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Register a new userLayer shift factor in layered hybrid perovskites -- univocal quantitative descriptor of composition-structure-property relationships
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Added by
Ekaterina Marchenko
Publication date
2020
fields
Physics
and research's language is
English
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Asceding interest of the scientific community in layered hybrid halide perovskites (LHHPs) as materials for innovative photovoltaic and optoelectronic applications led to unprecedented expansion of this family of compounds, reaching now several hundred refined structures. Despite the unique structural diversity of LHHPs, traditional approaches of describing their structures, such as dividing into Dion-Jacobson (DJ) or Ruddlesden-Popper (RP) phases for mostt structures are ambiguous and unquantifiable. Here, we introduced a quantitative layer shift factor (LSF) for a univocal classification and quantitative comparison of the structures. We also developed an algorithm for automatic calculation of the LSF for such structures. We demonstrate the application of the proposed approach for an analysis of correlations between LSF and band gap to reveal structure-property relationships. Our study gives a simple and useful approach to classify of either the layered perovskite-like structures or other layered compounds composed of layers of vertex-connected octahedra as a structural unit.
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ABX3 perovskites have attracted intensive research interest in recent years due to their versatile composition and superior optoelectronic properties. Their counterparts, antiperovskites (X3BA), can be viewed as electronically inverted perovskite derivatives, but they have not been extensively studied for solar applications. Therefore, understanding their composition-property relationships is crucial for future photovoltaic application. Here, taking six antiperovskite nitrides X3NA (X2+ = Mg, Ca, Sr; A3- = P, As, Sb, Bi) as an example, we investigate the effect of X- and A-sites on the electronic, dielectric, and mechanical properties from the viewpoint of the first-principles calculations. Our calculation results show that the X-site dominates the conduction band, and the A-site has a non-negligible contribution to the band edge. These findings are completely different from traditional halide perovskites. Interestingly, when changing X- or A-site elements, a linear relationship between the tolerance factor and physical quantities, such as electronic parameters, dielectric constants, and Youngs modulus, is observed. By designing the Mg3NAs1-xBix alloys, we further verify this power of the linear relationship, which provides a predictive guidance for experimental preparation of antiperovskite alloys. Finally, we make a comprehensive comparison between the antiperovskite nitrides and conventional halide perovskites for pointing out the future device applications.
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.
Emergent functionalities of structural and topological defects in ferroelectric materials underpin an extremely broad spectrum of applications ranging from domain wall electronics to high dielectric and electromechanical responses. Many of these have been discovered and quantified via local scanning probe microscopy methods. However, the search for these functionalities has until now been based by either trial and error or using auxiliary information such as topography or domain wall structure to identify potential objects of interest based on the intuition of operator or preexisting hypotheses, with subsequent manual exploration. Here, we report the development and implementation of a machine learning framework that actively discovers relationships between local domain structure and polarization switching characteristics in ferroelectric materials encoded in the hysteresis loop. The latter and descriptors such as nucleation bias, coercive bias, hysteresis loop area, or more complex functionals of hysteresis loop shape and corresponding uncertainties are used to guide the discovery via automated piezoresponse force microscopy (PFM) and spectroscopy experiments. As such, this approach combines the power of machine learning methods to learn the correlative relationships between high dimensional data, and human-based physics insights encoded in the acquisition function. For ferroelectric, this automated workflow demonstrates that the discovery path and sampling points of on-field and off-field hysteresis loops are largely different, indicating the on-field and off-field hysteresis loops are dominated by different mechanisms. The proposed approach is universal and can be applied to a broad range of modern imaging and spectroscopy methods ranging from other scanning probe microscopy modalities to electron microscopy and chemical imaging.
Behaving like atomically-precise two-dimensional quantum wells with non-negligible dielectric contrast, the layered HOIPs have strong electronic interactions leading to tightly bound excitons with binding energies on the order of 500 meV. These strong interactions suggest the possibility of larger excitonic complexes like trions and biexcitons, which are hard to study numerically due to the complexity of the layered HOIPs. Here, we propose and parameterize a model Hamiltonian for excitonic complexes in layered HOIPs and we study the correlated eigenfunctions of trions and biexcitons using a combination of diffusion Monte Carlo and very large variational calculations with explicitly correlated Gaussian basis functions. Binding energies and spatial structures of these complexes are presented as a function of the layer thickness. The trion and biexciton of the thinnest layered HOIP have binding energies of 35 meV and 44 meV, respectively, whereas a single exfoliated layer is predicted to have trions and biexcitons with equal binding enegies of 48 meV. We compare our findings to available experimental data and to that of other quasi-two-dimensional materials.
Materials combining the optoelectronic functionalities of semiconductors with control of the spin degree of freedom are highly sought after for the advancement of quantum technology devices. Here, we report the paramagnetic Ruddlesden-Popper hybrid perovskite Mn:(PEA)2PbI4 (PEA = phenethylammonium) in which the interaction of isolated Mn2+ ions with magnetically brightened excitons leads to circularly polarized photoluminescence. Using a combination of superconducting quantum interference device (SQUID) magnetometry and magneto-optical experiments, we find that the Brillouin-shaped polarization curve of the photoluminescence follows the magnetization of the material. This indicates coupling between localized manganese magnetic moments and exciton spins via a magnetic proximity effect. The saturation polarization of 15% at 4 K and 6 T indicates a highly imbalanced spin population and demonstrates that manganese doping enables efficient control of excitonic spin states in Ruddlesden-Popper perovskites. Our finding constitutes the first example of polarization control in magnetically doped hybrid perovskites and will stimulate research on this highly tuneable material platform that promises tailored interactions between magnetic moments and electronic states.
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