Work Description

Date: 13 December, 2023

Dataset Title: Complex motion of steerable vesicular robots filled with active colloidal rods

Dataset Creators: Lee, Sophie Y., Schönhöfer Philipp W.A., Glotzer, Sharon C.

Dataset Contact: Sophie Lee syjlee@umich.edu

Funding: DE-SC0000989 (DOE), DMR140129 (NSF grant ACI-1548562, NSF grants #2138259, #2138286, #2138307, #2137603, and #2138296)

Key Points:
- 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 designed multiple types of directed motion of the vesicle superstructure.

Research Overview:
While the collective motion of active particles has been studied extensively, effective strategies to navigate particle swarms without external guidance remain elusive. We introduce a method to control the trajectories of two-dimensional swarms of active rod-like particles by confining the particles to rigid bounding membranes (vesicles) with non-uniform curvature. We show that the propelling agents spontaneously form clusters at the membrane wall and collectively propel the vesicle, turning it into an active superstructure. To further guide the motion of the superstructure, we add discontinuous features to the rigid membrane boundary in the form of a kinked tip, which acts as a steering component to direct the motion of the vesicle. We report that the system’s geometrical and material properties, such as the aspect ratio and Péclet number of the active rods as well as the kink angle and flexibility of the membrane, determine the stacking of active particles close to the kinked confinement and induce a diverse set of dynamical behaviors of the superstructure, including linear and circular motion both in the direction of, and opposite to, the kink. From a systematic study of these various behaviors, we design vesicles with switchable and reversible locomotions by tuning the confinement parameters. The observed phenomena suggest a promising mechanism for particle transportation and could be used as a basic element to navigate active matter through complex and tortuous environments.

Methodology:
The data were generated using Molecular Dynamics (MD) simulations using Hoomd-Blue 3.0 on the ACCESS Bridges 2 supercomputer. Trajectories of each simulation were visualized with Ovito. Quantitative analysis from molecular dynamics simulation trajectories was computed using the Freud analysis package and other Python packages. Data are managed and organized with Signac.

Instrument and/or Software specifications: signac 1.8.0, signac-flow 0.16.0, python 3.9.18, Hoomd 3.0.0

Files contained here:
Six Signac workspace folders ('nokink' and 'number-density_*') have two subfolders 'dimer' and 'trimer' each. (Except for the folder 'number-density_16' which has only 'dimer') Each subfolder contains Python scripts to run simulations and analysis on trajectories generated from the simulation.
(note, number-density_17 is a folder that has two zipped folders 'dimer' and 'trimer' because of its large capacity)
Each of these Signac workspaces utilizes Signac version 1. and Hoomd version 3.0.0.

To run the code, the user should execute in the command line:

python init.py
python project.py run -o run
python calc_velocities.py run -o run
python analytic_angular.py run -o run

The first command initializes the Signac workspace and the second line runs the HOOMD Molecular dynamics simulation.
The third and fourth commands are to perform velocity analysis and analytic analysis of individual simulated trajectories as a result of the second line and to create metadata of the results in npy for analysis which will be done in Jupyter Notebook.

** When executing the Python scripts and Jupyter Notebook, you need to replace the path of the files and Python executable to properly run with the Signac package.

- analysis: Contains Jupyter Notebook files that conduct analysis

- nokink: runs simulations of vesicle without kink. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

- number-density_12: runs simulations of a vesicle with kink angles of 60,90,120,150 and harmonic angle coefficients of 500 and 1000. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

-number-density_13: runs simulations of a vesicle with kink angles of 60,90,120,150 and harmonic angle coefficients of 500 and 1000. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

-number-density_14: runs simulations of a vesicle with kink angles of 75,105,135 and harmonic angle coefficients of 1000. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

-number-density_15: runs simulations of a vesicle with kink angles of 105 and harmonic angle coefficients of 500. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

-number-density_16: runs simulations of a vesicle with kink angles of 120,135 and harmonic angle coefficients of 1000. A subfolders 'dimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

-number-density_17: runs simulations of a vesicle with kink angles of 60,75,90,105,120,135,150 and harmonic angle coefficients of 500 and 1000. Two subfolders 'dimer' and 'trimer' contains Python scripts (calc_velocities.py, analytic angular.py) that run simulations and follow-up analysis based on the trajectories from running project.py

Related publication(s):
Lee, Sophie Y., Schönhöfer Philipp W.A., Glotzer, Sharon C. (2023). Complex motion of steerable vesicular robots filled with active colloidal rods., Scientific Reports (Provisional Citation)

Use and Access:
This data set is made available under a Creative Commons Public Domain license https://creativecommons.org/licenses/by/4.0/.

To Cite Data:
Lee, Sophie Y., Schönhöfer Philipp W.A., Glotzer, Sharon C. (2023). Complex motion of steerable vesicular robots filled with active colloidal rods [Data set]. University of Michigan - Deep Blue. https://doi.org/10.7302/mwe9-1v96