kALDo Examples

Official repository demonstrating various examples to use kALDo for thermal transport calculations.

Overview

This repository provides examples demonstrating how to compute thermal conductivity using kALDo with two complementary approaches:

• Boltzmann Transport Equation (BTE): Solves for phonon populations under a temperature gradient
• Quasi-Harmonic Green-Kubo (QHGK): A unified approach interpolating between particle-like and wave-like thermal transport

The examples cover workflows with:

• Machine Learning Potentials (orb, NEP, MatterSim, ACE, UPET)
• Density Functional Theory (Quantum ESPRESSO, D3Q)
• Empirical Potentials (Any Empirical Potentials Supported in LAMMPS)
• Finite Temperature Effective Potentials (TDEP)

Contributing

We welcome contributions from the community! If you have a thermal transport workflow using kALDo, whether with a new potential, a different material system, or an alternative method, we'd love to include it.

How to contribute an example

1. Fork the repository and create a new branch (git checkout -b your-branch-name)
2. Add your example in the appropriate category folder (machine_learning_potentials/, density_functional_theory/, or empirical_potentials/)
3. Include a README.md describing the calculation and a Jupyter notebook (.ipynb) for visualization
4. Push your branch and open a Pull Request

The documentation is auto-generated from the example folders, so your example will automatically appear on the docs site once merged.

For questions or suggestions, feel free to open an issue.

Building the Documentation

Requirements

pip install sphinx sphinx-immaterial nbsphinx myst-parser

Build

cd docs
make html

The documentation will be generated in docs/_build/html/.