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Experimentally available kinetic codes as a tool for promising data extraction in thermal analysis

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Abstract

By the study of 3000 kinetic runs for all homogeneous two-step models under variation of activation and signal parameters, it has been stated that the generated Mechanistic Concentration Code (=MCC) is the best vehicle for data extraction in Thermal Analysis. It summarises the rate-controlling steps and their molecularities, independently of their activation data and (to 80–90%) of their method-specific signal parameters. Hence, an optimum evaluation needs the internal (best-fitted) reference step, the initial concentration of a reference reactant, and equal weight of theoretical and experimental results, reached using the same algorithms. Thus, the MCC of any series measured in general allows for a reliable model determination via the distribution into all two-step models, using the tools of probability and decision theory. A transfer of the strategy to heterogeneous reactions is discussed.

Zusammenfassung

Durch die Untersuchung von über 3000 kinetischen Abläufen für alle homogenkinetischen Zweistufen-Modelle wurde festgestellt, da\ der Mechanistische Konzentrations-Code (= MCC) ein optimaler Datenträger in der Thermischen Analyse ist: Er beschreibt die geschwindigkeitsbestimmenden Schritte und ihre Molekularität, unab- hängig von deren Aktivierungsdaten und, zu 80–90%, von ihren methodenspezifischen Signalparametern. Ein optimales Auswerteverfahren benötigt einen internen (optimal angepa\ten) Referenzschritt, die Startkonzentration eines Referenz-Reaktanten und Gleichberechtigung theoretischer und experimenteller Befunde, erreicht, durch Verwendung derselben Algorithmen. Allgemein ermöglicht der MCC aus einer Reihe von Experimenten dann eine Modellbestimmung über eine Verteilung, die durch entscheidungstheoretische Kriterien die Wahrscheinlichkeiten aller Zweistufenmodelle auflistet.

Eine übertragung des Verfahrens auf heterogene Prozesse wird diskutiert.

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Koch, E. Experimentally available kinetic codes as a tool for promising data extraction in thermal analysis. Journal of Thermal Analysis 38, 289–294 (1992). https://doi.org/10.1007/BF01915493

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