Deep learning for synthetic microstructure in a materials-by-design framework for heterogeneous energetic materials

Sehuyn Chun, Sidhartha Roy, Yen Thi Nguyen, Joseph B. Choi, H.S. Udaykumar, Stephen S. Baek. (2020). Deep learning for synthetic microstructure in a materials-by-design framework for heterogeneous energetic materials._Scientific Report 10, 13307.

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Planned changes:

• migration to TensorFlow/Keras or PyTorch
• modularization
• refactor

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Getter Started

Virtual Environment

For an optimal setup, consider establishing a virtual environment using Anaconda or Miniconda. Installing the necessary dependencies for our GAN model within this isolated environment ensures smooth functioning. To create a virtual environment, enter the following command in your terminal or command prompt:

conda env create -f requirements.yml

Change the name of the virtual environment by modifying the first line of requirements.yml file. Otherwise, the created virtual environment will be named VIL-GAN.

Demo

The GAN model with training script is implemented in the demo/gan.ipynb notebook.

Citation

To cite this work, please use the following:

@article{chun2020gan,
  title={Deep learning for synthetic microstructure generation in a materials-by-design framework for heterogeneous energetic materials},
  author={Chun, Sehyun and Roy, Sidhartha and Nguyen, Yen Thi and Choi, Joseph B and Udaykumar, Holavanahalli S and Baek, Stephen S},
  journal={Scientific reports},
  volume={10},
  number={1},
  pages={13307},
  year={2020},
  publisher={Nature Publishing Group UK London}
}