Publications Repository - Helmholtz-Zentrum Dresden-Rossendorf


Data and Scripts for "Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory"

Fiedler, L.; Moldabekov, Z.; Shao, X.; Jiang, K.; Dornheim, T.; Pavanello, M.; Cangi, A.

# Data and Scripts for "Accelerating Equilibration in First-Principles Molecular Dynamics with Orbital-Free Density Functional Theory"

This dataset contains data and calculation scripts for the publication "Boosting first-principles molecular dynamics with orbital-free density functional theory".
Its goal is to enable interested parties to reproduce the experiments we have carried out. 

## Prerequesites

The following software versions are needed for the python scripts:

- `python`: 3.8.x
- `mala`: 1.1.0 (with `dftpy` installed)

Further, make sure you have a working `Quantum ESPRESSO` and `VASP` installation and have downloaded additional 
data such as local pseudopotentials and ML models (for references, see publication).

## Contents

- `scripts/`: Example scripts for the three principal python tasks associated with out work: ML inference, trajectory
analysis and OF-DFT-MD runs (via DFTPy). The scripts are general blueprints for these experiments and can be adjusted
to perform all of the calculations given in the publication.
- `data/`: Contains raw calculation data for the three investigated systems (hydrogen, beryllium and aluminium).
Since the main goal of this work is to compare OF-DFT-MD initialized and ideal crystal structure initialized 
trajectories and inferences, each of the three system-folders contains a `MD_ideal_crystal_structure` and 
`MD_ofdft_init` folder, with ideal crystal structure and OF-DFT-MD initialized data, respectively. Therein, contents
may differ; e.g. aluminium contains DFT calculation data, for beryllium data is divided by system size and Nosé mass,
while for hydrogen data for different temperatures is given. 

Related publications

Downloads

Permalink: https://www.hzdr.de/publications/Publ-34767
Publ.-Id: 34767