ions 0.5.1

A python library for studying ionic conductors

Contents

• About
• Installation
• Minimal usage example
• Notebooks
• How to cite

About

ions is a python library made for studying crystalline ionic conductors

Installation

pip install ions

or

git clone https://github.com/dembart/ions
cd ions
pip install .

Minimal usage examples:

Note: The last library update was not systematically tested. Errors are expected. Be careful.

Inequivalent ionic jumps (edges) forming a percolating network

from ase.io import read
from ions import Percolator

file = '/Users/artemdembitskiy/Downloads/LiFePO4.cif'
atoms = read(file)  

pl = Percolator(atoms, mobile_specie='Li', upper_bound=5.0)

bottleneck_radius = 0.5 
mincut, maxdim = pl.mincut_maxdim(bottleneck_radius)
print(f'Maximum percolation dimensionality: {maxdim}')
print(f'Jump distance cutoff: {mincut} angstrom', '\n')

edges = pl.unique_edges(mincut, bottleneck_radius, method = 'naive')
print(f'Inequivalent edges forming {maxdim}D percolating network:')
print(edges)

Maximum percolation dimensionality: 2
Jump distance cutoff: 4.755859375 angstrom 

Inequivalent edges forming 2D percolating network:
[[ 0  3  0 -1  0]
 [ 0  0 -1  0  0]]

Notebooks

• Percolations barriers from nudged elastic band (NEB) calculations using universal machine learning interatomic potentials (UMLIPS)
• Available data

How to cite

If you use the library consider citing the following paper:

@article{dembitskiy2025benchmarking,
  title={Benchmarking machine learning models for predicting lithium ion migration},
  author={Dembitskiy, Artem D and Humonen, Innokentiy S and Eremin, Roman A and Aksyonov, Dmitry A and Fedotov, Stanislav S and Budennyy, Semen A},
  journal={npj Computational Materials},
  volume={11},
  number={1},
  pages={131},
  year={2025},
  publisher={Nature Publishing Group UK London}
}