PorosityPlus: Characterisation of defective, nanoporous and amorphous materials

As both porous and amorphous semiconductors have different advantages the challenge becomes knowing how to select one over the other, and knowing how to anticipate the degree of crystallinity or the fraction of voids as a function of a controllable feature such as the density. These sorts of relationships can be modelled computationally but unambiguous characterisation of the porosity of complex and disordered structures requires specialist tools. In this paper we demonstrate the use of PorosityPlus to investigate porosity in the vacancy induced amorphisation of defective crystals of carbon, silicon and germanium. The PorosityPlus software allows for the identification of vacancies, twin vacancies and larger pores, along with their relative locations and their respective populations. Void migration and coalescence along with the associated density changes can also be calculated. We show that, with increasing initial vacancies (reduced density) carbon (diamond), silicon and germanium exhibit characteristic density-dependent porosity profiles, coupled with simultaneous amorphisation. This is an ideal tool for integration into advanced computational workflows, such as creating fingerprints for topological data analysis or machine learning, since the porosity profile for each configuration is unique.