GitHub Resources | ARC Centre of Excellence in Exciton Science

Follow the links below to access useful python resources in GitHub.


PyPhotonics is a post-processing python code that calculates photonic properties of materials. Based on the outcome of DFT, constrained DFT and vibrational calculations using DFT performed using VASP for a defect system, PyPhotonics uses the results in the output files and calculates the Huang-Rhys factor of the defect and the photoluminescence line-shape. Soon, the code will calculate the carrier capture coefficient and carrier lifetimes for defects, which are essential quantities for assessing the photovoltaic efficiency of materials.


CrystalFeatures is a set of python codes that extract features of crystal systems, using only the CIF file as input, for machine learning applications. There are three classes of features in CrystalFeatures: basic descriptors, which include statistical properties of the atoms in the materials as well as the crystal symmetry; geometry features, which are based on bonding properties; and SDFT features, which stands for "superficial" DFT, where the eigen values of the material are obtained using a single-point single step calculation is performed using GPAW.

You can also access Exciton Science's library of online tutorial recordings here: