Optimization of greenhouse gas valorization over ceria‐promoted Co–Ni/graphene oxide catalytic materials using response surface methodology

Author:

Mageed Alyaa K.1ORCID,Alsaffar May Ali1ORCID,Abdel Ghany Mohamed Abdel Rahman1ORCID,Sukkar Khalid A.1ORCID,Ayodele Bamidele Victor23ORCID

Affiliation:

1. Department of Chemical Engineering University of Technology‐Iraq Baghdad Iraq

2. Department of Chemical Engineering Universiti Teknologi PETRONAS Bandar Seri Iskandar Malaysia

3. Centre of Carbon Capture, Utilization and Storage (CCCUS) Institute of Sustainable Energy and Resources, Universiti Teknologi PETRONAS Bandar Seri Iskandar Malaysia

Abstract

AbstractBackgroundThe mitigation of global warming effect requires intensified research efforts to reduce greenhouse gas emissions. This study was aimed at investigating the valorization of two principal greenhouse gases, namely carbon dioxide (CO2) and methane (CH4), over CeO2‐doped Co–Ni/GO catalytic materials. The CeO2‐doped Co–Ni/GO catalysts were synthesized using a sequential wet impregnation method and employed for CO2 reforming of CH4. The catalytic materials were characterized using various instrumental techniques. Response surface methodology (RSM) was employed to investigate the impact of process factors, namely reaction temperature (ranging from 700 to 800 °C), CeO2 loading (ranging from 5% to 15%) and feed flowrate (ranging from 10n to 50 mL min−1), on the CH4 conversions.ResultsThe three factors were observed to have significant influence on the CH4 conversion based on analysis of variance. The analysis of the RSM quadratic model revealed that the optimum conditions of 800 °C, 14.22% and 10.00 mL min−1 were obtained for the reaction temperature, CeO2 loading and feed flowrate resulting in maximum CH4 conversion of 98.24%. The desirability function for these results was calculated to be 0.934. The predicted process parameters aligned with the results of the actual experimental analysis.ConclusionThis study has demonstrated that the conversion of CH4 to value‐added products such as syngas can be optimized using RSM. The optimum conditions obtained could be used to improve the process performance. © 2024 Society of Chemical Industry (SCI).

Publisher

Wiley

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