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A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates

Rare-earth monosilicates are used as environmental barrier coatings (EBCs) due to their excellent water vapor corrosion resistance. However, existing experimental studies on the water vapor corrosion behavior of rare-earth monosilicates are discrepant and even contradictory. Previous theoretical inv...

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Detalles Bibliográficos
Autores principales: Wang, Qianqian, Huang, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999253/
https://www.ncbi.nlm.nih.gov/pubmed/35407746
http://dx.doi.org/10.3390/ma15072414
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author Wang, Qianqian
Huang, Jian
author_facet Wang, Qianqian
Huang, Jian
author_sort Wang, Qianqian
collection PubMed
description Rare-earth monosilicates are used as environmental barrier coatings (EBCs) due to their excellent water vapor corrosion resistance. However, existing experimental studies on the water vapor corrosion behavior of rare-earth monosilicates are discrepant and even contradictory. Previous theoretical investigations on water vapor corrosion resistance mainly focus on a Mulliken analysis of Si-O bonds in the monosilicates. In this study, the structural and electronic properties of rare-earth monosilicates have been studied by density functional theory (DFT) calculations, and a descriptor correlated to the corrosion resistance has been developed. The maximum isosurface value of the valence band maximum (VBM(Fmax)) can be used to predict the water vapor corrosion resistance of RE(2)SiO(5). The results show that RE(2)SiO(5) with a smaller VBM(Fmax) may have better water vapor corrosion resistance.
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spelling pubmed-89992532022-04-12 A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates Wang, Qianqian Huang, Jian Materials (Basel) Communication Rare-earth monosilicates are used as environmental barrier coatings (EBCs) due to their excellent water vapor corrosion resistance. However, existing experimental studies on the water vapor corrosion behavior of rare-earth monosilicates are discrepant and even contradictory. Previous theoretical investigations on water vapor corrosion resistance mainly focus on a Mulliken analysis of Si-O bonds in the monosilicates. In this study, the structural and electronic properties of rare-earth monosilicates have been studied by density functional theory (DFT) calculations, and a descriptor correlated to the corrosion resistance has been developed. The maximum isosurface value of the valence band maximum (VBM(Fmax)) can be used to predict the water vapor corrosion resistance of RE(2)SiO(5). The results show that RE(2)SiO(5) with a smaller VBM(Fmax) may have better water vapor corrosion resistance. MDPI 2022-03-25 /pmc/articles/PMC8999253/ /pubmed/35407746 http://dx.doi.org/10.3390/ma15072414 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 Communication
Wang, Qianqian
Huang, Jian
A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title_full A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title_fullStr A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title_full_unstemmed A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title_short A DFT-Based Descriptor to Predict the Water Vapor Corrosion Resistance of Rare-Earth Monosilicates
title_sort dft-based descriptor to predict the water vapor corrosion resistance of rare-earth monosilicates
topic Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8999253/
https://www.ncbi.nlm.nih.gov/pubmed/35407746
http://dx.doi.org/10.3390/ma15072414
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