doped is a Python software for the generation, pre-/post-processing and analysis of defect supercell calculations, implementing the defect simulation workflow in an efficient, reproducible, user-friendly yet powerful and fully-customisable manner.

Defect structure-searching employing chemically-guided bond distortions

Quantum dynamics package based on tensor network states

Preforms De novo protein design using machine learning and PyRosetta to generate a novel protein structure

A plugin to AiiDA for running simulations with VASP

Band structure unfolding made easy!

Ab initio full cell dynamical mean-field theory (DMFT) and GW+DMFT for solids

A library of density matrix embedding theory (DMET).

RosettaDesign using PyRosetta

A Python package for calculating thermodynamic properties under quasi-harmonic approximation, using data from ab-initio calculations

Materials informatics framework for ab initio data repositories

A script that computationally designs a vaccine

Semiemperical quasiharmonic thermal elasticity

A Python module for scripting with Q-Chem

AiiDA plugin of the high-performance density functional theory code FLEUR (www.judft.de) for high-throughput electronic structure calculations.

AiiDA plugin of the high-performance density functional theory code JuKKR (www.judft.de) for high-throughput electronic structure calculations.

Calculate thermodynamic properties of matter using phonon gas model (PGM)

Pseudopotential converter from upf to psp8

Wannier & vASP Postprocessing module

Extract patterns from ab-initio molecular dynamics simulations using machine learning.