(684c) 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 as part of the design of experiments (DOE) to thoroughly investigate the effect of the various operating conditions. DOE is a statistical strategy that is used to improve a process plan, so that the comprehensive understanding of the mechanism that is gained can be used to optimise the process with the fewest possible series of experiments. It can be used to focus on the impact of different components simultaneously, as well as on the dynamic interaction between them, in a methodical manner. The aims of this paper were to explore the components that influence the production of olefins and paraffin wax in the Fischer-Tropsch (FT) process and then optimise the key components using factorial design and RSM. The parameters evaluated were: hydrogen to carbon monoxide (H2:CO) ratio; reaction temperature; reaction pressure; gas speed GHSV. By employing multivariate DOE, the effect and the probable synergistic effect of these components were investigated simultaneously. 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; GHSV= 1241h^-1.