Published December 20, 2022 | Version v1
Dataset Open

Exploring the configuration space of elemental carbon with empirical and machine learned interatomic potentials

  • 1. University of Warwick
  • 2. Aalto University

Description

This dataset contains a vertical slice of the data used to generate the results found in the publication "Exploring the configuration space of elemental carbon with empirical and machine learned interatomic potentials"
It contains nested sampling input files and trajectory files for each potential studied, as well as the xml files and training data for the new potential, GAP-20U+gr.

Files

Files (209.4 MB)

Name Size Download all
md5:8352c3ef7af4028353095ff70c7081c8
209.4 MB Download

Additional details

Related works

Continues
Working paper: arXiv:2208.09692 (arXiv)

Funding

Sulis: An EPSRC platform for ensemble computing delivered by HPC Midlands+ EP/T022108/1
UK Research and Innovation
Novel computational routes to materials discovery EP/T000163/1
UK Research and Innovation
Next-generation interatomic potentials to simulate new cellulose-based materials (NEXTCELL) 330488
Academy of Finland
Exploring All-Solid-State Batteries using First-Principles Modelling: Effective Computational Strategies towards Better Batteries EP/T026138/1
UK Research and Innovation