Abstract
Fragility is one of the central concepts in glass and liquid sciences, as it characterizes the extent of deviation of viscosity from Arrhenius behavior and is linked to a range of glass properties. However, the intervention of crystallization often prevents the assessment of fragility in poor glass-formers, such as supercooled metallic liquids. Hence experimental data on their compositional dependence are scarce, let alone fundamentally understood. In this work, we use fast scanning calorimetry to overcome this obstacle and systematically study the fragility in a ternary La-Ni-Al system, over previously inaccessible composition space. We observe fragility dropped in a small range with the Al alloying, indicating an alloying-induced fragility crossover. We use x-ray photoelectron spectroscopy, resistance measurements, electronic structure calculations, and DFT-based deep-learning atomic simulations to investigate the cause of this fragility drop. These results show that the fragility crossover can be fundamentally ascribed to the electronic covalency associated with the unique Al-Al interactions. Our findings provide insight into the origin of fragility in metallic liquids from an electronic structure perspective and pave a new way for the design of metallic glasses.
| Original language | English |
|---|---|
| Article number | 025002 |
| Journal | Materials Futures |
| Volume | 3 |
| Issue | 2 |
| DOIs | |
| Publication status | Published - Jun 2024 |
Keywords
- deep learning potential
- density functional theory
- fast scanning calorimetry
- fragility
- metallic glass