Synthetic Data

AC-2D-22

Amorphous, 2D graphene structures generated using a Monte Carlo bond-switching algorithm, as described in Figure 3 of the paper: Exploring the Configurational Space of Amorphous Graphene with Machine-Learned Atomic Energies. Files are downloaded from Zenodo.

C-SYNTH-23M

The complete “synthetic” dataset of carbon structures from Synthetic Data Enable Experiments in Atomistic Machine Learning. This dataset comprises 546 uncorrelated MD trajectories, each containing 200 atoms, driven by the C-GAP-17 interatomic potential, and sampled every 1ps. The structures cover a wide range of densities, temperatures and degrees of dis/order.