Discovery of high-entropy ceramics via machine learning

Kaufmann, Kevin; Maryanovsky, Daniel; Mellor, William M.; Zhu, Chaoyi; Rosengarten, Alexander S.; Harrington, Tyler; Oses, Corey; Toher, Cormac; Curtarolo, Stefano; Vecchio, Kenneth S.

doi:10.1038/s41524-020-0317-6

Cited by 188 publications

(104 citation statements)

References 65 publications

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“…We believe that this work can be practically applied to find new multi-element alloy by combining with further experiments, likewise the previous works based on machine learning 49 , 57 . Further experiment should be needed about the issue which can`t be solved in machine learning level for the lack of data.…”

Section: Resultssupporting

confidence: 54%

Accelerated crystal structure prediction of multi-elements random alloy using expandable features

Jin

Park

et al. 2021

Sci Rep

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Properties of solid-state materials depend on their crystal structures. In solid solution high entropy alloy (HEA), its mechanical properties such as strength and ductility depend on its phase. Therefore, the crystal structure prediction should be preceded to find new functional materials. Recently, the machine learning-based approach has been successfully applied to the prediction of structural phases. However, since about 80% of the data set is used as a training set in machine learning, it is well known that it requires vast cost for preparing a dataset of multi-element alloy as training. In this work, we develop an efficient approach to predicting the multi-element alloys' structural phases without preparing a large scale of the training dataset. We demonstrate that our method trained from binary alloy dataset can be applied to the multi-element alloys' crystal structure prediction by designing a transformation module from raw features to expandable form. Surprisingly, without involving the multi-element alloys in the training process, we obtain an accuracy, 80.56% for the phase of the multi-element alloy and 84.20% accuracy for the phase of HEA. It is comparable with the previous machine learning results. Besides, our approach saves at least three orders of magnitude computational cost for HEA by employing expandable features. We suggest that this accelerated approach can be applied to predicting various structural properties of multi-elements alloys that do not exist in the current structural database.

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Section: Resultssupporting

confidence: 54%

Accelerated crystal structure prediction of multi-elements random alloy using expandable features

Jin

Park

et al. 2021

Sci Rep

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“…It is not only the high-entropy single phase state but also the mediumentropy state or multi-phase state can provide intriguing properties. Therefore, the development of HEMs is on its way to compositionally complex materials [26,[264][265][266][267].…”

Section: Biocompatible Coatingsmentioning

confidence: 99%

High-entropy ceramics: Present status, challenges, and a look forward

et al. 2021

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High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Although in the infant stage, the emerging of this new family of materials has brought new opportunities for material design and property tailoring. Distinct from metals, the diversity in crystal structure and electronic structure of ceramics provides huge space for properties tuning through band structure engineering and phonon engineering. Aside from strengthening, hardening, and low thermal conductivity that have already been found in high-entropy alloys, new properties like colossal dielectric constant, super ionic conductivity, severe anisotropic thermal expansion coefficient, strong electromagnetic wave absorption, etc., have been discovered in HECs. As a response to the rapid development in this nascent field, this article gives a comprehensive review on the structure features, theoretical methods for stability and property prediction, processing routes, novel properties, and prospective applications of HECs. The challenges on processing, characterization, and property predictions are also emphasized. Finally, future directions for new material exploration, novel processing, fundamental understanding, in-depth characterization, and database assessments are given.

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“…The EFA ratings imply that there is a continuum of how easy it is to synthesize a high-entropy ceramic phase with one crystal structure and homogeneous random mixing of elements. Indeed, it was shown by Kaufmann et al that high-entropy carbides with lower EFA values, displaying some chemical segregation (but only one detectable crystal structure), could be homogenized with a longer annealing time 11 . Similarly, HECN #3 can be considered to be in the middle of the EFA continuum, where it could potentially be synthesized as a homogenous single-phase, but would require more energetic input (i.e.…”

Section: Single-phase Formation: Random Distribution Of Elements To mentioning

confidence: 99%

“…maintained equiatomic character. This may be used as an indicator of high-temperature phase stability, and is also a characteristic of having a higher EFA value, as Kaufmann et al noted chromium loss in lower EFA carbides 11 . High-temperature phase stability and thus increased melting temperatures are theorized to be an asset of high-entropy systems, due to the increased contribution of entropy (S) to the Gibb's free energy G = H-TS at high temperatures 16 .…”

Section: Equiatomic Phase Formationmentioning

confidence: 99%

“…High entropy ceramics have been gaining traction in recent years 1 , 2 , since Rost et al adapted the idea of high-entropy alloys 3 , 4 to synthesize the first entropy-stabilized oxide 5 . The field of bulk high-entropy ceramics has grown to include borides 6 , carbides 7 – 11 , silicides 12 , 13 , perovskite oxides 14 , and fluorite oxides 15 . Many of these bulk high-entropy ceramics have increased hardness over their constituents 6 , 7 , 9 , and have the potential for increased phase stability at high temperatures 16 , according to the increased entropy term (S) in the Gibb’s free energy equation G = H-TS.…”

Section: Introductionmentioning

confidence: 99%

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Bulk high-entropy nitrides and carbonitrides

Dippo

Mesgarzadeh

Harrington

et al. 2020

Sci Rep

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121

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High-entropy ceramics have potential to improve the mechanical properties and high-temperature stability over traditional ceramics, and high entropy nitrides and carbonitrides (HENs and HECNs) are particularly attractive for high temperature and high hardness applications. The synthesis of 5 bulk HENs and 4 bulk HECNs forming single-phase materials is reported herein among 11 samples prepared. The hardness of HENs and HECNs increased by an average of 22% and 39%, respectively, over the rule-of-mixtures average of their monocarbide and mononitride precursors. Similarly, elastic modulus values increased by an average of 17% in nitrides and 31% in carbonitrides over their rule-of-mixtures values. The enhancement in mechanical properties is tied to an increase in the configurational entropy and a decrease in the valence electron concentration, providing parameters for tuning mechanical properties of high-entropy ceramics.

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Discovery of high-entropy ceramics via machine learning

Cited by 188 publications

References 65 publications

Accelerated crystal structure prediction of multi-elements random alloy using expandable features

Accelerated crystal structure prediction of multi-elements random alloy using expandable features

High-entropy ceramics: Present status, challenges, and a look forward

Bulk high-entropy nitrides and carbonitrides

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