SR-electrolytes

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SR-electrolytes

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Symbolic Regression on High-throughput electrolyte data

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# 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](https://doi.org/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](https://big-map.github.io/SR-electrolytes/)

## How to use
We have drafted a Jupyter Notebook explaining how to use the modules. You can find it [here](./example_use.ipynb). 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.

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