2,314 research outputs found

    Vectorial formalism for analysis and design of polyphase synchronous machines

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    A vectorial formalism for analysis and design of polyphase synchronous machines without reluctance and saturation effects is described. We prove the equivalence of such a machine with a set of magnetically independent machines, which are electrically and mechanically coupled. Specific problems of polyphase machines can thus be favorably analyzed with this concept. Rules of conception and constraints on electric supply can be deduced. Moreover the vectorial approach, which generalizes the complex phasor method, can also be used to control n-leg Voltage Source Inverters. This methodology is applied to 3-phase and 6- phase synchronous machines

    Convergence and pitfalls of density functional perturbation theory phonons calculations from a high-throughput perspective

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    The diffusion of large databases collecting different kind of material properties from high-throughput density functional theory calculations has opened new paths in the study of materials science thanks to data mining and machine learning techniques. Phonon calculations have already been employed successfully to predict materials properties and interpret experimental data, e.g. phase stability, ferroelectricity and Raman spectra, so their availability for a large set of materials will further increase the analytical and predictive power at hand. Moving to a larger scale with density functional perturbation calculations, however, requires the presence of a robust framework to handle this challenging task. In light of this, we automatized the phonon calculation and applied the result to the analysis of the convergence trends for several materials. This allowed to identify and tackle some common problems emerging in this kind of simulations and to lay out the basis to obtain reliable phonon band structures from high-throughput calculations, as well as optimizing the approach to standard phonon simulations

    Influence of the "second gap" on the transparency-conductivity compromise in transparent conducting oxides: an ab initio study

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    Transparent conducting oxides (TCOs) are essential to many technologies. These materials are doped (\emph{n}- or \emph{p}-type) oxides with a large enough band gap (ideally >>3~eV) to ensure transparency. However, the high carrier concentration present in TCOs lead additionally to the possibility for optical transitions from the occupied conduction bands to higher states for \emph{n}-type materials and from lower states to the unoccupied valence bands for \emph{p}-type TCOs. The "second gap" formed by these transitions might limit transparency and a large second gap has been sometimes proposed as a design criteria for high performance TCOs. Here, we study the influence of this second gap on optical absorption using \emph{ab initio} computations for several well-known \emph{n}- and \emph{p}-type TCOs. Our work demonstrates that most known \emph{n}-type TCOs do not suffer from second gap absorption in the visible even at very high carrier concentrations. On the contrary, \emph{p}-type oxides show lowering of their optical transmission for high carrier concentrations due to second gap effects. We link this dissimilarity to the different chemistries involved in \emph{n}- versus typical \emph{p}-type TCOs. Quantitatively, we show that second gap effects lead to only moderate loss of transmission (even in p-type TCOs) and suggest that a wide second gap, while beneficial, should not be considered as a needed criteria for a working TCO.Comment: 6 pages, 4 figures, APS March Meetin

    MODNet -- accurate and interpretable property predictions for limited materials datasets by feature selection and joint-learning

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    In order to make accurate predictions of material properties, current machine-learning approaches generally require large amounts of data, which are often not available in practice. In this work, an all-round framework is presented which relies on a feedforward neural network, the selection of physically-meaningful features and, when applicable, joint-learning. Next to being faster in terms of training time, this approach is shown to outperform current graph-network models on small datasets. In particular, the vibrational entropy at 305 K of crystals is predicted with a mean absolute test error of 0.009 meV/K/atom (four times lower than previous studies). Furthermore, joint-learning reduces the test error compared to single-target learning and enables the prediction of multiple properties at once, such as temperature functions. Finally, the selection algorithm highlights the most important features and thus helps understanding the underlying physics.Comment: 5 pages, 2 figure

    High-Throughput Identification of Electrides from all Known Inorganic Materials

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    In this paper, we present the results of a large-scale, high-throughput computational search for electrides among all known inorganic materials. Analyzing a database of density functional theory results on more than 60,000 compounds, we identify 69 new electride candidates. We report on all these candidates and discuss the structural and chemical factors leading to electride formation. Among these candidates, our work identifies the first partially-filled 3d transition metal containing electrides Ba3CrN3 and Sr3CrN3; an unexpected finding that contravenes conventional chemistry.Comment: 5 page manuscript in letter format, 27 page Supplementary Informatio

    Low-Dimensional Transport and Large Thermoelectric Power Factors in Bulk Semiconductors by Band Engineering of Highly Directional Electronic States

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    Thermoelectrics are promising to address energy issues but their exploitation is still hampered by low efficiencies. So far, much improvement has been achieved by reducing the thermal conductivity but less by maximizing the power factor. The latter imposes apparently conflicting requirements on the band structure: a narrow energy distribution and a low effective mass. Quantum confinement in nanostructures or the introduction of resonant states were suggested as possible solutions to this paradox but with limited success. Here, we propose an original approach to fulfill both requirements in bulk semiconductors. It exploits the highly-directional character of some orbitals to engineer the band-structure and produce a type of low-dimensional transport similar to that targeted in nanostructures, while retaining isotropic properties. Using first-principles calculations, the theoretical concept is demonstrated in Fe2_2YZ Heusler compounds, yielding power factors 4-5 times larger than in classical thermoelectrics at room temperature. Our findings are totally generic and rationalize the search of alternative compounds with a similar behavior. Beyond thermoelectricity, these might be relevant also in the context of electronic, superconducting or photovoltaic applications.Comment: 6 pages, 2 figure

    Automation methodologies and large-scale validation for GWGW, towards high-throughput GWGW calculations

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    The search for new materials, based on computational screening, relies on methods that accurately predict, in an automatic manner, total energy, atomic-scale geometries, and other fundamental characteristics of materials. Many technologically important material properties directly stem from the electronic structure of a material, but the usual workhorse for total energies, namely density-functional theory, is plagued by fundamental shortcomings and errors from approximate exchange-correlation functionals in its prediction of the electronic structure. At variance, the GWGW method is currently the state-of-the-art {\em ab initio} approach for accurate electronic structure. It is mostly used to perturbatively correct density-functional theory results, but is however computationally demanding and also requires expert knowledge to give accurate results. Accordingly, it is not presently used in high-throughput screening: fully automatized algorithms for setting up the calculations and determining convergence are lacking. In this work we develop such a method and, as a first application, use it to validate the accuracy of G0W0G_0W_0 using the PBE starting point, and the Godby-Needs plasmon pole model (G0W0GNG_0W_0^\textrm{GN}@PBE), on a set of about 80 solids. The results of the automatic convergence study utilized provides valuable insights. Indeed, we find correlations between computational parameters that can be used to further improve the automatization of GWGW calculations. Moreover, we find that G0W0GNG_0W_0^\textrm{GN}@PBE shows a correlation between the PBE and the G0W0GNG_0W_0^\textrm{GN}@PBE gaps that is much stronger than that between GWGW and experimental gaps. However, the G0W0GNG_0W_0^\textrm{GN}@PBE gaps still describe the experimental gaps more accurately than a linear model based on the PBE gaps.Comment: 12 pages, 11 figure

    First-principles study of intrinsic and hydrogen point defects in the earth-abundant photovoltaic absorber Zn3P2

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    Zinc phosphide (Zn3P2) has had a long history of scientific interest largely because of its potential for earth-abundant photovoltaics. To realize high-efficiency Zn3P2 solar cells, it is critical to understand and control point defects in this material. Using hybrid functional calculations, we assess the energetics and electronic behavior of intrinsic point defects and hydrogen impurities in Zn3P2. All intrinsic defects are found to act as compensating centers in p-type Zn3P2 and have deep levels in the band gap, except for zinc vacancies which are shallow acceptors and can act as a source of doping. Our work highlights that zinc vacancies rather than phosphorus interstitials are likely to be the main source of p-type doping in as-grown Zn3P2. We also show that Zn-poor and P-rich growth conditions, which are usually used for enhancing p-type conductivity of Zn3P2, will facilitate the formation of certain deep-level defects (P_Zn and P_i) which might be detrimental to solar cell efficiency. For hydrogen impurities, which are frequently present in the growth environment of Zn3P2, we study interstitial hydrogen and hydrogen complexes with vacancies. The results suggest small but beneficial effects of hydrogen on the electrical properties of Zn3P2
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