Data underlying the publication: Microstructural features governing fracture of a two-dimensional amorphous solid identified by machine learning
doi:10.4121/c4883858-a901-4e93-b716-2869a664acb0.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/c4883858-a901-4e93-b716-2869a664acb0
doi: 10.4121/c4883858-a901-4e93-b716-2869a664acb0
Datacite citation style:
Huisman, Max; Huerre, Axel; Saikat Saha; Crocker, John C.; Valeria Garbin (2024): Data underlying the publication: Microstructural features governing fracture of a two-dimensional amorphous solid identified by machine learning. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/c4883858-a901-4e93-b716-2869a664acb0.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
CC BY 4.0
Datasets for paper "Microstructural features governing fracture of a two-dimensional amorphous solid identified by machine learning".
We applied isotropic dilational strain to a densely packed monolayer of attractive colloidal microspheres, resulting in fracture. Using brightfield microscopy and particle tracking, it is possible to examine the microstructural evolution of the monolayer during fracturing. Furthermore, using a quantified representation of the microstructure in combination with a machine learning algorithm, we calculate the likelihood of regions of the monolayer to be on a crack line.
The raw data from 20 independent experiments are provided here. The original datasets were sliced for ease of handling the file size, resulting in 79 separate files included here. Each of the 79 datasets consists of two files:
(1) particle trajectories of all particles in the monolayer
(2) classification labels for Machine Learning: particles receive a label '0' if the do not participate in the fracture, or '1' if they do.
The names of both files (1) and (2) begin with the same string, containing information on the experiment, and end with 'positions' and 'labels' respectively. A README file containing all details accompanies the datasets.
history
- 2024-08-22 first online, published, posted
publisher
4TU.ResearchData
format
positions/.csv; classification labels/.csv
references
organizations
TU Delft, Faculty of Applied Sciences, Department of Chemical EngineeringUniversity of Edinburgh, School of Physics and Astronomy, Institute for Condensed Matter and Complex Systems
Université Paris Cité, Laboratoire Matière et Systèmes Complexes
University Of Pennsylvania, School of Engineering and Applied Science, Department of Chemical and Biomolecular Engineering
DATA
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