A5074073454- Machine Learning in Materials Science
- Quantum Dots Synthesis And Properties
- Chalcogenide Semiconductor Thin Films
- Copper-based nanomaterials and applications
- Advanced Chemical Physics Studies
- Semiconductor materials and interfaces
- Graphene research and applications
- Silicon Nanostructures and Photoluminescence
- Nanowire Synthesis and Applications
- 2D Materials and Applications
- Electronic and Structural Properties of Oxides
- Boron and Carbon Nanomaterials Research
- ZnO doping and properties
- X-ray Diffraction in Crystallography
- Inorganic Chemistry and Materials
- High-pressure geophysics and materials
- Semiconductor materials and devices
- Perovskite Materials and Applications
- Diamond and Carbon-based Materials Research
- Semiconductor Quantum Structures and Devices
- Ga2O3 and related materials
- Advanced Thermoelectric Materials and Devices
- Spectroscopy and Quantum Chemical Studies
- Superconductivity in MgB2 and Alloys
- Carbon Nanotubes in Composites
European Theoretical Spectroscopy Facility
2013-2024
Friedrich Schiller University Jena
2015-2024
Ruhr University Bochum
2023-2024
Lund University
2021
Eindhoven University of Technology
2021
École Polytechnique Fédérale de Lausanne
2020
Martin Luther University Halle-Wittenberg
2018
Université Claude Bernard Lyon 1
2008-2017
Centre National de la Recherche Scientifique
2008-2017
Institut Lumière Matière
2012-2017
Abstract One of the most exciting tools that have entered material science toolbox in recent years is machine learning. This collection statistical methods has already proved to be capable considerably speeding up both fundamental and applied research. At present, we are witnessing an explosion works develop apply learning solid-state systems. We provide a comprehensive overview analysis research this topic. As starting point, introduce principles, algorithms, descriptors, databases...
A very popular ab initio scheme to calculate electronic properties in solids is the use of hybrid functionals density functional theory (DFT) that mixes a portion Fock exchange with DFT functionals. In spite its success, major problem still remains, related one single mixing parameter for all materials. Guided by physical arguments connect dielectric solid, and ultimately band gap, we propose method this from alone. This approach able cut significantly error traditional large small gap...
Through a systematic structural search we found an allotrope of carbon with Cmmm symmetry which predict to be more stable than graphite for pressures above 10 GPa. This material, refer as Z-carbon, is formed by pure sp(3) bonds and it provides explanation several features in experimental x-ray diffraction Raman spectra under pressure. The transition from Z-carbon can occur through simple sliding buckling graphene sheets. Our calculations that transparent wide band-gap semiconductor hardness...
<italic>Ab initio</italic> high-throughput materials screening of inorganic perovskites yields candidates for applications in photovoltaics, ferroelectrics, magnetoelectrics, and as transparent contacts.
We perform a large scale benchmark of machine learning methods for the prediction thermodynamic stability solids. start by constructing data set that comprises density functional theory calculations around 250000 cubic perovskite systems. This includes all possible and antiperovskite crystals can be generated with elements from hydrogen to bismuth, excluding rare gases lanthanides. Incidentally, these already reveal number systems (around 500) are thermodynamically stable but not present in...
Abstract We conducted a large-scale density-functional theory study on the influence of exchange-correlation functional in calculation electronic band gaps solids. First, we use large materials data set that have recently proposed to benchmark 21 different functionals, with particular focus approximations meta-generalized-gradient family. Combining these results for 12 functionals our previous work, can analyze detail characteristics each approximation and identify its strong and/or weak...
We compile a large data set designed for the efficient benchmarking of exchange-correlation functionals calculation electronic band gaps. The comprises information on experimental structure and gap 472 nonmagnetic materials includes diverse group covalent-, ionic-, van der Waals-bonded solids. used it to benchmark 12 functionals, ranging from standard local semilocal passing through meta-generalized-gradient approximations, several hybrids. included both general purpose like...
Abstract In recent years, we have been witnessing a paradigm shift in computational materials science. fact, traditional methods, mostly developed the second half of XXth century, are being complemented, extended, and sometimes even completely replaced by faster, simpler, often more accurate approaches. The new approaches, that collectively label machine learning, their origins fields informatics artificial intelligence, but making rapid inroads all other branches With this mind, Roadmap...
Hydrogen-rich superconductors are promising candidates to achieve room-temperature superconductivity. However, the extreme pressures needed stabilize these structures significantly limit their practical applications. An effective strategy reduce external pressure is add a light element M that binds with H form ${\mathrm{MH}}_{x}$ units, acting as chemical precompressor. We exemplify this idea by performing ab initio calculations of Ac--Be--H phase diagram, proving metallization Ac--H...
For the calculation of neutral excitations, time-dependent density functional theory (TDDFT) is an exact reformulation many-body Schrödinger equation, based on knowledge instead wavefunction. The can be determined in efficient scheme by solving one-particle non-interacting equations—the Kohn–Sham equations. complication problem hidden the—unknown—time-dependent exchange and correlation potential that appears equations for which it essential to find good approximations. Many approximations...
We discuss the effects of a static long-range contribution $\ensuremath{-}\ensuremath{\alpha}{/q}^{2}$ to exchange-correlation kernel ${f}_{\mathrm{xc}}(\mathbf{q})$ time-dependent density functional theory. show that optical absorption spectrum solids exhibiting strong continuum excitonic effect is considerably improved with respect calculations where adiabatic local-density approximation used. limitations this simple approach, and in particular same improvement cannot be found for whole...
Several chalcogenide alloys exhibit a pronounced contrast between the optical absorption in metastable rocksalt and amorphous phase. This phenomenon is basis for their application data storage. Here we present ab initio calculations of properties GeTe ${\mathrm{Ge}}_{1}{\mathrm{Sb}}_{2}{\mathrm{Te}}_{4}$ two phases. The analysis our computations experimental reveal correlation local structural changes as well origin these materials. We find that change cannot be attributed to smearing...
We present state-of-the-art first-principles calculations of the electronic and optical properties silicon allotropes with interesting characteristics for applications in thin-film solar cells. These new phases consist distorted $s{p}^{3}$ networks have a lower formation energy than other experimentally produced phases. Some these structures turned out to quasidirect dipole-allowed band gaps range 0.8--1.5 eV, display absorption coefficients comparable those chalcopyrites used record
We present a first-principles study of the electronic properties CuIn(S,Se){2} (CIS) using state-of-the-art self-consistent GW and hybrid functionals. The calculated band gap depends strongly on anion displacement u, an internal structural parameter that measures lattice distortion. This contrasts with observed stability CIS solar panels under operating conditions, where relatively large dispersion values for u occurs. solve this apparent paradox considering coupled effect copper vacancies...
Perovskites are one of the most studied classes materials, with a variety applications in diverse fields science and technology. Their basic composition is ABX3, where X nonmetal normally from VIA or VIIA group. In this article we investigate possibility existence perovskites = N. Our approach based on combination high-throughput techniques global structural prediction methods. We find 21 new compositions form ABN3 that thermodynamically stable (considering all possible decomposition...
We calculate the band structures of kesterite and stannite Cu2ZnSnS4 Cu2ZnSnSe4, using a state-of-the-art self-consistent GW approach. Our accurate quasiparticle states allow to discuss: dependence gap on anion displacement; key-role nonlocality exchange-correlation potential obtain good structural parameters; reliability less expensive hybrid functional generalized gradient approximation+U approaches. In particular, we show that even if is correctly reproduced by functionals, band-edge...
We study the electronic and optical properties of 39 small molecules containing transition metal atoms 7 others related to quantum-dots for photovoltaics. explore in particular merits many-body GW formalism, as compared ΔSCF approach within density functional theory, description ionization energy affinity. Mean average errors 0.2–0.3 eV with respect experiment are found when using PBE0 a starting point GW. The effect partial self-consistency at level is explored. Further, excitations,...
A recent study associates carbon with single photon emitters (SPEs) in hexagonal boron nitride (h-BN). This observation, together the high mobility of h-BN, suggests existence SPEs based on clusters. Here, by means density functional theory calculations, we studied clusters substitutional atoms up to tetramers h-BN. Two different conformations neutral trimers have zero-point line energies and shifts phonon sideband compatible typical photoluminescence spectra. Moreover, some two small C next...
Crystal graph attention networks speed up the prediction of new thermodynamically stable materials in high-throughput searches.
Abstract We propose an efficient high-throughput scheme for the discovery of stable crystalline phases. Our approach is based on transmutation known compounds, through substitution atoms in crystal structure with chemically similar ones. The concept similarity defined quantitatively using a measure chemical replaceability, extracted by data-mining experimental databases. In this way we build 189,981 possible phases, including 18,479 that are convex hull stability. resulting success rate...
Crystal-graph attention neural networks have emerged recently as remarkable tools for the prediction of thermodynamic stability. The efficacy their learning capabilities and reliability is however subject to quantity quality data they are fed. Previous exhibit strong biases due inhomogeneity training data. Here a high-quality dataset engineered provide better balance across chemical crystal-symmetry space. trained with this show unprecedented generalization accuracy. Such applied perform...
The Open Databases Integration for Materials Design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability materials chemical data. Since first release OPTIMADE specification (v1.0), API has undergone significant development, leading v1.2 release, underpinned multiple scientific studies. In this work, we highlight latest features format, accompanying software tools, provide...
Abstract Silicon is indisputably the most advanced material for scalable electronics, but it a poor choice as light source photonic applications, due to its indirect band gap. The recently developed hexagonal Si 1− x Ge semiconductor features direct bandgap at least > 0.65, and realization of quantum heterostructures would unlock new opportunities optoelectronic devices based on SiGe system. Here, we demonstrate synthesis characterization wells realized in Photoluminescence experiments...