A physics-guided neural network model for the prediction of structural, thermodynamic and dynamic properties of aluminosilicate melts and glasses.
Project description
i-Melt
i-Melt is a physics-guided neural network model, that combines deep neural networks with physical equations to predict the structural, thermodynamic and dynamic properties of aluminosilicate melts and glasses.
- Web app https://i-melt.streamlit.app/
- Documentation (in progress) https://i-melt.readthedocs.io/en/latest/
- Source code: https://github.com/charlesll/i-melt/tree/main/i-melt/src/
- License: https://github.com/charlesll/i-melt/LICENSE
- References: https://i-melt.readthedocs.io/en/latest/references.html
- Bug reports: https://github.com/charlesll/i-melt/issues
- Contact lelosq@ipgp.fr
Software Contributors
Charles Le Losq, University Paris Cité, Institut de physique du globe de Paris, lelosq@ipgp.fr
Barbara Baldoni, University Paris Cité, Institut de physique du globe de Paris, baldoni@ipgp.fr
Andrew P. Valentine, Durham University, andrew.valentine@durham.ac.uk
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file imelt-2.1.3.tar.gz
.
File metadata
- Download URL: imelt-2.1.3.tar.gz
- Upload date:
- Size: 50.6 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0608ca26e7a36c25ea5b5357d168efb10370fe5d21e40d9b83a44f393af1b86b |
|
MD5 | 03174faa8fbfbdac5781d45de06e765b |
|
BLAKE2b-256 | 43c5e1706e330726cd4c553bdc0cb40f5c766cd7100c2cc46f9c348a77a039e7 |
File details
Details for the file imelt-2.1.3-py3-none-any.whl
.
File metadata
- Download URL: imelt-2.1.3-py3-none-any.whl
- Upload date:
- Size: 39.2 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4e98764f1f5b7edb4c279438a69bbca5581f0ce247409290067a2dd97c99e680 |
|
MD5 | 41e80c71b5205dcf9f5bdd6bedaeaca8 |
|
BLAKE2b-256 | eb768abb755f63da7368d0545f9da376fc73c5c904ac55b0688af2f794fe05dd |