Comportamiento de crecimiento de recubrimientos de Fe₂B modelado mediante el método inverso de Stefan

Juan D. Bautista Hernández; Arturo Cruz Avilés; Jorge Zuno Silva; Martín Ortiz Domínguez

doi:10.29057/escs.v13i26.17353

Autores/as

Juan D. Bautista Hernández Universidad Autónoma del Estado de Hidalgo | Escuela Superior de Ciudad Sahagún | Ciudad Sahagún-Hidalgo | México https://orcid.org/0009-0006-4668-3195
Arturo Cruz Avilés Universidad Autónoma del Estado de Hidalgo | Escuela Superior de Ciudad Sahagún | Ciudad Sahagún-Hidalgo | México https://orcid.org/0000-0003-0455-1646
Jorge Zuno Silva Universidad Autónoma del Estado de Hidalgo | Escuela Superior de Ciudad Sahagún | Ciudad Sahagún-Hidalgo | México https://orcid.org/0000-0002-1997-5399
Martín Ortiz Domínguez Universidad Autónoma del Estado de Hidalgo | Escuela Superior de Ciudad Sahagún | Ciudad Sahagún-Hidalgo | México https://orcid.org/0000-0003-4475-9804

DOI:

https://doi.org/10.29057/escs.v13i26.17353

Palabras clave:

Boruración, boruros, cinética, energía de activación, desgaste, análisis ANOVA

Resumen

En este estudio se desarrolló un nuevo modelo matemático basado en la el modelo inverso de Stefan, con el propósito de estimar el crecimiento de los recubrimientos de fase Fe₂B formados sobre la superficie del acero ASTM A29. La caracterización morfológica y el análisis del espesor promedio de los recubrimientos se realizaron mediante Microscopía Electrónica de Barrido (SEM) y Microscopía Óptica (OM). Las propiedades tribológicas del acero base y del material borurado se evaluaron a través de ensayos de desgaste tipo pin-on-disc. Los resultados revelaron una reducción significativa en el coeficiente de fricción, que disminuyó de 0.725 en el material sin tratar a 0.35 en el material tratado, lo que representa una mejora aproximada del 99.97% en la resistencia al desgaste. Finalmente, se llevó a cabo un Análisis de Varianza (ANOVA) para determinar la influencia de los parámetros de proceso sobre el espesor de la capa (u). Los resultados evidenciaron que tanto la temperatura (T) como el tiempo de tratamiento (t) ejercen una influencia significativa, con contribuciones relativas del 64.68% y 27.37%, respectivamente, mientras que la interacción entre ambos factores (T × t) aportó un 5.13 %.

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