Automated double-Bader analysis (DBA)
The dbaAutomator Python code is designed to help BerkeleyGW users working on molecular crystals verify the convergence of the fine k-point grid and perform double-Bader analysis (DBA) of exciton character. To check the fine grid convergence, dbaAutomator applies a criterion based on requiring that the exciton wave-function should be mostly contained in the central region of the super-cell. To streamline the performance of DBA, the code determines the hole positions to sample, generates input files for BerkeleyGW calculations, and computes the degree of charge transfer character for the resulting exciton wave-functions. The dbaAutomator code is distributed under an open-source GPL license.
Bayesian optimization of the Hubbard U parameter in DFT+U
The BayesianOpt4dftu Python code determines the Hubbard U parameters in DFT+U via Bayesian optimization. The objective function is formulated to reproduce as closely as possible the band gap and the features of a reference hybrid functional band structure. The code is compatible with the Dudarev formalism of DFT+U as implemented in the VASP code.
Python package for Molecular Volume Estimation (PyMoVE)
The PyMoVE library contains tools for training and validating machine learned models for molecular crystal volume estimation, including constructing the packing-accessible surface and the molecular topological fragment representation. In addition, PyMoVE contains tools for calculating the molecular volume using the projected marching cubes algorithm, as well as utilities for identifying the molecular units and calculating the packing factor for a given molecular crystal structure.
Visualizer for VASP
Vaspvis is a visualizer for electronic structure calculations using the VASP code. Vaspvis can generate band structure and density of states (DOS) plots including projections of the contributions from specific atoms/ orbitals. Vaspvis can also perform “bulk unfolding” by projecting the band structure of a supercell slab onto the bulk primitive cell.
Reference: J. Phys. Condensed Matter, 34 233002 (2022)