Tutorial-0X: Miscellaneous Assists

Some of the calculations required to obtain the data to run e.g. AMSET and Phono3py can be very expensive. To reduce that burden, there are a few basic functions to make calculations more efficient. The first is specific to VASP, but the rest are more general.

Zero-Weighted k-points

AMSET and BoltzTraP require dense k-point grids to get accurate results. Not all k-points are created equal, however, so we have provided a tool to combine two KPOINTS files, the converged KPOINTS file which must be weighted, and a second file of less equal k-points which can be zero- weighted, to increase the population without costing so much as their bretheren.

tp.setup.get_kpoint('weighted_KPOINTS', 'unweighted_KPOINTS')

tp gen kpoints -k weighted_KPOINTS -z unweighted_KPOINTS

When setting KPAR, unweighted k-points should not be considered. Our KPAR generator suggests suitable KPAR values, ignoring the zero- weighted k-points.

tp.setup.get_kpar('KPOINTS')

tp gen kpar-k KPOINTS

Target Lattice Thermal Conducitivity

The kappa-target plot shows what lattice thermal conductivity would be required to achieve a specified ZT. If it’s too low, you may not want to bother with the expensive third-order+ phonon caculations!

Merge

tp.data.utilities.merge uses the tp metadata to combine multiple data dictionaries, so one can obtain denser data for memory- intensive calculations (such as AMSET) by running multiple times and merging the data dictionaries before plotting.