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:

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: 47

Showing 1-25 of 47 citing articles:

Biomass/Biochar carbon materials for CO2 capture and sequestration by cyclic adsorption processes: A review and prospects for future directions
Mohsen Karimi, Mohammad Shirzad, José A. C. Silva, et al.
Journal of CO2 Utilization (2022) Vol. 57, pp. 101890-101890
Open Access | Times Cited: 154
Carbon dioxide separation and capture by adsorption: a review
Mohsen Karimi, Mohammad Shirzad, José A. C. Silva, et al.
Environmental Chemistry Letters (2023) Vol. 21, Iss. 4, pp. 2041-2084
Open Access | Times Cited: 102
Machine learning applications in catalytic hydrogenation of carbon dioxide to methanol: A comprehensive review
Ermias Girma Aklilu, Tijani Bounahmidi
International Journal of Hydrogen Energy (2024) Vol. 61, pp. 578-602
Closed Access | Times Cited: 15
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
Comparative analysis to study the Darcy–Forchheimer Tangent hyperbolic flow towards cylindrical surface using artificial neural network: An application to Parabolic Trough Solar Collector
Anum Shafiq, Andaç Batur Çolak, Tabassum Naz Sindhu
Mathematics and Computers in Simulation (2023) Vol. 216, pp. 213-230
Closed Access | Times Cited: 37
A review of biowaste remediation and valorization for environmental sustainability: Artificial intelligence approach
Ria Aniza, Wei‐Hsin Chen, Anélie Pétrissans, et al.
Environmental Pollution (2023) Vol. 324, pp. 121363-121363
Closed Access | Times Cited: 36
Development of an intelligent computing system using neural networks for modeling bioconvection flow of second-grade nanofluid with gyrotactic microorganisms
Anum Shafiq, Andaç Batur Çolak, Tabassum Naz Sindhu
Numerical Heat Transfer Part B Fundamentals (2023), pp. 1-18
Closed Access | Times Cited: 23
Hydrothermal carbonization of biomass waste and application of produced hydrochar in organic pollutants removal
Tingyu Pan, Zhicong Guo, Xionghao Zhang, et al.
Journal of Cleaner Production (2024) Vol. 457, pp. 142386-142386
Closed Access | Times Cited: 9
Harnessing artificial intelligence for enhanced bioethanol productions: a cutting-edge approach towards sustainable energy solution
Christopher Selvam Damian, Yuvarajan Devarajan, Thandavamoorthy Raja, et al.
International Journal of Chemical Reactor Engineering (2024) Vol. 22, Iss. 7, pp. 719-727
Closed Access | Times Cited: 9
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
MIL-160(Al) as a Candidate for Biogas Upgrading and CO2 Capture by Adsorption Processes
Mohsen Karimi, Alexandre Ferreira, Alı́rio E. Rodrigues, et al.
Industrial & Engineering Chemistry Research (2023) Vol. 62, Iss. 12, pp. 5216-5229
Open Access | Times Cited: 16
Machine learning-aided modeling of the hydrogen storage in zeolite-based porous media
Tao Hai, Farhan A. Alenizi, Adil Hussein Mohammed, et al.
International Communications in Heat and Mass Transfer (2023) Vol. 145, pp. 106848-106848
Closed Access | Times Cited: 14
Energy-agriculture nexus: Exploring the future of artificial intelligence applications
Masud Kabir, Sami Ekici
Energy Nexus (2023) Vol. 13, pp. 100263-100263
Open Access | Times Cited: 14
Biogas upgrading using shaped MOF MIL-160(Al) by pressure swing adsorption process: Experimental and dynamic modelling assessment
Mohsen Karimi, Rafael Magalhães Siqueira, Alı́rio E. Rodrigues, et al.
Separation and Purification Technology (2024) Vol. 344, pp. 127260-127260
Closed Access | Times Cited: 5
Robust intelligent paradigms for estimating fouling in phosphoric acid / steam heat exchanger
Rania Jradi, Christophe Marvillet, Mohamed Razak Jeday
Energy (2025) Vol. 315, pp. 134439-134439
Closed Access
An integrated ML model for the prediction of the melting points, phase diagrams, and eutectic points of the Type III and V deep eutectic solvents
Dian Jin, Haotian He, Li Sun, et al.
Chemical Engineering Science (2025), pp. 121245-121245
Closed Access
Theoretical Understanding of Pharmaceutics Solubility in Supercritical CO2; Thermodynamic Modeling and Machine learning study
He Liu, Chen Zhang, Ke Hu, et al.
The Journal of Supercritical Fluids (2025), pp. 106605-106605
Closed Access
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
Relationship between production condition, microstructure and final properties of chitosan/graphene oxide–zinc oxide bionanocomposite
Nazi Azimi, Asghar Gandomkar, Mehdi Sharif
Polymer Bulletin (2022) Vol. 80, Iss. 6, pp. 6455-6469
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
Artificial Neural Networking (ANN) Model for Drag Coefficient Optimization for Various Obstacles
Khalil Ur Rehman, Andaç Batur Çolak, Wasfı Shatanawi
Mathematics (2022) Vol. 10, Iss. 14, pp. 2450-2450
Open Access | Times Cited: 19
Prediction model for biochar energy potential based on biomass properties and pyrolysis conditions derived from rough set machine learning
Jia Yong Tang, Boaz Yi Heng Chung, Jia Chun Ang, et al.
Environmental Technology (2023) Vol. 45, Iss. 15, pp. 2908-2922
Open Access | Times Cited: 11
Simulating and Comparing CO2/CH4 Separation Performance of Membrane–Zeolite Contactors by Cascade Neural Networks
Seyyed Amirreza Abdollahi, AmirReza Andarkhor, Afham Pourahmad, et al.
Membranes (2023) Vol. 13, Iss. 5, pp. 526-526
Open Access | Times Cited: 11
Page 1 - Next Page

Scroll to top