The trajectory data and codes were generated for our work "Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation" (amidst peer review process). The data sets contain trajectory data in GSD file format for 7 test systems, including cubic structures, two-dimensional and three-dimensional patchy particle shape systems, hexagonal bipyramids with two aspect ratios, and truncated shapes with two degrees of truncation. Besides, the corresponding Python code and Jupyter notebook used to perform data augmentation, MLP classifier training, and MLP classifier testing are included.
The dataset is organized as follows: the data for each of the three target structures is contained within a directory with the structure name (e.g., kagome, pyrocholore and snub-square). Within each structure directory, data obtained from alchemical and self-assembly simulations are separated into alchem and self-assembly directories respectively. An additional suboptimal-self-assembly directory is only present for the snub-square structure and contains the data for the pattern registration analysis discussed in the SI. For a detailed description of each file contained within each directory, please refer to the README file.
Rivera-Rivera, LY, Moore, TC & SC Glotzer. Inverse design of triblock Janus spheres for self-assembly of complex structures in the crystallization slot via digital alchemy. Soft Matter, 2023, 19, 2726-2736 doi: 10.1039/d2sm01593e