NU-CUCIS / ElemNet
Deep Learning the Chemistry of Materials From Only Elemental Composition for Enhancing Materials Property Prediction
Why this job: works in the areas we cover, but does not say which job it does


What it does
ElemNet is a deep neural network model that takes only the elemental compositions as inputs and leverages artificial intelligence to automatically capture the essential chemistry to predict materials properties. ElemNet can automatically learn the chemical interactions and similarities between different elements which allows it to even predict the phase diagrams of chemical systems absent from the training dataset more accurately than the conventional machine learning models based on physical attributes levaraging domain knowledge.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Inactive
- Last commit 10 months ago
- Stars
- 104
- On GitHub
- Licence
- Custom
- Read before business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Jupyter Notebook
- 98% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 67% closed
- 2 still open
- Pull requests
- 16 merged
- 0 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Jupyter Notebook 98%
- Python 2%
- Scala <1%
Topics
- chemistry
- deep-learning
- deep-neural-networks
- machine-learning
- materials-science
Project record
- JobOther AI tools
- StatusListed
- Commits83
- Forks35
- Watching5
- Stars in 28 days0
- CreatedOct 9, 2018
- First seen by usNov 7, 2026
- CheckedNov 8, 2026
