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Related Experiment Video

Updated: Jul 6, 2025

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

Disordered enthalpy-entropy descriptor for high-entropy ceramics discovery.

Simon Divilov^1,2, Hagen Eckert^1,2, David Hicks^1,2

¹Department of Mechanical Engineering and Materials Science, Duke University, Durham, NC, USA.

|January 3, 2024

Summary

High-entropy ceramics offer improved functionalities for extreme environments. A new disordered enthalpy-entropy descriptor (DEED) accelerates their computational discovery, guiding experimental efforts.

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Area of Science:

Materials Science
Computational Materials Science
Solid State Chemistry

Background:

Growing demand for materials with enhanced functionalities in extreme environments drives interest in high-entropy ceramics.
Traditional experimental methods for discovering high-entropy ceramics are slow, necessitating more efficient theoretical approaches.
Existing computational methods, like the entropy-forming-ability descriptor for carbides, have limitations in broad applicability.

Purpose of the Study:

To introduce a novel descriptor, the disordered enthalpy-entropy descriptor (DEED), for predicting the synthesizability of multicomponent ceramics.
To develop a computational algorithm that significantly reduces the resources required for these calculations.
To guide the experimental discovery of new single-phase high-entropy carbonitrides and borides.

Main Methods:

Development of the disordered enthalpy-entropy descriptor (DEED) to quantify the balance between entropy and enthalpy.
Implementation of a convolutional algorithm to optimize computational efficiency.
Integration of the DEED descriptor and computational tools into the AFLOW computational ecosystem.

Main Results:

The DEED descriptor accurately classifies the functional synthesizability of multicomponent ceramics across diverse chemistries and structures.
The convolutional algorithm drastically reduces computational resource requirements for materials discovery.
DEED successfully guides the identification of potential new single-phase high-entropy carbonitrides and borides.

Conclusions:

The DEED descriptor represents a significant advancement in the theoretical prediction of high-entropy ceramic synthesizability.
The developed computational approach accelerates the discovery process, overcoming limitations of purely experimental methods.
This work provides a valuable resource for researchers seeking novel high-entropy materials for demanding applications.