Our group works in the development and application of stateoftheart abinitio methods to systems of both fundamental and technological interest. Until 2014 the group was located at the Institut Lumière Matière, situated at the Université Claude Bernard Lyon 1, in Lyon, France. Since then we are at the Institut für Physik of the MartinLutherUniversität HalleWittenberg. We are also members of the European Theoretical Spectroscopy Facility. We are also sponsored by the following institutions: 

Highlights (all highlights)
February 04, 2019
Special issue in honor of Eberhard K.U. Gross for his 65th birthday
With this special issue of the European Physical Journal B we pay homage to the scientific career of Eberhard Kurt Ulrich (Hardy) Gross, on occasion of his 65th birthday. Hardy is one of the most influential researchers in the field of theoretical density functional theory (DFT). His significant contributions started early, already as a student of Reiner Dreizler in Frankfurt and as a postdoc with the Nobel prize laureate Walter Kohn. In those years, Hardy Gross contributed to the birth of timedependent density functional theory (TDDFT), DFT for superconductors, ensemble DFT, etc. Later, he was interested in other topics of electronic structure theory. This issue contains original contributions with topics close to Hardy’s heart (some of them already mentioned above),and is a mixture of colloquium and research papers.
This special issue has just been published in the Eur. Phys. J. B.
February 20, 2018
Local hybrid density functional for interfaces
Hybrid functionals in density functional theory are becoming the stateoftheart for the calculation of electronic properties of solids. The key of their performance is the way in which an amount of Fock exchange is mixed with semilocal exchangecorrelation functionals. We propose here a local mixing dependent on the density alone, extending the results of a previously reported functional [Phys. Rev. B 83, 035119 (2011)] to enable accurate calculations for interfaces and nanostructures. We verify that this hybrid functional has the potential to yield results of comparable quality as GW for band alignments and defects energy levels at interfaces, at the reduced cost of a hybrid density functional. This is possible as the form of the mixing is derived from GW theory, accounting for the electronic screening through its dependence on a density estimator of the local dielectric function. In contrast with other recent selfconsistent schemes for the mixing parameter, our approach does not require to calculate the dielectric function and therefore it leads to a negligible increase of the computation time.
This work has just been accepted in J. Chem. Theory Comput..
December 01, 2017
Libxc 4.0
We are happy two annouce the release of version 4.0 of libxc.
This is a library of exchangecorrelation functionals for densityfunctional theory. We are concerned with semilocal functionals (or the semilocal part of hybrid functionals), namely localdensity approximations, generalized gradient approximations, and metageneralizedgradient approximations. Currently we include around 400 functionals for the exchange, correlation, and the kinetic energy, spanning more than 50 years of research. Moreover, libxc is by now included in more than 20 codes, not only from the atomic, molecular, and solidstate physics, but also from the quantum chemistry community.
This work has just been published in Software X. The software can be downloaded here.
May 29, 2017
Predicting the stability of solids with machine learning
We perform a large scale benchmark of machine learning methods for
the prediction of the thermodynamical stability of solids. We start
by constructing a data set that comprises density functional theory
calculations of around 250000 cubic perovskite systems. This
includes all possible perovskite and antiperovskite crystals that
can be generated with elements from hydrogen to bismuth, and
neglecting rare gases and lanthanides. Incidentally, these
calculations already reveal a large number of systems (around 500)
that are thermodynamically stable, but that are not present in
crystal structure databases. Moreover, some of these phases have
unconventional compositions and define completely new families of
perovskites. This data set is then used to train and test a series
of machine learning algorithms to predict the energy distance to the convex
hull of stability. In particular, we study the performance of ridge
regression, random forests, extremely randomized trees (including
adaptive boosting), and neural networks. We find that extremely
randomized trees give the best results, achieving errors in the test
set of around 120 meV/atom when trained in 20000
prediction accuracy is not uniform across the periodic table, being
worse for firstrow elements and elements forming magnetic
compounds. Our results point to the fact that machine learning can be
successfully used to guide highthroughput density functional theory
calculations to speed up by at least a factor of 5 systematic
searches of new materials, without any degradation of the accuracy.
This work has just been accepted in Chemistry of Materials.
March 08, 2017
Highthroughput search of ternary chalcogenides for ptype transparent electrodes
Delafossite crystals are fascinating ternary oxides that have demonstrated transparent conductivity and ambipolar doping. We used a highthroughput approach based on density functional theory to find delafossite and related layered phases of composition ABX_{2}, where A and B are elements of the periodic table, and X is a chalcogen (O, S, Se, and Te). From the 15624 compounds studied in the trigonal delafossite prototype structure, 285 are within 50 meV/atom from the convex hull of stability. These compounds were further investigated using global structural prediction methods to obtain their lowestenergy crystal structure. We find 79 systems not present in the materials project database that are thermodynamically stable and crystallize in the delafossite or in closely related structures. These novel phases were then characterized by calculating their band gaps and hole effective masses. This characterization unveils a large diversity of properties, ranging from normal metals, magnetic metals, and some candidate compounds for ptype transparent electrodes.
This work has just been accepted for publication in Scientific Reports.
May 03, 2016
Prediction of a new topological crystalline insulator
Topological crystalline insulators are a type of topological insulators whose topological surface states are protected by a crystal symmetry, thus the surface gap can be tuned by applying strain or an electric field. In this paper we predicted by means of ab initio calculations a new phase of Bi which is a topological crystalline insulator characterized by a mirror Chern number nM = −2, but not a Z2 strong topological insulator. This system presents an exceptional property: at the (001) surface its Dirac cones are pinned at the surface highsymmetry points. As a consequence they are also protected by timereversal symmetry and can survive against weak disorder even if inplane mirror symmetry is broken at the surface. Taking advantage of this dual protection, we presented a strategy to tune the bandgap based on a topological phase transition unique to this system. Since the spintexture of these topological surface states reduces the backscattering in carrier transport, this effective bandengineering is expected to be suitable for electronic and optoelectronic devices with reduced dissipation.
This work has just been published in Scientific Reports.