From data to knowledge in disorder ceramics for ultra-high-temperature applications

Mechanical Engineering and Materials Science Seminar Series

Seminars are held weekly at 2:30 PM. Please contact Diana Qiu, Amir Pahlavan, or Rebecca Kramer-Bottiglio with speaker suggestions.

December 13, 2021

"From data to knowledge in disorder ceramics for ultra-high-temperature applications"
Stefano Curtarolo
Edmund T. Pratt, Jr. Distinguished Professor
Materials Science, Electrical Engineering and Physics
Director, Center for Autonomous Materials Design
Duke University

Abstract: Disordered multicomponent systems - occupying the mostly uncharted centers of phase diagrams - have been studied for the last two decades for their potential revolutionary properties [1]. Very resilient compositions can be stabilized by maximizing entropy (configurational and/or vibrational) of (near) equimolar mixtures [2]. The search for new systems is mostly performed with trial-and-error techniques, as effective computational discovery is challenged by the immense number of configurations [3]: the synthesizability of high-entropy ceramics is typically assessed using ideal entropy along with the formation enthalpies from density functional theory, with simplified descriptors [4,5,6] or machine learning methods [7]. With respect to vibrations — even if they may have significant impact on phase stability — their contributions are drastically approximated to reduce the high computational cost, or often avoided with the hope of them being negligible, due to the technical difficulties posed in calculating them for disordered systems [8]. In this presentation I will address many of the problems in the discovery of disordered systems, offer some data-based effective solutions, and discuss the avenues opened by the latter. Research sponsored by DoD-ONR.

[1] Oses et al., "High-entropy ceramics,", Nat. Rev. Mater. 5, 295 (2020);
[2] Rost et al., "Entropy Stabilized Oxides", Nat. Comms. 6, 8485 (2015);
[3] Toher et al., "Unavoidable disorder and entropy in multi-component systems", npj Comput. Mater. 5(Brief Comm.), 69 (2019);
[4] The 2021 Materials Genome Initiative Strategic Plan, page 9 of https://www.mgi.gov/sites/default/files/documents/MGI-2021-Strategic-Pla...
[5] Sarker et al., "High-entropy high-hardness metal carbides discovered by entropy descriptors", Nat. Comms. 9, 4980 (2018);
[6] Lederer et al., "The search for high entropy alloys: a high-throughput ab-initio approach", Acta Mater. 159, 364 (2018);
[7] Hart et al., "Machine Learning and Alloys", Nat. Rev. Mater. 6, 730-755 (2021);
[8] Esters et al "Settling the matter of the role of vibrations in the stability of high-entropy carbides", Nat. Comms. 12, 5747 (2021).