Optimization of hydrogen-rich syngas production from valorization of methane and carbon dioxide over Gallium promoted Ni/zirconia catalyst using response surface quadratic modeling

• Response surface quadratic modelling and optimization of hydrogen-rich syngas production was investigated. • Based on analysis of variance, the individual factors have significant effects on the hydrogen-rich syngas produced. • Response surface quadratic model was significant is simulating the effect of the factors on the hydrogen-syngas. • At desirability function of 0.995, optimum conditions of 15,000h -1 , 800 °C, and 1.4 were obtained. One of the major constraints of using Ni as a catalyst in methane dry reforming is its susceptibility to deactivation by carbon deposition and sintering which often reduce its activity. To overcome this constraint, this study employed response surface optimization strategy to investigate the optimum experimental condition that could maximize the performance of Gallium (Ga) promoted Ni/ZrO 2 used for the valorization of methane (CH 4 ) and carbon dioxide (CO 2 ) to hydrogen-rich syngas. The Ga promoted Ni/ZrO 2 catalyst was prepared by sequential wet impregnation method and characterized using thermogravimetric analysis (TGA), X-ray diffraction analysis (XRD), N 2 physisorption analysis, Field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDS). The characterization of the catalysts revealed a promising physicochemical property suitable for the reforming reaction as reflected by the average pore diameter of 36.28 nm. The analysis of variance (ANOVA) of the combination of the different factors and their corresponding responses revealed that GHSV, reaction temperature, and CO 2 /CH 4 ratio significantly influenced the CH 4 conversion, CO 2 conversion, H 2 yield, and CO yield. At desirability function of 0.995, the optimum conditions of 15,000 h -1 , 800 °C, and 1.4 were obtained for GHSV, temperature, and CO 2/ CH 4 ratio, respectively. Based on the optimum conditions, CH 4 conversion, CO 2 conversion, H 2 yield and CO yield of 89.79 %, 93.85 %, 88.13 % and 89.52 % were obtained, respectively. This study has demonstrated the robustness of the RSM and CCD in determining the effect of selected process parameters and suggesting the appropriate optimum conditions that maximize the reactants conversion and the product yield.