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2 Polish Journal of Chemical Technology

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Correlation of kinetic parameters of sodium acetate thermal decomposition

Olszak-Humienik M., Możejko J.

Polish Journal of Chemical Technology

2006

Vol. 8, nr 2

22-25

Thermogravimetry and differential thermal analysis were used in the study of the kinetics of non-isothermal sodium acetate's thermal decomposition under an air atmosphere. The diagrams were recorded on a sample mass of 20 mg at temperatures ranging from 20 to 600°C. Five different heating rates were used. The relations of α vs. T were estimated from the mass losses. The values of the kinetic parameters (activation energy and the pre-exponential factor) of the thermal decomposition were calculated from α(T) data in several ways: by using the integral method, applying the Coats-Redfern approximation, the modified isoconversional Coats-Redfern method, the differential method of Friedman and the Kissinger's method. A correlation was found between kinetic parameters estimated by different kinetic methods.

Analysis of the decomposition process of CuSO4 · 5H2O under non-isothermal conditions

Straszko J., Strzelczak A., Chrościechowska J.

Polish Journal of Chemical Technology

2005

Vol. 7, nr 2

54-61

The results of the investigation on thermal decomposition of CuSO4 · 5H2O under the non-isothermal conditions are presented. The measurements were carried out at the following heating rates: 2, 4, 6, 8 and 10 [K/min]. The mass of the used samples was about 30mg. The process occurred in five steps. Three of them were associated with dehydration and the two of them with the decomposition of the anhydrous salt. The dependencies of the conversion degree on temperature were determined for every stage of the process. They were the basis of the presented quantitative description . The Coats and Redfern equation was applied. The g(alpha) function (kinetic model) of the best accuracy for the individual step and the kinetic parameters of the Arrhenius equation were determined. The identification of the kinetic models was carried out by means of the artificial neural networks. A and E coefficients were evaluated using statistical methods. The described conversions were assumed as stochastic processes.