This repository contains the analysis codes and deep learning models associated with "ElemNet: Deep Learning the Chemistry of Materials FromOnly Elemental Composition" by D. Jha et al. [ PDF].
The deep learning model produced in this work is available in the elemnet folder.
The other folders contain scripts associted with different analyses performed to characterize ElemNet. Each folder contains a README file that describes what the analyses are, and the notebooks should be self-describing.
As this git repository uses submodules, you need to clone it with git clone --recursive to gather all of the required source code.
The basic requirement for re-using these environments are a Python 3 Jupyter environment with the packages listed in requirements.txt.
Some analyses required the use of Magpie, which requires Java JDK 1.7 or greater. See [the Magpie documentation for details]
D. Jha, L. Ward, A. Paul, W.-keng Liao, A. Choudhary, C. Wolverton, and A. Agrawal, “ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition,” Scientific Reports, 8, Article number: 17593 (2018) [DOI:10.1038/s41598-018-35934-y] [PDF].