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

Abstract

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.

Transitioning from Ionic Liquids to Deep Eutectic Solvents

“…We also performed quantum semiempirical calculations at the density functional tight binding (DFTB) level of theory to complement the MD simulations. We used the extended tight binding GFN1-xTB method developed by Grimme et al , This method contains a parametrization for almost all the elements of the periodic table (up to Z - 86), and it has been particularly tested for describing the potential energy curve for the dissociation of ionic liquids and to compute a variety of properties of ionic crystals such as halide perovskites . To obtain the optimized structures of the EMIMCl· n AcOH mixtures, we performed geometry relaxations of 2000 random configurations of each composition and selected the most stable configurations.…”

“…We used the extended tight binding GFN1-xTB method developed by Grimme et al 57,58 This method contains a parametrization for almost all the elements of the periodic table (up to Z -86), and it has been particularly tested for describing the potential energy curve for the dissociation of ionic liquids 53 and to compute a variety of properties of ionic crystals such as halide perovskites. 59 To obtain the optimized structures of the EMIMCl•nAcOH mixtures, we performed geometry relaxations of 2000 random configurations of each composition and selected the most stable configurations. We performed energy minimizations using the fast inertial relaxation engine (FIRE) 60 with an energy and gradients convergence of 10 −5 Hartree and 10 −3 Hartree/Å, respectively.…”

Refined GFN1-xTB Parameters for Engineering Phase-Stable CsPbX3 Perovskites

“…Starting from the original GFN1-xTB parameters of Cs, Pb, Br, and I, we refined several parameters of each element to obtain a better description of the MHPs. These were trained against a set of DFT reference data using the covariance matrix adaption evolution strategy (CMA-ES) optimization method as implemented in the AMS2020 ParAMS module. , To avoid underestimation of the volume of the perovskite systems, we first optimized the parameters of the repulsion energy term (α A and Z A ), which is independent of the electronic part of the Hamiltonian. With halide perovskites being ionic crystals, electrostatic interactions have a significant influence on these systems and modifying the simple repulsive energy term was not sufficient for describing the properties of all the perovskite phases simultaneously.…”

“…A recent review of their performance for a range of MHPs shows promising results for describing their electronic properties. However, the lattice parameters remain underestimated …”

“…However, the lattice parameters remain underestimated. 33 In this work, we refine the GFN1-xTB parameters to accurately predict the various phases of both CsPbBr 3 and CsPbI 3 , allowing for the analysis of both pure and mixed halide perovskites using a single set of parameters. To obtain a representative set of parameters, the GFN1-xTB method is trained against a set of DFT reference data.…”