(532bw) Optimization and Screening of Iron Supported on Clinoptilolite As a Low-Temperature Fischer- Tropsch Synthesis Catalyst

Modelling renewable fuel production systems allows organizations to investigate the most effective aspects while operating under optimal conditions. As a result, an innovative data simulation technique based on Response Surface Methodology (RSM) is proposed to thoroughly investigate the effects of operating conditions as part of the Design of Experiments (DOE). DOE is a statistical strategy for improving a process plan such that the comprehensive understanding of the mechanism can be optimised with the minimum series of experiments possible. It can focus on the impact of different components simultaneously, as well as the dynamic interaction between them, in a methodical manner. The objectives of this paper were to examine the components that influence the production of olefins and paraffin wax utilising syngas in the Fischer-Tropsch (FT) process and then optimise the key components using factorial design and response surface methods. The parameters evaluated were hydrogen to carbon monoxide (H₂:CO) ratio, reaction temperature, reaction pressure and gas speed GHSV. Employing multivariate DOE, the influence of these components and their probable synergistic effect were investigated simultaneously, with the yield of various hydrocarbon compositions, carbon dioxide conversion and water gas shift (WGS) selectivity as the measured responses. Single and multicentre parameter optimisation was performed, and it was found that the maximum heavy hydrocarbon selectivity (C₅₊-C_∞) and the least amount of methane selectivity (CH₄) can be obtained under the following conditions: H2:CO = 1.9, T=241°C P=17,9 bar and GHSV=1241h^-1.