shang Wui Ng, Hakim Djema, Menad Nait Amar, et al.
International Journal of Hydrogen Energy (2022) Vol. 47, Iss. 93, pp. 39595-39605
Open Access | Times Cited: 58
A combined prediction model based on secondary decomposition and intelligence optimization for carbon emission
Hong Yang, Maozhu Wang, Guohui Li
Applied Mathematical Modelling (2023) Vol. 121, pp. 484-505
Closed Access | Times Cited: 29
Machine learning implemented exploration of the adsorption mechanism of carbon dioxide onto porous carbons
Sarvesh Namdeo, Vimal Chandra Srivastava, Paritosh Mohanty
Journal of Colloid and Interface Science (2023) Vol. 647, pp. 174-187
Closed Access | Times Cited: 22
Efficient Removal of Greenhouse Gases: Machine Learning-Assisted Exploration of Metal–Organic Framework Space
R. C. Xin, Chaohai Wang, Yingchao Zhang, et al.
ACS Nano (2024)
Closed Access | Times Cited: 13
Computational and Machine Learning Methods for CO2 Capture Using Metal–Organic Frameworks
Hossein Mashhadimoslem, Mohammad Ali Abdol, Peyman Karimi, et al.
ACS Nano (2024) Vol. 18, Iss. 35, pp. 23842-23875
Closed Access | Times Cited: 13
Application of power-law committee machine to combine five machine learning algorithms for enhanced oil recovery screening
Reza Yousefzadeh, Alireza Kazemi, Rashid S. Al‐Maamari
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 8
Machine learning prediction of methane, nitrogen, and natural gas mixture viscosities under normal and harsh conditions
Sayed Gomaa, Mohamed A. E. Abdalla, Khalaf G. Salem, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Exploring advanced artificial intelligence techniques for efficient hydrogen storage in metal organic frameworks
Arefeh Naghizadeh, Fahimeh Hadavimoghaddam, Saeid Atashrouz, et al.
Adsorption (2025) Vol. 31, Iss. 2
Closed Access
Predictive modeling on the surface tension and viscosity of ionic liquid-organic solvent mixtures via machine learning
Yang Lei, You Shu, Xuegang Liu, et al.
Journal of the Taiwan Institute of Chemical Engineers (2023) Vol. 151, pp. 105140-105140
Closed Access | Times Cited: 15
Soft computing approach on estimating the lateral confinement coefficient of CFRP veiled circular columns
Xingsi Xue, Ghaida Muttashar Abdulsahib, Osamah Ibrahim Khalaf, et al.
Alexandria Engineering Journal (2023) Vol. 81, pp. 599-619
Open Access | Times Cited: 9
Predicting the solubility of hydrogen in hydrocarbon fractions: Advanced data-driven machine learning approach and equation of state
Menad Nait Amar, Fahd Mohamad Alqahtani, Hakim Djema, et al.
Journal of the Taiwan Institute of Chemical Engineers (2023) Vol. 153, pp. 105215-105215
Closed Access | Times Cited: 8
Modeling gypsum (calcium sulfate dihydrate) solubility in aqueous electrolyte solutions using extreme learning machine
Mohammad Ebrahimi, Omid Deymi, Fahimeh Hadavimoghaddam, et al.
Journal of Water Process Engineering (2023) Vol. 57, pp. 104664-104664
Closed Access | Times Cited: 7
Modeling and estimation of water activity for the ionic-liquid-based aqueous ternary systems by smart paradigms
Ehsan Davoudi, Abolhasan Ameri
Journal of the Taiwan Institute of Chemical Engineers (2024) Vol. 157, pp. 105396-105396
Closed Access | Times Cited: 2
Toward reliable prediction of CO2 uptake capacity of metal–organic frameworks (MOFs): implementation of white-box machine learning
Aydin Larestani, Ahmadreza Jafari-Sirizi, Fahimeh Hadavimoghaddam, et al.
Adsorption (2024)
Closed Access | Times Cited: 2
Robust machine-learning model for prediction of carbon dioxide adsorption on metal-organic frameworks
Promise O. Longe, Shadfar Davoodi, Mohammad Mehrad, et al.
Journal of Alloys and Compounds (2024), pp. 177890-177890
Closed Access | Times Cited: 2
Hydraulic informed multi-layer perceptron for estimating discharge coefficient of labyrinth weir
Ali Mahmoud, Xiaohui Lei, Xiang Zeng, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 123, pp. 106435-106435
Closed Access | Times Cited: 6
Biooxidation of refractory sulfide-bearing ore using feroplasma acidophilum: Efficiency assessment and machine learning based prediction
Mohammad Hossein Karimi Darvanjooghi, Usman T. Khan, Sara Magdouli, et al.
Current Research in Biotechnology (2024) Vol. 7, pp. 100179-100179
Open Access | Times Cited: 1
Using the Experimental Cross-Association Energy and Artificial Neural Network for Modeling the Phase Equilibrium of Carbon Dioxide–Water System: What Advances Can Be Achieved?
Zahra Rahmani, Ehsan Davani, Shahin Khosharay
International Journal of Thermophysics (2024) Vol. 45, Iss. 2
Closed Access | Times Cited: 1
Modeling Study on Heat Capacity, Viscosity, and Density of Ionic Liquid–Organic Solvent–Organic Solvent Ternary Mixtures via Machine Learning
You Shu, Lei Du, Yang Lei, et al.
Processes (2024) Vol. 12, Iss. 7, pp. 1420-1420
Open Access | Times Cited: 1
Atmospheric Humidity Estimation From Wind Profiler Radar Using a Cascaded Machine Learning Approach
Anas Amaireh, Yan Zhang, Pak Wai Chan
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2023) Vol. 16, pp. 6352-6371
Open Access | Times Cited: 3
A new approach to mechanical brittleness index modeling based on conventional well logs using hybrid algorithms
Milad Zamanzadeh Talkhouncheh, Shadfar Davoodi, Babak Larki, et al.
Earth Science Informatics (2023) Vol. 16, Iss. 4, pp. 3387-3416
Closed Access | Times Cited: 3
Experimental and simulation study of CO2 breakthrough curves in a fixed-bed adsorption process
Marek Nedoma, Marek Staf, Jan Hrdlička
Acta Polytechnica (2022) Vol. 62, Iss. 3, pp. 370-385
Open Access | Times Cited: 5
Experimental Measurement and Accurate Prediction of Crude Oil Viscosity Utilizing Advanced Intelligent Approaches
Maryam Sadi, Abbas Shahrabadi
Natural Resources Research (2023) Vol. 32, Iss. 4, pp. 1657-1682
Closed Access | Times Cited: 2
Analysis of nanomedicine production via green processing: Modeling and simulation of pharmaceutical solubility using artificial intelligence
Abdulrahman Sumayli, Wael A. Mahdi, Jawaher Abdullah Alamoudi
Case Studies in Thermal Engineering (2023) Vol. 51, pp. 103587-103587
Open Access | Times Cited: 2
Page 1 - Next Page

Scroll to top