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Simulation study for generalized logistic function in thermal data modeling

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Abstract

The principal aim of the present study is to describe, analyze, and compare from a statistical standpoint the generalized logistic model with some well-known models used in the solid-state kinetics: power law, Avrami–Erofeev, and reaction order. For this purpose, synthetic conversion curves that simulate the kinetic processes were generated using the power law, Avrami–Erofeev, and reaction order models, where the Arrhenius equation was assumed in all the cases. This comprehensive simulation study allows to describe the relationship between the parameters belonging to the proposed generalized logistic model and the pointed traditional models’ parameters, and also to validate the performance of the generalized logistic model in a wide variety of cases where other methods can be applied. Performing this analysis has been necessary to employ some new statistical techniques in thermal analysis modeling as the generalized additive models, and to perform global optimization evolutionary algorithms as the differential evolution for solving the non-linear regression problem. In order to implement these techniques, R statistical software routines were developed and applied.

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Acknowledgements

This research has been partially supported by the Spanish Ministry of Science and Innovation. Grant MTM2011-22392 (ERDF included).

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Authors and Affiliations

  1. Escola Politécnica Superior, Universidade da Coruña, Ferrol, Spain

    Javier Tarrío-Saavedra, Jorge López-Beceiro, Salvador Naya & Ramón Artiaga

  2. Facultade de Informática, Universidade da Coruña, A Coruña, Spain

    Mario Francisco-Fernández

Authors
  1. Javier Tarrío-Saavedra
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  2. Jorge López-Beceiro
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  3. Salvador Naya
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  4. Mario Francisco-Fernández
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  5. Ramón Artiaga
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Correspondence to Javier Tarrío-Saavedra.

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Tarrío-Saavedra, J., López-Beceiro, J., Naya, S. et al. Simulation study for generalized logistic function in thermal data modeling. J Therm Anal Calorim 118, 1253–1268 (2014). https://doi.org/10.1007/s10973-014-3887-z

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  • DOI: https://doi.org/10.1007/s10973-014-3887-z

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