$py$GWBSE: A high throughput workflow package for GW-BSE calculations

TL;DR

pyGWBSE is an open-source Python package that automates GW-BSE calculations, enabling efficient and accurate prediction of quasiparticle and excitonic properties for materials research.

Contribution

It introduces a fully automated workflow for GW-BSE calculations, integrating convergence testing and Wannier90, facilitating high-throughput material property analysis.

Findings

Automates GW-BSE calculations with convergence tests

Generates databases of quasiparticle and excitonic data

Enables high-throughput materials screening

Abstract

We develop an open-source python workflow package, $py$GWBSE to perform automated first-principles calculations within the GW-BSE (Bethe-Salpeter) framework. GW-BSE is a many body perturbation theory based approach to explore the quasiparticle (QP) and excitonic properties of materials. The GW approximation has proven to be effective in accurately predicting bandgaps of a wide range of materials by overcoming the bandgap underestimation issues of the more widely used density functional theory (DFT). The BSE formalism, in spite of being computationally expensive, produces absorption spectra directly comparable with experimental observations. The $py$GWBSE package achieves complete automation of the entire multi-step GW-BSE computation, including the convergence tests of several parameters that are crucial for the accuracy of these calculations. $py$GWBSE is integrated with $Wannier90$, a program for calculating maximally-localized wannier functions, allowing the generation of QP bandstructures. $py$GWBSE also enables automated creation of databases of metadata and data, including QP and excitonic properties, which can be extremely useful for future material discovery studies in the field of ultra-wide bandgap semiconductors, electronics, photovoltaics, and photocatalysis.