Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy

Abstract The fracture toughness (KIC) of high-entropy oxides (HEOs) is critically important for several applications, but identification and quantification of the toughening mechanisms resulting from lattice-engineering/distortion in HEOs is challenging. Here, based on the classic Griffith criteria,...

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Main Authors: Ying Zhang, Ke Ren, William Yi Wang, Xingyu Gao, Jun Wang, Yiguang Wang, Haifeng Song, Xiubing Liang, Jinshan Li
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-024-01462-9
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author Ying Zhang
Ke Ren
William Yi Wang
Xingyu Gao
Jun Wang
Yiguang Wang
Haifeng Song
Xiubing Liang
Jinshan Li
author_facet Ying Zhang
Ke Ren
William Yi Wang
Xingyu Gao
Jun Wang
Yiguang Wang
Haifeng Song
Xiubing Liang
Jinshan Li
author_sort Ying Zhang
collection DOAJ
description Abstract The fracture toughness (KIC) of high-entropy oxides (HEOs) is critically important for several applications, but identification and quantification of the toughening mechanisms resulting from lattice-engineering/distortion in HEOs is challenging. Here, based on the classic Griffith criteria, a physics-driven theoretical equation combined with a knowledge-enabled data-driven machine-learning algorithm is proposed to predict the KIC and elucidate the toughening mechanisms of A2Zr2O7-type HEOs. Together with experimental verification, our proposed model is applied to a dataset comprising 41208 (nRE1/n)2Zr2O7 (n = 2~7) HEOs, considering the contributions of the intrinsic brittleness and increased toughness due to the local lattice distortion (LLD), thereby addressing the challenge of accurate estimating KIC in complex HEOs using the rule of mixtures. During crack tip propagation, the interaction mechanism of cations induces stress fields and charge variations of LLD and dissipates crack energy, thus, to yield the crack tip softening and the elastic shielding and to enhance the toughness of HEOs.
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institution Kabale University
issn 2057-3960
language English
publishDate 2024-12-01
publisher Nature Portfolio
record_format Article
series npj Computational Materials
spelling doaj-art-c6847750267c4dc79160465eb16ec17e2024-12-08T12:37:38ZengNature Portfolionpj Computational Materials2057-39602024-12-0110111010.1038/s41524-024-01462-9Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategyYing Zhang0Ke Ren1William Yi Wang2Xingyu Gao3Jun Wang4Yiguang Wang5Haifeng Song6Xiubing Liang7Jinshan Li8State Key Laboratory of Solidification Processing, Northwestern Polytechnical UniversityInstitute of Advanced Structure Technology, Beijing Institute of TechnologyState Key Laboratory of Solidification Processing, Northwestern Polytechnical UniversityLaboratory of Computational Physics, Institute of Applied Physics and Computational MathematicsState Key Laboratory of Solidification Processing, Northwestern Polytechnical UniversityInstitute of Advanced Structure Technology, Beijing Institute of TechnologyLaboratory of Computational Physics, Institute of Applied Physics and Computational MathematicsState Key Laboratory of Solidification Processing, Northwestern Polytechnical UniversityState Key Laboratory of Solidification Processing, Northwestern Polytechnical UniversityAbstract The fracture toughness (KIC) of high-entropy oxides (HEOs) is critically important for several applications, but identification and quantification of the toughening mechanisms resulting from lattice-engineering/distortion in HEOs is challenging. Here, based on the classic Griffith criteria, a physics-driven theoretical equation combined with a knowledge-enabled data-driven machine-learning algorithm is proposed to predict the KIC and elucidate the toughening mechanisms of A2Zr2O7-type HEOs. Together with experimental verification, our proposed model is applied to a dataset comprising 41208 (nRE1/n)2Zr2O7 (n = 2~7) HEOs, considering the contributions of the intrinsic brittleness and increased toughness due to the local lattice distortion (LLD), thereby addressing the challenge of accurate estimating KIC in complex HEOs using the rule of mixtures. During crack tip propagation, the interaction mechanism of cations induces stress fields and charge variations of LLD and dissipates crack energy, thus, to yield the crack tip softening and the elastic shielding and to enhance the toughness of HEOs.https://doi.org/10.1038/s41524-024-01462-9
spellingShingle Ying Zhang
Ke Ren
William Yi Wang
Xingyu Gao
Jun Wang
Yiguang Wang
Haifeng Song
Xiubing Liang
Jinshan Li
Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
npj Computational Materials
title Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
title_full Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
title_fullStr Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
title_full_unstemmed Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
title_short Smart design A2Zr2O7-type high-entropy oxides through lattice-engineering toughening strategy
title_sort smart design a2zr2o7 type high entropy oxides through lattice engineering toughening strategy
url https://doi.org/10.1038/s41524-024-01462-9
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