Published April 28, 2025 | Version v1

Dataset: Benchmarking Universal Machine Learning Interatomic Potentials for Real-Time Analysis of Inelastic Neutron Scattering Data

  • 1. EDMO icon Oak Ridge National Laboratory

Description

The dataset contains the unit cell structures (POSCAR-unitcell), force sets calculated with DFT, input files for Phonopy calculations and optional BORN files of 4869 materials. The data is used to generate the phonon properties with selected universal machine learning interatomic potentials. The phonon properties can be generated with the Python script provided in the GitHub repository (https://github.com/maplewen4/phonon_uMLIP).

Files

Files (19.7 MB)

Name Size
md5:860c5fbc09ab550fd5b7315584295d0e
19.7 MB Download

Additional details

Software

Repository URL
https://github.com/maplewen4/phonon_uMLIP
Programming language
Python