Kinetic modelling of thermal processes using a modified Sestak-Berggren equation

•Simultaneous fitting of multiple thermal events without prior peak discretization.•Akaike weights used to determine statistically relevant number of thermal events.•In silico and experimental validation of modified Sestak-Berggren methodology. This study outlines the principles of modelling the kinetics of solid-state reactions through the simultaneous fitting of multiple peak curves using the modified Sestak-Berggren equation. This mathematical model gives an indication of the mechanism occurring and allows kinetic parameters, such as activation energy, to be estimated. This methodology is demonstrated using in silico thermo-conductivity detector (TCD) data showing the internal consistency of the Sestak-Berggren modelling approach, its applicability to noisy data and its ability to predict mechanisms occurring during a thermally induced solid state reaction. Using these in silico data it has been confirmed that this empirical model can separate overlapped peaks without a priori peak deconvolution. A rigorous statistical methodology based on the Akaike Information Criteria, is recommended to identify the optimum number of thermal events that should be applied to a system. This modified Sestak-Berggren model is then applied to an experimental dataset of temperature programmed reduction of a calcined cobalt on alumina catalyst precursor. This allows for the identification of a statistically adequate kinetic triplet for each thermal event. Recommendations on the treatment of datasets which contain “shoulders” and closely overlapped peaks are also given.