Examples¶

Understanding thermal transport in materials is crucial for applications ranging from thermoelectrics to thermal management in electronics. Anharmonic lattice dynamics captures the phonon-phonon interactions that govern heat conduction beyond the harmonic approximation.

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

• Boltzmann Transport Equation (BTE): Solves for phonon populations under a temperature gradient, capturing both normal and Umklapp scattering processes.

• Quasi-Harmonic Green-Kubo (QHGK): A unified approach that interpolates between the particle-like (BTE) and wave-like (Allen-Feldman) pictures of thermal transport.

The examples cover workflows with machine learning potentials, density functional theory (DFT), and empirical potentials.

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

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.