  In recent years, metal halide perovskites (MHPs) for optoelectronic
applications have attracted the attention of the scientific community due to
their outstanding performance. The fundamental understanding of their
physicochemical features is essential for improving their efficiency and
stability. Atomistic and molecular simulations have played an essential role in
the description of the optoelectronic properties and dynamical behaviour of
MHPs, respectively. However, the complex interplay of the dynamical and
optoelectronic properties in MHPs requires the simultaneous modelling of
electrons and ions in relatively large systems, which entails a high
computational cost, sometimes not affordable by the standard quantum mechanics
methods, such as Density Functional Theory (DFT). Here, we explore the
suitability of the recently developed Density Functional Tight Binding (DFTB)
method, GFN1-xTB, for simulating MHPs with the aim of exploring an efficient
alternative to DFT. The performance of GFN1-xTB for computing structural,
vibrational and optoelectronic properties of several MHPs is benchmarked
against experiments and DFT calculations. In general, this method produces
accurate predictions for many of the properties of the studied MHPs, which are
comparable to DFT and experiments. However, we also identify a few
shortcomings, related to specific geometries and chemical compositions.
Nevertheless, we believe that the tunability of GFN1-xTB is the key to
resolving any observed issues and we propose specific targets, whose refinement
will turn this method into a powerful computational tool for the study of MHPs
and beyond.
