Discovering Stable Amorphous Ceramics: From Computational Prediction to Thin-Film Synthesis

Abstract

Amorphous materials offer unique functional characteristics, which are not observed in their crystalline counterparts making them invaluable for many applications in science and technology, such as electronic and optical devices, solid-state batteries, and protective coatings. However, finding compositions that are stable against crystallization and/or phase separation, and at the same time offer the needed functionality in the amorphous phase is still largely done by serendipity or trial-and-error. In this work, using yttrium tungsten nitride as a prototype, it is shown how computational random structure sampling provides a robust method to identify compositions that exhibit a highly corrugated potential energy surface with many narrow local minima, which are consequently hard to crystallize and remain stable in the amorphous phase. Synthesis experiments prove that the predicted nitride is readily synthesized in an amorphous phase with no detectable precipitates. High-throughput and conventional characterization of structural, physical, and functional properties of the discovered amorphous nitride compound reveal its attractive properties and possible application potential. The proposed workflow combining theory and experiment is broadly applicable to the discovery of a wide range of amorphous ceramic materials, paving the way for advanced amorphous materials for diverse emerging technologies.