Abstract

Kinetic modeling provides chemical engineers with a unique opportunity to better understand reaction kinetics in general and the underlying chemistry in particular. How to systematically approach a modeling assignment in chemical reaction kinetics is typically less clear, especially for novices in the field. The proposed modeling methodology pursues an adequate compromise between statistical significance and physical meaning of the kinetic model and the corresponding parameters and typically results in models of an appropriate complexity. It comprises the following activities: (1) data analysis, aiming at qualitative information on the reaction mechanism and corresponding rate equations, (2) model regression to quantify this information via optimal parameter values, and (3) validation of the statistical significance and physical meaning of the parameter estimates. This methodology is successfully applied to n‐hexane hydroisomerization on a bifunctional catalyst. © 2014 American Institute of Chemical Engineers AIChE J, 61: 880–892, 2015

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