en:
We probe the accuracy limit of ab initio calculations of carrier mobilities in semiconductors, within the framework of the Boltzmann transport equation. By focusing on the paradigmatic case of silicon, we show
that fully predictive calculations of electron and hole mobilities require many-body quasiparticle corrections to band structures and electron-phonon matrix elements, the inclusion of spin-orbit coupling, and an extremely fine sampling of inelastic scattering processes in momentum space. By considering all these factors we obtain excellent agreement with experiment, and we identify the band effective masses as the most critical parameters to achieve predictive accuracy. Our findings set a blueprint for future calculations of carrier mobilities, and pave the way to engineering transport properties in semiconductors by design.

en: Towards predictive many-body calculations of phonon-limited carrier mobilities in semiconductors

ab-initio-calculations

display_name: ab-initio-calculations

electrical-conductivity

display_name: electrical-conductivity

electron-phonon-coupling

display_name: electron-phonon-coupling

lattice-dynamics

display_name: lattice-dynamics

many-body-techniques

display_name: many-body-techniques

prace

display_name: prace

transport-phenomena

display_name: transport-phenomena

wannier-function-methods

display_name: wannier-function-methods


$oid: OBSOLETE

materialscloud

approval_status: approved

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


en:
The EPW (Electron-Phonon coupling using Wannier functions) software is a Fortran90 code that uses density-functional perturbation theory and maximally localized Wannier functions for computing
electron-phonon couplings and related properties in solids accurately and efficiently. The EPW v4 program can be used to compute electron and phonon self-energies, linewidths, electron-phonon scattering
rates, electron-phonon coupling strengths, transport spectral functions, electronic velocities, resistivity, anisotropic superconducting gaps and spectral functions within the Migdal-Eliashberg theory. The
code now supports spin-orbit coupling, time-reversal symmetry in non-centrosymmetric crystals, polar materials, and k and q-point parallelization. Considerable effort was dedicated to optimization and
parallelization, achieving almost a ten times speedup with respect to previous releases. A computer test farm was implemented to ensure stability and portability of the code on the most popular compilers
and architectures. Since April 2016, version 4 of the EPW code is fully integrated in and distributed with the Quantum ESPRESSO package, and can be downloaded through at https://gitlab.com/QEF/q-e

en: EPW: Electron-phonon coupling, transport and superconducting properties using maximally localized Wannier functions

electronic-transport

display_name: electronic-transport

superconductivity

display_name: superconductivity

wannier-functions

display_name: wannier-functions


en: High-strength metal alloys achieve their performance via careful control of precipitates and solutes. The nucleation, growth, and kinetics of precipitation, and the resulting mechanical properties, are inherently atomic-scale phenomena, particularly during early-stage nucleation and growth. Atomistic modeling using interatomic potentials is a desirable tool for understanding the detailed phenomena involved in precipitation and strengthening, which requires length and time scales far larger than those accessible by first-principles methods. Current interatomic potentials for alloys are not, however, sufficiently accurate for such studies. Here, a family of neural-network potentials (NNPs) for the Al-Cu-Mg system is presented as the first example of a machine-learning potential that can achieve near-first-principles accuracy for many different metallurgically-important aspects of this alloy. High fidelity predictions of intermetallic compounds, elastic constants, dilute solid-solution energetics, precipitate/matrix interfaces, generalized stacking fault energies, and surfaces for slip in matrix and precipitates, antisite defect energies, and other quantities, are shown.  The NNP shows some significant transferability to defects and properties outside the structures used to develop the NNP but also shows some errors, highlighting that the use of any interatomic potential requires careful validation in application to specific metallurgical problems of interest.

en: Machine learning for metallurgy: a neural network potential for Al-Cu-Mg

aluminum

display_name: aluminum

machine-learning

display_name: machine-learning

metallurgy

display_name: metallurgy


en: Most metallurgical properties, e.g., dislocation propagation, precipitate formation, can only be fully understood atomistically but most phenomena and quantities of interest cannot be measured experimentally.  Accurate simulation methods are essential but first-principles density functional theory (DFT) is prohibitively expensive while empirical interatomic potentials are rarely sufficiently accurate for alloys.  Machine learning (ML) is emerging as an approach to create computationally-efficient atomistic potentials achieving near-DFT accuracy.  Building on recent work on binary Al-Cu and ternary Al-Mg-Si, here a family of neural network potentials (NNPs) for Al alloys of Al-Cu-Mg and Al-Cu-Mg-Zn is developed and assessed using the Behler-Parinello formulation.  Training of the potentials uses a robust set of metallurgically-relevant structures including intermetallic phases, stacking faults, solute/solute and solute/stacking fault interactions, solute clusters, and matrix/precipitate interfaces.  The accuracy of these NNPs is then demonstrated across a comprehensive set of properties derived from the training set structures and, moreover, many important structures not represented in the training set such as the generalized stacking fault energy (GSFE) surface of the critical S-phase precipitate in Al-Mg-Cu, and antisite and vacancy formation energies for Al-Cu-Mg intermetallics.  The broader Al-Cu-Mg-Zn NNPs also have high accuracy for subtle properties such as Cu substitutional energies in the $\eta'$ and T phases and formation energies of small Al-Zn-Mg clusters.  Together with earlier results, this work shows how increasingly complex multicomponent alloy potentials can be systematically developed by expanding a training database, leading to a comprehensive set of potentials for a broad alloy family, demonstrated here for the technological Al-2xxx, Al-5xxx, and Al-7xxx Al alloys.

en: Machine learning for metallurgy: neural network potentials for Al-Cu-Mg and Al-Cu-Mg-Zn


en: When magnetism meets topology, colorful novel states can be created in materials. The realization of magnetic topological Dirac materials remains a major issue in topological physics studies. In this work, it is ascertained that the topologically nontrivial ground state of EuCd2As2 is a good candidate for different types of magnetic topological state: magnetic topological Dirac semimetal, axion insulator, antiferromagnetic TCI, and higher order topological insulator. This documents include all the raw data in the reference Advanced Materials 32, 1907565 (2020). This files contains all the raw data that published in the related paper. Fig.1.zip includes dat format transport measurement results which can be open by Origin. Fig.2.zip contains ibw format ARPES spectra which can be opened by IGOR. Fig.3.zip contains figures of the calculated FS, band structure. The dat format files can be open by IGOR. Fig.4.zip contains both ARPES spectra and STS data. sxm format file can be opened by SXM software which is commonly used for STM/STS data. The h5 format file can be opened by IGOR. H5 format is also commonly used for high dimensional data in ARPES experiments. Fig.5 is mainly the calculated band structure of the related fig.5. The itx format can be opened by IGOR. All the ibw format files are duplicated in the txt file with same name. The SXM file is also duplicated in txt file with same name.

en: Emergence of nontrivial low-energy Dirac fermions in antiferromagnetic EuCd2As2

axion-insulator

display_name: axion-insulator

high-order-topological-insulator

display_name: high-order-topological-insulator

magnetic-topological-dirac-semimetal

display_name: magnetic-topological-dirac-semimetal

magnetic-topological-insulator

display_name: magnetic-topological-insulator

marvel

display_name: marvel

snsf

display_name: snsf


en: Graphene nanoribbons (GNRs) have attracted much interest due to their largely modifiable electronic properties. Manifestation of these properties requires atomically precise GNRs which can be achieved through a bottom–up synthesis approach. This has recently been applied to the synthesis of width‐modulated GNRs hosting topological electronic quantum phases, with valence electronic properties that are well captured by the Su–Schrieffer–Heeger (SSH) model describing a 1D chain of interacting dimers. In this record we provide data to support our recent publication where we demonstrate that ultralow bandgap GNRs with charge carriers behaving as massive Dirac fermions can be realized when their valence electrons represent an SSH chain close to the topological phase boundary, i.e., when the intra‐ and interdimer coupling become approximately equal. Such a system has been achieved via on‐surface synthesis based on readily available pyrene‐based precursors and the resulting GNRs are characterized by scanning probe methods. The pyrene‐based GNRs (pGNRs) can be processed under ambient conditions and incorporated as the active material in a field effect transistor. A quasi‐metallic transport behavior is observed at room temperature, whereas at low temperature, the pGNRs behave as quantum dots showing single‐electron tunneling and Coulomb blockade. This study may enable the realization of devices based on carbon nanomaterials with exotic quantum properties.

en: Massive Dirac fermion behavior in a low bandgap graphene nanoribbon near a topological phase boundary

ab-initio

display_name: ab-initio

dirac-fermions

display_name: dirac-fermions

graphene-nanoribbons

display_name: graphene-nanoribbons


en: We present a scheme to extract the adsorption energy, adsorbate interaction parameter and the saturation coverage from temperature programmed desorption (TPD) experiments. We propose that the coverage dependent adsorption energy can be fit using a functional form including the configurational entropy and linear adsorbate-adsorbate interaction terms. As one example of this scheme, we analyze TPD of CO desorption on Au(211) and Au(310) surfaces. We determine that under atmospheric CO pressure, the steps of both facets adsorb between 0.4-0.9 ML coverage of CO*. We compare this result against energies obtained from five density functionals, RPBE, PBE, PBE-D3, RPBE-D3 and BEEF-vdW. We find that the energies and equilibrium coverages from RPBE-D3 and PBE are closest to the values determined from the TPD. This dataset contains all the DFT calculations run using AiiDA.

en: How to extract adsorption energies, adsorbate-adsorbate interaction parameters, and saturation coverages from temperature programmed desorption experiments

benchmark

display_name: benchmark

catalysis

display_name: catalysis


en: Koopmans' spectral  functionals aim to describe simultaneously ground state properties and charged excitations of atoms, molecules, nanostructures and periodic crystals. This is achieved augmenting standard density functionals with simple but physically motivated orbital-density-dependent corrections. These corrections act on a set of localized orbitals that, in periodic systems, resembles maximally localized Wannier function. At variance with a direct supercell implementation, we discuss here i) the complex but efficient formalism required for a periodic-boundary code using explicit Brillouin zone sampling, and ii) the calculation of the screened Koopmans' corrections with density-functional perturbation theory. The implementation in the Quantum ESPRESSO distribution and the application to prototypical insulating and semiconducting systems are presented and discussed.

en: Koopmans spectral functionals: an open-source periodic-boundary implementation

electronic-structure

display_name: electronic-structure

koopmans-spectral-functionals

display_name: koopmans-spectral-functionals

marvelosp

display_name: marvelosp

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals


en: The impact of the inner structure and thermal history of planets on their observable features, such as luminosity or magnetic field, crucially depends on the poorly known heat and charge transport properties of their internal layers. The thermal and electric conductivities of different phases of water (liquid, solid, and super-ionic) occurring in the interior of ice giant planets, such as Uranus or Neptune, are evaluated from equilibrium ab initio molecular dynamics, leveraging recent progresses in the theory and data analysis of transport in extended systems. In this record we collect the ab-initio time series of the energy flux and of the electronic and ionic charge fluxes for H2O at different planetary conditions, from which the related transport coefficients are extracted according to the Green-Kubo theory of linear response.

materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

en: Heat and charge transport in H2O at ice-giant conditions from ab initio molecular dynamics simulations

max

display_name: max

molecular-dynamics

display_name: molecular-dynamics

planetary-evolution-models

display_name: planetary-evolution-models

transport-properties

display_name: transport-properties

water-at-extreme-conditions

display_name: water-at-extreme-conditions


materialscloud

en: Materials Cloud

envi

en: Environment


en: Blending organic molecules to tune their energy levels is currently investigated as an approach to engineer the bulk and interfacial optoelectronic properties of organic semiconductors. It has been proven that the ionization energy (IE) and electron affinity (EA) can be equally shifted in the same direction by electrostatic effects controlled by blending similar halogenated derivatives with different energetics. Here, we show that the energy gap of organic semiconductors can be tuned by blending as well. We use oligothiophenes with different numbers of thiophene rings as example and investigate their structure and electronic properties. Photoelectron spectroscopy and inverse photoelectron spectroscopy show tunability of the single-particle gap, with the optical gaps showing similar, but smaller effects. Theoretical analysis shows that this tuning is mainly caused by a change in the dielectric constant with blend ratio. Further studies will explore the practical impact of this energy-level engineering strategy in optoelectronic devices.

en: Band gap engineering in blended organic semiconductor films based on dielectric interactions

dielectric-interactions

display_name: dielectric-interactions

energy-level-tuning

display_name: energy-level-tuning

photoelectron-spectroscopy

display_name: photoelectron-spectroscopy

theoretical-simulations

display_name: theoretical-simulations


en: Hematite as promising photoanode for solar water splitting suffers from severe bulk and surface charge recombination. This work describes that a protonation−annealing treatment can effectively suppress both bulk and surface charge recombination in hematite. Protons/electrons are electrochemically incorporated into hematite under 0.2 VRHE followed by annealing at 120 °C. The photocurrent density increases from ∼0.9 to 1.8 mA cm−2 at 1.23 VRHE under 1 sun, and further to 2.7 mA cm−2 after loading cobalt phosphate, stabilizing at round 2.4 mA cm−2. A cathodic shift of the onset potential of photocurrent is also observed. H2O2 oxidation, impedance spectroscopy, and Mott−Schottky measurements show that the protonation suppresses bulk recombination and enhances donor density, but introducing more surface recombination. The annealing reduces surface recombination, while preserving relatively high bulk charge separation efficiency. Different from previous reports on the electrochemically reduced hematite, this work demonstrates that the performance improvement should be ascribed to the proton incorporation instead of the formation of Fe3O4 or metal Fe. This facile treatment by protonation and annealing could be applied in other semiconductors to promote the development of high performing photoelectrodes.

en: Suppressed charge recombination in hematite photoanode via protonation and annealing

hematite-photoanode

display_name: hematite-photoanode

marvel

display_name: marvel

photoelectrochemistry

display_name: photoelectrochemistry

solar-water-splitting

display_name: solar-water-splitting


en: A pre-requisite for NMR studies of organic materials is assigning each experimental chemical shift to a set of geometrically equivalent nuclei.  Obtaining the assignment experimentally can be challenging and typically requires time-consuming multi-dimensional correlation experiments. An alternative solution for determining the assignment involves statistical analysis of experimental chemical shift databases, but no such database exists for molecular solids. Here, by combining the Cambridge structural database with a machine learning model of chemical shifts, we construct a statistical basis for probabilistic chemical shift assignment of organic crystals by calculating shifts for over 200,000 compounds, enabling the probabilistic assignment of organic crystals directly from their two-dimensional chemical structure. The approach is demonstrated with the 13C and 1H assignment of eleven molecular solids with experimental shifts, and benchmarked on 100 crystals using predicted shifts. The correct assignment was found among the two most probable assignments in over 80% of cases.

en: Bayesian probabilistic assignment of chemical shifts in organic solids

experimental

display_name: experimental

machine-learning

display_name: machine-learning

nmr

display_name: nmr

snsf

display_name: snsf


en: Hundreds of catalytic methods are developed each year to meet the demand for high-purity chiral compounds. The computational design of enantioselective organocatalysts remains a significant challenge, as catalysts are typically discovered through experimental screening. Recent advances in combining quantum chemical computations and machine learning (ML) hold great potential to propel the next leap forward in asymmetric catalysis. Within the context of quantum chemical machine learning (QML, or atomistic ML), the ML representations used to encode the structure of molecules and evaluate their similarity cannot easily capture the subtle energy differences that govern enantioselectivity. Here, we present a general strategy for improving molecular representations within an atomistic machine learning model to predict the enantiomeric excess of asymmetric propargylation organocatalysts solely from the structure of catalytic cycle intermediates. Mean absolute errors as low as 0.25 kcal mol-1 were achieved in predictions of the activation energy. This strategy opens the door for quickly and accurately predicting higher-selectivity catalysts for any reaction from available structural information.

en: Reaction-based machine learning representations for predicting the enantioselectivity of organocatalysts

catalysis

display_name: catalysis

enantioselectivity

display_name: enantioselectivity

organocatalyst

display_name: organocatalyst


en: Koopmans' spectral  functionals aim to describe simultaneously ground state properties and charged excitations of atoms, molecules, nanostructures and periodic crystals. This is achieved augmenting standard density functionals with simple but physically motivated orbital-density-dependent corrections. These corrections act on a set of localized orbitals that, in periodic systems, resembles maximally localized Wannier function. At variance with a direct supercell implementation, we discuss here i) the complex but efficient formalism required for a periodic-boundary code using explicit Brillouin zone sampling, and ii) the calculation of the screened Koopmans' corrections with density-functional perturbation theory. In addition to delivering improved scaling with system size, the present development makes the calculation of band structures with Koopmans functionals straightforward. The implementation in the Quantum ESPRESSO distribution and the application to prototypical insulating and semiconducting systems are presented and discussed.

electronic-structure

display_name: electronic-structure

koopmans-spectral-functionals

display_name: koopmans-spectral-functionals

marvelosp

display_name: marvelosp

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals


en: The marked interplay between the crystalline, electronic, and magnetic structure of atomically thin magnets has been regarded as the key feature for designing next-generation magneto-optoelectronic devices. In this respect, a detailed understanding of the microscopic interactions underlying the magnetic response of these crystals is of primary importance. Here, we combine model Hamiltonians with multireference configuration interaction wavefunctions to accurately determine the strength of the spin couplings in the prototypical single-layer magnet CrI₃. Our calculations identify the (ferromagnetic) Heisenberg exchange interaction J = −1.44 meV as the dominant term, being the inter-site magnetic anisotropies substantially weaker. We also find that single-layer CrI₃ features an out-of-plane easy axis ensuing from a single-ion anisotropy A = −0.10 meV, and predict g-tensor in-plane components gxx = gyy = 1.90 and out-of-plane component gzz  = 1.92. In addition, we assess the performance of a dozen widely used density functionals against our accurate correlated wavefunctions calculations and available experimental data, thereby establishing reference results for future first-principles investigations. Overall, our findings offer a firm theoretical ground to recent experimental observations.

en: Magnetic exchange interactions in monolayer CrI₃ from many-body wavefunction calculations

cscs

display_name: cscs

density-functional-calculations

display_name: density-functional-calculations

quantum-chemistry-calculations

display_name: quantum-chemistry-calculations

quantum-magnetism

display_name: quantum-magnetism


marvel

display_name: marvel


en: The outstanding performance of NiOOH/FeOOH-based oxygen evolution reaction (OER) catalysts is rationalized in terms of a bifunctional mechanism involving two distinct active sites. In this mechanism, the OOH_ads reaction intermediate, which unfavorably affects the overall OER activity due to the linear scaling relationship, is replaced by O2 adsorbed at the active site on FeOOH, and H_ads adsorbed at the NiOOH substrate. Here, we use the computational hydrogen electrode method to assess promising models of both the FeOOH catalyst and the NiOOH hydrogen acceptor. These two materials are interfaced in various ways to evaluate their performance as bifunctional OER catalysts. In some cases, overpotentials as low as 0.16 V are found, supporting the bifunctional mechanism as a means to overcome the limitations imposed by linear scaling relationships.

en: High-performance NiOOH/FeOOH electrode for OER catalysis

bifunctional-mechanism

display_name: bifunctional-mechanism

density-functional-theory

display_name: density-functional-theory

epfl

display_name: epfl

free-energy-steps

display_name: free-energy-steps

linear-scaling-relationships

display_name: linear-scaling-relationships

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: This record contains the experimental band structure of MoTe2. The material exhibits a structural phase transition at approximately 240 K, and in the low-temperature 1T' phase is expected to realize the type-II Weyl semimetal phase. In our data we compare the band structure and the Fermi surface in the topological and in the trivial (1T'') phase. We report the existence of large surface arc, which is persistent across the topological phase transition, and we conclude that its observation cannot be taken alone as a smoking gun of the Weyl semimetal phase. The study is completed by a spin-resolved ARPES study of the bulk electronic properties in the low-temperature topological phase

en: Persistence of a surface state arc in the topologically trivial phase of MoTe2

electronic-bands

display_name: electronic-bands

erc

display_name: erc

experimental

display_name: experimental

snsf

display_name: snsf

spin-properties

display_name: spin-properties

topological-phase-transition

display_name: topological-phase-transition

type-ii-weyl-semimetal

display_name: type-ii-weyl-semimetal


materialscloud

en: Materials Cloud

envi

en: Environment


en: Variations of volume plasmon energy of both ribbon and bulk FeMo14C15B6Erx (x=0-2) metallic glasses were measured as a function of the temperature in an analytical transmission electron microscope using valence electron energy loss spectroscopy (VEELS). The plasmon energy was found to decrease with increasing temperature, due not only to thermal expansion but also to chemical reordering in the glasses. The chemical reordering stimulates a specific solute cluster formation; M23(C, B)6 solute clusters began to form above about 200°C in both ribbon and bulk FeMo14C15B6Erx (x=0, 0.5, 1) metallic glasses. The formation of the M23(C, B)6 solute clusters was only found above 400°C in the ribbon FeMo14C15B6Er2 metallic glass, indicating inhibition of the M23(C, B)6 solute clusters occurred owing to the formation of Er-(C, B) complexes/clusters. The Er-(C, B) complexes/clusters were formed in the cooling process of the sample fabrication. In contrast to the ribbon sample, the formation of the M23(C, B)6 solute clusters did not occur in the bulk FeMo14C15B6Er2 metallic glass during heating. The amount of the Er-(C, B) complexes/clusters in the bulk sample was larger than that in the ribbon sample because of the slow cooling rate in the bulk sample fabrication. Because the solute carbon and boron atoms were mostly consumed by the formation of Er-(C, B) complexes/clusters in the bulk FeMo14C15B6Er2 metallic glass, the formation of M23(C, B)6 solute clusters was suppressed. This study demonstrates that chemical reordering during the relaxation of metallic glasses can be detected by the VEELS, providing valuable insight into the relaxation stage of metallic glass during heating.

en: Plasmon energy changes in FeMo14C15B6Erx (x=0-2) bulk metallic glass during in-situ heating

bulk-metallic-glass

display_name: bulk-metallic-glass

chemical-reordering

display_name: chemical-reordering

electron-energy-loss-spectroscopy

display_name: electron-energy-loss-spectroscopy

in-situ-heating

display_name: in-situ-heating

volume-plasmon

display_name: volume-plasmon


en: Understanding the physical mechanisms behind thermal effects in phosphors is crucial for white light-emitting device (WLEDs) applications, as thermal quenching of their photoluminescence might render them useless. We analyze from first-principles, before and after absorption/emission of light, two chemically close Eu-doped Ba₃Si₆O₁₂N₂ and Ba₃Si₆O₉N₄ crystals for WLEDs. The first one has an almost constant emission intensity with increasing temperature whereas the other one does not. Our results, in which the Eu-5d levels are obtained inside the band gap thanks to the removal of an electron from the 4f⁷ shell, and the atomic neighborhood properly relaxed in the excited state, attributes the above-mentioned experimental difference to an autoionization model of the thermal quenching, based on the energy difference between Eu 5d and the conduction band minimum. Our depleted-shifted 4f method can identify luminescent centers and therefore allows for effective crystal site engineering of luminescent centers in phosphors from first principles.

en: Understanding thermal quenching of photoluminescence in oxynitride phosphors from first principles

ab-initio

display_name: ab-initio

bson

display_name: bson

ceci

display_name: ceci

first-principles

display_name: first-principles

frs-fnrs

display_name: frs-fnrs

oxynitride-phosphors

display_name: oxynitride-phosphors

photoluminescence

display_name: photoluminescence

rare-earth

display_name: rare-earth

thermal-quenching

display_name: thermal-quenching


en: Materials composed of elements from the third and fifth columns of the periodic table display a very rich behavior, with the phase diagram usually containing a metallic liquid phase and a polar semiconducting solid. As a consequence, it is very hard to achieve transferable empirical models of interactions between the atoms that can reliably predict their behavior across the temperature and composition range that is relevant to the study of the synthesis and properties of III/V nanostructures and devices. We present a machine-learning potential trained on density functional theory reference data that provides a general-purpose model for the Ga/As system. We provide a series of stringent tests that showcase the accuracy of the potential, and its applicability across the whole binary phase space, computing with ab initio accuracy a large number of finite-temperature properties as well as the location of phase boundaries. We also show how a committee model can be used to reliably determine the uncertainty induced by the limitations of the machine-learning model on its predictions, to identify regions of phase space that are predicted with insufficient accuracy, and to iteratively refine the training set to achieve consistent, reliable modeling.

en: Modeling the Ga/As binary system across temperatures and compositions from first principles

gaas

display_name: gaas

gallium-arsenide

display_name: gallium-arsenide

marvel

display_name: marvel

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potential

display_name: neural-network-potential

snsf

display_name: snsf


en: The face-centered cubic medium-entropy alloy NiCoCr has received considerable attention for its good mechanical properties, uncertain stacking fault energy, etc, some of which have been attributed to chemical short-range order (SRO). Here, we examine the yield strength and misfit volumes of NiCoCr to determine whether SRO has measurably influenced mechanical properties. Polycrystalline strengths show no systematic trend with different processing conditions. Measured misfit volumes in NiCoCr are consistent with those in random binaries. Yield strength prediction of a random NiCoCr alloy matches well with experiments. Finally, we show that standard spin-polarized density functional theory (DFT) calculations of misfit volumes are not accurate for NiCoCr. This implies that DFT may be inaccurate for other subtle structural quantities such as atom-atom bond distance so that caution is required in drawing conclusions about NiCoCr based on DFT. These findings all lead to the conclusion that, under typical processing conditions, SRO in NiCoCr is either negligible or has no systematic measurable effect on strength.

en: Yield strength and misfit volumes of NiCoCr and implications for short-range-order

epfl

display_name: epfl

high-entropy-alloy

display_name: high-entropy-alloy

short-range-order

display_name: short-range-order

yield-strength

display_name: yield-strength


en: We investigate the effect of polar Sr-O vacancy pairs on the electric polarization of SrMnO3 (SMO) thin films using density functional theory (DFT) calculations. This is motivated by indications that ferroelectricity in complex oxides can be engineered by epitaxial strain but also via the defect chemistry. Our results suggest that intrinsic doping by cation and anion divacancies can induce a local polarization in unstrained non-polar SMO thin films and that a ferroelectric state can be stabilized below the critical strain of the stoichiometric material. This polarity is promoted by the electric dipole associated with the defect pair and its coupling to the atomic relaxations upon defect formation that polarize a region around the defect. This suggests that polar defect pairs affect the strain-dependent ferroelectricity in semiconducting antiferromagnetic SMO. For metallic ferromagnetic SMO we find a much weaker coupling between the defect dipole and the polarization due to much stronger electronic screening. Coupling of defect-pair dipoles at high enough concentrations along with their switchable orientation thus makes them a promising route to affect the ferroelectric transition in complex transition metal oxide thin films.

en: Ferroelectricity promoted by cation/anion divacancies in SrMnO3

cationanion-divacancies

display_name: cationanion-divacancies

cscs

display_name: cscs

dftu

display_name: dftu

ferroelectricity

display_name: ferroelectricity

point-defects

display_name: point-defects

polarization

display_name: polarization

strain

display_name: strain

thin-films

display_name: thin-films


en: In this work we elaborate on recently discovered invariance principles, according to which transport coefficients are, to a large extent, independent of the microscopic definition of the densities and currents of the conserved quantities being transported (energy, momentum, mass, charge). These invariance principles can be combined with new spectral analysis methods for the current time series to be fed into the Green-Kubo formula to obtain accurate estimates of transport coefficients from relatively short molecular dynamics simulations. In this record we collect the time series of the ab initio charge flux for a simulation of molten potassium chloride, together with the Jupyter Notebooks we employed to analyse the data and produce the figures in the related article.

en: Invariance principles in the theory and computation of transport coefficients

green-kubo

display_name: green-kubo

marie-curie-fellowship

display_name: marie-curie-fellowship

max

display_name: max

molecular-dynamics

display_name: molecular-dynamics

transport

display_name: transport


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).

snsf

display_name: snsf


en:
Some organic pollutants in snowpack undergo faster photodegradation than in solution. One possible explanation for such effect is that their UV-visible absorption spectra are shifted toward lower energy when the molecules are adsorbed at the air-ice interface. However, such bathochromic shift is difficult to measure experimentally.
Here we employ a multiscale/multimodel approach that combines classical and first-principles molecular dynamics, quantum chemical methods and statistical learning to compute the light absorption spectra of two phenolic molecules in different solvation environments at the relevant thermodynamic conditions.
Our calculations provide an accurate estimate of the bathochromic shift of the lowest-energy UV-visible absorption band when these molecules are adsorbed at the air-ice interface, and they shed light into its molecular origin.

en: Bathochromic shift in the UV-visible absorption spectra of phenols at ice surfaces: insights from first-principles calculations

absorption

display_name: absorption

guaiacol

display_name: guaiacol

ice

display_name: ice

phenol

display_name: phenol

spectra

display_name: spectra

water

display_name: water


materialscloud

en: Materials Cloud


en: A new implementation of linear-response time-dependent density functional theory (LR-TDDFT) for core level near-edge absorption spectroscopy is discussed. The method is based on established LR-TDDFT approaches to X-ray absorption spectroscopy (XAS) with additional accurate approximations for increased efficiency. We validate our implementation by reproducing benchmark results at the K-edge and showing that spin–orbit coupling effects at the L2,3-edge are well described. We also demonstrate that the method is suitable for extended systems in periodic boundary conditions and measure a favorable sub-cubic scaling of the calculation cost with system size. We finally show that GPUs can be efficiently exploited and report speedups of up to a factor 2.

en: Efficient and low-scaling linear-response time-dependent density functional theory implementation for core-level spectroscopy of large and periodic systems

envi

en: Environment

low-scaling-algorithm

display_name: low-scaling-algorithm

method-development

display_name: method-development

tddft

display_name: tddft

xas

display_name: xas


en: High nickel content in LiNixCoyMnzO2 (NCM, x ≥ 0.8, x + y + z = 1) layered cathode material allows high energy density in lithium-ion batteries (LIBs). However, Ni-rich NCM cathodes suffer from performance degradation, mechanical and structural instability upon prolonged cell cycling. Although the use of single-crystal Ni-rich NCM can mitigate these drawbacks, the ion-diffusion in large single-crystal particles hamper its rate capability. Herein, we report a strategy to construct an in situ Li1.4Y0.4Ti1.6(PO4)3 (LYTP) ion/electron conductive network which interconnects single-crystal LiNi0.88Co0.09Mn0.03O2 (SC-NCM88) particles. The LYTP network facilitates the lithium-ion transport between SC-NCM88 particles, mitigates mechanical instability and prevents detrimental crystalline phase transformation. When used in combination with a Li metal anode, the LYTP-containing SC-NCM88-based cathode enables a coin cell capacity of 130 mAh g-1 after 500 cycles at 5 C rate in the 2.75-4.4 V range at 25 °C. Tests in Li-ion pouch cell configuration (i.e., graphite used as negative electrode active material) demonstrate capacity retention of 85% after 1000 cycles at 0.5 C in the 2.75-4.4 V range at 25 °C for the LYTP-containing SC-NCM88-based positive electrode.

en: In situ inorganic conductive network enables superior high-voltage operation of single-crystal Ni-rich cathode

conductive-network

display_name: conductive-network

crystalline-phase-transformation

display_name: crystalline-phase-transformation

experimental

display_name: experimental

in-situ

display_name: in-situ

lithium-ion-transport

display_name: lithium-ion-transport

single-crystal-ni-rich-ncm

display_name: single-crystal-ni-rich-ncm


en: Nanostructured birnessite (δ-MnO2) exhibits high specific capacitance and nearly ideal capacitive behavior in aqueous electrolytes, rendering it an important electrode material for low-cost, high power energy storage devices. The mechanism of electrochemical capacitance in birnessite has been described as both faradaic (involving redox) and non-faradaic (involving only electrostatic interactions). To clarify the capacitive mechanism, we characterized birnessite's response to applied potential using ex situ X-ray diffraction, electrochemical quartz crystal microbalance, in situ Raman spectroscopy, and operando atomic force microscopy dilatometry to provide a holistic understanding of its structural, gravimetric, and mechanical response. These observations are supported by atomic-scale simulations using density functional theory for the cation-intercalated structure of birnessite and ReaxFF-based molecular dynamics, as well as ReaxFF-based grand canonical Monte Carlo simulations on the dynamics at the birnessite/water/electrolyte interface. We show that capacitive charge storage in birnessite is governed by interlayer cation intercalation. We conclude that the intercalation appears capacitive due to the presence of nanoconfined interlayer structural water, which mediates the interaction between the intercalated cation and the birnessite host and leads to minimal structural changes.

en: Effects of interlayer confinement and hydration on capacitive charge storage in birnessite

electrochemistry

display_name: electrochemistry

energy-storage

display_name: energy-storage

oxide

display_name: oxide


en: We have developed a polymer descriptor data set from the existing data. The data set has 188 descriptors which describe polymer atomic and molecular behavior. The descriptors are mapped to the specific heat of polymers using supervised and unsupervised machine learning approaches. The mapping helps predict the specific heat of polymers at room temperature. The descriptor data set is useful in synthesizing novel polymers with desired heat capacities.

en: Polymer descriptor data set for machine learning prediction of specific heat

descriptors

display_name: descriptors

polymer

display_name: polymer

specific-heat

display_name: specific-heat


en: An advanced modeling approach is presented to shed light on the thermal transport properties of van der Waals materials (vdWMs) composed of single-layer transition metal dichalcogenides (TMDs) stacked on top of each other with a total or partial overlap only in the middle region. It relies on the calculation of dynamical matrices from first principles and on their usage in a phonon quantum transport simulator. We observe that vibrations are transferred microscopically from one layer to the other along the overlap region which acts as a filter selecting out the states that can pass through it. Our work emphasizes the possibility of engineering heat flows at the nanoscale by carefully selecting the TMD monolayers that compose vdWMs.

en: Ab initio modeling of thermal transport through van der Waals materials

cscs

display_name: cscs

snsf

display_name: snsf

thermal-properties

display_name: thermal-properties

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides

van-der-waals-materials

display_name: van-der-waals-materials


en: We performed calculations of the electronic band structure and the Fermi surface as well as measured the longitudinal resistivity ρxx(T,H), Hall resistivity ρxy(T,H), and quantum oscillations of the magnetization as a function of temperature at various magnetic fields for MoO2 with a monoclinic crystal structure. The band structure calculations show that MoO2 is a nodal-line semimetal when the spin-orbit coupling is ignored. It was found that a large magnetoresistance reaching 5.03 × 10^4% at 2 K and 9 T, its nearly quadratic field dependence, and a field-induced up-turn behavior of ρxx(T), the characteristics common for many topologically nontrivial as well as trivial semimetals, emerge also in MoO2. The observed properties are attributed to a perfect charge-carrier compensation, evidenced by both calculations relying on the Fermi surface topology and the Hall resistivity measurements. Both the observation of negative magnetoresistance for the magnetic field along the current direction and the nonzero Berry phase in de Haas–van Alphen measurements indicate that pairs of Weyl points appear in MoO2, which may be due to the crystal symmetry breaking. These results highlight MoO2 as a platform for studying the topological properties of oxides.

en: Large magnetoresistance and nonzero Berry phase in the nodal-line semimetal MoO2

berry-phase

display_name: berry-phase

epfl

display_name: epfl

magnetoresistance

display_name: magnetoresistance

marvel

display_name: marvel


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: The decay dynamics of excited carriers in graphene have attracted wide scientific attention, as the gapless Dirac electronic band structure opens up relaxation channels that are not allowed in conventional materials. We report Fermi-level-dependent mid-infrared emission in graphene originating from a previously unobserved decay channel: hot plasmons generated from optically excited carriers. The observed Fermi-level dependence rules out Planckian light emission mechanisms and is consistent with the calculated plasmon emission spectra in photoinverted graphene. Evidence for bright hot plasmon emission is further supported by Fermi-level-dependent and polarization-dependent resonant emission from graphene plasmonic nanoribbon arrays under pulsed laser excitation. Spontaneous plasmon emission is a bright emission process as our calculations for our experimental conditions indicate that the spectral flux of spontaneously generated plasmons is several orders of magnitude higher than blackbody emission at a temperature of several thousand Kelvin. In this work, it is shown that a large enhancement in radiation efficiency of graphene plasmons can be achieved by decorating graphene surface with gold nanodisks, which serve as out-coupling scatterers and promote localized plasmon excitation when they are resonant with the incoming excitation light. These observations set a framework for exploration of ultrafast and ultrabright mid-infrared emission processes and light sources.

en: Mid-infrared radiative emission from bright hot plasmons in graphene

graphene

display_name: graphene

mid-infrared

display_name: mid-infrared

plasmon

display_name: plasmon

tunable-emission

display_name: tunable-emission


materialscloud

en: Materials Cloud


en: The superconductor theory based on the electron pair is reviewed and several viewpoints are proposed. A demonstrated case reveals the speed of each electron in the electron pair at Fermi level about 1.82x10^6 m/s in Pb. However, the fastest longitudinal and transverse speeds of crystal waves in Pb at 0 K are 2.18x10^3 m/s and 1.29x10^3 m/s in [100] direction, respectively. It seems to be very hard even impossible that the mediated phonon can real-time transfer momentum and energy between two so high-speed and antiparallel-momentum electrons in the superconducting state. In this research, we focus on single electron based on the experiments of Transmission Electron Microscopy. The new fitting temperature-dependent model for the London penetration depth is proposed. This model is much better than the one- and two-gap models and matches three experimental data much well. Then it further gives the temperature-dependent effective electron mass for the Nb superconductor film. Finally, the expression for the resistivity is deduced which can explain why the resistance is almost zero in the superconductor. All these new results are obtained by using the concept of single electron.

en: The new perspective for the superconductor

effective-electron-mass

display_name: effective-electron-mass

electron-pair

display_name: electron-pair

london-penetration-depth

display_name: london-penetration-depth

mediated-phonon

display_name: mediated-phonon

resistivity

display_name: resistivity

superconductor

display_name: superconductor

temperature-dependent

display_name: temperature-dependent


envi

en: Environment


en: Zeolites are nanoporous alumino-silicate frameworks widely used as catalysts and adsorbents. Even though millions of siliceous networks can be generated by computer-aided searches, no new hypothetical framework has yet been synthesized. The needle-in-a-haystack problem of finding promising candidates among large databases of predicted structures has intrigued materials scientists for decades; yet, most work to date on the zeolite problem has been limited to intuitive structural descriptors. Here, we tackle this problem through a rigorous data science scheme—the "zeolite sorting hat"—that exploits interatomic correlations to discriminate between real and hypothetical zeolites and to partition real zeolites into compositional classes that guide synthetic strategies for a given hypothetical framework. We find that, regardless of the structural descriptor used by the zeolite sorting hat, there remain hypothetical frameworks that are incorrectly classified as real ones, suggesting that they might be good candidates for synthesis. We seek to minimize the number of such misclassified frameworks by using as complete a structural descriptor as possible, thus focusing on truly viable synthetic targets, while discovering structural features that distinguish real and hypothetical frameworks as an output of the zeolite sorting hat. Further ranking of the candidates can be achieved based on thermodynamic stability and/or their suitability for the desired applications. Based on this workflow, we propose three hypothetical frameworks differing in their molar volume range as the top targets for synthesis, each with a composition suggested by the zeolite sorting hat. Finally, we analyze the behavior of the zeolite sorting hat with a hierarchy of structural descriptors including intuitive descriptors reported in previous studies, finding that intuitive descriptors produce significantly more misclassified hypothetical frameworks, and that more rigorous interatomic correlations point to second-neighbor Si-O distances around 3.2–3.4 Å as the key discriminatory factor.

en: Ranking the synthesizability of hypothetical zeolites with the sorting hat

erc

display_name: erc

machine-learning

display_name: machine-learning

zeolites

display_name: zeolites


epfl

display_name: epfl


en: Rare earth ions typically exhibit larger magnetic moments than transition metal ions and thus promise the opening of a wider exchange gap in the Dirac surface states of topological insulators. Yet, in a recent photoemission study of Eu-doped Bi2Te3 films, the spectra remained gapless down to T=20K. Here, we scrutinize whether the conditions for a substantial gap formation in this system are present by combining spectroscopic and bulk characterization methods with theoretical calculations. For all studied Eu doping concentrations, our atomic multiplet analysis of the M4,5 x-ray absorption and magnetic circular dichroism spectra reveals a Eu2+ valence and confirms a large magnetic moment, consistent with a 4f7 8S7/2 ground state. At temperatures below 10K, bulk magnetometry indicates the onset of antiferromagnetic (AFM) ordering. This is in good agreement with density functional theory, which predicts AFM interactions between the Eu impurities. Our results support the notion that antiferromagnetism can coexist with topological surface states in rare-earth doped Bi2Te3 and call for spectroscopic studies in the kelvin range to look for novel quantum phenomena such as the quantum anomalous Hall effect.

en: Incipient antiferromagnetism in the Eu-doped topological insulator Bi2Te3

aiida-kkr

display_name: aiida-kkr

density-functional-theory

display_name: density-functional-theory

jukkr

display_name: jukkr


en: We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew-Burke-Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

en: Viscosity in water from first-principles and deep-neural-network simulations

ab-initio

display_name: ab-initio

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-networks

display_name: neural-networks

transport

display_name: transport

viscosity

display_name: viscosity

water

display_name: water


en: We combine the linearized Boltzmann Transport Equation (LBTE) and quantum transport by means of the Non-equilibrium Green's Functions (NEGF) to simulate monolayer MoS2 and WS2 ultra-scaled transistors with carrier mobilities extracted from experiments. Electron-phonon, charged impurity, and surface optical phonon scattering are taken into account with all necessary parameters derived from ab initio calculations or measurements, except for the impurity concentration. The LBTE method is used to scale the scattering self-energies of NEGF, which only include local interactions. This ensures an accurate reproduction of the measured mobilities by NEGF. We then perform device simulations and demonstrate that the considered transistors operate far from their performance limit (from 50% for MoS2 to 60% for WS2). Higher quality materials and substrate engineering will be needed to improve the situation.

en: Ab initio mobility of single-layer MoS2 and WS2: comparison to experiments and impact on the device characteristics

lbte

display_name: lbte

quantum-transport

display_name: quantum-transport

snsf

display_name: snsf


en: The simultaneous condensation of electronic and structural degrees of freedom gives rise to new states of matter, including superconductivity and charge-density-wave formation. When exciting such a condensed system, it is commonly assumed that the ultrafast laser pulse disturbs primarily the electronic order, which in turn destabilizes the atomic structure. Contrary to this conception, we show here that structural destabilization of few atoms causes macroscopic melting of the charge-density wave in 1T-TiSe2. In detail, we use ultrafast pump-probe non-resonant and resonant X-ray diffraction to track the periodic lattice distortion and the electronic charge density wave in 1T-TiSe2 upon optical excitation. We observe a fluence regime in which the periodic lattice deformation is strongly suppressed but the charge density wave related Se 4p orbital order remains mostly intact. Complete melting of both structural and electronic order occurs 4-5 times faster than expected from a purely electronic charge-screening process, strongly suggesting a structurally assisted weakening of excitonic correlations. Our experimental data provides insight on the intricate coupling between structural and electronic order in stabilizing the periodic-lattice-distortion/charge-density-wave state in 1T-TiSe2. The results further show that electron-phonon-coupling can lead to different, energy dependent phase-transition pathways in condensed matter systems, opening new possibilities in the conception of non-equilibrium phenomena at the ultrafast scale.

en: Structural involvement in the melting of the charge density wave in 1T-TiSe2

charge-density-wave

display_name: charge-density-wave

marvel

display_name: marvel

paul-scherrer-institute

display_name: paul-scherrer-institute

transient-x-ray-diffraction

display_name: transient-x-ray-diffraction

xfel

display_name: xfel


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: We present a joint theoretical and experimental study of the oxygen K-edge spectra for LaFeO₃ and homovalent Ni-substituted LaFeO₃ (LaFe₀.₇₅Ni₀.₂₅O₃), using first-principles simulations based on density-functional theory with extended Hubbard functionals and x-ray absorption near edge structure (XANES) measurements. Ground-state and excited-state XANES calculations employ Hubbard on-site U and inter-site V parameters determined from first principles and the Lanczos recursive method to obtain absorption cross sections, which allows for a reliable description of XANES spectra in transition-metal compounds in a very broad energy range, with an accuracy comparable to that of hybrid functionals but at a substantially lower cost. We show that standard gradient-corrected exchange-correlation functionals fail in capturing accurately the electronic properties of both materials. In particular, for LaFe₀.₇₅Ni₀.₂₅O₃ they do not reproduce its semiconducting behaviour and provide a poor description of the pre-edge features at the O K edge. The inclusion of Hubbard interactions leads to a drastic improvement, accounting for the semiconducting ground state of LaFe₀.₇₅Ni₀.₂₅O₃ and for good agreement between calculated and measured XANES spectra. We show that the partial substitution of Ni for Fe affects the conduction-band bottom by generating a strongly hybridized O(2p)-Ni(3d) minority-spin empty electronic state. The present work, based on a consistent correction of self-interaction errors, outlines the crucial role of extended Hubbard functionals to describe the electronic structure of complex transition-metal oxides such as LaFeO₃ and LaFe₀.₇₅Ni₀.₂₅O₃ and paves the way to future studies on similar systems.

en: Electronic structure of pristine and Ni-substituted LaFeO₃ from near edge x-ray absorption fine structure experiments and first-principles simulations

cscs

display_name: cscs

dftu

display_name: dftu

dftuv

display_name: dftuv

hubbard-corrections

display_name: hubbard-corrections

perovskites

display_name: perovskites

transition-metal-oxides

display_name: transition-metal-oxides

xanes

display_name: xanes


materialscloud

en: Materials Cloud

density-functional-theory

display_name: density-functional-theory


en: The solar water splitting process assisted by semiconductor photocatalysts attracts growing research interests worldwide for the production of hydrogen as a clean and sustainable energy carrier. Due to their optical and electrical properties several oxynitride materials show great promise for the fabrication of efficient photocatalysts for solar water splitting. This study reports a comparative investigation of particle- and thin films-based photocatalysts using three different oxynitride materials. The absolute comparison of the photoelectrochemical activities favors the particle-based electrodes due to the better absorption properties and larger electrochemical surface area. However, thin films surpass the particle-based photoelectrodes due to their more suitable morphological features that improve the separation and mobility of the photo-generated charge carriers. Our analysis identifies what specific insights into the properties of materials can be achieved with the two complementary approaches.

en: Oxynitride thin films versus particle-based photoanodes: a comparative study for photoelectrochemical solar water splitting

oxynitride-photoanode

display_name: oxynitride-photoanode

pulsed-laser-deposition

display_name: pulsed-laser-deposition

solar-fuel

display_name: solar-fuel

solar-water-splitting

display_name: solar-water-splitting


envi

en: Environment


en: The record contains data to support our research findings regarding the development of a novel method for deriving localized basis sets in the projector augmented wave formalism, allowing to obtain a reduced basis set of atomic orbitals through the subdiagonalization of each atomic block of the Hamiltonian. The resulting local orbitals (LOs) inherit the information of the local crystal field. In the LO basis, it becomes apparent that the Hamiltonian is nearly block-diagonal, and we demonstrate that it is possible to keep only a subset of relevant LOs that provide an accurate description of the physics around the Fermi level. This reduces to some extent the redundancy of the original basis set, and at the same time, it allows one to perform post-processing of DFT calculations, ranging from the interpretation of electron transport to extracting effective tight-binding Hamiltonians, very efficiently and without sacrificing the accuracy of the results.

en: Smart local orbitals for efficient calculations within density functional theory and beyond

minimal-basis-sets

display_name: minimal-basis-sets

subdiagonalization

display_name: subdiagonalization

transport

display_name: transport


en: The dielectric properties of tetragonal hybrid perovskite CH3NH3PbI3 are studied through molecular dynamics at a temperature of 300 K in the presence of a finite electric field. The high-frequency dielectric constant ε∞ is found to be 4.5 along the a axis and 4.7 along the c axis. The values of the respective static dielectric constants ε0 are 43 ± 1 and 53 ± 3, much larger than the value of ∼25 pertaining to the orthorhombic phase, in which the organic cations cannot rotate. At frequencies below 3 cm–1, we observe a significant increase in ε0 by ∼23 (a axis) and ∼30 (c axis) compared to a vibrational approach, which does not account for the reorientation of the molecular units. The decomposition shows that the reorientation of the organic cations accounts for an increase of only ∼10. An increase of similar size results from the displacement of the cations within the cages of the lattice. The dominant contribution is found to arise from lattice vibrations coupled to the motion of the organic cations.

en: Low-frequency dielectric response of tetragonal perovskite CH3NH3PbI3

dielectric-properties

display_name: dielectric-properties

epfl

display_name: epfl

hybrid-perovskite

display_name: hybrid-perovskite

molecular-dynamics

display_name: molecular-dynamics


en: Ionosorbed oxygen is the key player in reactions on metal-oxide surfaces. This is particularly evident for chemiresistive gas sensors, which operate by modulating the conductivity of active materials through the formation/removal of surface O-related acceptors. Herein, we carried out a detailed study of various charged oxygen species on three naturally occurring surfaces of SnO2. We employed first-principles calculations and revealed that two types of surface acceptors can form spontaneously upon the adsorption of atmospheric oxygen: (i) superoxide O2 (in 1- charged state) on the (110) and the (101) surfaces and (ii) doubly ionized O (in 2- charged state) on the (100) facet, with the experimental evidence pointing to the latter as the source of sensing response. In this dataset, we present the optimized geometries (in CIF format) of different O and O_2 adsorption configurations in the most relevant charged states.

en: Chemistry of oxygen ionosorption on SnO2 surfaces

charged-oxygen-species

display_name: charged-oxygen-species

chemiresistive-sensing

display_name: chemiresistive-sensing

ionosorption-model

display_name: ionosorption-model

surface-chemistry

display_name: surface-chemistry


en:
Intermolecular interactions play an important role for the understanding of catalysis, biochemistry and pharmacy. Double-hybrid density functionals (DHDFs) combine the proper treatment of short-range interactions of common density functionals with the correct description of long-range interactions of wave-function correlation methods. Up to now, there are only a few benchmark studies available examining the performance of DHDFs in condensed phase. We studied the performance of a small but diverse selection of DHDFs implemented within Gaussian and plane waves formalism on cohesive energies of four representative dispersion interaction dominated crystal structures. We found that the PWRB95 and ωB97X-2 functionals provide an excellent description of long-ranged interactions in solids. In addition, we identified numerical issues due to the extreme grid dependence of the underlying density functional for PWRB95. The basis set superposition error (BSSE) and convergence with respect to the super cell size are discussed for two different large basis sets.

This record contains raw data (input files, output files, restart files) and changes to the LibXC 4.3.4 source code.

en: Double-hybrid DFT functionals for the condensed phase: Gaussian and plane waves implementation and evaluation

benchmark

display_name: benchmark

cscs

display_name: cscs

double-hybrid-density-functional-theory

display_name: double-hybrid-density-functional-theory


density-functional-theory

display_name: density-functional-theory


en:
Selector devices are indispensable components of large-scale nonvolatile memory and neuromorphic array systems. Besides the conventional silicon transistor, two-terminal ovonic threshold switching (OTS) devices with much higher scalability are currently the most industrially favored selector technology. Despite industrial confidence in OTS selectors, current devices rely heavily on intricate control of material stoichiometry and generally suffer from toxic and complex dopants to remedy the intrinsic demerits of the principal functioning materials. Here, we report on a selector with a large drive current density of 34 MA/cm2 and a ~106 high nonlinearity, realized in an environment-friendly and earth-abundant sulfide binary semiconductor, GeS. Both experiments and first-principles calculations have revealed Ge pyramid-dominated network and high density of near-valence band trap states in amorphous GeS. The high drive current capacity is associated with the strong Ge-S covalency and the high nonlinearity could arise from the synergy of the mid-gap traps assisted electronic transition and local Ge-Ge chain growth as well as locally enhanced bond alignment under high electric field. Besides the superior selector function, we have also demonstrated stochastic integrate-and-fire neuron behavior using GeS device, providing an intriguing opportunity for all-chalcogenide neuromorphic electronics.
The source data underlying Figs. 1c-e, Figs. 2a–e, and Figs. 3b, d, f are provided as a Source Data file.

en: Ultrahigh drive current and large selectivity in GeS selector

ges

display_name: ges

ots

display_name: ots

phase-change-memory

display_name: phase-change-memory

selector

display_name: selector


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: The self-consistent evaluation of Hubbard parameters using linear-response theory is crucial for quantitatively predictive calculations based on Hubbard-corrected density-functional theory. Here, we extend a recently-introduced approach based on density-functional perturbation theory (DFPT) for the calculation of the on-site Hubbard U to also compute the inter-site Hubbard V. DFPT allows to reduce significantly computational costs, improve numerical accuracy, and fully automate the calculation of the Hubbard parameters by recasting the linear response of a localized perturbation into an array of monochromatic perturbations that can be calculated in the primitive cell. In addition, here we generalize the entire formalism from norm-conserving to ultrasoft and projector-augmented wave formulations, and to metallic ground states. After benchmarking DFPT against the conventional real-space Hubbard linear response in a supercell, we demonstrate the effectiveness of the present extended Hubbard formulation in determining the equilibrium crystal structure of LiₓMnPO₄ (x=0,1) and the subtle energetics of Li intercalation.

en: Self-consistent Hubbard parameters from density-functional perturbation theory in the ultrasoft and projector-augmented wave formulations

density-functional-perturbation-theory

display_name: density-functional-perturbation-theory

extended-hubbard-functionals

display_name: extended-hubbard-functionals

li-ion-batteries

display_name: li-ion-batteries

linear-response-theory

display_name: linear-response-theory

marvel

display_name: marvel

monochromatic-perturbations

display_name: monochromatic-perturbations

projector-augmented-wave-method

display_name: projector-augmented-wave-method

self-interaction-corrections

display_name: self-interaction-corrections

ultrasoft-pseudopotentials

display_name: ultrasoft-pseudopotentials

voltages

display_name: voltages


materialscloud

en: Materials Cloud

cscs

display_name: cscs


en: An advanced modeling approach is presented to shed light on the thermal transport properties of van der Waals materials (vdWMs) composed of single-layer transition metal dichalcogenides (TMDs) stacked on top of each other with a total or partial overlap only in the middle region. It relies on the calculation of dynamical matrices from first principles and on their usage in a phonon quantum transport simulator. We observe that vibrations are transferred microscopically from one layer to the other along the overlap region which acts as a filter selecting out the states that can pass through it. Our work emphasizes the possibility of engineering heat flows at the nanoscale by carefully selecting the TMD monolayers that compose vdWMs.

en: Ab initio modeling of thermal transport through van der Waals materials

snsf

display_name: snsf

thermal-properties

display_name: thermal-properties

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides

van-der-waals-materials

display_name: van-der-waals-materials


envi

en: Environment


en: Radiative cooling is a passive cooling technology by reflecting sunlight and emitting radiation in the sky window. Although highly desired, full daytime sub-ambient radiative cooling in commercial-like single-layer particle-matrix paints is yet to be achieved. Here we demonstrate full daytime sub-ambient radiative cooling in CaCO3-acrylic paint by utilizing the large bandgap CaCO3 fillers, a high particle concentration of 60% and a broad size distribution. Our paint shows high solar reflectance of 95.5% and high normal emissivity of 0.94 in the sky window. Field tests show cooling power exceeding 37W/m2 and surface temperature more than 1.7˚C below ambient at noon. A figure of merit RC is proposed to compare the cooling performance independent of weather conditions. The standard RC of our paint is 0.49, among the best radiative cooling performance while offering unprecedented benefits of the convenient paint form, low cost, and the compatibility with commercial paint fabrication process.

en: Full daytime sub-ambient radiative cooling in commercial-like paints with high figure of merit

atmospheric-sky-window

display_name: atmospheric-sky-window

daytime-radiative-cooling

display_name: daytime-radiative-cooling

figure-of-merit

display_name: figure-of-merit

lorentz-mie-theory

display_name: lorentz-mie-theory

monte-carlo-simulation

display_name: monte-carlo-simulation

particle-matrix-paint

display_name: particle-matrix-paint


en: While alloy design has practically shown an efficient strategy to mediate two seemingly conflicted performances of writing speed and data retention in phase-change memory, the detailed kinetic pathway of alloy-tuned crystallization is still unclear. Here, we propose hierarchical melt and coordinate bond strategies to solve them, where the former stabilizes a medium-range crystal-like region and the latter provides a rule to stabilize amorphous. The Er0.52Sb2Te3 compound we designed achieves writing speed of 3.2 ns and ten-year data retention of 161 °C. We provide a direct atomic-level evidence that two neighbor Er atoms stabilize a medium-range crystal-like region, acting as a precursor to accelerate crystallization; meanwhile, the essential reason of stabilization originates from the formation of coordinate bonds by sharing lone-pair electrons of chalcogenide atoms with the empty 5d orbitals of Er atoms. The two rules pave the way for the development of storage-class memory with excellent comprehensive performance to achieve next revolutionary technology node.

en: Designing crystallization to tune the performance of phase-change memory: rules of hierarchical melt and coordinate bond

coordinate-bond

display_name: coordinate-bond

er-sb-te

display_name: er-sb-te

experimental

display_name: experimental

hierarchical-melt

display_name: hierarchical-melt

phase-change-memory

display_name: phase-change-memory


en: This work details how to determine structural prototypes for the cubic perovskite structure that are used to study the B-site displacements in the cubic, paraelectric phase. Car-Parrinello MD simulations of cubic barium titanate (BaTiO3) show the titanium displacements from the undistorted cubic structure. Using a systematic symmetry analysis we construct microscopic templates, i.e. representative structural models in the form of supercells that satisfy a desired point symmetry but are built from the combination of lower-symmetry primitive cells. Density functional theory calculations, using the microscopic templates as starting structures for a relaxation, are carried out to find structural prototypes of BaTiO3 with local polar distortions but with cubic point symmetry. The stability of these structures is studied as a function of volume and with respect to the zone-boundary phonons of pristine cubic BaTiO3. The stable distortions patterns for BaTiO3 are investigated for other titanates and for a handful of niobates and zirconates.

en: A microscopic picture of paraelectric perovskites from structural prototypes

group-subgroup-relations

display_name: group-subgroup-relations

marvelosp

display_name: marvelosp

max

display_name: max

paraelectricity

display_name: paraelectricity

perovskite

display_name: perovskite


en: Amorphous alumina (a-AlOx), which plays important roles in several technological fields, shows wide variation of the density and composition. However, their influences on the properties of a-AlOx have rarely been investigated from a theoretical perspective. In this study, high dimensional neural network (NN) potentials were constructed to generate a series of atomic structures of a-AlOx with different densities (2.6–3.3 g/cm3) and O/Al ratios (1.0–1.75). The structural, vibrational, mechanical, and thermal properties of the a-AlOx models were investigated, as well as the Li and Cu diffusion behaviour in the models. The results showed that the density and composition had different degrees of effects on the different properties. The structural and vibrational properties were strongly affected by the composition, whereas the mechanical properties were mainly determined by the density. The thermal conductivity was affected by both the density and composition of a-AlOx. However, the effects on the Li and Cu diffusion behaviour were relatively unclear.

en: Effects of the density and composition on the properties of amorphous alumina: a high dimensional neural network potential study

aluminum-oxide

display_name: aluminum-oxide

amorphous

display_name: amorphous

neural-network-potential

display_name: neural-network-potential


en:
Data includes the the ab initio molecular dynamic simulation of Li7P3S11 that was used to measure the performance of the GNNFF. The data is divided into training and testing sets.

Brief descirption of the work: Recently, machine learning (ML) has been used to address the computational cost that has been limiting ab initio molecular dynamics (AIMD). Here, we present GNNFF, a graph neural network framework to directly predict atomic forces from automatically extracted features of the local atomic environment that are translationally-invariant, but rotationally-covariant to the coordinate of the atoms. We demonstrate that GNNFF not only achieves high performance in terms of force prediction accuracy and computational speed on various materials systems, but also accurately predicts the forces of a large MD system after being trained on forces obtained from a smaller system. Finally, we use our framework to perform an MD simulation of Li7P3S11, a superionic conductor, and show that resulting Li diffusion coefficient is within 14% of that obtained directly from AIMD. The high performance exhibited by GNNFF can be easily generalized to study atomistic level dynamics of other material systems.

en: Accurate and scalable multi-element graph neural network force field and molecular dynamics with direct force architecture

density-functional-theory

display_name: density-functional-theory

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en:
Colour is at the core of chemistry and has been fascinating humans since ancient times. It is also a key descriptor of optoelectronic properties of materials and is used to assess the success of a synthesis.
However, predicting the colour of a material based on its structure is challenging.
In this work, we leverage subjective and categorical human assignments of colours to build a model that can predict the colour of compounds on a continuous scale, using chemically meaningful reasoning.
In the process of developing the model, we also uncover inadequacies in current reporting mechanisms.
For example, we show that the majority of colour assignments are subject to perceptive spread that would not comply with common printing standards.
To remedy this, we suggest and implement an alternative way of reporting colour that is more suitable for a data-driven approach to materials science.

en: A data-driven perspective on the colours of metal-organic frameworks

color

display_name: color

epfl

display_name: epfl

erc

display_name: erc

lsmo

display_name: lsmo

marvel

display_name: marvel

ml

display_name: ml


materialscloud

en: Materials Cloud


en: Koopmans-compliant functionals provide an orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system with respect to the occupation of any orbital. In crystalline materials, due to the orbital-density-dependent nature of the functionals, minimization of the total energy to a ground state provides a set of minimizing variational orbitals that are localized and thus break the periodicity of the underlying lattice. Despite this, we show that Bloch symmetry can be preserved and it is possible to describe the electronic states with a band-structure picture, thanks to the Wannier-like character of the variational orbitals. We also present a method to unfold and interpolate the electronic bands from supercell (Γ-point) calculations, which enables us to calculate full band structures with Koopmans-compliant functionals. The results obtained for a set of benchmark semiconductors and insulators show very good agreement with state-of-the-art many-body perturbation theory and experiments, underscoring the reliability of these spectral functionals in predicting band structures.

en: Bloch's theorem in orbital-density-dependent functionals: Band structures from Koopmans spectral functionals

dft

display_name: dft

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

koopmans-functionals

display_name: koopmans-functionals

orbital-density-dependent

display_name: orbital-density-dependent

photoemission-spectra

display_name: photoemission-spectra


en: Intramolecular singlet fission (iSF) has shown potential to improve the power conversion efficiency in photovoltaic devices by promoting the splitting of a photon-absorbing singlet exciton into two triplet excitons within a single molecule. Among different possibilities, the donor-acceptor modular strategy of copolymers has shown great promise in its ability to undergo iSF under certain conditions. However, the number of iSF donor-acceptor copolymers reported in the literature remains remarkably narrow and clear trends for the molecular design of better candidates have not yet been established. In this work, we identify the trade-off between the main iSF requirements of the donor-acceptor strategy and formulate design rules that allow them to be tuned simultaneously in a fragment-based approach. Based on a library of 2944 donor-acceptor copolymers, we establish simple guidelines to build promising novel materials for iSF. These consist in (1st) selecting an acceptor core with high intrinsic singlet-triplet splitting, (2nd) locating a donor with a larger monomer frontier molecular orbital (FMO) gap than that of the acceptor, and (3rd) tuning the relative energy of donor and/or acceptor FMOs through functionalization to promote photoinduced charge transfer in the resulting polymer. Remarkably, systems containing benzothiadiazole and thiophene-1,1-dioxide acceptors, which have been shown to undergo iSF, fulfill all criteria simultaneously when paired with appropriate donors. This is due to their particular electronic features, which make them highly promising candidates in the quest for iSF materials.

en: Identifying the trade-off between intramolecular singlet fission requirements in donor-acceptor copolymers

envi

en: Environment

conjugated-polymers

display_name: conjugated-polymers

excited-states

display_name: excited-states

singlet-fission

display_name: singlet-fission


en:
Exploration of structure-property relationships as a function of dopant concentration is commonly based on mean field theories for solid solutions. However, such theories that work well for semiconductors tend to fail in materials with strong correlations, either in electronic behavior or chemical segregation. In these cases, the details of atomic arrangements are generally not explored and analyzed. The knowledge of the generative physics and chemistry of the material can obviate this problem, since defect configuration libraries as stochastic representation of atomic level structures can be generated, or parameters of mesoscopic thermodynamic models can be derived. To obtain such information for improved predictions, we use data from atomically resolved microscopic images that visualize complex structural correlations within the system and translate them into statistical mechanical models of structure formation. Given the significant uncertainties about the microscopic aspects of the material's processing history along with the limited number of available images, we combine model optimization techniques with the principles of statistical hypothesis testing. We demonstrate the approach on data from a series of atomically-resolved scanning transmission electron microscopy images of MoxRe1−xS2 at varying ratios of Mo/Re stoichiometries, for which we propose an effective interaction model that is then used to generate atomic configurations and make testable predictions at a range of concentrations and formation temperatures.

This dataset includes STEM image data files and associated python code to perform statistical analysis of the images and simulations.

en: Thermodynamics of order and randomness in dopant distributions inferred from atomically resolved images

dichalcogenide

display_name: dichalcogenide

monte-carlo-simulation

display_name: monte-carlo-simulation

segregation

display_name: segregation

statistical-inference

display_name: statistical-inference


en: The reorganization energy (λ), which quantifies the structural rearrangement of a molecule when accommodating a charge, is a key parameter in the evaluation of charge mobility in molecular solids. However, it is unclear how λ is influenced by conformational isomerism, which co-exist in amorphous solids. Here, we examine the conformational space of a family of model amorphous organic hole transport materials (HTMs), derived from triphenylamine in a core-arm template, and probe the effect of conformational complexity on λ. We observe an extreme dependence of λ on the conformer geometry of sterically congested HTMs, which to the best of our knowledge has not been described previously. These results serve as a cautionary tale that, while extracting the reorganization energy from a single molecular conformer optimized in the gas phase may be appropriate for rigid and sterically unencumbered structures, it is not for many state-of-the-art HTMs that contain multiple bulky substituents.

en: Is a single conformer sufficient to describe the reorganization energy of amorphous organic transport materials?

amorphous-materials

display_name: amorphous-materials

charge-transport

display_name: charge-transport

epfl

display_name: epfl

erc

display_name: erc

reorganization-energy

display_name: reorganization-energy

replica-exchange-molecular-dynamics

display_name: replica-exchange-molecular-dynamics

triphenylamine

display_name: triphenylamine


en:
The record contains the data supporting our recent findings on asymmetric azide-alkyne Huisgen cycloaddition on chiral metal surfaces:
Achieving fundamental understanding of enantioselective heterogeneous synthesis is marred by the permanent presence of multitudinous arrangements of catalytically active sites in real catalysts. We address this issue by using structurally comparatively simple, well‐defined, and chiral intermetallic PdGa{111} surfaces as catalytic substrates. We demonstrate the impact of chirality transfer and ensemble effect for the thermally activated azide‐alkyne Huisgen cycloaddition between 3‐(4‐azidophenyl)propionic acid and 9‐ethynylphenanthrene on these threefold symmetric intermetallic surfaces under ultrahigh vacuum conditions. Specifically, we encounter a dominating ensemble effect for this reaction as on the Pd3‐terminated PdGa{111} surfaces no stable heterocoupled structures are created, while on the Pd1‐terminated PdGa{111} surfaces, the cycloaddition proceeds regioselectively. Moreover, we observe chirality transfer from the substrate to the reaction products, as they are formed enantioselectively on the Pd1‐terminated PdGa{111} surfaces. Our results evidence a determinant ensemble effect and the immense potential of PdGa as asymmetric heterogeneous catalyst.

en: Asymmetric azide‐alkyne Huisgen cycloaddition on chiral metal surfaces

ab-initio-simulations

display_name: ab-initio-simulations

asymmetric-heterogeneous-catalysis

display_name: asymmetric-heterogeneous-catalysis

azidealkyne-huisgen-cycloaddition

display_name: azidealkyne-huisgen-cycloaddition

experimental

display_name: experimental

onsurface-synthesis

display_name: onsurface-synthesis

snsf

display_name: snsf


en: Koopmans-compliant functionals provide a novel orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system with respect to the occupation of any orbital. In crystalline materials, due to the orbital-density-dependent nature of the functionals, minimization of the total energy to a ground state provides a set of minimizing variational orbitals that are localized, and thus break the periodicity of the underlying lattice. Despite this, we show that Bloch symmetry can be preserved and it is possible to describe the electronic states with a band-structure picture, thanks to the Wannier-like character of the variational orbitals. We also present a method to unfold and interpolate the electronic bands from supercell (Gamma-point) calculations, which enables us to calculate full band structures with Koopmans-compliant functionals. The results obtained for a set of benchmark semiconductors and insulators show a very good agreement with state-of-the-art many-body perturbation theory and experiments, underscoring the reliability of these spectral functionals in predicting band structures.

en: Bloch's theorem in orbital-density-dependent functionals: band structures from Koopmans spectral functionals

dft

display_name: dft

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

koopmans-functionals

display_name: koopmans-functionals

marvelosp

display_name: marvelosp

orbital-density-dependent

display_name: orbital-density-dependent

photoemission-spectra

display_name: photoemission-spectra


materialscloud

en:
Materials Cloud is a platform built to enable the seamless sharing and dissemination of resources in computational materials science, offering educational, research, and archiving tools; simulation software and services; and curated and raw data. These underpin published results and empower data-based discovery, compliant with data management plans and the FAIR principles.

In the Materials Cloud you can browse, explore, download, or deposit raw and curated data (in the Discover, Explore, and Archive sections); you can access cloud or redeployable simulation services (from AiiDAlab turnkey simulations to the Quantum Mobile virtual machine, the AiiDA registry of plugins and workflows, and the OSSCAR notebooks, in the Work section), and you can use all our educational material, tutorials and lectures (in the Learn section).


en: The design of novel cathode materials for Li-ion batteries requires accurate first-principles predictions of structural, electronic, and magnetic properties as well as intercalation voltages in compounds containing transition-metal (TM) elements. For such systems, density-functional theory (DFT) with standard (semi-)local exchange-correlation functionals is of limited use as it often fails due to strong self-interaction (delocalization) errors that are especially large for the partially filled d shells of the TMs. Here, we perform the first comparative study of the phospho-olivine cathode materials LixMnPO4, LixFePO4, and mixed-TM LixMn1/2Fe1/2PO4 (x=0, 1/4, 1/2, 3/4, 1) using four electronic structure methods: DFT, DFT+U, DFT+U+V, and HSE06. We show that DFT+U+V outperforms the other three methods, provided that the onsite U and intersite V Hubbard parameters are determined from first-principles and self-consistently with respect to the structural parameters by means of density-functional perturbation theory (linear response). In particular, we demonstrate that DFT+U+V is the only method that correctly predicts the digital change in oxidation states of the TM ions in all compounds for the mixed-valence phases occurring at intermediate Li concentrations, leading to voltages in remarkable agreement with experiments. We thus show that the inclusion of intersite Hubbard interactions is essential for the accurate prediction of thermodynamic quantities when electronic localization occurs while in the presence of inter-atomic orbital hybridization. At variance with the other methods, DFT+U+V alone is capable to describe such localization-hybridization interplay, and thus opens the door for the study of more complex cathode materials as well as for a reliable exploration of the chemical space of compounds for Li-ion batteries.

en: Accurate electronic properties and intercalation voltages of olivine-type Li-ion cathode materials from extended Hubbard functionals

cscs

display_name: cscs

dftu

display_name: dftu

dftuv

display_name: dftuv

extended-hubbard-functionals

display_name: extended-hubbard-functionals

first-principles-calculations

display_name: first-principles-calculations

formation-energy

display_name: formation-energy

hybrid-functionals

display_name: hybrid-functionals

intercalation-voltages

display_name: intercalation-voltages

li-ion-batteries

display_name: li-ion-batteries

phospho-olivine-cathode-materials

display_name: phospho-olivine-cathode-materials


materialscloud

en: Materials Cloud


en: Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements frequently need theoretical support in order to unambiguously decipher and assign complex spectra. Linear-response theory provides an effective way to obtain the higher-order derivatives needed, but its applicability to modern exchange-correlation functionals remains limited. Here, we devise an automated, open-source, user-friendly approach based on ground-state density-functional theory and the electric enthalpy functional to allow seamless calculations of first-principles infrared and Raman spectra. By employing a finite-displacement and finite-field approach, we allow for the use of any functional, as well as an efficient treatment of large low-symmetry structures. Additionally, we propose a simple scheme for efficiently sampling the Brillouin zone with different electric fields. To demonstrate the capabilities of our approach, we provide illustrations using the ferroelectric LiNbO₃ crystal as a paradigmatic example. We predict infrared and Raman spectra using various (semi)local, Hubbard corrected, and hybrid functionals. Our results also show how PBE0 and extended Hubbard functionals yield in this case the best match in term of peak positions and intensities, respectively.

en: Automated all-functionals infrared and Raman spectra

ab-initio

display_name: ab-initio

aiida

display_name: aiida

automated

display_name: automated

density-functional-theory

display_name: density-functional-theory

infrared

display_name: infrared

phonons

display_name: phonons

raman

display_name: raman

vibrational-properties

display_name: vibrational-properties