Atomic Configuration Dataset of Zr₄₄Cu₅₆ Metallic Glass Generated by MD Simulation under Varying Cooling and Annealing Protocols

This dataset contains atomic configurations of a 2000-atom Zr₄₄Cu₅₆ metallic glass system generated using molecular dynamics simulations used in paper "Dual Machine Learning Pinpoints the Radius of Informative Structural Environments in Metallic Glasses". The corresponding code is provided in https://github.com/muchen1453/RISE.

All samples were initially equilibrated in the liquid state at 2000 K and subsequently cooled to 0 K under a range of cooling rates. After quenching, selected configurations were further subjected to sub-Tg annealing at various temperatures to explore structural relaxation effects.

The dataset is used to study the relationship between atomic-scale structural environments and inherent structural energy, and serves as the primary data source for identifying the Radius of Informative Structural Environments (RISE) using machine-learning models.

The atomic configurations provided here are intended to support reproducibility and further analysis of structure-property relationships in metallic glasses.