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Register a new userAccurate and efficient band gap predictions of metal halide perovskites using the DFT-1/2 method: GW accuracy with DFT expense
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The outstanding optoelectronics and photovoltaic properties of metal halide perovskites, including high carrier motilities, low carrier recombination rates, and the tunable spectral absorption range are attributed to the unique electronic properties of these materials. While DFT provides reliable structures and stabilities of perovskites, it performs poorly in electronic structure prediction. The relativistic GW approximation has been demonstrated to be able to capture electronic structure accurately, but at an extremely high computational cost. Here we report efficient and accurate band gap calculations of halide metal perovskites by using the approximate quasiparticle DFT-1/2 method. Using AMX3 (A = CH3NH3, CH2NHCH2, Cs; M = Pb, Sn, X=I, Br, Cl) as demonstration, the influence of the crystal structure (cubic, tetragonal or orthorhombic), variation of ions (different A, M and X) and relativistic effects on the electronic structure are systematically studied and compared with experimental results. Our results show that the DFT-1/2 method yields accurate band gaps with the precision of the GW method with no more computational cost than standard DFT. This opens the possibility of accurate electronic structure prediction of sophisticated halide perovskite structures and new materials design for lead-free materials.
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The DFT-1/2 method in density functional theory [L. G. Ferreira et al., Phys. Rev. B 78, 125116 (2008)] aims to provide accurate band gaps at the computational cost of semilocal calculations. The method has shown promise in a large number of cases, however some of its limitations or ambiguities on how to apply it to covalent semiconductors have been pointed out recently [K.-H. Xue et al., Comput. Mater. Science 153, 493 (2018)]. In this work, we investigate in detail some of the problems of the DFT-1/2 method with a focus on two classes of materials: covalently bonded semiconductors and transition-metal oxides. We argue for caution in the application of DFT-1/2 to these materials, and the condition to get an improved band gap is a spatial separation of the orbitals at the valence band maximum and conduction band minimum.
Density Functional Theory calculations traditionally suffer from an inherent cubic scaling with respect to the size of the system, making big calculations extremely expensive. This cubic scaling can be avoided by the use of so-called linear scaling algorithms, which have been developed during the last few decades. In this way it becomes possible to perform ab-initio calculations for several tens of thousands of atoms or even more within a reasonable time frame. However, even though the use of linear scaling algorithms is physically well justified, their implementation often introduces some small errors. Consequently most implementations offering such a linear complexity either yield only a limited accuracy or, if one wants to go beyond this restriction, require a tedious fine tuning of many parameters. In our linear scaling approach within the BigDFT package, we were able to overcome this restriction. Using an ansatz based on localized support functions expressed in an underlying Daubechies wavelet basis -- which offers ideal properties for accurate linear scaling calculations -- we obtain an amazingly high accuracy and a universal applicability while still keeping the possibility of simulating large systems with only a moderate demand of computing resources.
Metal halide perovskites (MHPs) are nowadays one of the most studied semiconductors due to their exceptional performance as active layers in solar cells. Although MHPs are excellent solid-state semiconductors, they are also ionic compounds, where ion migration plays a decisive role in their formation, their photovoltaic performance and their long-term stability. Given the above-mentioned complexity, molecular dynamics simulations based on classical force fields are especially suited to study MHP properties, such as lattice dynamics and ion migration. In particular, the possibility to model mixed compositions is important since they are the most relevant to optimize the optical band gap and the stability. With this intention, we employ DFT calculations and a genetic algorithm to develop a fully transferable classical force field valid for the benchmark inorganic perovskite compositional set CsPb(Br_xI_(1-x))_3 (x = 0,1/3,2/3,1). The resulting force field reproduces correctly, with a common set of parameters valid for all compositions, the experimental lattice parameter as a function of bromide/iodide ratio, the ion-ion distances and the XRD spectra of the pure and mixed structures. The simulated thermal conductivities and ion migration activation energies of the pure compounds are also in good agreement with experimental trends. Our molecular dynamics simulations make it possible to predict the compositional dependence of the ionic diffusion coefficient on bromide/iodide ratio and vacancy concentration. For vacancy concentrations of around 9 10^21 cm^-3, we obtained ionic diffusion coefficients at ambient temperature of 10^-11 and 10^-13 cm2/s for CsPbBr3 and CsPbI3, respectively. Interestingly, in comparison with the pure compounds, we predict a significantly lower activation energy for vacancy migration and faster diffusion for the mixed perovskites.
Using the GW approximation, we study the electronic structure of the recently synthesized hydrogenated graphene, named graphane. For both conformations, the minimum band gap is found to be direct at the $Gamma$ point, and it has a value of 5.4 eV in the stable chair conformation, where H atoms attach C atoms alternatively on opposite sides of the two dimensional carbon network. In the meta-stable boat conformation the energy gap is 4.9 eV. Then, using a supercell approach, the electronic structure of graphane was modified by introducing either an hydroxyl group or an H vacancy. In this last case, an impurity state appears at about 2 eV above the valence band maximum.
The unprecedented structural flexibility and diversity of inorganic frameworks of layered hybrid halide perovskites (LHHPs) rise up a wide range of useful optoelectronic properties thus predetermining the extraordinary high interest to this family of materials. Nevertheless, the influence of different types of distortions of their inorganic framework on key physical properties such as band gap has not yet been quantitatively identified. We provided a systematic study of the relationships between LHHPs band gaps and six main structural descriptors of inorganic framework, including interlayer distances (dint), in-plane and out-of-plane distortion angles in layers of octahedra ({theta}in,{theta}out), layer shift factor (LSF), axial and equatorial Pb-I bond distances (dax,deq). Using the set on the selected structural distortions we realized the inverse materials design based on multi-step DFT and machine learning approach to search LHHPs with target values of the band gap. The analysis of calculated descriptors band gap dependences for the wide range of generated model structures of (100) single-layered LHHPs results in the following descending order of their importance:dint > {theta}in > dax > LSFmin > {theta}out > deq > LSFmax, and also implies a strong interaction value for some pairs of structural descriptors. Moreover,we found that the structures with completely different distortions of inorganic framework can have similar band gap, as illustrated by a number of both experimental and model structures.
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