Model-Fitting Methods for Evaluation of the Kinetics Triplet during Thermal Decomposition of Poly(ethylene terephthalate) (PET) Soft Drink Bottles

Different chemical reaction models (first-order, second-order, and nth-order) and six different model-fitting techniques (nth-order, Friedman, Freeman−Carroll, Chang, ASTM E689, and the standard deviation minimization technique (SDMT)) are used to evaluate the kinetics triplet (E, ln k 0, and n) for...

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Bibliographic Details
Published inIndustrial & engineering chemistry research Vol. 45; no. 23; pp. 7752 - 7759
Main Authors Saha, Biswanath, Ghoshal, Aloke K
Format Journal Article
LanguageEnglish
Published Washington, DC American Chemical Society 08.11.2006
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Summary:Different chemical reaction models (first-order, second-order, and nth-order) and six different model-fitting techniques (nth-order, Friedman, Freeman−Carroll, Chang, ASTM E689, and the standard deviation minimization technique (SDMT)) are used to evaluate the kinetics triplet (E, ln k 0, and n) for the thermal decomposition of waste soft drink poly(ethylene terephthalate) (PET) bottles (M/s Coca Cola). Nonisothermal experiments at four different heating rates (5, 10, 15, and 25 K/min) and isothermal experiments at four different temperatures (685, 693, 703, and 711 K) are conducted using thermogravimetric analysis (TGA). The experimental results are predicted through simulation of the kinetics models of decomposition. The model input parameters (i.e., the optimum kinetics triplet) are used as obtained from the different model-fitting techniques. Results show that the SDMT methodology with Agarwal and Sivasubramaniam approximation for the temperature integral is possibly the best and most versatile method to calculate the optimum kinetics triplet, because it, in contrast to other model-fitting methods, addresses multiple heating rates. The optimum kinetics triplet thus obtained for the thermal decomposition of the waste PET sample is E = 269.35 kJ/mol, ln k 0 = 44.94, and n = 1.
Bibliography:istex:99F9FE7F9DDA9242AE8AB494C84BEB983DC288D7
ark:/67375/TPS-FSBR5WRS-V
ISSN:0888-5885
1520-5045
DOI:10.1021/ie060282x