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We propose perovskite nitrides with magnetic rare-earth metals as novel materials with a range of technological applications. These materials appear to be thermodynamically stable and, in spite of possessing different crystal structures and different atomic environments, they retain the magnetic moment of the corresponding elemental rare-earth metal. We find both magnetic metals and semiconductors, with a wide range of magnetic moments and some systems posses record high magnetic anisotropy energies. Further tuning of the electronic and magnetic properties can also be expected by doping with other rare-earths or by creating solid solutions. The synthesis of these exotic materials with unusual compositions would not only extend the accepted stability domain of perovskites, but also open the way for a series of applications enabled by their rich physics.

The question of material stability is of fundamental importance to any analysis of system properties in condensed matter physics and materials science. The ability to evaluate chemical stability, i.e., whether a stoichiometry will persist in some chemical environment, and structure selection, i.e. what crystal structure a stoichiometry will adopt, is critical to the prediction of materials synthesis, reactivity and properties. Here, we demonstrate that density functional theory, with the recently developed strongly constrained and appropriately normed (SCAN) functional, has advanced to a point where both facets of the stability problem can be reliably and efficiently predicted for main group compounds, while transition metal compounds are improved but remain a challenge. SCAN therefore offers a robust model for a significant portion of the periodic table, presenting an opportunity for the development of novel materials and the study of fine phase transformations even in largely unexplored systems with little to no experimental data.

The dream of any solid-state theorist is to be able to predict new materials with tailored properties from scratch, i.e., without any input from experiment. Over the past decades, we have steadily approached this goal. Recent developments in the field of high-throughput calculations focused on finding the best material for specific applications. However, a key input for these techniques still had to be obtained experimentally, namely, the crystal structure of the materials. Here, we give a step further and show that one can indeed optimize material properties using as a single starting point the knowledge of the periodic table and the fundamental laws of quantum mechanics. This is done by combining state-of-the-art methods of global structure prediction that allow us to obtain the ground-state crystal structure of arbitrary materials, with an evolutionary algorithm that optimizes the chemical composition for the desired property. As a first showcase demonstration of our method, we perform an unbiased search for superhard materials and for transparent conductors. We stress that our method is completely general and can be used to optimize any property (or combination of properties) that can be calculated in a computer.

International audience; Despite more than 50 years of investigation, the understanding of the metal-insulator transition in $VO_2$ remains incomplete and requires additional experimental and theoretical works. Using Raman scattering under pressure, we first confirm the known transition around 11 GPa affecting the V orbital occupancy in the absence of structural changes. Moreover, we disclose a transition around 19 GPa involving the V orbitals together with a structural distortion, revealed by the splitting of a phonon branch associated with the V chains. The high-pressure metallic $X$ phase is found to be of low symmetry and becomes the lowest-enthalpy structure at high pressure by ab initio structural prediction calculations. In contrast to a well-established picture of the metal-insulator transition (i.e., the Peierls transition), the high-pressure metallic phase here is of lower symmetry than the ambient pressure insulating phase.

International audience; We employed ab initio global structural prediction algorithms to obtain the ground-state structure of CuBO2 This is a very promising p-type transparent conductive oxide that was synthesized recently, and thought to belong to the delafossite family. We proved that the true ground state is certainly not the delafossite structure, and that the most promising candidate is a low symmetry monoclinic phase. This is still a layered structure, but with boron and copper having a different coordination with respect to the delafossite phase.

The GCMC simulation of CO 2 adsorption in MOF-5 is revisited, finding a surprising role of the BDC organic ligand in this process. A novel structure partition methodology is introduced to decompose the relative contributions of the metal oxoclusters and the organic ligands. The origin of the primary step in the CO 2 adsorption isotherm in MOF-5 is explained by a synergistic effect arising from specific short-range interactions between the sorbate and the MOF components with equal contributions from both the metal oxocluster and the organic ligand, together with an additional contribution due to the nano-confinement of the adsorbate.

We present an ab initio study of the phase diagram of the Li–Si binary system using the minima hopping method for global structural prediction. By varying the chemical composition we obtained the theoretical convex hull, whose vertices are constituted by three stoichiometries, two of them have not been reported previously. Additionally, we find five more unreported meta-stable structures, which are slightly higher in energy with respect to the convex hull line. We further characterize all these obtained phases by calculating their electronic, mechanical, and dynamical properties. Finally, and as this class of systems is viewed with interest for possible anodes in lithium batteries, we also report the potential–composition curve and compare it with available experimental measurements.

Thermodynamically stable nitride perovskites (ABN3) are predicted in the ground state based on a combination of high-throughput techniques and global structural prediction methods.

Self-consistent $GW$ calculations and the solution of the Bethe-Salpeter equation are to date the best available approaches to simulate electronic excitations in a vast class of materials, ranging from molecules to solids. However, up to now numerical instabilities made it impossible to use these techniques to calculate optical absorption spectra of the best-known thin-film absorbers for solar cells: ${\mathrm{Cu}(\mathrm{In},\mathrm{Ga})(\mathrm{S},\mathrm{Se})}_{2}$ chalcopyrites and ${\mathrm{Cu}}_{2}{\mathrm{ZnSn}(\mathrm{S},\mathrm{Se})}_{4}$ kesterites/stannites. We show here how to solve this problem using a finite-difference method in $k$ space to evaluate the otherwise diverging dipole matrix elements, obtaining an excellent agreement with experiments. Having established the validity of this approach, we use it then to calculate the optical response of the less studied, but promising, ${\mathrm{Cu}}_{2}{\mathrm{ZnGe}(\mathrm{S},\mathrm{Se})}_{4}$ compounds, opening the way to predictive calculations of still unknown materials.

Perovskites are one of the most studied classes of materials, with a variety of applications in diverse fields of science and technology. Their basic composition is ABX3, where X is a nonmetal normally from the VIA or VIIA group. In this article we investigate the possibility of the existence of perovskites with X = N. Our approach is based on a combination of high-throughput techniques and global structural prediction methods. We find 21 new compositions of the form ABN3 that are thermodynamically stable (considering all possible decomposition channels) and that have therefore excellent chances of being experimentally accessible. Most of these materials crystallize in monoclinic phases, but three compounds, namely, LaReN3, LaWN3, and YReN3, are predicted to have distorted perovskite structures in their ground state. In particular, LaWN3 is a semiconductor and displays a large ferroelectric polarization. The addition of nitride compounds to the perovskite family poses numerous questions related to the che...

We present a semiempirical exchange-correlation functional for density functional theory tailored to calculate energies of formation of solids. It has the same form of a Perdew-Burke-Ernzerhof functional, but three parameters have been fitted to reproduce experimental energies of formation of a representative set of binaries. The quality of the obtained functional has then been assessed for a control set of binary and ternary compounds. Our functional succeeds in reducing the error of the Perdew-Burke-Ernzerhof generalized gradient approximation for energies of formation by a factor of 2. Furthermore, this result is achieved preserving the quality of the optimized geometry.

Structural and electronic properties of Cu(In,Ga)S2 (CIGS) alloys as a function of the In/Ga ratio are studied by combining near edge X-ray absorption fine structure and extended X-ray absorption fine structure spectroscopy with density functional theory calculations. While the S absorption edge shifts with the change of the In/Ga ratio, consistently with the corresponding variation of the band gap, the edges of the other elements are largely independent of composition. Our calculations reproduce this behavior and identify its origin in the dependence of the electronic properties on the local atomic environment. These results point to the importance of an accurate atomic-scale description of the structure of this family of alloys for reliable calculations of their electronic properties., S.B. acknowledges financial support from the French ANR project ANR-12-BS04-0001-02. AR acknowledge financial support from the European Research Council Advanced Grant DY-Namo (ERC-2010-AdG-267374), Spanish Grant (FIS2010-21282-C02-01) and Grupos Consolidados UPV/EHU del Gobierno Vasco (IT-578-13). C.S.S. was supported by the Carl-Zeiss-Stiftung Germany and by the German BMU in the framework of the comCIGS-II project. Computational resources were provided by GENCI (project x2013096017).

PARAFAC analysis of time-varying EEG spectra data provides a parsimonious representation in terms of topographic, temporal and spectral signatures, which allows for the identification of functional neural networks. This networks work in a critical state where short and long range connections coexist. Although PARAFAC is unique through usual least squares estimation, the use of penalized least squares allows to incorporate this kind of knowledge into the decomposition. Here we propose the use of Information Entropy-based penalties for obtaining atoms with minimum spectral entropy. They offer sparse spectral signatures corresponding to networks oscillating in a well-defined (sharp) frequency band.

International audience; Intermetallic Li–Al compounds are on the one hand key materials for light-weight engineering, and on the other hand, they have been proposed for high-capacity electrodes for Li batteries. We determine from first-principles the phase diagram of Li–Al binary crystals using the minima hopping structural prediction method. Beside reproducing the experimentally reported phases (LiAl, Li3Al2, Li9Al4, LiAl3, and Li2Al), we unveil a structural variety larger than expected by discovering six unreported binary phases likely to be thermodynamically stable. Finally, we discuss the behavior of the elastic constants and of the electric potential profile of all Li–Al stable compounds as a function of their stoichiometry.