Published July 11, 2022
| Version v1
Dataset
Open
Research data supporting: "Classifying soft self-assembled materials via unsupervised machine learning of defects"
- 1. Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy
- 2. Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Lugano-Viganello, Switzerland
- 3. Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy; Department of Innovative Technologies, University of Applied Sciences and Arts of Southern Switzerland, Lugano-Viganello, Switzerland
Description
Research data supporting: "Classifying soft self-assembled materials via unsupervised machine learning of defects".
The root folder contains 5 folders:
- FIBERS
- MEMBRANES_and_MICELLES
- NANOPARTICLES
- COMPARISON
- paper_images
The folders 1. to 3. contain the data for every soft-matters architecture used to produce the results discussed in the main paper. Each of these folders contain additional sub-fordels: TRAJ, SOAP, PCA, CLUSTERING, containing the files discussed in the main paper.
Folder 4. contains the data of the comparison between different classes of materials (SOAP, PCA, and CLUSTERING sub-folders).
Folder 5. contains the images that are showed in the main paper and in the Supporting Information.
Files
supp_material.zip
Files
(12.6 GB)
| Name | Size | Download all |
|---|---|---|
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md5:723a8ac24e80bf7ebb51382cc7d19e64
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12.6 GB | Preview Download |
Additional details
Related works
- Is cited by
- Journal article: 10.1038/s42004-022-00699-z (DOI)