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Article

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Title

Kinetic Modelling of Powder-Pack Boronized 4Cr5MoSiV1 Steel by Two Distinct Approaches

Authors

[ 1 ] Instytut Inżynierii Materiałowej, Wydział Inżynierii Materiałowej i Fizyki Technicznej, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.8] Materials engineering

Year of publication

2023

Published in

Coatings

Journal year: 2023 | Journal volume: vol. 13 | Journal number: iss. 6

Article type

scientific article

Publication language

english

Keywords
EN
  • boronizing
  • iron borides
  • diffusion
  • bilayer model
  • dimensional analysis
  • activation energy
Abstract

EN This work attempts to model the powder-pack boronizing kinetics of 4Cr5MoSiV1 steel in the interval of 1133 and 1253 K in order to predict the layers’ thicknesses. The first approach is referred to as the bilayer model and relies on the conservation principle of mass balance equations at the two phase fronts accounting for the linearity of boron distribution across each boride phase. The second approach deals with the application of dimensional analysis to simulate the boronizing kinetics of 4Cr5MoSiV1 steel. Using the bilayer model and the classical parabolic law, the boron activation energies in FeB and Fe2B were evaluated and discussed in light of the literature data. The estimated boron activation energies from the bilayer model were respectively equal to 164.92 and 153.39 kJ mol−1. These values were very comparable to those calculated from the classical parabolic law. Finally, it was proven that the dimensional analysis was able to simulate the layers’ thicknesses for the selected processing parameters.

Date of online publication

20.06.2023

Pages (from - to)

1132-1 - 1132-14

DOI

10.3390/coatings13061132

URL

https://www.mdpi.com/2079-6412/13/6/1132

Comments

Article number: 1132

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Date of Open Access to the publication

at the time of publication

Ministry points / journal

100

Impact Factor

2,9

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