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Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel

A non-isothermal transformation model was proposed to determine the austenite formation kinetics in a steel alloyed with 2.6% wt. Si by dilatometric analysis, considering that the nucleation mechanism does not change with the heating rate. From the dilatometric analysis, it was observed that the aus...

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Autores principales: Gallegos-Pérez, Alexis Iván, Vázquez-Gómez, Octavio, Herrejón-Escutia, Martín, Vergara-Hernández, Héctor Javier, Arreola-Villa, Sixtos Antonio, Garnica-González, Pedro, López-Martínez, Edgar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877153/
https://www.ncbi.nlm.nih.gov/pubmed/35207916
http://dx.doi.org/10.3390/ma15041376
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author Gallegos-Pérez, Alexis Iván
Vázquez-Gómez, Octavio
Herrejón-Escutia, Martín
Vergara-Hernández, Héctor Javier
Arreola-Villa, Sixtos Antonio
Garnica-González, Pedro
López-Martínez, Edgar
author_facet Gallegos-Pérez, Alexis Iván
Vázquez-Gómez, Octavio
Herrejón-Escutia, Martín
Vergara-Hernández, Héctor Javier
Arreola-Villa, Sixtos Antonio
Garnica-González, Pedro
López-Martínez, Edgar
author_sort Gallegos-Pérez, Alexis Iván
collection PubMed
description A non-isothermal transformation model was proposed to determine the austenite formation kinetics in a steel alloyed with 2.6% wt. Si by dilatometric analysis, considering that the nucleation mechanism does not change with the heating rate. From the dilatometric analysis, it was observed that the austenite formation occurs in two stages; critical temperatures, degree and austenite formation rate were determined. The activation energies associated with each of the stages were obtained employing the Kissinger method (226.67 and 198.37 kJ·mol(−1) for the first and second stage) which was used in concert with the austenite formation rate in the non-isothermal model as a first approximation, with acceptable results in the second stage, but not in the first due to the activation energies magnitude. Then, the activation energies were adjusted by minimizing the minimal squares error between estimated and experimental austenite formation degree, obtaining values of 158.50 kJ·mol(−1) for the first and 165.50 kJ·mol(−1) for the second stage. These values are consistent with those reported for the diffusion of carbon in austenite-FCC in silicon steels. With these activation energies it was possible to predict the austenite formation degree with a better level of convergence when implementing the non-isothermal model.
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spelling pubmed-88771532022-02-26 Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel Gallegos-Pérez, Alexis Iván Vázquez-Gómez, Octavio Herrejón-Escutia, Martín Vergara-Hernández, Héctor Javier Arreola-Villa, Sixtos Antonio Garnica-González, Pedro López-Martínez, Edgar Materials (Basel) Article A non-isothermal transformation model was proposed to determine the austenite formation kinetics in a steel alloyed with 2.6% wt. Si by dilatometric analysis, considering that the nucleation mechanism does not change with the heating rate. From the dilatometric analysis, it was observed that the austenite formation occurs in two stages; critical temperatures, degree and austenite formation rate were determined. The activation energies associated with each of the stages were obtained employing the Kissinger method (226.67 and 198.37 kJ·mol(−1) for the first and second stage) which was used in concert with the austenite formation rate in the non-isothermal model as a first approximation, with acceptable results in the second stage, but not in the first due to the activation energies magnitude. Then, the activation energies were adjusted by minimizing the minimal squares error between estimated and experimental austenite formation degree, obtaining values of 158.50 kJ·mol(−1) for the first and 165.50 kJ·mol(−1) for the second stage. These values are consistent with those reported for the diffusion of carbon in austenite-FCC in silicon steels. With these activation energies it was possible to predict the austenite formation degree with a better level of convergence when implementing the non-isothermal model. MDPI 2022-02-13 /pmc/articles/PMC8877153/ /pubmed/35207916 http://dx.doi.org/10.3390/ma15041376 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gallegos-Pérez, Alexis Iván
Vázquez-Gómez, Octavio
Herrejón-Escutia, Martín
Vergara-Hernández, Héctor Javier
Arreola-Villa, Sixtos Antonio
Garnica-González, Pedro
López-Martínez, Edgar
Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title_full Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title_fullStr Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title_full_unstemmed Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title_short Application of a Non-Isothermal Numerical-Analytical Model to Determine the Kinetics of Austenite Formation in a Silicon Alloyed Steel
title_sort application of a non-isothermal numerical-analytical model to determine the kinetics of austenite formation in a silicon alloyed steel
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877153/
https://www.ncbi.nlm.nih.gov/pubmed/35207916
http://dx.doi.org/10.3390/ma15041376
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