Finite-temperature interplay of structural stability, chemical complexity, and elastic properties of bcc multicomponent alloys from 
<i>ab initio</i>
 trained machine-learning potentials

Gubaev, Konstantin; Ikeda, Yûji; Tasnádi, Ferenc; Neugebauer, Jörg; Shapeev, Alexander V.; Grabowski, Blazej; Körmann, Fritz

doi:10.1103/physrevmaterials.5.073801

Cited by 15 publications

(11 citation statements)

References 60 publications

(78 reference statements)

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“…There is also some promise in predicting mechanical properties from machine learning . MLIPs for high entropy alloys have been used to screen the temperature and composition dependence of elastic constants identifying alloys displaying invariable elasticity . Given the promise of these materials for applications such as thermoelectrics and ion conductors, enabling high-throughput calculations of electronic, thermal, and ionic transport properties is perhaps the most rewarding route.…”

Section: Discussionmentioning

confidence: 99%

Understanding the Role of Entropy in High Entropy Oxides

et al. 2023

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The field of high entropy oxides (HEOs) flips traditional materials science paradigms on their head by seeking to understand what properties arise in the presence of profound configurational disorder. This disorder, which originates from multiple elements sharing a single lattice site, can take on a kaleidoscopic character due to the vast numbers of possible elemental combinations. High configurational disorder appears to imbue some HEOs with functional properties that far surpass their nondisordered analogs. While experimental discoveries abound, efforts to characterize the true magnitude of the configurational entropy and understand its role in stabilizing new phases and generating superior functional properties have lagged behind. Understanding the role of configurational disorder in existing HEOs is the crucial link to unlocking the rational design of new HEOs with targeted properties. In this Perspective, we attempt to establish a framework for articulating and beginning to address these questions in pursuit of a deeper understanding of the true role of entropy in HEOs.

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Section: Discussionmentioning

confidence: 99%

Understanding the Role of Entropy in High Entropy Oxides

et al. 2023

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“…Based on the configurations obtained from MD simulations, they successfully separated the static, dynamic, thermal expansion, and chemical short-range order (CSRO) contributions to the LLD, as well as their impacts on the elastic properties. Gubaev et al [174] investigated the elastic constants of TiZrHfTa by chemically tuning the concentration of Ta, using MTP-informed MD simulations. They found that structural phase change can profoundly impact elastic properties.…”

Section: Molecular-dynamics Simulationsmentioning

confidence: 99%

Machine learning for high-entropy alloys: Progress, challenges and opportunities

Liu

Zhang

Pei

2023

Progress in Materials Science

116

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“…To quantify the displacive phase transformation at the atomistic level, we introduce a structural descriptor ∆ along similar lines as done previously for materials showing the bcc-ω phase transformation [28][29][30]. The key requirements are as follows:…”

Section: B Structural Descriptor ∆mentioning

confidence: 99%

Dynamic stabilization of perovskites at elevated temperatures: A comparison between cubic BaFeO$_{\textbf{3}}$ and vacancy-ordered monoclinic BaFeO$_{\textbf{2.67}}$

Ou,

Ikeda,

Clemens

et al. 2022

Preprint

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The impact of ordered vacancies on the dynamic stability of perovskites is investigated under the ab initio framework with a focus on cubic BaFeO3 (P m 3m) and vacancy-ordered monoclinic BaFeO2.67 (P 21/m). The harmonic approximation shows that both structures are dynamically unstable at 0 K. For the monoclinic structure, the instability is related to rotational distortions of the Fe coordination tetrahedra near the ordered vacancies. Ab initio molecular dynamics simulations in combination with the introduced structural descriptor demonstrate that both structures are stabilized above 130 K. Our results suggest that the ordered vacancies do not significantly alter the critical temperature at which Ba-Fe-O perovskites are dynamically stabilized. Further, strong anharmonicity for the vacancy-ordered structure above its critical temperature is revealed by a significant asymmetry of the trajectories of O anions near the ordered vacancies.

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Finite-temperature interplay of structural stability, chemical complexity, and elastic properties of bcc multicomponent alloys from ab initio trained machine-learning potentials

Cited by 15 publications

References 60 publications

Understanding the Role of Entropy in High Entropy Oxides

Understanding the Role of Entropy in High Entropy Oxides

Machine learning for high-entropy alloys: Progress, challenges and opportunities

Dynamic stabilization of perovskites at elevated temperatures: A comparison between cubic BaFeO$_{\textbf{3}}$ and vacancy-ordered monoclinic BaFeO$_{\textbf{2.67}}$

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