Efficient Computation of Structural and Electronic Properties of Halide Perovskites Using Density Functional Tight Binding: GFN1-xTB Method

[Image: see text] 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.