Breakdown of the static picture of defect energetics in halide perovskites: the case of the Br vacancy in CsPbBr3

We consider the Br vacancy in CsPbBr3 as a prototype for the impact of structural dynamics on defect energetics in halide perovskites (HaPs). Using first-principles molecular dynamics based on density functional theory, we find that the static picture of defect energetics breaks down; the energy of the Br vacancy level is found to be intrinsically dynamic, oscillating by as much as 1 eV on the ps time scale at room temperature. These significant energy fluctuations are correlated with the distance between the neighboring Pb atoms across the vacancy and with the electrostatic potential at these Pb atomic sites. We expect this unusually strong coupling of structural dynamics and defect energetics to bear important implications for both experimental and theoretical analysis of defect characteristics in HaPs. It may also hold significant ramifications for carrier transport and defect tolerance in this class of photovoltaic materials.Comment: 5 figures, 1 tabl

Reliable energy level alignment at physisorbed molecule-metal interfaces from density functional theory.

A key quantity for molecule-metal interfaces is the energy level alignment of molecular electronic states with the metallic Fermi level. We develop and apply an efficient theoretical method, based on density functional theory (DFT) that can yield quantitatively accurate energy level alignment information for physisorbed metal-molecule interfaces. The method builds on the "DFT+Σ" approach, grounded in many-body perturbation theory, which introduces an approximate electron self-energy that corrects the level alignment obtained from conventional DFT for missing exchange and correlation effects associated with the gas-phase molecule and substrate polarization. Here, we extend the DFT+Σ approach in two important ways: first, we employ optimally tuned range-separated hybrid functionals to compute the gas-phase term, rather than rely on GW or total energy differences as in prior work; second, we use a nonclassical DFT-determined image-charge plane of the metallic surface to compute the substrate polarization term, rather than the classical DFT-derived image plane used previously. We validate this new approach by a detailed comparison with experimental and theoretical reference data for several prototypical molecule-metal interfaces, where excellent agreement with experiment is achieved: benzene on graphite (0001), and 1,4-benzenediamine, Cu-phthalocyanine, and 3,4,9,10-perylene-tetracarboxylic-dianhydride on Au(111). In particular, we show that the method correctly captures level alignment trends across chemical systems and that it retains its accuracy even for molecules for which conventional DFT suffers from severe self-interaction errors

Dynamic Shortening of Disorder Potentials in Anharmonic Halide Perovskites

Halide perovskites are semiconductors that exhibit sharp optical absorption edges and small Urbach energies allowing for efficient collection of sunlight in thin-film photovoltaic devices. However, halide perovskites also exhibit large nuclear anharmonic effects and disorder, which is unusual for efficient optoelectronic materials and difficult to rationalize in view of the small Urbach energies that indicate a low amount of disorder. To address this important issue, the disorder potential induced for electronic states by the nuclear dynamics in various paradigmatic halide perovskites is studied with molecular dynamics and density functional theory. We find that the disorder potential is dynamically shortened due to the nuclear motions in the perovskite, such that it is short-range correlated, which is shown to lead to favorable distributions of band edge energies. This dynamic mechanism allows for sharp optical absorption edges and small Urbach energies, which are highly desired properties of any solar absorber material

Energy Level Alignment at Molecule-Metal Interfaces from an Optimally-Tuned Range-Separated Hybrid Functional

The alignment of the frontier orbital energies of an adsorbed molecule with the substrate Fermi level at metal-organic interfaces is a fundamental observable of significant practical importance in nanoscience and beyond. Typical density functional theory calculations, especially those using local and semi-local functionals, often underestimate level alignment leading to inaccurate electronic structure and charge transport properties. In this work, we develop a new fully self-consistent predictive scheme to accurately compute level alignment at certain classes of complex heterogeneous molecule-metal interfaces based on optimally-tuned range-separated hybrid functionals. Starting from a highly accurate description of the gas-phase electronic structure, our method by construction captures important nonlocal surface polarization effects via tuning of the long-range screened exchange in a range-separated hybrid in a non-empirical and system-specific manner. We implement this functional in a plane-wave code and apply it to several physisorbed and chemisorbed molecule-metal interface systems. Our results are in quantitative agreement with experiments, both the level alignment and work function changes. Our approach constitutes a new practical scheme for accurate and efficient calculations of the electronic structure of molecule-metal interfaces.Comment: 15 pages, 8 figure

Delta Machine Learning for Predicting Dielectric Properties and Raman Spectra

We propose a machine learning method for predicting polarizabilities with the goal of providing Raman spectra from molecular dynamics trajectories at reduced computational cost. A linear-response model is used as a first step and symmetry-adapted machine learning is employed for the higher-order contributions as a second step. We investigate the performance of the approach for several systems including molecules and extended solids. The method can reduce training set sizes required for accurate dielectric properties and Raman spectra in comparison to a single-step machine learning approach

Dynamic tight binding for large-scale electronic-structure calculations of semiconductors at finite temperatures

Calculating the electronic structure of materials at finite temperatures is important for rationalizing their physical properties and assessing their technological capabilities. However, finite-temperature calculations typically require large system sizes or long simulation times. This is challenging for non-empirical theoretical methods because the involved bottleneck of performing many first-principles calculations can pose a steep computational barrier for larger systems. While machine-learning molecular dynamics enables large-scale/long-time simulations of the structural properties, the difficulty of computing in particular the electronic structure of large and disordered materials still remains. In this work, we suggest an adaptation of the tight-binding formalism which allows for computationally efficient calculations of temperature-dependent properties of semiconductors. Our dynamic tight-binding approach utilizes hybrid-orbital basis functions and a modeling of the distance dependence of matrix elements via numerical integration of atomic orbitals. We show that these design choices lead to a dynamic tight-binding model with a minimal amount of parameters which are straightforwardly optimized using density functional theory. Combining dynamic tight-binding with machine learning molecular dynamics and hybrid density functional theory, we find that it accurately describes finite-temperature electronic properties in comparison to experiment for the prototypical semiconductor gallium-arsenide

Magnetic configurations of open-shell molecules on metals: The case of CuPc and CoPc on silver

For nanostructured interfaces between open-shell molecules and metal surfaces that involve charge transfer upon adsorption, the investigation of molecular magnetic properties is an interesting yet difficult task, because in principle different magnetic configurations with distinct properties can be found. Here, we study the magnetic properties of CuPc-Ag and CoPc-Ag interfaces, which constitute interesting test cases because charge is transferred to the initially open-shell Pc molecules upon adsorption. Using hybrid density functional theory, we examine the stability of the various magnetic configurations occurring at these nanoscale interfaces, as well as for the corresponding gas-phase anions, and compare our findings to those of previous experimental studies. For CuPc-Ag, we identify a high-spin triplet configuration as the most likely configuration at the interface, whereas for CoPc-Ag a quenching of the total magnetic moment is found. Interestingly, such quenching is consistent with two distinctly different interfacial electronic configurations. These important differences in the magnetic properties of CuPc and CoPc on Ag are rationalized by variations in the interaction of their central metal atoms with the substrate. Our work facilitates a deeper understanding of the magnetic configuration and interlinked electronic-structure properties of molecule-metal interfaces. Furthermore, it highlights the necessity of an appropriate choice of methodology in tandem with a detailed evaluation of the different emerging magnetic properties