Modelling and optimization of syngas production by methane dry reforming over samarium oxide supported cobalt catalyst: response surface methodology and artificial neural networks approach

• Published in: Clean technologies and environmental policy 2017-05, Vol.19 (4), p.1181-1193
• Main Authors: Ayodele, Bamidele V., Khan, Maksudur R., Nooruddin, Safdar Sk, Cheng, Chin Kui
• Format: Article
• Language: English
• Subjects: Carbon dioxide; Carbon monoxide; Catalysts; Cobalt; Design of experiments; Earth and Environmental Science; Environment; Environmental Economics; Environmental Engineering/Biotechnology; Environmental policy; Greenhouse gases; Industrial and Production Engineering; Industrial Chemistry/Chemical Engineering; Methane; Natural gas; Neural networks; Optimization; Original Paper; Partial pressure; Reforming; Samarium; Sintering; Stainless steel; Sustainable Development; Synthesis gas; Synthetic fuels; X-ray spectroscopy
• ISSN: 1618-954X; 1618-9558
• DOI: 10.1007/s10098-016-1318-5

The reforming of methane by carbon dioxide for the production of syngas is a potential technological route for the mitigation of greenhouse gases. However, the process is highly endothermic and often accompanied by catalyst deactivation from sintering and carbon deposition. Besides, the applications of dissimilar catalytic systems in methane dry reforming have made it difficult to obtain generalized optimum conditions for the desired products. Hence, optimization studies of any catalytic system often resulted in a unique optimum condition. The present study aimed to investigate optimum conditions of variables such as methane (CH 4 ) partial pressure, carbon dioxide (CO 2 ) partial pressure and reaction temperature that will maximize syngas yields from methane dry reforming over samarium oxide supported cobalt (Co/Sm 2 O 3 ) catalyst. The Co/Sm 2 O 3 catalyst was synthesized using wet-impregnation method and characterized by thermogravimetric analysis), field emission scanning electron microscopy, energy-dispersive X-ray spectroscopy, X-ray powder diffraction and nitrogen (N 2 ) physisorption. Syngas production by methane dry reforming over the synthesized Co/Sm 2 O 3 catalyst was investigated in a stainless steel fixed-bed reactor. The process variables (CH 4 partial pressure, CO 2 partial pressure and reaction temperature) for the syngas production were optimized using response surface methodology (RSM). The RSM and artificial neural networks (ANNs) were used to predict the syngas production from the experimental data. The comparative analysis between the two models showed that the ANN model has better prediction of the syngas yields compared to the RSM model as evident from the good agreement between the observed and the predicted values. At maximum desirability value of 0.97, optimum CH 4 and CO 2 partial pressures of 47.9 and 48.9 kPa were obtained at reaction temperature of 735 °C resulting in syngas yield of ~79.4 and 79.0% for hydrogen (H 2 ) and carbon monoxide (CO), respectively.