Direct observation of phase transitions in truncated tetrahedral microparticles under quasi-2D confinement
Data files
Feb 27, 2024 version files 212.86 MB
-
NATCOMMUN_Datasetv3.zip
-
README.md
Abstract
Colloidal crystals are used to understand fundamentals of atomic rearrangements in condensed matter and build complex metamaterials with unique functionalities. Simulations predict a multitude of self-assembled crystal structures from anisotropic colloids, but these shapes have been challenging to fabricate. Here, we use two-photon lithography to fabricate Archimedean truncated tetrahedrons and self-assemble them under quasi-2D confinement. These particles self-assemble into a hexagonal phase under an in-plane gravitational potential. Under additional gravitational potential, the hexagonal phase transitions into a quasi-diamond two-unit basis. In-situ imaging reveal this phase transition is initiated by an out-of-plane rotation of a particle at a crystalline defect and causes a chain reaction of neighboring particle rotations. Our results provide a framework of studying different structures from hard-particle self-assembly and demonstrates the ability to use confinement to induce unusual phases.
README: Direct observation of phase transitions in truncated tetrahedral microparticles under quasi-2D confinement
https://doi.org/10.5061/dryad.sbcc2frdf
This dataset contains the images, .csv files, and code needed to reproduce the results to support the conclusion of the manuscript.
Files and Folders
The file structure is ordered relative to the dataset collected for each main figure in the manuscript, as well as some of the supplemental information data. Each folder can contain images (.png, .tif), .csv files, and Jupyter notebooks (.ipynb) that will help reproduce the dataset in the main manuscript. Each folder that has code has a README.md
that helps facilitate installing and running the code.
/Figure 1
README.md
- Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code for the data in Figure 1.
environment.yml
- YAML (.yml) file that declares all necessary python libraries to run the analysis code (orderParams.py and OrderParameterAnalysis.ipynb)
orderParams.py
- Python (.py) file containing necessary functions to run analysis code (OrderParameterAnalysis.ipynb)
OrderParameterAnalysis.ipynb
- Jupyter notebook (.ipynb) file that contains the analysis code to generate the spatial pair distribution function, g(r), and the bond order parameter image found in Figure 1.
WP-008-H11.png
- Portable Network Graphics (.png) file of truncated tetrahedrons assembled on a 2D surface at a low gravitational field. This is the raw data/image used to run the analysis code on (OrderParameterAnalysis.ipynb).
WP-008-H11_centers.csv
- Comma separated valued (.csv) file of the centers of the particles found in WP-008-H11.png. The first column is the x-pixel value and the second column is the y-pixel value. This is needed to run the analysis code (OrderParameterAnalysis.ipynb).
/Figure 2
README.md
- Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code for the data in Figure 2.
environment.yml
- YAML (.yml) file that declares all necessary python libraries to run the analysis code (orderParams.py and OrderParameterAnalysis.ipynb)
orderParams.py
- Python (.py) file containing necessary functions to run analysis code (OrderParameterAnalysis.ipynb)
OrderParameterAnalysis.ipynb
- Jupyter notebook (.ipynb) file that contains the analysis code to generate the spatial pair distribution function, g(r), graph and the bond order parameter image in Figure 2.
SUM_WP-008-H11_001.png
- Portable Network Graphics (.png) file of truncated tetrahedrons assembled on a 2D surface at a higher gravitational field. This is the raw image used to run the analysis code (OrderParameterAnalysis.ipynb).
SUM_WP-008-H11_001.czi
- .CZI file of truncated tetrahedrons assembled on a 2D surface at a higher gravitational field. This is the raw confocal image with multiple z-planes.
SUM_WP-008-H11_001_centers.csv
- Comma separated valued (.csv) file of the centers of the particles found in SUM_WP-008-H11_001.png. The first column is the x-coordinate (in microns) and the second column is the y -coordinate (in microns). This is needed to run the analysis code (OrderParameterAnalysis.ipynb).
/Figure 3
README.md
- Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code to generate data in Figure 3.
environment_entropy.yml
- YAML (.yml) file that declares all necessary python libraries to run the entropy model analysis code (EntropyModel.ipynb)
EntropyModel.ipynb
- Jupyter notebook (.ipynb) file that contains the code to generate the single-cell occupancy free energy curves as a function of packing fraction seen in Figure 3.
environment_hpmc.yml
- YAML (.yml) file that declares all the necessary python libraries to run the hard-particle Monte Carlo (hpmc) simulations (hpmc.ipynb)
hpmc.ipynb
- Jupyter notebook (.ipynb) file that contains the code to generate the hard-particle Monte Carlo simulations seen in Figure 3.
ATT_centered.stl
- 3D model (.STL) file of an Archimedean truncated tetrahedron that is used for the hard-particle Monte Carlo simulations (hpmc.ipynb).
/Supplemental_Avrami
README.md
- Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code to generate data in Supplementary Figure 5.
environment.yml
- YAML (.yml) file that declares all necessary python libraries to run the entropy model analysis code (grainAnalysis.ipynb)
grainAnalysis.ipynb
- Jupyter notebook (.ipynb) file that contains the code to estimate the number of particles in either a 3-fold or 6-fold bond order configuration for the data found in Supplementary Figure 5.
/output
- Empty folder for the generated output image data generated from grainAnalysis.ipynb.
WP-009-L14_timelapse_10x002-3.tif
- Multi-image file (.tif) of raw data for calculating the number of particles in either a 3-fold or 6-fold bond order configuration. This is the same file as the Supplementary Video 3. Each frame corresponds to ~5 seconds. This is needed to run the analysis code (grainAnalysis.ipynb)
WP-009-L14_timelapse_10x002-3_centers.csv
- Comma separated valued (.csv) file of the centers of the particles found in WP-009-L14_timelapse_10x002-3.tif for each frame. Each particle is denoted by an ID (Column B), which has a unique x coordinate (in pixels), Column E "POSITION_X", and y coordinate (in pixels), Column F "POSITION_Y" . Each frame can be identified by the Column I "FRAME". This is needed to run the analysis code (grainAnalysis.ipynb).
Code/Software
The code run on each dataset is provided in each folder in the form of a Jupyter notebook
that is tested in a conda
environment. The dependencies are given in the form of a .yml
file. Each folder that has code has an individual README.md
that helps facilitate installing and running the code. Each code was tested on 11/28/2023 by author(s) and the output cells that are available in the notebook
reflect the code run on the dataset given.