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Phosphorus, Sulfur, and Silicon and the Related Elements Volume 191, 2016 - Issue 9
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Original Articles

Artificial intelligence techniques for modeling and optimization of the HDS process over a new graphene based catalyst

Zeinab HajjarInstitute for Nano Science & Nano Technology, Sharif University of Technology, Tehran, Iran;Research Institute of Petroleum Industry (RIPI), Tehran, IranCorrespondence[email protected] [email protected]
,
Mohammad KazemeiniInstitute for Nano Science & Nano Technology, Sharif University of Technology, Tehran, Iran;Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran
,
Alimorad RashidiResearch Institute of Petroleum Industry (RIPI), Tehran, IranCorrespondence[email protected] [email protected]
&
Shokoufe TayyebiResearch Institute of Petroleum Industry (RIPI), Tehran, Iran
Pages 1256-1261 | Received 28 Oct 2015, Accepted 13 Mar 2016, Published online: 11 Jul 2016

Citations (11)

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Muharrem Karabörk, Ban Abdullelah Muhammed, Mehmet Tümer & Serhan Uruş. (2022) Organosilane-functionalized graphene oxide hybrid material: Efficient adsorbent for heavy metal ions in drinking water. Phosphorus, Sulfur, and Silicon and the Related Elements 197:2, pages 133-143.
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Zeinab Hajjar, Mohammad Kazemeini, Alimorad Rashidi & Saeed Soltanali. (2018) Hydrodesulfurization catalysts based on carbon nanostructures: A review. Fullerenes, Nanotubes and Carbon Nanostructures 26:9, pages 557-569.
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Articles from other publishers (9)

Masoud Sheikhi Kordkheili & Farshad Rahimpour. (2023) Artificial neural network and semi-empirical modeling of industrial-scale Gasoil hydrodesulfurization reactor temperature profile. Mathematics and Computers in Simulation 206, pages 198-215.
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Saheed A. Ganiyu. (2021) Hierarchical Hybrid Supports and Synthesis Strategies for Hydrodesulfurization of Recalcitrance Organosulfur Compounds. Chemistry – An Asian Journal 16:11, pages 1307-1323.
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Hamdi A. Al-Jamimi & Tawfik A. Saleh. (2019) Transparent predictive modelling of catalytic hydrodesulfurization using an interval type-2 fuzzy logic. Journal of Cleaner Production 231, pages 1079-1088.
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Babak Behnejad, Majid Abdouss & Ahmad Tavasoli. (2019) NI-MO SUPPORTED NANOPOROUS GRAPHENE AS A NOVEL CATALYST FOR HDS AND HDN OF HEAVY NAPHTHA. Brazilian Journal of Chemical Engineering 36:1, pages 265-273.
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Hamdi A. Al-Jamimi. (2019) Prediction of Sulfur Content in Desulfurization Process Using a Fuzzy-Logic Based Model. Solid State Phenomena 287, pages 80-85.
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Zeinab Hajjar, Shokoufe Tayyebi & Mohammad Hosein Eghbal Ahmadi. 2018. Artificial Intelligence - Emerging Trends and Applications. Artificial Intelligence - Emerging Trends and Applications.
Alimorad Rashidi, Fatemeh Mohammadzadeh & Sedigheh Sadegh Hassani. 2018. Nanotechnology in Oil and Gas Industries. Nanotechnology in Oil and Gas Industries 193 210 .
Zeinab Hajjar, Mohammad Kazemeini, Alimorad Rashidi & Saeed Soltanali. (2017) Optimizing parameters affecting synthesis of a novel Co–Mo/GO catalyst in a Naphtha HDS reaction utilizing D-optimal experimental design method. Journal of the Taiwan Institute of Chemical Engineers 78, pages 566-575.
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Zeinab Hajjar, Mohammad Kazemeini, Alimorad Rashidi, Saeed Soltanali & Farzad Bahadoran. (2017) Naphtha HDS over Co-Mo/Graphene catalyst synthesized through the spray pyrolysis technique. Journal of Analytical and Applied Pyrolysis 123, pages 144-151.
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