Phenomenological approaches for quantitative temperature-programmed reduction (TPR) and desorption (TPD) analysis

Temperature-programmed reduction (TPR) and temperature-programmed desorption (TPD) are techniques widely used for catalyst characterization, providing information about active sites. However, results from these experiments are usually interpreted with the aid of empirical models, based on the representation of reduction or desorption profiles as summations of empirical reference curves. In this context, phenomenological approaches can present several advantages over this traditional empirical approach, as in this case the extracted information can be based on theoretical models that allows for a deeper understanding of the catalyst properties. For this reason, in the present work, empirical and phenomenological modelling approaches are evaluated for the quantitative analysis of H-2-TPR and NH3-TPD profiles, obtained from the characterization of Ni/SiO2 and Al2O3 alumina catalysts, respectively, and results from both approaches are thoroughly compared and discussed for the first time. Our results, obtained from the fitting of both modelling approaches to the whole experimental profile by using nonlinear regression, indicate that the phenomenological modelling approach can be considered better and should therefore be preferred, as it allows for significantly more accurate quantification and correct discrimination of distinct active sites, in addition to simultaneously enabling the determination of reduction or desorption kinetics parameters. (C) 2020 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved.

Automated summary

Temperature-programmed reduction (TPR) and temperature-programmed desorption (TPD) are commonly used techniques for catalyst characterization, with empirical and phenomenological modeling approaches being compared in this study for the first time. The results suggest that phenomenological modeling approach allows for more accurate quantification and discrimination of distinct active sites in catalysts.