Research data for "Exploring the configurational space of amorphous graphene with machine-learned atomic energies"

<p>This dataset supports the paper: &quot;Exploring the configurational space of amorphous graphene with machine-learned atomic energies&quot; (<a href="https://doi.org/10.1039/D2SC04326B">https://doi.org/10.1039/D2SC04326B</a>).</p> <p>Trajectory data for the 200-atom structures (Fig. 3)&nbsp;and the final configurations for the 612-atom structures as well as the GAP-17-optimised 610-atom structure from Toh et al are provided (Fig. 4). Additionally, the structures used for data analysis in Fig. 5 are given.</p> <p>The files&nbsp;are&nbsp;in extended xyz&nbsp;(.xyz) format and contain&nbsp;the raw data for coordinates, forces, and&nbsp;atomic energies (labelled &#39;c_1&#39;). The files also contain&nbsp;the atomic energies relative to pristine graphene, labelled &quot;Energy_per_atom&quot;, and the locally averaged energy relative to pristine graphene,&nbsp;labelled &quot;NN_Energy_per_atom&quot;. Topological information is included&nbsp;at the end of the .xyz file&nbsp;for the 612-atom structures (&#39;fig_4&#39;/)&nbsp;and for the structures in &#39;fig_5/&#39;.</p> <p>All raw atomic&nbsp;energies were computed using LAMMPS default settings and were output with six significant figures, with the exception of the Toh et al. structure (for which&nbsp;ASE was used,&nbsp;outputting&nbsp;a higher number of significant figures).&nbsp;</p> <p>The data can be read using, for example,&nbsp;the Atomic Simulation Environment (ASE), or visualised using Ovito.</p> <p>&nbsp;</p>