Importance of proper baseline identification for the subsequent kinetic analysis of derivative kinetic data

Abstract

Listen

Translate article

Using theoretically simulated kinetic datasets, the performance of various types of commonly accessible baselines was tested when the heat capacity of reactants and products is not the same. The quality of the approximation of the true thermokinetic background was compared to the (correct) tangential area-proportional interpolation. Undoubtedly, the most accurate results were provided by the Bezier interpolation, followed by the cubic spline function. In the case of the cubic spline, however, great care needs to be paid to its setting to perform acceptably. The worst results were provided by the simple linear interpolation. Regarding the accuracy of the consequent kinetic analysis, even in the case of large heat capacity changes underlying the kinetic peak, the evaluation of apparent activation energy and pre-exponential factor (model-free analysis) showed only negligible errors for all three tested types of baselines. However, larger heat capacity changes resulted in considerable errors (even ~30 %) in the integral area under the peak. Model-based kinetic analysis provided varied results for different methodologies; while the multivariate curve-fitting exhibited acceptable (small) deviations, the peak-shaped analysis provided considerably worse results, particularly the application of the simple linear interpolation led to large errors.