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Filtering by: Creator Glotzer, Sharon C. Language Python

Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation

Creator:

Lee, Shih Kuang, Tsai, Sun Ting, and Glotzer, Sharon C.

Description:

The trajectory data and codes were generated for our work "Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation" (amidst peer review process). The data sets contain trajectory data in GSD file format for 7 test systems, including cubic structures, two-dimensional and three-dimensional patchy particle shape systems, hexagonal bipyramids with two aspect ratios, and truncated shapes with two degrees of truncation. Besides, the corresponding Python code and Jupyter notebook used to perform data augmentation, MLP classifier training, and MLP classifier testing are included.

Keyword:

Machine Learning, Colloids Self-Assembly, Crystallization, and Order Parameter

Citation to related publication:

https://doi.org/10.48550/arXiv.2312.11822

Discipline:

Other, Science, and Engineering
A Microscopic Theory of Entropic Bonding – Energy/Simulation Scripts with Representative Data

Creator:

Vo, Thi and Glotzer, Sharon C.

Description:

The goal of this project is to develop a first principle driven approach for predicting the self-assembly behavior of entropically driven crystallization. We first developed a set of mean-field theoretical framework that captures the relevant energetic contributions to the assembly process and then evaluate relevant terms within our framework to determine the excess free energy of formation for each lattice (matlab/octave codes). We then validate theoretical predictions of relevant features like shape and bonding orbitals using standard MD simulations using HOOMD-Blue (simulation scripts). and This research was supported by the Office of the Undersecretary of Defense for Research and Engineering (OUSD(R&E)), Newton Award for Transformative Ideas during the COVID-19 Pandemic, Award number HQ00342010030.

Keyword:

Self-Assembly, Entropy, Thermodynamics, Simulations, and Theory

Citation to related publication:

Vo, T., & Glotzer, S. C. (2021). Microscopic Theory of Entropic Bonding for Colloidal Crystal Prediction. ArXiv:2107.02081 [Cond-Mat]. http://arxiv.org/abs/2107.02081

Discipline:

Science

Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation

A Microscopic Theory of Entropic Bonding – Energy/Simulation Scripts with Representative Data

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Classification of complex local environments in systems of particle shapes through shape-symmetry encoded data augmentation

A Microscopic Theory of Entropic Bonding – Energy/Simulation Scripts with Representative Data

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