Study of syngas conversion to light olefins by statistical models

This paper presents the application of the statistical models in CO hydrogenation to light olefins studies. The effect of support content as a structural variable of a precipitated Fe–Co–Mn catalyst in conjunction with two reactor variables, temperature and total pressure was investigated via an Orthogonal Second-order Design. A quadratic polynomial was successfully fitted to the experimental data and the significance of regression coefficients was statistically investigated by t-student test. The results were also compared with simulated artificial neural network results that was constructed and trained based on data collected according to the experimental designs. The response surface model (RSM) simulated data were also employed to kinetic study of CO hydrogenation under condition of support 20%, temperature 340–380 °C, pressure 3–7 bar and a rate equation based on direct reaction of hydrogen from gas phase with molecularly adsorbed CO were proposed. The estimated activation energy under above conditions was 40 kJ/mol.