SR-electrolytes

Symbolic Regression on High-throughput electrolyte data.

This repositrory contains modules and an example to train symbolic regression models, following the methodology in the article:

Flores, Eibar, et al. "Learning the laws of lithium-ion transport in electrolytes using symbolic regression." Digital Discovery 1.4 (2022): 440-447. DOI:10.1039/D2DD00027J

Interactive plot of model predictions

We have set-up a small site with an interactive plot illustrating the predictions of the model foun in the article. To visit follow this link: EFlores2022_SR2022

How to use

We have drafted a Jupyter Notebook explaining how to use the modules. You can find it here. The modules use the following dependencies:

• numpy
• sympy
• pandas
• scikit-learn
• autofeat

Aknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 957189.