Enhanced predictive optimization of methane dry reforming via ResponseSurface methodology and artificial neural network approaches: Insights using a novel nickel-strontium-zirconium-aluminum catalyst-Reference-Cited by-同舟云学术

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Enhanced predictive optimization of methane dry reforming via ResponseSurface methodology and artificial neural network approaches: Insights using a novel nickel-strontium-zirconium-aluminum catalyst

Published:2024-06 Issue: Volume:562 Page:114216
ISSN:2468-8231
Container-title:Molecular Catalysis
language:en
Short-container-title:Molecular Catalysis

Author:

Gendy Tahani S.,El-Salamony Radwa A.^ORCID,Alrashed Maher M.,Bentalib Abdulaziz,Osman Ahmed I.^ORCID,Kumar Rawesh,Fakeeha Anis H.^ORCID,Al-Fatesh Ahmed S.^ORCID

Funder

King Saud University

Publisher

Elsevier BV

Reference99 articles.

1. Syngas production via dry reforming of methane over Ni/MgO-ZrO2 catalyst;Farooqi,2023

2. A mini-review on lanthanum–Nickel-based perovskite-derived catalysts for hydrogen production via the dry reforming of methane (DRM);Georgiadis;Catalysts.,2023

3. Tailored Ni-MgO catalysts: unveiling temperature-driven synergy in CH4-CO2 reforming;Alghamdi;Catalysts.,2024

4. Dry reforming of methane over sub-stoichiometric NiAl2O4-mediated Ni/Al2O3 catalysts;Choya;Fuel,2024

5. CO2 reforming of methane over Ni-Ru supported catalysts: On the nature of active sites by operando DRIFTS study;Álvarez;J. CO2 Util.,2018

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Theoretical insights into CH4 and CO2 activation by Ni1/CeO2(111);Molecular Catalysis;2024-08

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