en: Graph neural networks are a popular deep-learning architecture in applications to materials and molecules, and the most widespread implementations rely on interatomic distances as geometric descriptors. Unfortunately, GNNs based on distances are not complete, i.e. there are geometries, corresponding to molecules and/or periodic structures, that are indistinguishable by the GNN. For these, the corresponding machine-learning models will be unable to learn differences in the properties of the "degenerate" structures. This dataset contains a collection of molecular and solid structures that cannot be discriminated by distance-based graph neural networks, together with example code showing how to parse them and use to demonstrate the shortcomings of this class of machine-learning algorithms.

en: Incompleteness of graph neural networks for points clouds in three dimensions

materialscloud

en: Materials Cloud

graph-neural-networks

display_name: graph-neural-networks

machine-learning

display_name: machine-learning

marvel

display_name: marvel

point-clouds

display_name: point-clouds


$oid: OBSOLETE

en: The design of stealthy hyperuniform (SHU) materials has been a critical topic in realizing bandgap materials without crystalline order. Most previous approaches to constructing SHU materials, such as the collective coordinate method, have assumed the closed system, maintaining the number of particles inside a system during the design process. Here, I develop the concept of evolving wave networks, allowing for the open-system design of disordered materials based on the evolution process. The programs are applied to introduce the concept of evolving wave networks (Code_Set_Fig_2), classify material states according to network parameters (Code_Set_Fig_3), generate the stealthy hyperuniformity (SHU) shielding of existing materials (Code_Set_Fig_4), realize preferential attachment in evolving wave networks (Code_Set_Fig_5), and obtain the following phase diagram of disordered materials (Code_Set_Fig_6).

en: Evolving scattering networks for material classification, stealthy hyperuniform shielding, preferential attachment, and material phase diagram

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).

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

disordered-material

display_name: disordered-material

evolution

display_name: evolution

network

display_name: network

scattering

display_name: scattering


en:
Seven imidazolium-based ionic liquids (ILs) with different anions and cations were investigated as catholytes for the CO₂ electrocatalytic reduction to CO over silver. A significant activity and stability, but different selectivities for CO₂ reduction or the side H₂ evolution were observed. Density functional theory results show that the role of the IL anions is to tune the ratio between the CO₂ captured and electrochemically converted. Acetate anions (being strong Lewis bases) are more prone to CO₂ capture, enhancing H₂ evolution, while fluorinated anions (being weaker Lewis bases) favour the CO₂ electroreduction. Differently from the hydrolytically unstable 1-butyl-3-methylimidazolium tetrafluoroborate, 1-Butyl-3-Methylimidazolium Triflate was the most promising IL showing the highest Faradaic efficiency to CO (>95%), up to 8h of stable operation at high current rates (-20mA & -60 mA).
These results open the way for a strategic selection of the most suitable IL for the CO₂ electroreduction and its future process scale-up.

en: Understanding imidazolium-based ionic liquids role in the CO₂ electroreduction reaction: experimental and theoretical study

dft

display_name: dft

experimental

display_name: experimental

free-energy

display_name: free-energy

quantum-espresso

display_name: quantum-espresso


en: The phase of the quantum-mechanical wave function can encode a topological structure with wide-ranging physical consequences, such as anomalous transport effects and the existence of edge states robust against perturbations. While this has been exhaustively demonstrated for electrons, properties associated with the elementary quasiparticles in magnetic materials are still underexplored. Here, we show theoretically and via inelastic neutron scattering experiments that the bulk ferromagnet Mn₅Ge₃ hosts gapped topological Dirac magnons. Although inversion symmetry prohibits a net Dzyaloshinskii-Moriya interaction in the unit cell, it is locally allowed and is responsible for the gap opening in the magnon spectrum. This gap is predicted and experimentally verified to close by rotating the magnetization away from the c-axis. Hence, Mn₅Ge₃ is the first realization of a gapped Dirac magnon material in three dimensions. Its tunability by chemical doping or by thin film nanostructuring defines an exciting new platform to explore and design topological magnons.

en: Topological magnons driven by the Dzyaloshinskii-Moriya interaction in the centrosymmetric ferromagnet Mn₅Ge₃

dzyaloshinskii-moriya-interaction

display_name: dzyaloshinskii-moriya-interaction

inelastic-neutron-scattering

display_name: inelastic-neutron-scattering

spin-waves

display_name: spin-waves

topological-magnon

display_name: topological-magnon


en: We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the probability distribution of the off-diagonal elements of a Wishart matrix, we develop a consistent and unbiased estimator for the Seebeck coefficient, whose statistical uncertainty can be arbitrarily reduced in the long-time limit. We assess the efficacy of our method by benchmarking it against extensive equilibrium molecular dynamics simulations conducted on molten CsF using empirical force fields. We then employ this procedure to calculate the Seebeck coefficient of molten NaCl, KCl and LiCl using neural network force fields trained on ab initio data over a range of pressure-temperature conditions.

en: Seebeck coefficient of ionic conductors from Bayesian regression analysis

bayesian

display_name: bayesian

ionic-conductors

display_name: ionic-conductors

seebeck

display_name: seebeck


en: Photocatalytic conversion of CO₂ into fuel feed stocks is a promising method for sustainable fuel production. A highly attractive class of materials, inorganic-core@metal–organic-framework heterogeneous catalysts, boasts a significant increase in catalytic performance when compared to the individual materials. However, due to the ever-expanding chemical space of inorganic-core catalysts and metal–organic frameworks (MOFs), identification of these optimal heterojunctions is difficult without appropriate computational screening. In this work, a novel high-throughput screening method of nano-hybrid photocatalysts is presented by screening 65'784 inorganic-core materials and 20'375 MOF-shells for their ability to reduce CO₂ based on their synthesizability, aqueous stability, visible light absorption, and electronic structure; the passing materials were then paired based on their electronic structure to create novel heterojunctions. The results showed 58 suitable inorganic-core materials and 204 suitable MOFs ranging from never-beforesynthesized catalysts to catalysts that have been overlooked for their photocatalytic ability. These materials lay a new foundation of photocatalysts that have passed theoretical requirements and can significantly increase the rate of catalyst discovery.

en: High-throughput screening of nano-hybrid metal–organic-frameworks for photocatalytic CO₂ reduction

coreshell

display_name: coreshell

metal-organic-frameworks

display_name: metal-organic-frameworks

photocatalyst

display_name: photocatalyst


neural-network-potential-for-zr-h

en: The introduction of Hydrogen (H) into Zirconium (Zr) influences many mechanical properties, especially due to low H solubility and easy formation of Zirconium hydride phases. Understanding the various effects of H requires studies with atomistic resolution but at scales that incorporate defects such as cracks, interfaces, and dislocations. Such studies thus demand accurate interatomic potentials. Here, a neural network potential (NNP) for the Zr-H system is developed within the  Behler-Parrinello framework. The Zr-H NNP retains the accuracy of a recent NNP for hcp Zr and exhibits excellent agreement with first-principles density functional theory (DFT) for (i) H interstitials and their diffusion in hcp Zr, (ii) formation energies, elastic constants, and surface energies of relevant Zr hydrides, and (iii) energetics of a common Zr/Zr-H interface. The Zr-H NNP shows physical behavior for many different crack orientations in the most-stable ε-hydride and structures and reasonable relative energetics for the ⟨a⟩ screw dislocation in pure Zr. This Zr-H NNP should thus be very powerful for future study of many phenomena driving H degradation in Zr that require atomistic detail at scales far above those accessible by first-principles

en: Neural network potential for Zr-H

title_for_slug: neural-network-potential-for-zr-h

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potentials

display_name: neural-network-potentials

zirconium-hydrides

display_name: zirconium-hydrides


en: Thermal annealing experiments evidence opposite effect on the degradation kinetics of Cu/W nano-multilayers from compressive to tensile in-plane strain.  Besides higher activation energy, nano-multilayers with tensile strains degrade to nanocomposites faster than those with compressive strains. By assuming a vacancy-driven diffusion mechanism of degradation, we applied ab initio calculations to quantify different contributions to the corresponding diffusion coefficients in relation to in-plane strain. The average vacancy formation energy increases as the strain changes from compressive to tensile, which explains the higher experimental activation energy. The bulk in-plane and out-of-plane vacancy migration energies and corresponding diffusion prefactors highlight that enhanced transformation rate under tension can be explained by the segregation of non-equilibrium W vacancies to Cu/W interfaces. Our thermodynamic evaluation of grain boundary wetting and grooving by hybrid molecular dynamics/Monte Carlo method further supports this point, as both stress states enhance W grain separation to the same level.

en: Explaining the effect of in-plane strain on thermal degradation kinetics of Cu/W nano-multilayers

ab-initio-calculations

display_name: ab-initio-calculations

cuw

display_name: cuw

degradation-kinetics

display_name: degradation-kinetics

in-plane-strain

display_name: in-plane-strain

nano-multilayers

display_name: nano-multilayers

vacancy-driven-diffusion

display_name: vacancy-driven-diffusion


en: Topological materials have been a main focus of studies in the past decade due to their protected properties that can be exploited for the fabrication of new devices. Among them, Weyl semimetals are a class of topological semimetals with non-trivial linear band crossing close to the Fermi level. The existence of such crossings requires the breaking of either time-reversal or inversion symmetry and is responsible for the exotic physical properties. In this work we identify the full-Heusler compound InMnTi₂, as a promising, easy to synthesize, T- and I-breaking Weyl semimetal. This material exhibits several features that are comparatively more intriguing with respect to other known Weyl semimetals: the distance between two neighboring nodes is large enough to observe a wide range of linear dispersions in the bands, and only one kind of such node's pairs is present in the Brillouin zone. We also show the presence of Fermi arcs stable across a wide range of chemical potentials. Finally, the lack of contributions from trivial points to the low-energy properties makes the materials a promising candidate for practical devices.

en: Prediction of a novel type-I antiferromagnetic Weyl semimetal

materialscloud

en: Materials Cloud

surface-properties

display_name: surface-properties

topological-materials

display_name: topological-materials

weyl-semimetal

display_name: weyl-semimetal


en: The accurate description of redox reactions remains a challenge for first-principles calculations, but it has been shown that extended Hubbard functionals (DFT+U+V) can provide a reliable approach, mitigating self-interaction errors, in materials with strongly localized d or f electrons. Here, we first show that DFT+U+V molecular dynamics is capable to follow the adiabatic evolution of oxidation states over time, using representative Li-ion cathode materials.  In turn, this allows to develop redox-aware machine-learned potentials. We show that considering atoms with different oxidation states (as accurately predicted by DFT+U+V) as distinct species in the training leads to potentials that are able to identify the correct ground state and pattern of oxidation states for redox elements present. This is achieved, e.g., trough a combinatorial search for the lowest energy configuration. This brings the advantages of machine-learned potential to key technological applications (e.g., rechargeable batteries), which require an accurate description of the evolution of redox states.

en: Teaching oxidation states to neural networks

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).

dftuv

display_name: dftuv

machine-learning

display_name: machine-learning

max

display_name: max

oxidation-states

display_name: oxidation-states


en: Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describing the interactions between atoms,  hich is further complicated by chemical order through cross-species interactions. The large scales needed to observe rare nucleation events are far beyond the capabilities of ab initio simulations. Machine-learning is used for overcoming these limitations in terms of both accuracy and speed, by building a high-dimensional neural network potential for binary Al-Ni alloys, which serve as a model system relevant to many industrial applications. The potential is validated against experimental diffusion, viscosity, and scattering data, and is applied to large-scale molecular dynamics simulations of homogeneous nucleation at equiatomic composition, as well as for pure Ni. Pure Ni nucleates in a single-step into an fcc crystal phase, in contrast to previous results obtained with a classical empirical potential. This highlights the sensitivity of nucleation pathways to the underlying atomic interactions. Our findings suggest that the nucleation pathway for AlNi proceeds in a single step toward a B2 structure, which is discussed in relation to the pure elements counterparts.

en: Homogeneous nucleation of undercooled Al-Ni melts via a machine-learned interaction potential

envi

en: Environment

aluminium

display_name: aluminium

interaction-potential

display_name: interaction-potential

nickel

display_name: nickel


en: The dataset provides records of tensile properties of nuclear structural materials. The focus is on studying the influence of specimen dimensions and geometry on mechanical properties such as yield strength, ultimate tensile strength, uniform elongation, and total elongation. The dataset was created through an extensive literature review of scientific articles and databases. The search inclusion criteria targeted peer-reviewed studies on tensile testing of sub-sized specimens, providing quantitative data on tensile properties relative to specimen size. The extracted data points from the literature review were organized into a tabular format database containing 1,070 tensile testing records with 54 parameters, including material type and composition, manufacturing information, irradiation conditions, specimen size and dimensions, and tensile properties. Materials science experts conducted systematic checks to validate the collected data, ensuring accuracy in the material type, manufacturing processes and treatment methods, and testing conditions, as well as verifying the chemical composition and other pertinent information. Our team performed statistical analyses to identify and address data outliers, ensuring the reliability of the dataset.

en: Dataset of tensile properties for sub-sized specimens of nuclear structural materials

nuclear-structural-materials

display_name: nuclear-structural-materials

specimen-size-effect

display_name: specimen-size-effect

sub-sized-specimens

display_name: sub-sized-specimens

tensile-properties

display_name: tensile-properties


en:
The intermetallic quasi-one-dimensional binary superconductor V2Ga5 was recently found to exhibit a topologically nontrivial normal state, making it a natural candidate for a topological superconductor.
By combining dc-magnetization, nuclear magnetic resonance, and muon-spin rotation (µSR) measurements on high-quality V2Ga5 single crystals, we investigate the electronic properties of its normal- and superconducting ground states. NMR measurements in the normal state indicate a strong anisotropy in both the line shifts and the relaxation rates. Such anisotropy persists also in the superconducting state, as shown by the magnetization and µSR-spectroscopy results. In the latter case, data collected at different temperatures, pressures, and directions of the magnetic field (with respect to the crystalline axes) evidence a fully-gapped, strongly anisotropic superconductivity. At the same time, hydrostatic pressure is shown to only lower the Tc value, but not to change the superfluid density nor its temperature dependence. Lastly, we discuss the search for topological signatures in the normal state of V2Ga5, as well as a peak splitting in the FFT of the µSR spectrum, possibly related to an unconventional vortex lattice. Our results suggest that V2Ga5 is a novel system, whose anisotropy plays a key role in determining its unusual electronic properties.

en: Anisotropic superconductivity in the quasi-one-dimensional superconductor

nuclear-magnetic-resonance

display_name: nuclear-magnetic-resonance

superconductivity

display_name: superconductivity


en: Solidification control is crucial in manufacturing technologies, as it determines the microstructureand,  consequently,  the performance of the final product.  Investigating the mechanisms occurring during the early stages of nucleation remains experimentally challenging as it initiates on nanometer length and sub-picoseconds time scales.  Large scale molecular dynamics simulations using machinelearning interatomic potential with quantum accuracy appears the dedicated approach to complex,atomic level, multidimensional mechanisms with local symmetry breaking.  A potential trained ona high-dimensional neural network on density functional theory-based ab initio molecular dynamics(AIMD) trajectories for liquid and undercooled states for Al-Si binary alloys enables us to study the  nucleation  mechanisms  occurring  at  the  early  stages  from  the  liquid  phase  near  the  eutectic composition.  Our results indicate that nucleation starts with Al at hypoeutectic compositions and with Si at hypereutectic compositions.  Whereas Al nuclei grow in a globular shape, Si ones grow with polygonal faceting, whose underlying mechanisms are further discussed.

en: Crystal nucleation in eutectic Al-Si alloys by machine-learned molecular dynamics

aluminum-silicon

display_name: aluminum-silicon

hdnnp

display_name: hdnnp

machine-learning-interatomic-potential

display_name: machine-learning-interatomic-potential


en: We report a first-principles study of the electronic and optical properties of recently identified one-dimensional semiconducting materials exfoliable from van der Waals-bonded bulk crystals. Specifically, we investigate four chalcogenide-based atomic chains, the covalently bonded S3 and Te3 chains, and polar-bonded As2S3 and Bi2Te3 chains, using a fully first-principles approach that combines density functional theory (DFT), density functional perturbation theory (DFPT), and many-body perturbation theory within the GW approximation and Bethe−Salpeter equation (BSE). Our vibrational analysis shows that the isolated, freestanding wires remain dynamically stable, with the zone-center optical phonon modes leading to infrared activity. The main finding of this study is the presence of very strong exciton binding energies (1−3 eV), which make these exfoliable 1D materials suitable platforms for room-temperature excitonic applications. Interestingly, the exciton character remains Wannier−Mott-like, as indicated by average electron−hole separations greater than the lattice constant. Notably, the optical gaps of these materials span a wide range - from infrared (0.8 eV, Bi2Te3), through the visible spectrum (yellow: 2.17 eV, Te3; blue: 2.71 eV, As2S3), up to ultraviolet (4.07 eV, S3) - highlighting their versatility for broadband optoelectronic applications. Our results offer a detailed, many-body perspective on the optoelectronic behavior of these low-dimensional materials and underscore their potential for applications in nanoscale optoelectronic devices.

en: Quasiparticle effects and strong excitonic features in exfoliable 1D semiconducting materials

dft

display_name: dft

exciton

display_name: exciton

gw

display_name: gw

one-dimensional-materials

display_name: one-dimensional-materials

phonons

display_name: phonons

van-der-waals-wires

display_name: van-der-waals-wires


en: This dataset contains experimental and theoretical results from the study of heat transport in suspended single-crystal diamond cantilevers with sub-micrometer widths. "Imaging heat transport in suspended diamond nanostructures with integrated spindefect thermometers", Physical Review Letters, 2026Temperature profiles are measured using embedded nitrogen-vacancy (NV) spin defects acting as in-situ thermometers, enabling spatially resolved thermal mapping under laser heating. The data include measured temperature gradients, extracted effective thermal conductivities as a function of cantilever width, and first-principles simulations based on the linearized phonon Boltzmann transport equation and viscous heat equations. The combined experimental and computational results demonstrate non-diffusive, sub-ballistic heat transport arising from the interplay of intrinsic phonon scattering and boundary effects.

en: Imaging heat transport in suspended diamond nanostructures with integrated spin defect thermometers

diamond-nanostructures

display_name: diamond-nanostructures

heat-transport

display_name: heat-transport

nanoscale-thermometry

display_name: nanoscale-thermometry

nitrogen-vacancy-centers

display_name: nitrogen-vacancy-centers

non-diffusive-thermal-conduction

display_name: non-diffusive-thermal-conduction

phonon-boltzmann-transport-equation

display_name: phonon-boltzmann-transport-equation

viscous-heat-equations

display_name: viscous-heat-equations


en: Defect engineering in two-dimensional semiconductors has been exploited to tune the optoelectronic properties and introduce new quantum states in the band gap. Chalcogen vacancies in transition metal dichalcogenides in particular have been found to strongly impact charge carrier concentration and mobility in 2D transistors as well as feature subgap emission and single-photon response. In this Letter, we investigate the layer-dependent charge-state lifetime of Se vacancies in WSe2. In one monolayer WSe2,we observe ultrafast charge transfer from the lowest unoccupied orbital of the top Se vacancy to the graphene substrate within 1 ± 0.2 ps measured via the current saturation in scanning tunneling approach curves. For Se vacancies decoupled by transition metal dichalcogenide (TMD) multilayers, we find a subexponential increase of the charge lifetime from 62 ±14 ps in bilayer to a few nanoseconds in four-layer WSe2, alongside a reduction of the defect state binding energy. Additionally, we attribute the continuous suppression and energy shift of the dI=dV in-gap defect state resonances at very close tip-sample distances to a current saturation effect. Our results provide a key measure of the layer-dependent charge transfer rate of chalcogen vacancies in TMDs.

en: Layer-dependent charge-state lifetime of single Se vacancies in WSe2

materialscloud

en: Materials Cloud

defect-engineering

display_name: defect-engineering

scanning-tunneling-microscopy-stm

display_name: scanning-tunneling-microscopy-stm

transition-metal-dichalcogenide-tmd

display_name: transition-metal-dichalcogenide-tmd


en: Two-dimensional topological insulators are characterized by an insulating bulk and conductive edge states protected by the nontrivial topology of the bulk electronic structure. They remain robust against moderate disorder until Anderson localization occurs and destroys the topological phase. Interestingly, disorder can also induce a topological phase—known as a topological Anderson insulator—starting from an otherwise pristine trivial phase. While topological invariants are generally regarded as global quantities, we argue that space-resolved topological markers can act as local order parameters, revealing the role of fluctuations and correlations in the local topology under Anderson disorder and vacancies. With this perspective, we perform numerical simulations of disorder-driven topological phase transitions in the Haldane and Kane-Mele models, using supercells with both open and periodic boundary conditions. We find that short-scale fluctuations of topological markers vanish upon coarse-graining, except at the topological phase transition, where their correlation length peaks and large-scale fluctuations remain. Notably, such a topological correlation function is characterized by critical exponents that appear universal across disorder types, yet they can resolve different topological phase transitions.

en: Fluctuations and correlations of local topological order parameters in disordered two-dimensional topological insulators

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).

anderson-disorder

display_name: anderson-disorder

critical-exponents

display_name: critical-exponents

fluctuations-and-correlations

display_name: fluctuations-and-correlations

haldane-model

display_name: haldane-model

kane-mele-model

display_name: kane-mele-model

local-topology

display_name: local-topology

topological-order-parameters

display_name: topological-order-parameters

vacancies

display_name: vacancies


en: Lithium thiophosphate (LPS) has demonstrated promising properties for use as a solid electrolyte for the next-generation of lithium ion batteries. However, the high reactivity of LPS with common contaminants such as atmospheric water hinders commercialization of the cells. We employ a machine learning interatomic potential to gain fundamental, atomistic understanding on the mechanical, chemical and electronic properties of an LPS surface. Our focus lies first on the identification of relevant surface complexions formed by surface reconstructions, which differ greatly in properties from the bulk and define the form of the reactive sites. Then, we reveal the complex reactivity of the LPS surface with water and identify the surface moieties that play a relevant role in the material’s degradation. Thus, we uncover the impact of dynamical changes of the surfaces and their electronic structure on the material’s reactivity.This dataset includes all files necessary to reproduce the data reported in Reconstructions and dynamics of 𝛽 -lithium thiophosphate surfaces.This includes the MLIP model and dataset, generated surface structures with certain Miller indices, Wulff constructions, as well the input and result files of LAMMPS and DFT calculations.

envi

en: Environment

deutsche-forschungsgemeinschaft

display_name: deutsche-forschungsgemeinschaft

lps

display_name: lps

machine-learning

display_name: machine-learning

machine-learning-interatomic-potentials

display_name: machine-learning-interatomic-potentials

marvel

display_name: marvel

molecular-dynamics

display_name: molecular-dynamics

smoothsoap

display_name: smoothsoap

solid-electrolyte

display_name: solid-electrolyte

surface-complexion

display_name: surface-complexion


en: Experiments reveal negative (non-Laplacian) surface stresses in metal oxide nanoparticles, partly associated with humidity during fabrication and annealing. Using a neural network interatomic potential for MgO, we prove that water adsorption induces surface hydroxylation, shifting facets from {100} to {110} to {111} and switching the average surface stress from positive to negative. Predicted lattice strains versus nanoparticle size agree well with experiments, clarifying experimental correlations. The new framework informs broad applications in catalysis, sensors, batteries, and biomedicine.

en: Hydroxylation-driven surface reconstruction at the origin of compressive-to-tensile stress transition in metal oxide nanoparticles

nanoparticles

display_name: nanoparticles

surface-reconstruction

display_name: surface-reconstruction

surface-stress

display_name: surface-stress

xrd

display_name: xrd


en: The electron-phonon Wannier interpolation (EPWI) method is an efficient way to compute the properties of electron-phonon interactions (EPIs) accurately. This study presents a GPU-accelerated implementation of the EPWI method for computing transport properties, followed by a performance analysis. The implementation is tested on common systems such as aluminum andsilicon. The results show complete consistency with those obtained through CPU computations. The proposed algorithm has the capability of computing the conductivity of aluminum in 20 minutes on a single NVIDIA Tesla V100 GPU, adopting a 2003 electron and phonon sampling grid. This speed is 54 times higher than the CPU-based algorithm, running on two nodes of the Intel Xeon Platinum 8260 CPU. Such impressive acceleration is achieved by carefully designing the algorithm to exploit the GPU’s specific features. The idea of this approach can also be applied to the GPU code for other EPI-related properties. This record includes the input/output files of this work. The code snippets of the core GPU implementation can be found in https://github.com/zheliu137/EPWI_BTE_GPU

en: A high-performance GPU implementation of the electron-phonon Wannier interpolation and the related transport properties

boltzmann-transport-equation

display_name: boltzmann-transport-equation

electron-phonon-coupling

display_name: electron-phonon-coupling

gpu-acceleration

display_name: gpu-acceleration


en: Density functional theory calculations have been a pillar of computational materials science in the past two decades, and the recent development of AI and data-driven methods has reiterated their importance. ABACUS (Atomic-orbital Based Ab-initio Computation at USTC) is an open-source density functional theory code that supports both plane-wave and numerical atomic orbital basis sets. It is designed as a versatile platform integrating various electronic structure methods and is particularly well-suited for deep-learning-assisted materials simulations. The accuracy of a density functional theory code is crucial for its wide deployment. In this work, we use the verification protocol established by E. Bosoni et al. [Nat. Rev. Phys. 6, 45-58 (2024)] based on the AiiDA common workflows framework to validate the precision of ABACUS by comparing its results with previously generated all-electron benchmarks. Our results show that, using consistent pseudopotentials and comparable calculation settings, ABACUS yields highly consistent results compared to other established codes such as QE, Abinit, and CASTEP. This entry contains all the data, calculations, and scripts required to reproduce the results.

en: Precision verification results data for ABACUS@PW|PseudoDojo-v0.4

automation

display_name: automation

dft

display_name: dft

equation-of-state

display_name: equation-of-state

pseudopotentials

display_name: pseudopotentials

verification

display_name: verification


en: The direct conversion of methane to methanol (DCMM) under continuous flow and atmospheric pressure offers notable environmental benefits and industrial promise, but remains a long-standing challenge due to the difficulty of activating CH4 while avoiding over-oxidation of methanol. Here, we demonstrate that pure ceria (CeO2), without any metal promoters, enables gas-phase DCMM with up to 80 % selectivity at 300–350 °C, upon optimization of the H2O/O2 ratio. At 550 °C, methanol and formaldehyde are formed at rates of 24 and 36 μmol g-1 h-1, respectively-both dropping below 1 μmol g-1 h-1 in the absence of O2. Ex situ transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and Raman spectroscopy confirm that CeO2 maintains structural integrity and resists carbon deposition during reaction. Combining kinetic studies, steady-state in-situ diffuse reflectance infrared Fourier transform spectroscopy (in-situ DRIFTS), and density functional theory (DFT) reveals that hydroxyl groups (OH), generated from water dissociation, play a multifaceted role: they facilitate C–H bond activation, promote methoxy formation, and enhance methanol desorption. In-situ ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) directly reveals the evolution of surface intermediates and shows that co-feeding O2 and H2O suppresses CH3O and CHx accumulation while boosting methanol yield—indicating a rapid intermediate turnover as key to sustained activity. AP-XPS O 1s spectra further highlight that O2 promotes H2O dissociation, regenerating reactive OH groups and maintaining performance at elevated temperature. These findings offer molecular-level insights into how water and oxygen cooperatively tune reactivity, enabling efficient methane-to-methanol conversion on a metal-free oxide catalyst.

en: Synergy of oxygen and water in ceria-catalyzed direct conversion of methane to methanol under continuous flow

ap-xps

display_name: ap-xps

in-situ

display_name: in-situ

in-situ-drifts

display_name: in-situ-drifts

methane-to-methanol

display_name: methane-to-methanol

reaction-mechanism

display_name: reaction-mechanism


en: We present a comprehensive first-principles study of the magnetoresistance in ZrSiX (X = S, Se, Te) topological nodal-line semimetals. Our study demonstrates that all primary features of the experimentally measured magnetoresistance in these materials are captured by our calculations, including the unusual butterfly-shaped anisotropic magnetoresistance. This anisotropic magnetoresistance can be accurately reproduced using the semiclassical Boltzmann transport theory without introducing any information on the topological nature of bands or the concepts of topological phase transition. Considering the complex structure of the Fermi surface in these topological materials, we develop a theoretical description explaining the features observed in magnetoresistance measurements. Additionally, the atypical Hall resistance can be interpreted by the same semiclassical approach. Our findings establish magnetotransport as a powerful tool for analyzing the geometry of the Fermi surface, complementing angle-resolved photoemission spectroscopy and quantum oscillation measurements. This approach is demonstrated to be particularly useful for determining the role of non-trivial topology in transport properties.

en: Magnetoresistance in ZrSiX (X = S, Se, Te) nodal-line semimetals

boltzmann-theory

display_name: boltzmann-theory

density-functional-calculations

display_name: density-functional-calculations

fermi-surface

display_name: fermi-surface

first-principles-calculations

display_name: first-principles-calculations

hall-effect

display_name: hall-effect

magnetoresistance

display_name: magnetoresistance

node-line-semimetals

display_name: node-line-semimetals

topological-materials

display_name: topological-materials


en: Cobalt-based oxides have been investigated as potential alternatives to Ir/Ru-based oxides for catalyzing the oxygen evolution reaction (OER) in acidic media. Past research, however, is mainly focused on the spinel oxide structure so far. Exploring alternative crystal structures is essential for expanding the material library and developing highly efficient OER catalysts for acidic environments. As a proof of concept, we demonstrate that Co-based perovskite oxides can drive acidic OER effectively. Appling hard/soft X-ray absorption spectroscopy (hXAS/sXAS) characterizations, we show that the La and Ce doped SrCoO3 (denoted as LSC and CSC, respectively) have a bulk-average Co oxidation state close to 3+ and surface-dominant low-spin CoIII species. Electrochemical analysis reveals that they only show one Co redox pair, similar to CoOOH in acidic environments. The recorded Tafel slopes are around ~65 mV dec-1, comparable to the benchmarking Ir/Ru-based catalysts. The combination of the spectroscopic and electrochemical findings presented here highlights the important role of low-spin CoIII species in catalyzing OER in acidic environments and contributes to the rational design of non-noble metal OER catalysts.

en: Cobalt-based perovskite oxides as catalysts for acidic oxygen evolution reaction

acidic-oxygen-evolution-reaction

display_name: acidic-oxygen-evolution-reaction

cobalt-based-catalysts

display_name: cobalt-based-catalysts

cobalt-oxidation-state

display_name: cobalt-oxidation-state

experimental

display_name: experimental

perovskite-oxides

display_name: perovskite-oxides

x-ray-adsorption-spectroscopy

display_name: x-ray-adsorption-spectroscopy


en: The total energy is a fundamental characteristic of solids, molecules, and nanostructures. In most first-principles calculations of the total energy, the nuclear kinetic operator is decoupled from the many-body electronic Hamiltonian and the dynamics of the nuclei is reintroduced afterwards. This two-step procedure introduced by Born and Oppenheimer (BO) is approximate. Energies beyond the electronic and vibrational (or phononic) main contributions might be relevant when small energy differences are important, such as when predicting stable polymorphs or describing magnetic energy landscape. We clarify the different flavors of BO decoupling and give an exact formulation for the total energy in the basis of BO electronic wavefunctions. Then, we list contributions, beyond the main ones, that appear in a perturbative expansion in powers of M0-1/4, where M0 is a typical nuclear mass, up to sixth order. Some of these might be grouped and denoted the electron-phonon contribution to total energy,  Eelph, that first appears at fourth order. The electronic inertial mass contributes at sixth order. We clarify that the sum of the Allen-Heine-Cardona zero-point renormalization of eigenvalues over occupied states is not the electron-phonon contribution to the total energy but a part of the phononic contribution. The computation of the lowest-order Eelph is implemented and shown to be small but non-negligible (3.8 meV per atom) in the case of diamond and its hexagonal polymorph. We also estimate the electronic inertial mass contribution and confirm the size-consistency of all computed terms.

en: In search of the electron-phonon contribution to total energy

materialscloud

en: Materials Cloud

ab-initio

display_name: ab-initio

diamond

display_name: diamond

electron-phonon-coupling

display_name: electron-phonon-coupling

total-energy

display_name: total-energy


en: Photothermal (photonic) sintering crystallizes as-deposited amorphous LiCoO2 (LCO) cathodes for solid-state thin-film batteries using millisecond, surface-localized heating. However, process design often relies on 1D models with phase-averaged, temperature-independent properties, which can mispredict peak temperatures and thermal damage margins. Here we develop a multiscale, data-driven framework that provides phase- and grain-size–resolved thermophysical inputs for stoichiometric LCO. We train an Allegro neural network potential with near-ab initio accuracy, enabling Green–Kubo calculations of thermal conductivity for crystalline and amorphous phases. The low, weakly density-dependent conductivity of amorphous LCO motivates its use as an effective intergranular phase in a thin-interface model that reproduces observed grain-size–dependent thermal transport. Combined with measured wavelength-resolved optical properties in 1D multiphysics simulations, we show amorphous LCO absorbs more strongly and reaches higher peak temperatures than crystalline LCO; thus crystalline, constant-property models systematically overestimate safe operating windows.

en: Critical role of phase-dependent properties in modeling photothermal sintering of LiCoO2 cathodes

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).

heat-transfer

display_name: heat-transfer

molecular-dynamics

display_name: molecular-dynamics

neural-network-potential

display_name: neural-network-potential

photonic-sintering

display_name: photonic-sintering

thermal-conductivity

display_name: thermal-conductivity


en: Mechanical properties of ultrathin coatings can deviate from bulk values due to growth-stage and interface effects. Elastic moduli of bulk amorphous alumina were calculated using a near-ab initio-accurate neural-network interatomic potential to provide a modeling benchmark for hydroxylated alumina coatings deposited by atomic layer deposition at 50 °C. Experimentally, elastic moduli were evaluated by both spherical nanoindentation and laser-induced surface acoustic wave spectroscopy (LiSAWS). For coatings thicker than 7 nm, both techniques indicated a weakly decreasing modulus from ~137 GPa to ~126 GPa (nanoindentation) and ~116 GPa to ~108 GPa (LiSAWS). These values are consistent with the simulated Young’s modulus.

en: Modulus and yield strength determination at ultra-thin atomic layer deposited hydroxylated alumina coatings using spherical nanoindentation and surface acoustic waves

envi

en: Environment

atomic-layer-deposition-ald

display_name: atomic-layer-deposition-ald

foundation-model

display_name: foundation-model

hydroxylated-alumina

display_name: hydroxylated-alumina

spherical-nanoindentation

display_name: spherical-nanoindentation

ultrathin-coatings

display_name: ultrathin-coatings

yield-strength

display_name: yield-strength

youngs-modulus

display_name: youngs-modulus


en: We study the electronic structure and dynamical correlations in antiferromagnetic BiFeO3, a prototypical room-temperature multiferroic, using a variety of static and dynamical first-principles methods. Conventional static Hubbard corrections (DFT+U, DFT+U+V) incorrectly predict a deep-valence Fe 3d peak (around -7 eV) in antiferromagnetic BiFeO3, in contradiction with hard-X-ray photoemission. We resolve this failure by using a recent generalization of DFT+U to include a frequency-dependent screening – DFT+U(ω) – or using a dynamical Hubbard functional (dynH). The screened Coulomb interaction U(ω), computed with spin-polarized RPA and projected onto maximally localized Fe 3d Wannier orbitals, is expressed as a sum-over-poles, yielding a self-energy that augments the Kohn–Sham Hamiltonian. This DFT+U(ω) approach predicts a fundamental band gap of 1.53 eV, consistent with experiments, and completely eliminates the unphysical deep-valence peak. The resulting simulated HAXPES spectrum reproduces the experimental lineshape with an accuracy comparable to state-of-the-art approaches. Our work highlights the critical nature of dynamical screening in complex oxides and of DFT+U(ω) as a predictive and computationally efficient approach to address the electronic structure of correlated materials.

en: Electronic structure and dynamical correlations in antiferromagnetic BiFeO3

density-functional-theory

display_name: density-functional-theory

dynamical-correlations

display_name: dynamical-correlations

electronic-structure

display_name: electronic-structure


en:
This archive provides the AiiDA workflows, metadata, and computational datasets associated with the study of vibrational frequencies and Stark tuning rates at electrochemical interfaces within the framework of grand-canonical density functional theory (GC-DFT) combined with continuum electrochemical models.

In this work, the electrochemical potential is treated as a degree of freedom by adjusting the number of electrons in the Kohn-Sham equations, enabling simulations at fixed potential. Based on the relationship between free energy and grand potential, physical properties such as atomic forces, vibrational frequencies, and Stark tuning rates are consistently evaluated. While atomic forces are found to be equivalent to Hellmann-Feynman forces in the canonical ensemble, vibrational frequencies and Stark tuning rates exhibit distinct behavior under grand-canonical conditions.

The archive contains input parameters, workflows, and computed results obtained using finite-displacement methods for the evaluation of vibrational properties and Stark tuning rates. These data enable the reproduction of the results reported in the associated publication and provide a reference for future studies of electrochemical interfaces under constant potential conditions.

en: Vibrational frequencies and stark tuning rate with continuum electro-chemical models and grand canonical density functional theory

grand-canonical-dft

display_name: grand-canonical-dft

stark-tuning-rate

display_name: stark-tuning-rate

vibrational-frequencies

display_name: vibrational-frequencies


en: This dataset presents the results of a comprehensive crystal structure search for ternary compounds in the Lu–N–H system. Thousands of candidate structures were evaluated, and their thermodynamic stability was assessed through the construction of the convex hull of formation enthalpies. To ensure reliable energetic ordering, all calculations were performed using the highly accurate r2SCAN density functional in an all-electron framework, avoiding possible pseudopotential-related inaccuracies.  A previously unreported lutetium hydride phase (HLu₂) is identified on the convex hull, indicating thermodynamic stability. However, subsequent electron–phonon coupling analysis shows that this structure is not a promising candidate for near-ambient superconductivity. Apart from this additional phase, the results are in close agreement with earlier structure prediction studies, demonstrating strong reproducibility across independent computational approaches. This consistency highlights the maturity and reliability of modern crystal structure prediction methods. Overall, the dataset provides further evidence that no thermodynamically stable structure within the Lu–N–H system is likely to exhibit conventional high-temperature superconductivity under near-ambient conditions, as would be required to explain previously reported experimental claims.

en: Ternary phase diagram of nitrogen doped lutetium hydrides

dft

display_name: dft

minimahopping

display_name: minimahopping

superconductor

display_name: superconductor


en: Strain soliton networks strongly influence the structural and electronic properties of heterodeformed bilayer systems, yet their design remains challenging due to the high dimensionality of heterodeformation space and the absence of a direct map between deformation and network geometry. In this work, we introduce a geometric framework that establishes a one-to-one mapping between heterodeformations and the geometry of the strain soliton network expressed as line vector-Burgers vector pairs. The admissible networks are constrained by topology dictated by the generalized stacking fault energy landscape. We show that the moiré Bravais lattice, corresponding to a uniform heterodeformation, alone is insufficient to characterize the interface: distinct heterodeformations can share identical moiré Bravais lattices while producing different soliton networks, reflecting an inherent many-to-one mapping when only translational symmetry is considered. In contrast, the soliton network encodes the full multilattice geometry of the interface, including topology and connectivity, which are not captured by the moiré Bravais lattice alone. The proposed framework enables the direct construction of heterodeformations from target networks, providing a systematic route for inverse design of moiré interfaces beyond conventional twist-based approaches.

en: Inverse design of heterodeformations for strain soliton networks in bilayer 2D materials

heterodeformations

display_name: heterodeformations

inverse-design

display_name: inverse-design

strain-soliton-networks

display_name: strain-soliton-networks


en: We present a combined density-functional theory and dynamical mean-field theory (DFT+DMFT) study of the full structural phase space of rutile-based vanadium dioxide (VO2), including also the less studied M2 and T phases, using an unconventional bond-centered orbital basis. The use of bond-centered orbitals allows us to treat all main phases of VO2, and the structural transitions between them, using one consistent approach with moderate computational cost and without pre-pattering of the structure into dimerized and undimerized V--V pairs. We obtain two distinct insulating states on the two different types of vanadium chains in the M2 phase, a singlet-insulator on the dimerized chains and a Mott-insulator on the zigzag-distorted chains, which, however, are strongly coupled in the M2 phase and thus the metal-insulator transition always occurs concomitantly for both types of sites. We also demonstrate that the M2 phase corresponds to a local energy minimum in the structural phase space of VO2, the stability of which, apart from the internal structural distortion, depends crucially on the unit cell strain relative to the undistorted rutile phase. Our calculations further indicate that the symmetry-distinct triclinic T phase corresponds electronically to either an M1 or an M2-type insulator with an abrupt transition as a function of distortion. Finally, we disentangle the effect of the dimerization and zigzag distortions by constructing hypothetical structures that contain only one site type, finding that the zigzag distortion strongly favors emergence of the Mott-insulating state, both as function of distortion and on-site interaction.

en: Towards a unified first-principles-based description of VO2 using DFT+DMFT with bond-centered orbitals

dftdmft

display_name: dftdmft

mit

display_name: mit


en:
We establish a set of exact sum rules that relate the interatomic force constants to the frequency-dependent electromagnetic susceptibility of a solid or molecule, thereby generalizing the long-established principles of rototranslational symmetry to the nonadiabatic regime. Crucially, we show that in practical numerical implementations these sum rules are violated, unless special precautions are taken in the treatment of the atomic pseudopotentials. We solve these issues once and for all by correctly adapting the pseudopotential to the motion of the corresponding nucleus, with a velocity dependence of the nonlocal operator. This prescription restores the correct Galilean covariance of the Schr"odinger equation, and the expected identity between mechanical rototranslations and electromagnetic perturbations. These results conclusively fix a number of worrisome inconsistencies that were pointed out over the years in the context of linear-response theory restoring, e.g., the validity of the Larmor theorem, and the equivalence between the inertial and electrical definitions of the Drude weight in metals.

This dataset contains the input and output files used to produce the results presented in the manuscript.

en: Rototranslational sum rules for nuclear dynamics via traveling pseudopotentials

materialscloud

en: Materials Cloud

nonadiabatic-regime

display_name: nonadiabatic-regime

pseudopotentials

display_name: pseudopotentials


en: Cs2KInI6 is a promising lead-free halide double perovskite with a calculated direct band gap of 1.94 eV, ideal for solar cell applications. Our first-principles calculations reveal that its cubic phase (Fm3̅m) is dynamically unstable. Using an accelerated machine learning approach, we identify 42 dynamically stable structures and further validate these findings using first-principles calculations on 11 of these. The most stable phase has Cmc21 symmetry with 20 atoms/unit cell. It lies 13 meV/atom above the convex hull but lacks octahedral cation coordination. The most stable perovskite-like structure has P3̅ symmetry with 10 atoms/unit cell and low octahedral connectivity. Structure-property trade-offs are highlighted, with calculated distortions generally widening the band gap, shifting it from direct to indirect, and flattening the band edges. This work showcases the synergy of genetic algorithms, machine-learned potentials, and first principles validation for discovering stable, complex materials. This archive contains all our input, output files, the data and scripts.

en: From symmetry to stability: structural and electronic transformation in Cs₂KInI₆

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).

first-principles

display_name: first-principles

halide-double-perovskite

display_name: halide-double-perovskite

machine-learned-interatomic-potentials

display_name: machine-learned-interatomic-potentials

phonons

display_name: phonons

polymorphs

display_name: polymorphs


en: The FAIR principles have transformed how computational materials data and workflows are shared, yet existing repositories can only serve pre-computed entries — their coverage is perpetually incomplete and cannot adapt to new questions on demand. We built OptiMat Alloys, a large-language-model-powered conversational agent for multi-principal element alloy exploration, on three pillars: a living database that stores every calculation with provenance, low-barrier accessibility through a web interface that requires zero programming expertise, and built-in uncertainty quantification via cross-potential and cross-configuration validation. By coupling foundational machine-learning interatomic potentials that span nearly the entire periodic table with natural-language interaction, the agent enables targeted, on-demand computation guided by the user's own domain knowledge — extending FAIR from pre-computed repositories to on-demand knowledge generation, and making computational alloy screening accessible to any materials scientist.

en: OptiMat Alloys: a FAIR, living database of multi-principal element alloys enabled by a conversational agent

envi

en: Environment

fair-principle

display_name: fair-principle

llm-agent

display_name: llm-agent

materials-informatics

display_name: materials-informatics

multi-principal-element-alloys

display_name: multi-principal-element-alloys

universal-machine-learning-potentials

display_name: universal-machine-learning-potentials


en:
This dataset contains the data (as well as the code required to generate the data) for the numerical experiments of our manuscript "Quantum Finite Temperature Lanczos Method".

Abstract:

The computation of thermal properties of quantum many-body systems is a central challenge in our understanding of quantum mechanics. We introduce the Quantum Finite Temperature Lanczos Method (QFTLM), which extends the finite-temperature Lanczos method to quantum computers by combining real-time quantum Krylov methods with efficient preparation of typical states for trace estimation. This approach enables the computation of thermal expectation values while avoiding the exponential scaling inherent to classical exact simulation techniques. Numerical experiments on the transverse-field Ising model show that QFTLM can reproduce thermal observables over a wide temperature range. We further analyze the influence of Krylov dimension, number of trace-estimator states, and Trotter error, and show that suitable regularization is essential for robustness in noisy settings. These results establish QFTLM as a promising framework for finite-temperature quantum simulation.

en: Data for manuscript on the quantum finite temperature Lanczos method

finite-temperature

display_name: finite-temperature

krylov

display_name: krylov

lanczos

display_name: lanczos

quantum

display_name: quantum

simulation

display_name: simulation


en: Maximally-localized Wannier functions are quantum wavefunctions resembling atomic orbitals that are used to describe electrons in condensed matter. Since their introduction in 1997, these functions have become ubiquitous in ab initio materials simulations, including applications in linear-scaling methods, strongly correlated electron systems, quantum transport, electron-phonon interactions, and topological materials. Despite their widespread adoption in a vast software ecosystem, Wannier functions have not yet attained their fullest potential in the presence of entangled bands, as their optimization remains challenging and labor-intensive. Here, we introduce a universal meta-optimization method that leverages workflow abstraction and machine-learning techniques like differential evolution and Bayesian optimization to generate globally optimized Wannier functions without human intervention. We demonstrate this approach through three applications: (i) autonomous interpolation of entangled band structures with millielectronvolt accuracy starting from coarse Brillouin zone grids, (ii) thousand-fold acceleration of fully ab initio Boltzmann transport calculations via the use of minimal coarse Brillouin zone grids, and (iii) ultrafast high-throughput calculations of high-precision Wannier functions for large materials libraries. This work brings calculations that previously required supercomputers within the reach of personal computers.The data generated in this work and reported in the manuscript is attached in the Data.tar.gz with full description in the Readme.md.

en: Meta-optimization of maximally-localized Wannier functions

machine-learning

display_name: machine-learning

meta-optimization

display_name: meta-optimization

wannier-functions

display_name: wannier-functions


en: Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs. This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on SiNWs using the slab models for the Si facets since our reference are samples with diameters of SiNWs around 50 nm, while the quantum confinement effects are important for diameters below 10 nm. For each configuration, structural characterization was conducted by calculating quantities including the bond distance between the two carbons closest to the surface and their respective bond angle relative to the z-axis, the carbon-silicon bond distance and its respective bond angle relative to the z-axis, along with the molecule's rotation angle in the xy plane. The values obtained are summarized in the main folder. The version v1 of dataset contains data related to the Si(111) surface and alkanes, alkenes, and alkynes with lengths from C2 to C10. The version v2 and v3 include also the moieties from C12 to C18. The version v4 extends the dataset with the data related to the Si(110) surface and alkanes, alkenes, and alkynes with lengths from C2 to C18. The version v5 also includes the optimized structures of SiNWs oriented along ⟨112⟩, exposing Si(110) and Si(111) facets, and featuring three different sizes: small (d = 0.7 nm), medium (d = 1.7 nm), and large (d = 2.6 nm). In this version (v6) the relaxation calculations for all the considered moieties are provided. For each system the most stable configuration is identified, and the analysis of the electronic properties is conducted in the listed references.

en: Density functional theory study of silicon nanowire surfaces functionalized by grafting organic molecules

aliphatic-molecules

display_name: aliphatic-molecules

dft

display_name: dft

nanowires

display_name: nanowires

silicon

display_name: silicon

surface-adsorption

display_name: surface-adsorption


en: Hydrogen carriers that enable efficient transport and on-demand release of molecular hydrogen (H2) are crucial for practical hydrogen-based energy systems. Hydrogen boride (HB) nanosheets, composed of boron and hydrogen in a 1:1 stoichiometric ratio, have promising potential as safe and lightweight hydrogen carriers owing to their high gravimetric hydrogen density (8.5 wt %). In particular, heating of HB nanosheets results in H2 release over a broad temperature range from 423 to 1473 K. However, the mechanism of the multimodal H₂ desorption remains unclear. In this work, we elucidate that the interlayer H···H distances (dH···H) determine the multimodal desorption of H2 especially in the lower-temperature range (< 623 K). HB nanosheets subjected to various temperatures under different H2 pressures were prepared to investigate the thermal stability of their bonding configurations. Infrared spectroscopy and temperature-programmed desorption measurements revealed the occurrence of hydrogen depletion while the bonding configuration remains unchanged. The first to third nearest dH···H, along with the numbers of the corresponding H···H pairs, were systematically calculated for four possible interlayer stacking types. The calculated H···H pairs distribution closely matched the experimental profile for the thermally induced H2 desorption, suggesting that the multimodal desorption of H2 in the lower-temperature range is governed by the distribution of hydrogen distances. This study elucidates the unique mechanisms of H2 formation in HB nanosheets and provides valuable insights into the design of two-dimensional hydrogen containing materials.

en: Interlayer hydrogen-hydrogen spacing regulates the formation of molecular hydrogen in hydrogen boride nanosheets

hydrogen-boride-nanosheet

display_name: hydrogen-boride-nanosheet

hydrogen-release

display_name: hydrogen-release

interlayer-space

display_name: interlayer-space

two-dimensional-materials

display_name: two-dimensional-materials


en: The Shastry-Sutherland compound SrCu2(BO3)2 (SCBO) is a paradigmatic low-dimensional quantum spin system, featuring geometrically frustrated interacting spin dimers and a rich landscape of emergent quantum phenomena. While its magnetic properties have been extensively explored, the nature of its electronic excitations - particularly the Cu2+ d–d transitions - remains poorly understood. A detailed characterization of these excitations is essential to determine the crystal field splitting and the degree of Cu 3d–O 2p hybridization, both of which underpin superexchange interactions and magnetic behavior in SCBO. Here, the electronic properties of SCBO are investigated by combining spectroscopic techniques with theoretical approaches for first-principles band structure calculations.Experimentally, we employ L3-edge resonant inelastic x‑ray scattering (RIXS) to directly probe intra-d excitations, supplemented by broadband infrared reflectivity and ellipsometry measurements to resolve charge-transfer (CT) features. Theoretically, multireference quantum chemistry calculations accurately reproduce the energies (1.8–2.4 eV) and symmetries of the observed d–d excitations, while band-structure calculations based on density functional theory elucidate the CT excitation spectrum. These combined approaches define the energy scales for both d–d and CT transitions, validate the computational framework, and provide quantitative microscopic parameters essential for refining superexchange-based magnetic models in this prototypical frustrated quantum antiferromagnet.

en: Probing high-energy electronic excitations in the Shastry-Sutherland compound SrCu2(BO3)2 with resonant inelastic x-ray scattering and optical spectroscopy

d-d-excitations

display_name: d-d-excitations

dftu

display_name: dftu

resonant-inelastic-x-ray-scattering

display_name: resonant-inelastic-x-ray-scattering

shastry-sutherland-model

display_name: shastry-sutherland-model


en: This dataset supports a spin-polarized density functional theory study examining whether O₂-activation-favorable active-site environments at Fe- and Co-substituted sulfur vacancies in monolayer MoS₂ can produce a comparable response for H-free N₂ adsorption. Side-on and end-on N₂ adsorption branches were evaluated together with projected density of states and crystal orbital Hamilton population analyses to distinguish coordination geometry, thermodynamic preference, and intramolecular bond weakening. A perpendicular electric field and K/Na co-adsorption were further considered as physical and chemical perturbations. The calculations show that shared side-on coordination does not produce O₂-like N₂ activation, while the thermodynamically preferred end-on branch retains a shorter and stronger N–N bond. Alkali co-adsorption substantially enhances N–N bond weakening but does not eliminate the O₂–N₂ activation gap or reverse the end-on thermodynamic preference. The archive provides the optimized structures, representative computational input and output data, and numerical source data supporting the reported analyses.

en: Alkali promotion partially bridges a geometry-activation mismatch for N2 at O2-active MoS2 single-atom sites

materialscloud

en: Materials Cloud

alkali-promotion

display_name: alkali-promotion

cohp

display_name: cohp

density-functional-theory

display_name: density-functional-theory

nitrogen-activation

display_name: nitrogen-activation

single-atom-catalysis

display_name: single-atom-catalysis


en: Summing all Feynman diagrams with quantitative accuracy is a holy grail in theoretical physics. In condensed matter, the lattice vibration (phonon) field couples with the electrons, leading to the formation of entangled electron-phonon (e-ph) states called polarons.  In the intermediate- and strong-coupling regimes common to many conventional and quantum materials, a many-body treatment of polarons requires adding up a large number of e-ph diagrams. Diagrammatic Monte Carlo (DMC) is an efficient method for diagram summation and has been employed to study polarons within simplified e-ph models (Holstein, Frohlich, etc.).  Here we show DMC calculations based on accurate first-principles e-ph interactions, enabling numerically exact results for ground-state and dynamical properties of polarons in real materials, including the polaron formation energy, effective mass, spectral weight, phonon cloud distribution, optical conductivity, and mobility. We demonstrate such DMC calculations in systems with polarons ranging from small (localized) to large (delocalized), including LiF, SrTiO3, and TiO2 rutile and anatase. This advance is enabled by our recently developed technique for compressing first-principles e-ph interaction matrices, together with a matrix-product formalism that mitigates the DMC sign problem from multiple electronic bands. Our work enables precise modeling of e-ph interactions and polarons in coupling regimes ranging from weak to strong, opening doors to studies of transport, linear response, and superconductivity in the strong e-ph coupling regime.

en: Dataset for first-principles diagrammatic Monte Carlo for electron-phonon interactions and polaron

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).

diagrammatic-monte-carlo

display_name: diagrammatic-monte-carlo

first-principles

display_name: first-principles

lif

display_name: lif

many-body-physics

display_name: many-body-physics

polaron

display_name: polaron

strong-e-ph-interactions

display_name: strong-e-ph-interactions


gebaude-und-wohnungen-im-kanton-zurich

name: Fachstelle Open Government Data des Kantons Zürich

de: Gebäude und Wohnungen im Kanton Zürich gemäss eidgenössischem Gebäude- und Wohnungsregister (eidg. GWR). Es verzeichnet die Gebäude und jede Wohnung im Kanton umfassend in Merkmalen gemäss Merkmalsbeschreibung (siehe Link). Die Ressourcen lassen sich über die EGID verknüpfen. Das eidg. GWR wird durch die Gemeinden des Kantons Zürich geführt, die kantonale Koordinationsstelle GWR-ZH begleitet und berät sie dabei. Die Koordinationsstelle GWR-ZH stellt die Daten alle 3 Monate zur Verfügung und werden zum Stichtag vollständig ersetzt. Ein Zeitverlauf ist in den Daten nicht ersichtlich. Datenquelle bildet das eidg. GWR des Bundesamts für Statistik (BFS). Die Daten bilden den Stand des eidg. GWR ab, wie er durch die Gemeinden erfasst wird. Abweichungen vom tatsächlichen Zustand der Gebäude und Wohnungen sind möglich und im Bereich Energiequellen (Solaranlagen) sowie Wärmequellen (Heizungen) wahrscheinlich. Hinweise auf Abweichungen senden Sie bitte direkt an die Gemeinde, auf deren Boden sich das Objekt befindet, respektive an Statistik Stadt Zürich für Daten auf dem Stadtgebiet Zürich.

de: Gebäude und Wohnungen im Kanton Zürich

de: wohnung strassen wohnungen wohnungsbestand gebaeude gebaeudeart heizungsart heizung gemeinden

fachstelle-ogd-kanton-zuerich

de: Die Fach- und Koordinationsstelle Open Government Data (OGD) ist das kantonale Kompetenzzentrum für offene Behördendaten im Statistischen Amt. Wir unterstützen die Organisationseinheiten und Organe des Kantons bei der Bereitstellung ihrer nicht schützenswerten Daten als Open Data.

de: Fach- und Koordinationsstelle Open Government Data Kanton Zürich

political_level: canton

de: Bezug tagesaktueller Daten des eidg. GWR über die Schnittstelle des Bundes

de: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

de: Merkmalsbeschreibung des eidg. Gebäude- und Wohnungsregisters

title_for_slug: gebaude-und-wohnungen-im-kanton-zurich

value: ZH-Kt Fachstelle OGD - DCAT Harvester

soci

de: Bevölkerung und Gesellschaft

en: Population and society

fr: Population et société

it: Popolazione e società

de: Daten des eidg. GWR mit Bezug zu ganzen Gebäuden und ihrer Haustechnik. Aus den Daten lassen sich umfassende Angaben zum Gebäudebestand ablesen, beispielsweise zum Gebäudealter oder den Wärme- und Energiequellen. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter "weitere Informationen" im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt. Für die einfachere Nutzung fügt die Fach- und Koordinationsstelle OGD vor der Publikation folgende Merkmale hinzu: Für das Merkmal 'Kanton' wird für alle Beobachtungen ZH abgefüllt. Das Merkmal 'Gemeindename' wird mittels BFS-Nummer entsprechend der Gemeindetabelle des Statistischen Amts ausgegeben. Das Merkmal 'Anzahl_Wohnungen' wird anhand der Ressource Wohnungen berechnet.

de: Gebäude

format: CSV

media_type: text/csv

de: Daten des eidg. GWR mit Bezug zu den einzelnen Wohnungen in einem Gebäude. Aus den Daten lassen sich beispielsweise Alter, Fläche, Lage im Gebäude und Ausstattungsangaben herauslesen. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter "weitere Informationen" im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt.

de: Wohnungen

de: Daten des eidg. GWR mit Bezug zu den einzelnen Eingängen zu einem Gebäude. Adressen beziehen sich auf einzelne Gebäudeeingänge und sind deswegen pro Eingang in diesem File zu finden. Die Merkmale entsprechen denen im Merkmalskatalogs des eidg. GWR (siehe Link unter 'weitere Informationen' im Datensatzbeschrieb) und sind dort beschrieben. Leerwerte wurden in den Gemeinden nicht ausgefüllt, ihr Wert ist unbekannt.

de: Gebäudeeingänge bzw. Adressen pro Gebäude

gebaeude

display_name: gebaeude

gebaeudeart

display_name: gebaeudeart

gemeinden

display_name: gemeinden

heizung

display_name: heizung

heizungsart

display_name: heizungsart

strassen

display_name: strassen

wohnung

display_name: wohnung

wohnungen

display_name: wohnungen

wohnungsbestand

display_name: wohnungsbestand


leerwohnungszahlen

name: Amt für Statistik und Daten, Analysen & Studien

de:
Leerwohnungsdaten der Gemeinden im Kanton Zürich. Die Daten werden für die Leerwohnungszählung erhoben.

Jährlich aktualisiert wird nur die Ressource "Anzahl Leerwohnungen pro Gemeinde im Kanton Zürich seit 1994". Weitere Informationen dieser Ressource finden sie in den dazugehörigen Metadaten

de: Leerwohnungszahlen

statistisches-amt-kanton-zuerich

de: Das Amt für Statistik und Daten umfasst das Kompetenzzentrum Daten des Kantons Zürich, organisiert, koordiniert und steuert die politische Teilhabe inkl. der Wahlen und Abstimmungen im Kanton und beobachtet die Entwicklung des Kantons mit statistischen Methoden. Wir versorgen Bevölkerung, Verwaltung, Politik, Gemeinden, Medien, Firmen und sonstige Organisationen mit qualitativ hochstehenden Daten, Information und Fakten zum Kanton Zürich. Inhaltlich arbeiten wir unabhängig und objektiv.

de: Amt für Statistik und Daten Kanton Zürich

de: Kantonale Webseite zu den Leerwohnungszahlen

en: Vorbereiteter Code in R oder Python für jedes Dataset mit csv-Datei(en)

title_for_slug: leerwohnungszahlen

value: ZH-Kt Statistisches Amt - DCAT Harvester

de: Die Variablenliste bezieht sich auf eine alte Datenstruktur und ist nicht mehr aktuell. Die neue Datenstruktur sollte selbsterklärend sein.

de: Variablenliste zu Anzahl Leerwohnungen pro Gemeinde im Kanton Zürich seit 1994

format: XLS

de: Stichtag der Erhebung ist der 1. Juni, die Angaben beziehen sich auf den Gemeindestand (Variable bfs) zum Zeitpunkt der Erhebung. Erhoben werden die Daten von den Gemeinden nach Vorgaben des BFS. Weiter Angaben zur Erhebung finden sich hier unter Methode: https://www.zh.ch/de/planen-bauen/raumplanung/immobilienmarkt/leerwohnungen.html#-291192554

de: Anzahl Leerwohnungen pro Gemeinde im Kanton Zürich seit 1994 nach Anzahl Zimmer, Gebäudetyp, Eigentumsverhältnis und Alter der Wohnung (Alt vs. Neubau)

leerwohnungen

display_name: leerwohnungen

leerwohnungsziffer

display_name: leerwohnungsziffer

mietwohnungen

display_name: mietwohnungen


gemeindesteuern-der-zurcher-gemeinden

name: Amt für Statistik und Daten, Data Management

de: Gemeindesteuerdaten (Steuerertrag, Steuerkraft, berichtigte Steuerkraft, Steuerfüsse, Steuergrundlagen) seit 2011 gemäss Finanzausgleich

de: Gemeindesteuern der Zürcher Gemeinden

de: steuerertrag finanzausgleich steuerfuss steuerkraft steuern gemeinden

title_for_slug: gemeindesteuern-der-zurcher-gemeinden

gove

de: Regierung und öffentlicher Sektor

en: Government and public sector

fr: Gouvernement et secteur public

it: Governo e settore pubblico

econ

de: Wirtschaft und Finanzen

en: Economy and finance

fr: Économie et finances

it: Economia e finanze

de: Steuerkraft (Steuerertrag zu 100%) der Zürcher Gemeinden gemäss Finanzausgleich seit 2011.

de: Steuerkraft seit 2011

de: Steuerbares Einkommen, & Vermögen, Gewinn & Kapital seit 1990.

de: Steuergrundlagen seit 1990

de: Steuerfüsse der Zürcher Gemeinden seit 2012

de: Steuerfüsse seit 2012

de: Steuererträge der Zürcher Gemeinden gemäss Finanzausgleich seit 2011.

de: Steuerertrag seit 2011

de: Berichtige Steuerkraft der Zürcher Gemeinden gemäss Finanzausgleich seit 2011.

de: Berichtige Steuerkraft seit 2011

finanzausgleich

display_name: finanzausgleich

steuerertrag

display_name: steuerertrag

steuerfuss

display_name: steuerfuss

steuerkraft

display_name: steuerkraft

steuern

display_name: steuern


fr: La mise en oeuvre d'une gestion intégrée des eaux au niveau cantonal se base sur quatre outils de planification, tous validés par le Conseil d'État : - Les schémas de protection, d'aménagement et de gestion des eaux ; - La planification stratégique 2030 en matière de renaturation ; - Les plans régionaux d'évacuation des eaux (PREE) ; - Les plans généraux d'évacuation des eaux (PGEE). 32 plans de planification sont réalisés au total, soit 6 SPAGE, 1 planification stratégique, 6 PREE et 19 PGEE. Ces outils de planification se concrétisent par des plans d'actions. Chaque action planifiée fait l'objet d'une fiche présentant toutes les informations nécessaires à sa réalisation (description, responsabilité, coût, délai de réalisation, …). Seules les actions validées se retrouvent dans cette couche. Pour des actions liées à des planifications en cours, prière de contacter l'office cantonal de l'eau.

fr: Actions des planifications de l'Office cantonal de l'eau

canton-geneve

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

de: Der Kanton Genf verfolgt seit einigen Jahren eine Open Data Strategie. Auf diesem Portal finden Sie Daten aus der kantonalen Verwaltung die die Prinzipien des Open Government Data erfüllen, sowie sämtliche "Open-Geodaten" des Genfer Geoinformationssystems (SITG). ***Die Datensätze finden Sie unter der betreffenden Organisation***

en: The canton of Geneva has been committed to making public data open for a few years now. On this portal, you will find all the data from the Geneva cantonal administration that meet the principles of Open Government Data, as well as geodata from the geographic information system of Geneva (SITG) that fall under the OpenData policy.

it: Il cantone di Ginevra si è impegnato in un processo di apertura dei dati pubblici per diversi anni. Su questo portale, è possibile trovare tutti i dati dell'amministrazione del cantone di Ginevra che soddisfano i principi del Open Government Data, inoltre ai geodati OpenData del Sistema Informativo Territoriale di Ginevra (SITG).

de: Kanton Genf

en: Canton of Geneva

fr: Canton de Genève

it: Cantone di Ginevra

fr: Office cantonal de l'eau

de: geocat.ch Permalink

fr: geocat.ch permalien

it: geocat.ch link permanente

en: geocat.ch permalink

spatial: GE

agri

de: Landwirtschaft, Fischerei, Forstwirtschaft und Nahrungsmittel

en: Agriculture, fisheries, forestry and food

fr: Agriculture, pêche, sylviculture et alimentation

it: Agricoltura, pesca, silvicoltura e prodotti alimentari

regi

de: Regionen und Städte

en: Regions and cities

fr: Régions et villes

it: Regioni e città

envi

de: Umwelt

en: Environment

format: API

format: WFS

format: WMS

fr: Serveur de fichiers Opendata

fr: CSV

fr: GDB

format: ZIP

fr: GML

format: GML

fr: KML

format: KML

fr: SHP

format: SHP

value: GEOCAT canton GE


name: Direction de l'information du territoire

fr: Marquise: Tout abri, sans poteaux, fixé au-dessus d'une entrée d'un bâtiment ou courant le long de la facade.

fr: Marquises

fr: Environnement


fr: Depuis décembre 2003, tous les DDP (droits distincts permanents de superficie) avant radiation ou modification de leur assiette par une mutation juridique sont transférés par duplication en couche historique des droits distincts permanents. Entre juin 2006 et février 2008 en plus de la règle ci-dessus, une partie des DDP modifié par numérisation (amélioration de sa précision planimétrique) furent intégrés dans cette classe d'entités. Depuis mars 2008, tous DDP subissant une modification géométrique ou attributaire sont intégrés dans cette classe d'entités. Voir couche en vigueur : Droits distincts permanents

fr: Historique des droits distincts permanents

fr: Direction de l'information du territoire


name: Office cantonal de l'agriculture et de la nature

fr: Les interventions réalisées par les techniciens forestiers sont indiquées dans cette couche. Cela permet de renseigner les tâches effectuées, si une planification est projetée où un objectif sylvicole est déterminé. Elles font parties du modèle de gestion GESFOR.

fr: Interventions en forêt

canton-geneve

fr: Le canton de Genève s'est engagé dans une démarche d’ouverture des données publiques depuis plusieurs années. Sur ce portail, vous trouvez toutes les données provenant de l'administration cantonale genevoise qui répondent aux principes de l'Open Government Data, ainsi que les géodonnées OpenData du Système d’Information du Territoire à Genève (SITG).

fr: Canton de Genève


fr: La couche des parkings à usage public recense tous les parkings publics. Il s'agit des parkings publics ou privés qui sont accessibles au public. Il s'agit cependant d'une sélection des parkings les plus importants, tous les parkings n'étant pas représentés. Cette donnée est gérée en collaboration avec la Fondation des Parkings. Certains de ces parkings peuvent être consultés sur Infomobilité avec leur taux de remplissage en temps réel.

fr: Parkings à usage public

fr: Office cantonal des transports

fr: geocat.ch permalien

tran

de: Verkehr

en: Transport

fr: Transports

it: Trasporti

econ

de: Wirtschaft und Finanzen

fr: Économie et finances


fr: La couche stationnement sur la voie publique recense les places de stationnement sur la voie publique destinées aux véhicules motorisés et non motorisés. Chaque vecteur représente un nombre de place ayant un type de stationnement défini par son statut et sa durée. Cette donnée est utilisés pour connaître et suivre l'évolution de l'offre en stationnement sur la voie publique. La saisie des données est faite dans les communes fortement urbanisées et ont souvent été initiées au moment de la mise en place de nouvelle politique du stationnement. La plupart des modifications de ces aménagements font l'objet d'une approbation d'un plan de marquage, qui servent également à la mise à jour des données.

fr: Stationnement sur la voie publique

fr: Serveur de fichiers Opendata

fr: CSV

fr: GDB

fr: GML

fr: KML

fr: SHP


name: Centre de compétences et de coordination OGD / Kompetenz- und Koordinationszentrum für OGD

fr: Ce jeu de données présente l'aperçu mensuel des nuitées dans les hôtels et les établissements de cure (établissement de cure = hébergement spécialisé, orienté vers des séjours thérapeutiques, de convalescence ou de bien-être, sous encadrement médical ou paramédical) dans le canton de Fribourg et dans l'ensemble de la Suisse, depuis 1992. Deux remarques :Aucune donnée statistique n'est disponible pour l'année 2004, la série a été interrompue à fin 2003 par l'Office fédéral de la statistique puis a été reprise en 2005.Dès 2014, il n'existe plus d'établissement de cure dans le canton de Fribourg. Pour en savoir plus concernant les métadonnées de l'hébergement touristique : [https://www.bfs.admin.ch/bfs/fr/home/statistiques/tourisme/enquetes/hesta.assetdetail.35950522.html](https://www.bfs.admin.ch/bfs/fr/home/statistiques/tourisme/enquetes/hesta.assetdetail.35950522.html)

fr: tourisme nuitees hotels etablissements conjoncture-fribourgeoise indicateurs-conjoncturels

ssd

fr: Le Service de la statistique et de la donnée est le centre de compétence cantonal pour la statistique publique. Il collecte, analyse et diffuse des données statistiques sur la situation et l’évolution du canton, soutient les services de l’État dans la gestion des données et coordonne la diffusion des données administratives en libre accès.

en: The Statistics and Data Service is the cantonal competence center for public statistics. It collects, analyzes, and disseminates statistical data on the situation and development of the canton, supports state services in data management, and coordinates the dissemination of administrative data in open access.

de: Das Amt für Statistik und Daten ist das kantonale Kompetenzzentrum für die öffentliche Statistik. Es erhebt, analysiert und verbreitet statistische Daten über die Lage und die Entwicklung des Kantons, unterstützt die Dienststellen des Staats bei der Verwaltung ihrer Daten und koordiniert die Veröffentlichung der offenen Verwaltungsdaten.

it: Il Servizio Statistiche e Dati è il centro di competenza cantonale per la statistica pubblica. Raccoglie, analizza e diffonde dati statistici sulla situazione e l'evoluzione del cantone, supporta i servizi statali nella gestione dei dati e coordina la diffusione dei dati amministrativi ad accesso aperto.

de: Amt für Statistik und Daten Freiburg

en: Statistics and Data Service Fribourg

fr: Service de la statistique et de la donnée Fribourg

it: Servizio Statistiche e Dati Friburgo

de: ssd

value: DCAT Harvester Kt. FR

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (csv)

fr: csv

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (json)

fr: json

format: JSON

media_type: application/json

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (jsonl)

fr: jsonl

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (parquet)

fr: parquet

format: PARQUET

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (rdfxml)

fr: rdfxml

format: RDF XML

media_type: application/rdf+xml

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (jsonld)

fr: jsonld

format: JSON-LD

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (turtle)

fr: turtle

format: RDF Turtle

media_type: text/turtle

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (n3)

fr: Nuitées dans les hôtels et établissements de cure, par mois, dès 1992 (xlsx)

fr: xlsx

conjoncture-fribourgeoise

display_name: conjoncture-fribourgeoise

etablissements

display_name: etablissements

hotels

display_name: hotels

indicateurs-conjoncturels

display_name: indicateurs-conjoncturels

nuitees

display_name: nuitees

tourisme

display_name: tourisme


liniennetz-vb

de: Der Datensatz stellt die verschiedenen Linien des öffentlichen Verkehrsnetzes im Stadtgebiet von Biel dar, die von den Verkehrsbetriebe Biel (VB) betrieben werden.

fr: Le jeu de données représente les différentes lignes du réseau de transports publics de l’agglomération de Bienne exploitées par les Transports publics biennois (TPB)

de: Liniennetz VB

fr: Plan du réseau TPB

infrastruktur-mobilitaet-biel-bienne

fr: Bienne est la plus grande ville bilingue de Suisse et la métropole mondiale de l’horlogerie. Elle compte environ 56 000 habitantes et habitants. Grâce à son ouverture sur le monde et à sa situation centrale entre la Suisse alémanique et la Suisse romande, elle ne cesse de se développer de manière dynamique. Située au bord du lac de Bienne et au pied du Jura, elle jouit d’une qualité de vie remarquable.

de: Biel ist die grösste zweisprachige Stadt der Schweiz und Uhren-Weltmetropole. Sie zählt rund 56 000 Einwohnerinnen und Einwohner. Mit ihrer Weltoffenheit und dank ihrer zentralen Lage zwischen der deutschen und französischen Schweiz entwickelt sie sich stets dynamisch weiter. Am Bielersee und Jurasüdfuss gelegen bietet sie eine hohe Lebensqualität.

it: Bienne è la più grande città bilingue della Svizzera e la capitale mondiale dell’orologeria. Conta circa 56 000 abitanti. Grazie al suo cosmopolitismo e alla sua posizione centrale tra la Svizzera tedesca e quella francese, è in costante sviluppo dinamico. Situata sul lago di Bienne e ai piedi delle montagne del Giura, vanta un'elevata qualità di vita.

de: Infrastruktur und Mobilität Stadt Biel

fr: Infrastructures et mobilité Ville de Bienne

political_level: commune

de: Verkehrsbetriebe Biel

fr: Transports publics biennois

fr: geocat.ch permalien

spatial: Biel/Bienne

title_for_slug: liniennetz-vb

tran

fr: Transports

fr: Visualiser les données (WebGIS)

format: HTML

media_type: text/html

value: Stadt Biel/Bienne Infrastruktur und Mobilitaet - geocat Harvester


de: Liste der anerkannten Institutionen im Bereich der frühen Sprachförderung (aktueller Stand)Eingangskoordinaten gemäss [kantonalem Gebäude- und Wohnungsregister](https://data.bl.ch/explore/dataset/12180)

de: sprache sprachforderung kita spielgruppe adresse telefonnummer e-mail-adresse adressdaten fruhe-forderung deutsch vorkindergarten anerkannte-angebote-sprachforderung anerkannte-angebote-deutschforderung administrativdaten bewilligung

kanton-basel-landschaft

en:
The Canton of Basel-Country publishes open datasets of cantonal offices and agencies.
Further information at https://ogd.bl.ch/

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

de: Kanton Basel-Landschaft

en: Canton of Basel-Country

fr: Canton de Bâle-Campagne

it: Cantone di Basilea-Campagna

de: kanton-basel-landschaft

value: BL - DCAT

educ

de: Bildung, Kultur und Sport

en: Education, culture and sport

fr: Éducation, culture et sport

it: Istruzione, cultura e sport

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (csv)

de: csv

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (json)

de: json

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (fgb)

de: fgb

format: OCTET

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (geojson)

de: geojson

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (gpx)

de: gpx

format: GPX

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (jsonl)

de: jsonl

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (kml)

de: kml

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (ov2)

format: TXT

media_type: text/plain

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (parquet)

de: parquet

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (rdfxml)

de: rdfxml

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (jsonld)

de: jsonld

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (turtle)

de: turtle

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (n3)

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (shp)

de: shp

media_type: application/zip

de: Adressen der anerkannten Institutionen im Bereich der frühen Sprachförderung (xls)

de: xls


de: Energiestatistik. Der Bruttoenergieverbrauch in Megawattstunden entspricht der Energie, wie sie in die Gemeinde importiert oder in der Gemeinde aus natürlichen Quellen gewonnen wird. Der Treibstoffverbrauch wird in diesem Datensatz nicht ausgewiesen, da er nur auf Ebene des gesamten Kantons bekannt ist.Die Energiegewinnung aus Wasserkraftwerken ist ebenfalls nicht berücksichtigt, da die dort produzierte Energie nur zu einem geringen Teil in der Gemeinde selber verbraucht wird.

de: energieverbrauch emission klima statistikdaten biogas elektrizitat erdgas fernwarme flussiggas heizol holz industrieabfall photovoltaik thermische-solarenergie umweltwarme wasser

kanton-basel-landschaft

de:
Der Kanton Basel-Landschaft veröffentlicht nach und nach Open Government Datensätze von kantonalen Ämtern und Dienststellen.
Weitere Informationen unter https://ogd.bl.ch/

de: Kanton Basel-Landschaft

de: kanton-basel-landschaft

ener

de: Energie

en: Energy

fr: Énergie

it: Energia

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (csv)

de: csv

format: CSV

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (json)

de: json

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (jsonl)

de: jsonl

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (parquet)

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (rdfxml)

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (jsonld)

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (turtle)

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (n3)

de: Bruttoenergieverbrauch nach Gemeinde und Jahr (seit 2018) (xls)

format: XLS

biogas

display_name: biogas

elektrizitat

display_name: elektrizitat

emission

display_name: emission

energieverbrauch

display_name: energieverbrauch

erdgas

display_name: erdgas

fernwarme

display_name: fernwarme

flussiggas

display_name: flussiggas

heizol

display_name: heizol

holz

display_name: holz

industrieabfall

display_name: industrieabfall

klima

display_name: klima

photovoltaik

display_name: photovoltaik

statistikdaten

display_name: statistikdaten

thermische-solarenergie

display_name: thermische-solarenergie