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A first step towards computational design of W-containing self-healing ferritic creep resistant steels

In this work, we combine a generic alloy-by-design model with a novel concept, the nucleation barrier for the formation of Laves phase to fill the creep cavities, in order to develop multi-component creep resistant steels with kinetically tuned self-healing behaviour. In the model the high-temperatu...

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Autores principales: Yu, Hao, Xu, Wei, van der Zwaag, Sybrand
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534302/
https://www.ncbi.nlm.nih.gov/pubmed/33061837
http://dx.doi.org/10.1080/14686996.2020.1814679
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author Yu, Hao
Xu, Wei
van der Zwaag, Sybrand
author_facet Yu, Hao
Xu, Wei
van der Zwaag, Sybrand
author_sort Yu, Hao
collection PubMed
description In this work, we combine a generic alloy-by-design model with a novel concept, the nucleation barrier for the formation of Laves phase to fill the creep cavities, in order to develop multi-component creep resistant steels with kinetically tuned self-healing behaviour. In the model the high-temperature long-term strength is estimated by integrating precipitation strengthening due to M23C6 carbides and solid solution strengthening, while the optimized compositional solutions are determined by employing the coupled thermodynamic and kinetic principles. W-containing Laves phase herein is selected as the self-healing agent to autonomously fill the grain boundary cavities, so as to prolong the creep lifetime. To achieve the effective healing reaction, the nucleation time for Laves precipitates are expected to coincide simultaneously with which creep cavities start to form or reach a healable size. Using experimental data from literature, an empirical relationship to estimate the incubation time for Laves phase formation has been constructed, from which the thermodynamic driving force for onset of precipitation as a function of temperature and intended precipitate nucleation time was derived. Three sample alloys have been selected among the desirable solutions, which are predicted to have the same strength but widely different Laves phase nucleation times. The calculations are also performed for different use temperatures to explore the compatibility between high temperature strength and timely cavity filling behaviour. In its current form the model is not expected to yield the truly optimal composition but to demonstrate how the kinetics of the healing reaction can affect the predicted optimal alloy compositions.
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spelling pubmed-75343022020-10-14 A first step towards computational design of W-containing self-healing ferritic creep resistant steels Yu, Hao Xu, Wei van der Zwaag, Sybrand Sci Technol Adv Mater Focus on Self-Healing Materials In this work, we combine a generic alloy-by-design model with a novel concept, the nucleation barrier for the formation of Laves phase to fill the creep cavities, in order to develop multi-component creep resistant steels with kinetically tuned self-healing behaviour. In the model the high-temperature long-term strength is estimated by integrating precipitation strengthening due to M23C6 carbides and solid solution strengthening, while the optimized compositional solutions are determined by employing the coupled thermodynamic and kinetic principles. W-containing Laves phase herein is selected as the self-healing agent to autonomously fill the grain boundary cavities, so as to prolong the creep lifetime. To achieve the effective healing reaction, the nucleation time for Laves precipitates are expected to coincide simultaneously with which creep cavities start to form or reach a healable size. Using experimental data from literature, an empirical relationship to estimate the incubation time for Laves phase formation has been constructed, from which the thermodynamic driving force for onset of precipitation as a function of temperature and intended precipitate nucleation time was derived. Three sample alloys have been selected among the desirable solutions, which are predicted to have the same strength but widely different Laves phase nucleation times. The calculations are also performed for different use temperatures to explore the compatibility between high temperature strength and timely cavity filling behaviour. In its current form the model is not expected to yield the truly optimal composition but to demonstrate how the kinetics of the healing reaction can affect the predicted optimal alloy compositions. Taylor & Francis 2020-09-14 /pmc/articles/PMC7534302/ /pubmed/33061837 http://dx.doi.org/10.1080/14686996.2020.1814679 Text en © 2020 The Author(s). Published by National Institute for Materials Science in partnership with Taylor & Francis Group. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Focus on Self-Healing Materials
Yu, Hao
Xu, Wei
van der Zwaag, Sybrand
A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title_full A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title_fullStr A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title_full_unstemmed A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title_short A first step towards computational design of W-containing self-healing ferritic creep resistant steels
title_sort first step towards computational design of w-containing self-healing ferritic creep resistant steels
topic Focus on Self-Healing Materials
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7534302/
https://www.ncbi.nlm.nih.gov/pubmed/33061837
http://dx.doi.org/10.1080/14686996.2020.1814679
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