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Importance of proper baseline identification for the subsequent kinetic analysis of derivative kinetic data Part 1
Year: 2016
Type of publication: článek v odborném periodiku
Name of source: Journal of Thermal Analysis and Calorimetry
Publisher name: Springer
Place: Heidelberg
Page from-to: 1717-1725
Titles:
Language Name Abstract Keywords
cze Důležitost správné identifikace nulové linie pro následnou kinetickou analýzu diferenciálních kinetických dat Část 1 Za použití teoreticky simulovaných kinetických dat byl testován vliv výběru různého typu nulové linie v případě materiálů, u nichž tepelná kapacita reaktantů a produktů se liší. Ovlivnění hodnoty aktivační energie i samotného sledovaného kinetického mechanismu bylo ukázáno. nulová linie; zkreslení dat; kinetická analýza
eng Importance of proper baseline identification for the subsequent kinetic analysis of derivative kinetic data Part 1 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 similar to 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. Baseline; Data distortion; Kinetic analysis

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