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 properties 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 behavior of MHPs, respectively. However,
the complex interplay of the dynamical and optoelectronic properties
in MHPs requires the simultaneous modeling 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 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. We also identify
further challenges in the computation of specific geometries and chemical
compositions. Nevertheless, we believe that the tunability of GFN1-xTB
offers opportunities to resolve these issues and we propose specific
strategies for the further refinement of the parameters, which will
turn this method into a powerful computational tool for the study
of MHPs and beyond.