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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:

Scavenging carbon deposition on alumina supported cobalt catalyst during renewable hydrogen-rich syngas production by methane dry reforming using artificial intelligence modeling technique
May Ali Alsaffar, Bamidele Victor Ayodele, Siti Indati Mustapa
Journal of Cleaner Production (2019) Vol. 247, pp. 119168-119168
Closed Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Biogas Reforming to Syngas: A Review
Xianhui Zhao, Babu Joseph, John N. Kuhn, et al.
iScience (2020) Vol. 23, Iss. 5, pp. 101082-101082
Open Access | Times Cited: 149
Recent advances of biogas reforming for hydrogen production: Methods, purification, utility and techno-economics analysis
Ravindra Kumar, Anil Kumar
International Journal of Hydrogen Energy (2024) Vol. 76, pp. 108-140
Closed Access | Times Cited: 16
Dry reforming of methane for syngas production: A review and assessment of catalyst development and efficacy
Apoorva M. Ranjekar, Ganapati D. Yadav
Journal of the Indian Chemical Society (2021) Vol. 98, Iss. 1, pp. 100002-100002
Closed Access | Times Cited: 94
A review of different catalytic systems for dry reforming of methane: Conventional catalysis-alone and plasma-catalytic system
Cong Yun Shi, Sha Wang, Xiang Ge, et al.
Journal of CO2 Utilization (2021) Vol. 46, pp. 101462-101462
Closed Access | Times Cited: 83
Recent advances in the design of high-performance cobalt-based catalysts for dry reforming of methane
Yinghui Sun, Yanbin Zhang, Xifei Yin, et al.
Green Chemistry (2024) Vol. 26, Iss. 9, pp. 5103-5126
Closed Access | Times Cited: 6
Modeling the effect of process parameters on the photocatalytic degradation of organic pollutants using artificial neural networks
Bamidele Victor Ayodele, May Ali Alsaffar, Siti Indati Mustapa, et al.
Process Safety and Environmental Protection (2020) Vol. 145, pp. 120-132
Closed Access | Times Cited: 63
Artificial intelligence (AI)‐driven strategic business model innovations in small‐ and medium‐sized enterprises. Insights on technological and strategic enablers for carbon neutral businesses
Aqueeb Sohail Shaik, Safiya Mukhtar Alshibani, Girish Jain, et al.
Business Strategy and the Environment (2023) Vol. 33, Iss. 4, pp. 2731-2751
Closed Access | Times Cited: 17
Modeling the prediction of hydrogen production by co‐gasification of plastic and rubber wastes using machine learning algorithms
Bamidele Victor Ayodele, Siti Indati Mustapa, Ramesh Kanthasamy, et al.
International Journal of Energy Research (2021) Vol. 45, Iss. 6, pp. 9580-9594
Open Access | Times Cited: 36
A tailored and rapid approach for ozonation catalyst design
Min Li, Liya Fu, Liyan Deng, et al.
Environmental Science and Ecotechnology (2023) Vol. 15, pp. 100244-100244
Open Access | Times Cited: 11
Backpropagation neural networks modelling of photocatalytic degradation of organic pollutants using TiO2‐based photocatalysts
Bamidele Victor Ayodele, May Ali Alsaffar, Siti Indati Mustapa, et al.
Journal of Chemical Technology & Biotechnology (2020) Vol. 95, Iss. 10, pp. 2739-2749
Closed Access | Times Cited: 33
CO2 reforming of methane over Ta-promoted Ni/ZSM-5 fibre-like catalyst: Insights on deactivation behavior and optimization using response surface methodology (RSM)
Hambali Umar Hambali, A.A. Jalil, Abdulrahman A. Abdulrasheed, et al.
Chemical Engineering Science (2020) Vol. 231, pp. 116320-116320
Closed Access | Times Cited: 33
Tailoring strontium-promoted alumina-zirconia supported Ni-catalysts for enhanced CO2 utilization via dry reforming of methane: Sr loading effects and process optimization
Ahmed S. Al‐Fatesh, Maher M. Alrashed, Radwa A. El‐Salamony, et al.
Journal of CO2 Utilization (2023) Vol. 75, pp. 102578-102578
Open Access | Times Cited: 10
Artificial Neural Network Modeling of Thermo-catalytic Methane Decomposition for Hydrogen Production
May Ali Alsaffar, Mohamed Abdel Rahman Abdel Ghany, Jamal M. Ali, et al.
Topics in Catalysis (2021) Vol. 64, Iss. 5-6, pp. 456-464
Closed Access | Times Cited: 23
Evaluation of Fischer-Tropsch synthesis to light olefins over Co- and Fe-based catalysts using artificial neural network
Higor Azevedo Garona, Fábio Machado Cavalcanti, Thiago F. Abreu, et al.
Journal of Cleaner Production (2021) Vol. 321, pp. 129003-129003
Closed Access | Times Cited: 20
Process intensification of hydrogen production by catalytic steam methane reforming: Performance analysis of multilayer perceptron-artificial neural networks and nonlinear response surface techniques
Bamidele Victor Ayodele, May Ali Alsaffar, Siti Indati Mustapa, et al.
Process Safety and Environmental Protection (2021) Vol. 156, pp. 315-329
Closed Access | Times Cited: 18
Correlation between the Experimental and Theoretical Photoelectrochemical Response of a WO3 Electrode for Efficient Water Splitting through the Implementation of an Artificial Neural Network
M. Diaby, Asma Alimi, A. Bardaoui, et al.
Sustainability (2023) Vol. 15, Iss. 15, pp. 11751-11751
Open Access | Times Cited: 6
Process Optimization for Syngas Production from the Dry Reforming of Methane over 5Ni+3Sr/10Zr+Al Catalyst Using Multiple Response Surface Methodology
Ahmed S. Al‐Fatesh, Radwa A. El‐Salamony, Mai Hassan Roushdy, et al.
Advanced Materials Interfaces (2023) Vol. 11, Iss. 1
Open Access | Times Cited: 6
Modeling photocatalytic hydrogen production from ethanol over copper oxide nanoparticles: a comparative analysis of various machine learning techniques
Alyaa K. Mageed
Biomass Conversion and Biorefinery (2021) Vol. 13, Iss. 4, pp. 3319-3327
Closed Access | Times Cited: 16
Carbon dioxide reforming of methane over Ni-based catalysts: Modeling the effect of process parameters on greenhouse gasses conversion using supervised machine learning algorithms
Bamidele Victor Ayodele, May Ali Alsaffar, Siti Indati Mustapa, et al.
Chemical Engineering and Processing - Process Intensification (2021) Vol. 166, pp. 108484-108484
Closed Access | Times Cited: 16
Effect of Textural Properties on the Degradation of Bisphenol from Industrial Wastewater Effluent in a Photocatalytic Reactor: A Modeling Approach
May Ali Alsaffar, Mohamed Abdel Rahman Abdel Ghany, Alyaa K. Mageed, et al.
Applied Sciences (2023) Vol. 13, Iss. 15, pp. 8966-8966
Open Access | Times Cited: 5
Impact of Gallium Loading and Process Conditions on H2 Production from Dry Reforming of Methane over Ni/ZrO2-Al2O3 Catalysts
Ahmed S. Al‐Fatesh, Yuvrajsinh B. Rajput, Mohammed O. Bayazed, et al.
Applied Catalysis A General (2024) Vol. 681, pp. 119794-119794
Open Access | Times Cited: 1
High throughput screening of promoted bimetallic catalysts supported on alumina for production of light olefins via Fischer-Tropsch synthesis with artificial neural network and response surface methodology
Deniz Uykun Mangaloğlu, Pelin Güzel, Selim Şenkan, et al.
Fuel (2024) Vol. 371, pp. 131935-131935
Closed Access | Times Cited: 1
Catalyst breakthroughs in methane dry reforming: Employing machine learning for future advancements
Somavia Ameen, Muhammad Umar Farooq, Samia, et al.
International Journal of Hydrogen Energy (2024)
Closed Access | Times Cited: 1
Neuro-genetic machine learning framework accelerates the optimization of Ag/MnOx catalyst for total oxidation of toluene
Jiaqian Yang, Zhiping Ye, Guanjie Wang, et al.
Applied Catalysis A General (2021) Vol. 622, pp. 118221-118221
Closed Access | Times Cited: 13
High-precision prediction of unionized hydrogen sulfide generation based on limited datasets and its impact on anaerobic digestion of sulfate-rich wastewater
Wanxin Yin, Ye Yuan, Fan Chen, et al.
Journal of Cleaner Production (2022) Vol. 341, pp. 130875-130875
Open Access | Times Cited: 9
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