Modeling of Catalytic CO 2 Methanation Using Smart Computational Schemes

An analyzing tool as a sustainable method to combine CO 2 capture and production of CH 4 by utilizing CO 2 as a feedstock is proposed. The impact of incorporating metallic promoters such as Fe, La, Ce, and Co to an Al 2 O 3 ‐supported catalyst containing Ni as the first metal in the CO 2 methanation was modeled. Smart models were employed to analyze the CO 2 conversion and CH 4 selectivity in CH 4 production from CO 2 . The genetic programming (GP) model provides a mathematical framework for the estimation of CO 2 conversion and CH 4 selectivity. The model inputs are catalyst surface area, temperature, H 2 /CO 2 ratio, gas‐hourly space velocity, and catalyst pore volume and diameter. The results confirm that the GP model estimates the CO 2 conversion and CH 4 selectivity very well.