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
This dataset was generated for our work: "Complex motion of steerable vesicular robots filled with active colloidal rods". In this project, we used Brownian molecular dynamics simulations to study the rich dynamical behavior of rigid kinked vesicles that contain self-propelling rod-shaped particles. We identified that kinks in the vesicle membrane bias the emergent clustering and alignment of the active agents. Based on the system's geometrical and material properties, we were able to design multiple types of directed motion of the vesicle superstructure. This dataset includes simulation data for two-dimensional systems of self-propelling rod particles confined by teardrop-shaped coarse-grained vesicles. The trajectory of each simulation is saved in a GSD format file with parameter metadata in a JSON file. Due to the large number of replicas of each pair of parameters, simulation data were grouped into 5 different folders. Collective quantitative analysis for simulated trajectories was performed with Jupyter Notebook. and Workspaces_simulations.zip contains all the workspaces of simulations Each folder has subfolders called 'dimer' and 'trimer' depending on the length of the propelling rod particles used in the simulation. (Except for the folder 'number-density_16' which has only 'dimer') In the subfolders, we include the Python scripts used in this work for simulating and trajectory analysis for individual trajectory data. The parameter space of each folder is noted in init.py.
Analysis_jupyter_notebooks.zip includes Jupyter notebooks that can reproduce the collective analysis done for this work.