There is a newer version of the record available.

Published August 7, 2021 | Version v2
Dataset Restricted

Data for "Unfolding the Structural Stability of Nanoalloys via a Combination of Symmetry-Constrained Genetic Algorithm and Neural Network Potential"

Authors/Creators

  • 1. Technical University of Denmark

Description

PtNi_alloy_eam.db is the dataset (ase.db object) consisting of 55982 intially sampled Pt-Ni alloy structures with EAM energies and forces.

PtNi_alloy_dft.db is the dataset (ase.db object) consisting of the final 6828 resampled Pt-Ni alloy structures with DFT energies and forces calculated by VASP. This is the training set for the NNP, and could be very useful for fitting other machine learning models.

PtNi_nanoalloy_vertices_nnp.db is the dataset (ase.db object) consisting of all the vertices (stable structures) on the convex hulls obtained from NNP-based SCGA runs on 36 Pt-Ni nanoalloy systems. The energies are given by the NNP. Additional information such as mixing energy, motif and symmetry axis are also saved in the dataset and can be queried by the 'data' keyword.

Input_and_scripts.zip provides all the input files and scripts for hybrid MC-MD simulations, QBC resampling, DFT calculations, NNP training, NNP-based SCGA runs and convex hull analysis.

Files

Restricted

The record is publicly accessible, but files are restricted. Log in to check if you have access.

Request access

If you would like to request access to these files, please fill out the form below.

You need to satisfy these conditions in order for this request to be accepted:

Collaborators and consortium members only.

You are currently not logged in. Do you have an account? Log in here

Additional details

Funding

European Commission
BIKE - Bimetallic catalyst knowledge-based development for energy applications 813748