Research data supporting "Signatures of paracrystallinity in amorphous silicon"

This dataset reports the following study: https://arxiv.org/abs/2407.16681

Dataset ranging from disorder to order

The dataset contains 3,069 a-Si structures, for a total of approximately 1.3 million atomic environments. These structures range from highly disordered to more crystalline-like. It is separated into .xyz files for each cell structure size.

A pickled dataframe is also provided with additional information on the structures, which can be loaded with pandas as follows:

import pandas as pd
df=pd.read_pickle('./data/df_rev1.pckl.gzip',compression="gzip")
df.keys()

Index(['ase_atoms', 'nb_atoms', 'size', 'vol_per_atom', 'label', 'nnb',
   'Category_2', 'Category_color_2', 'gap_energy', 'dE_gap', 'gap_at_E_NN',
   'mtp_energy', 'dE_mtp', 'mtp_at_E_NN', 'forces', 'F_max',
   'soap_sim_cSi', 'atomistic_soap_sim_cSi', 'PTM', 'CNA', 'stein_sim'],
  dtype='object')

Selected structures

We analyze four structural models (denoted I through IV) of 1,000 atoms of increasing paracrystallinity, which corresponds to the indices 2512, 2545, 2561 and 2568 of the dataframe, respectively.

We also compare prototypical structures from each category: thse indices are 2491 for CRN, 2576 for Paracrystalline and 2604 for Polycrystalline.

Large-scale structures

We also provide larger structural models of 100,000 atoms, namely a paracrystalline and a polycrystalline structure generated with quench rates of $10^{11}$ and $10^{10}$ K/s respectively.

Structure generation

All structures were generated following the protocol described in the manuscript. These simulations were carried out in LAMMPS using the $M_{16}^{''}$ ML potential. Only the ultimate frame from each trajectory was added to the database.

Data analysis

We will provide our scripts for the analysis and plotting of all figures in the manuscript in the scripts and src folders upon journal publication.