RESUMEN
Transparent conducting oxides have become ubiquitous in modern optoelectronics. However, the number of oxides that are transparent to visible light and have the metallic-like conductivity necessary for applications is limited to a handful of systems that have been known for the past 40 years. In this work, we use hybrid density functional theory and defect chemistry analysis to demonstrate that tri-rutile zinc antimonate, ZnSb2O6, is an ideal transparent conducting oxide and to identify gallium as the optimal dopant to yield high conductivity and transparency. To validate our computational predictions, we have synthesized both powder samples and single crystals of Ga-doped ZnSb2O6 which conclusively show behavior consistent with a degenerate transparent conducting oxide. This study demonstrates the possibility of a family of Sb(V)-containing oxides for transparent conducting oxide and power electronics applications.
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Invited for this month's cover are researchers from Bundesanstalt für Materialforschung und -prüfung (Federal Institute for Materials Research and Testing) in Germany, Friedrich Schiller University Jena, Université catholique de Louvain, University of Oregon, Science & Technology Facilities Council, RWTH Aachen University, Hoffmann Institute of Advanced Materials, and Dartmouth College. The cover picture shows a workflow for automatic bonding analysis with Python tools (green python). The bonding analysis itself is performed with the program LOBSTER (red lobster). The starting point is a crystal structure, and the results are automatic assessments of the bonding situation based on Crystal Orbital Hamilton Populations (COHP), including automatic plots and text outputs. Coordination environments and charges are also assessed. More information can be found in the Research Article by J. George, G. Hautier, and co-workers.
RESUMEN
Understanding crystalline structures based on their chemical bonding is growing in importance. In this context, chemical bonding can be studied with the Crystal Orbital Hamilton Population (COHP), allowing for quantifying interatomic bond strength. Here we present a new set of tools to automate the calculation of COHP and analyze the results. We use the program packages VASP and LOBSTER, and the Python packages atomate and pymatgen. The analysis produced by our tools includes plots, a textual description, and key data in a machine-readable format. To illustrate those capabilities, we have selected simple test compounds (NaCl, GaN), the oxynitrides BaTaO2 N, CaTaO2 N, and SrTaO2 N, and the thermoelectric material Yb14 Mn1 Sb11 . We show correlations between bond strengths and stabilities in the oxynitrides and the influence of the Mn-Sb bonds on the magnetism in Yb14 Mn1 Sb11 . Our contribution enables high-throughput bonding analysis and will facilitate the use of bonding information for machine learning studies.
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We present an in-depth first-principles study of the lattice dynamics of the tin sulphides SnS2, Pnma and π-cubic SnS and Sn2S3. An analysis of the harmonic phonon dispersion and vibrational density of states reveals phonon bandgaps between low- and high-frequency modes consisting of Sn and S motion, respectively, and evidences a bond-strength hierarchy in the low-dimensional SnS2, Pnma SnS and Sn2S3 crystals. We model and perform a complete characterisation of the infrared and Raman spectra, including temperature-dependent anharmonic linewidths calculated using many-body perturbation theory. We illustrate how vibrational spectroscopy could be used to identify and characterise phase impurities in tin sulphide samples. The spectral linewidths are used to model the thermal transport, and the calculations indicate that the low-dimensional Sn2S3 has a very low lattice thermal conductivity, potentially giving it superior performance to SnS as a candidate thermoelectric material.
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Forming a four-component compound from the first 103 elements of the periodic table results in more than 1012 combinations. Such a materials space is intractable to high-throughput experiment or first-principle computation. We introduce a framework to address this problem and quantify how many materials can exist. We apply principles of valency and electronegativity to filter chemically implausible compositions, which reduces the inorganic quaternary space to 1010 combinations. We demonstrate that estimates of band gaps and absolute electron energies can be made simply on the basis of the chemical composition and apply this to the search for new semiconducting materials to support the photoelectrochemical splitting of water. We show the applicability to predicting crystal structure by analogy with known compounds, including exploration of the phase space for ternary combinations that form a perovskite lattice. Computer screening reproduces known perovskite materials and predicts the feasibility of thousands more. Given the simplicity of the approach, large-scale searches can be performed on a single workstation.
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The unusual chemistry of sulfur is illustrated by the tendency for catenation. Sulfur forms a range of open and closed S n species in the gas phase, which has led to speculation on the composition of sulfur vapours as a function of temperature and pressure for over a century. Unlike elemental gases such as O2 and N2, there is no widely accepted thermodynamic potential for sulfur. Here we combine a first-principles global structure search for the low energy clusters from S2 to S8 with a thermodynamic model for the mixed-allotrope system, including the Gibbs free energy for all gas-phase sulfur on an atomic basis. A strongly pressure-dependent transition from a mixture dominant in S2 to S8 is identified. A universal chemical potential function, µS(T,P), is proposed with wide utility in modelling sulfurisation processes including the formation and annealing of metal chalcogenide semiconductors.
RESUMEN
Correction for 'A universal chemical potential for sulfur vapours' by Adam J. Jackson et al., Chem. Sci., 2016, 7, 1082-1092.
RESUMEN
Standard procedures for local crystal-structure optimisation involve numerous energy and force calculations. It is common to calculate an energy-volume curve, fitting an equation of state around the equilibrium cell volume. This is a computationally intensive process, in particular, for low-symmetry crystal structures where each isochoric optimisation involves energy minimisation over many degrees of freedom. Such procedures can be prohibitive for non-local exchange-correlation functionals or other "beyond" density functional theory electronic structure techniques, particularly where analytical gradients are not available. We present a simple approach for efficient optimisation of crystal structures based on a known equation of state. The equilibrium volume can be predicted from one single-point calculation and refined with successive calculations if required. The approach is validated for PbS, PbTe, ZnS, and ZnTe using nine density functionals and applied to the quaternary semiconductor Cu2ZnSnS4 and the magnetic metal-organic framework HKUST-1.
