| Abstract Scope |
The need for improved functionalities in extreme environments is fueling interest in high-entropy ceramics. While resilient compositions can be stabilized by maximizing entropy, the search for new systems is mostly performed with trial-and-error and phenomenological techniques, as effective computational discovery is challenged by the immense number of configurations. Often, the synthesis of high-entropy ceramics is assessed using ideal/regular entropy along with the formation enthalpies from density functional theory, with simplified descriptors or machine learning methods. In this presentation I will address many of the problems/solutions in the discovery of disordered ceramics, including the concept of functional synthesizability, [Nature 625, 66 (2024)], offer some data-based effective solutions [Nat. Comms 15, 3328 (2024)], and discuss the avenues opened by the latter, especially for plasmonic-hyperbolic applications – ripe for ultra-high temperature thermal management [Nat. Comms 13, 5993 (2022)]. |
