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# An AI-driven Microcstructure Optimization Framework
This repository contains the code for [AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems](https://www.nature.com/articles/s41524-023-01067-8). The code provides the following functions:

- An end to end microstructure optimization framework to generate multiple polycrystalline microstructures.

## Installation Requirements
The basic requirement for using the files is a Python 3.8.19 environment.

## Source Files
Here is a brief description of the file and folder content:

- Simulator: folder where example data generated using proposed end2end framework.
- end2end_v2.py: code for the proposed end2end framework which can generated microstructures (represented by ODF vectors).

## Running the code
To generate the dataset, run end2end_v2.py file.

## Developer Team
The code was developed by Yuwei Mao from the [CUCIS](http://cucis.ece.northwestern.edu/) group at the Electrical and Computer Engineering Department at Northwestern University.

## Publication
1. Mao, Yuwei, Mahmudul Hasan, Arindam Paul, Vishu Gupta, Kamal Choudhary, Francesca Tavazza, Wei-keng Liao, Alok Choudhary, Pinar Acar, and Ankit Agrawal. "An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems." npj Computational Materials 9, no. 1 (2023): 111. [PDF](https://www.nature.com/articles/s41524-023-01067-8)

## Disclaimer
The research code shared in this repository is shared without any support or guarantee on its quality. However, please do raise an issue if you find anything wrong and I will try my best to address it.

email: yuweimao2019@u.northwestern.edu

Copyright (C) 2023, Northwestern University.

See COPYRIGHT notice in top-level directory.

## Funding Support
This work was supported primarily by National Science Foundation (NSF) CMMI awards 2053929/2053840. Partial support from NIST award 70NANB19H005 and DOE awards DE-SC0019358, DE-SC0021399 is also acknowledged.