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Kinetic Modeling of the Thermal Decomposition of Zinc Sulfate Through a Global Optimization Method

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Abstract

The thermal decomposition of zinc sulfate is a highly relevant process, as the final product (zinc oxide) has a great number of applications. Moreover, the process itself can be used for hydrogen production in thermochemical water-splitting cycles. The present manuscript proposes a different approach over the modeling of the decomposition reaction, using particle swarm optimization (PSO) to estimate the kinetic parameters (pre-exponential factor, activation energy, and reaction order). Thermodynamic simulations have been performed to evaluate the influence of the partial pressure of \({\text{SO}}_{3}\) and the temperature in the equilibrium of the system was made. The thermogravimetric runs were performed in a non-isotherm condition using inert atmosphere. The results indicate that the decomposition takes place in two different stages: zinc sulfate decomposes into \({\text{ZnO}}\cdot 2{\text{ZnSO}}_{4}\), which is further decomposed into zinc oxide. The reactions involved can occur simultaneously, as enough \({\text{ZnO}} \cdot 2 {\text{ZnSO}}_{4}\) is formed by the decomposition of \({\text{ZnSO}}_{4}\). The model showed an excellent agreement with the experimental data, with pre-exponential factor equal to 2.52\(\times 10^{12}\) and 1.25\(\times 10^{16}\) min\(^{-1}\), activation energy of 272 and 367 kJ mol\(^{-1}\), and reaction order of 2.0 and 1.0, for the thermal decomposition of \({\text{ZnSO}}_{4}\) and \({\text{ZnO}}\cdot 2{\text{ZnSO}}_{4}\), respectively. The activation energy values found in the present work are in the same range as the ones found in previous literature studies.

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Acknowledgments

This study was financed in part by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES) - Finance Code 001.

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Correspondence to Rogério C. S. Navarro.

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Rego, A.S.C., Navarro, R.C.S., Brocchi, E.A. et al. Kinetic Modeling of the Thermal Decomposition of Zinc Sulfate Through a Global Optimization Method. Metall Mater Trans B 53, 4105–4113 (2022). https://doi.org/10.1007/s11663-022-02670-8

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