Predicting Bulk Metallic Glass Forming Ability with the Thermodynamic Density of Competing Crystalline States

TL;DR

This paper introduces a heuristic descriptor based on the thermodynamic density of competing crystalline states to predict the glass-forming ability of metallic systems, validated through high-throughput experiments on CuZr and NiZr.

Contribution

It proposes a novel thermodynamic descriptor for predicting metallic glass formation, validated with experimental data, advancing the understanding of crystallization frustration.

Findings

The heuristic accurately predicts glass-forming ability in tested systems.

Experimental results support the descriptor's effectiveness.

The approach can accelerate discovery of new metallic glasses.

Abstract

Despite two decades of studies, the formation of metallic glasses, very promising systems for industrial applications, still remains mostly unexplained. This lack of knowledge hinders the search for new systems, still performed with combinatorial trial and error. In the past, it was speculated that some sort of "confusion" during crystallization could play a key role during their formation. In this article, we propose a heuristic descriptor quantifying such confusion. It is based on the "thermodynamic density of competing crystalline states", parameterized from high-throughput ab-initio calculations. The existence of highly enthalpy-degenerate but geometrically-different phases frustrates the crystallization process and promotes glass formation. Two test beds are considered. A good and a bad glass-former, CuZr and NiZr, are experimentally characterized with high-throughput synthesis. The experimental results corroborate the capability of the heuristic descriptor in predicting glass forming ability through the compositional space. Our analysis is expected to deepen the understanding of the underlying mechanisms and to accelerate the discovery of novel metallic glasses.