en:
The interplay between electron correlation and nuclear quantum effects makes our understanding of elemental hydrogen a formidable challenge. Here, we present the phase diagram of hydrogen and deuterium at low temperatures and high-pressure (P > 300 GPa) by accounting for highly accurate electronic and nuclear enthalpies. We evaluated internal electronic energies by diffusion quantum Monte Carlo, while nuclear quantum motion and anharmonicity have been included by the stochastic self-consistent harmonic approximation. Our results show that the long-sought atomic metallic hydrogen, predicted to host room-temperature superconductivity, forms at 577±10 GPa (640±14 GPa in deuterium). Indeed, anharmonicity pushes the stability of this phase towards pressures much larger than previous theoretical estimates or attained experimental values. Before atomization, molecular hydrogen transforms from a metallic phase III to another metallic structure that is still molecular (phase VI) at 422±40 GPa (442±30 GPa in deuterium). We predict clear-cut signatures in optical spectroscopy and DC conductivity that can be used experimentally to distinguish between the two structural transitions. According to our findings, the experimental evidence of metallic hydrogen has so far been limited to molecular phases.
The data uploaded here contains the structural information of the simulated phases of hydrogen and their quantum centroid position as a function of pressure and isotope.

en: Quantum phase diagram of high-pressure hydrogen

high-pressure-hydrogen

display_name: high-pressure-hydrogen


$oid: OBSOLETE

materialscloud

approval_status: approved

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

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

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


en: Li–S batteries are a promising alternative to Li-ion batteries, offering large energy storage capacity and wide operating temperature range. However, their performance is heavily affected by the Li-polysulphide (LiPS) shuttling. Computational screening of LiPS adsorption on single-atom catalyst (SAC) substrates is of great aid to the design of Li–S batteries which are robust against the LiPS shuttling from the cathode to the anode and the electrolyte. To facilitate this process, we develop a machine learning (ML) protocol to accelerate the systematic mapping of dominant local energy minima found with calculations based on the density functional theory (DFT), and, in turn, fast screening of LiPS adsorption properties on SACs. We first validate the approach by probing the potential energy surface for LiPS adsorbed on graphene decorated with a Fe–N4–C SAC. We identify minima whose binding energies are better or on par with the one previously reported in the literature. We then move to analyse the adsorption trends on Zn–N4–C SAC and observe similar adsorption strength and behaviour with the Fe–N4–C SAC, highlighting the good predictive power of our protocol. Our approach offers a comprehensive and computationally efficient alternative to conventional approaches studying LiPS adsorption

en: Accelerating the theoretical study of Li-polysulphide adsorption on single-atom catalysts via machine learning approaches

batteries

display_name: batteries

generalised-convex-hull

display_name: generalised-convex-hull

minima-search

display_name: minima-search


en: Smearing techniques are widely used in first-principles calculations of metallic and magnetic materials, where they improve the accuracy of Brillouin zone sampling and lessen the impact of level-crossing instabilities. Smearing introduces a fictitious electronic temperature that smooths the discontinuities of the integrands; consequently, a corresponding fictitious entropic term arises and needs to be considered in the total free energy functional. Advanced smearing techniques – such as Methfessel-Paxton and cold smearing – have been introduced to guarantee that the system's total free energy remains independent of the smearing temperature at least up to the second order. In doing so, they give rise to non-monotonic occupation functions (and, for Methfessel-Paxton, non-positive definite), which can result in the chemical potential not being uniquely defined. We explore this shortcoming in detail and introduce a numerical protocol utilizing Newton's minimization method that is able to identify the desired Fermi energy. We validate the method by calculating the Fermi energy of ~20,000 materials and comparing it with the results of standard bisection approaches. In passing, we also highlight how traditional approaches, based on Fermi-Dirac or Gaussian smearing, are actually equivalent for all practical purposes, provided the smearing width is appropriately renormalized by a factor ~2.565. This data set contains the AiiDA databases, scripts, and other data necessary for the reproduction of our results.

en: Fermi energy determination for advanced smearing techniques

fermi-energy

display_name: fermi-energy

insulators

display_name: insulators

intersect

display_name: intersect

marvel

display_name: marvel

semiconductors

display_name: semiconductors

smearing

display_name: smearing


en: Maximally-localized Wannier functions (MLWFs) are a powerful and broadly used tool to characterize the electronic structure of materials, from chemical bonding to dielectric response to topological properties. Most generally, one can construct MLWFs that describe isolated band manifolds, e.g. for the valence bands of insulators, or entangled band manifolds, e.g. in metals or describing both the valence and the conduction manifolds in insulators. Obtaining MLWFs that describe a target manifold accurately and with the most compact representation often requires chemical intuition and trial and error, a challenging step even for experienced researchers and a roadblock for automated high-throughput calculations. Here, we present a very natural and powerful approach that provides automatically MLWFs spanning the occupied bands and their natural complement for the empty states, resulting in WÎannier Hamiltonian models that provide a tight-binding picture of optimized atomic orbitals in crystals. Key to the success of the algorithm is the introduction of a projectability measure for each Bloch state onto atomic orbitals (here, chosen from the pseudopotential projectors) that determines if that state should be kept identically, discarded, or mixed into a disentangling algorithm. We showcase the accuracy of our method by comparing a reference test set of 200 materials against the selected-columns-of-the-density-matrix (SCDM) algorithm, and its reliability by Wannierizing 21 737 materials from the Materials Cloud.

en: Projectability disentanglement for accurate and automated electronic-structure Hamiltonians

high-throughput

display_name: high-throughput

snsf

display_name: snsf

wannier-functions

display_name: wannier-functions

wannierization

display_name: wannierization


en: The microscopic mechanism of heavy band formation, relevant for unconventional superconductivity in CeCoIn₅ and other Ce-based heavy fermion materials, depends strongly on the efficiency with which f electrons are delocalized from the rare earth sites and participate in a Kondo lattice. Replacing Ce³⁺ (4f 1, J = 5/2) with Sm³⁺ (4f 5, J = 5/2), we show that a combination of crystal field and on-site Coulomb repulsion causes SmCoIn₅ to exhibit a Γ7 ground state similar to CeCoIn5 with multiple f electrons. Remarkably, we also find that with this ground state, SmCoIn₅ exhibits a temperature-induced valence crossover consistent with a Kondo scenario, leading to increased delocalization of f holes below a temperature scale set by the crystal field, Tv ≈ 60 K. Our result provides evidence that in the case of many f electrons, the crystal field remains the most important tuning knob in controlling the efficiency of delocalization near a heavy fermion quantum critical point, and additionally clarifies that charge fluctuations are present and may play a generally important role in the ground state of "115" materials.

en: Charge fluctuations in the intermediate-valence ground state of SmCoIn₅

dftu

display_name: dftu

heavy-fermions

display_name: heavy-fermions

mixed-valence

display_name: mixed-valence


en: This data set includes the workflows (all steps including input parameters and output data) for the computation of the adsorption energies for atomic oxygen on different platinum nanoparticles using density functional theory. Different number of adsorbed oxygen atoms, starting from single adsorbed oxygen atoms, and different adsorption configurations have been considered. The lowest-energy adsorption configurations have been used to compute the phase diagrams describing the thermodynamic equilibrium in the platinum-oxygen system at different temperatures and pressures. For the construction of the phase diagrams, additional calculations for platinum oxide nanoparticles and a correction to the O2 dissociation energy have been performed.

en: Platinum nanoparticles under oxidizing conditions

oxygen-adsorption

display_name: oxygen-adsorption

platinum-nanocatalyst

display_name: platinum-nanocatalyst

platinum-nanoparticle

display_name: platinum-nanoparticle

pressure-temperature-phase-diagram

display_name: pressure-temperature-phase-diagram


en: For decades transition-metal oxides have generated a huge interest due to the multitude of physical phenomena they exhibit. In this class of materials, the rare-earth nickelates, RNiO₃, stand out for their rich phase diagram stemming from complex couplings between the lattice, electronic and magnetic degrees of freedom. Here, we present a first-principles study of the low-temperature phase for two members of the RNiO₃ series, with R = Pr, Y. We employ density-functional theory with Hubbard corrections accounting not only for the on-site localizing interactions among the Ni-3d electrons (U), but also the inter-site hybridization effects between the transition-metals and the ligands (V). All the U and V parameters are calculated from first-principles using density-functional perturbation theory, resulting in a fully ab initio methodology. Our simulations show that the inclusion of the inter-site interaction parameters V is necessary to simultaneously capture the features well-established by experimental characterizations of the low-temperature state: insulating character, antiferromagnetism and bond disproportionation. On the contrary, for some magnetic orderings the inclusion of on-site interaction parameters U alone completely suppresses the breathing distortion occurring in the low-temperature phase and produces an erroneous electronic state with a vanishing band gap. In addition - only when both the U and V are considered - we predict a polar phase with a magnetization-dependent electric polarization,  supporting very recent experimental observations that suggest a possible occurrence of type-II multiferroicity for these materials.

en: Hybridization driving distortions and multiferroicity in rare-earth nickelates

electronic-structure

display_name: electronic-structure

magnetism

display_name: magnetism

rare-earth-nickelates

display_name: rare-earth-nickelates


marvel

display_name: marvel


en: Linear scaling relations have led to an understanding of trends in catalytic activity and selectivity of many reactions in heterogeneous and electro-catalysis. Yet, linear scaling between the chemisorption energies of any two small molecule adsorbates is not guaranteed. A prominent example is the lack of scaling between the chemisorption energies of carbon and oxygen on transition metal surfaces. In this work, we show that this lack of scaling originates from different re-normalised adsorbate valence energies of lower-lying oxygen versus higher-lying carbon. We develop a model for chemisorption of small molecule adsorbates within the d-band model by combining a modified form of the Newns-Anderson hybridisation energy with an effective orthogonalization term. We develop a general descriptor to a priori determine if two adsorbates are likely to scale with each other. This record contains the AiiDA archive required to reproduce all calculations in the manuscript.

en: Limits to scaling relations between adsorption energies?

catalysis

display_name: catalysis

d-band-model

display_name: d-band-model

scaling-relations

display_name: scaling-relations


materialscloud

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

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


en: Conversion of graphene into pure free-standing graphane — where each C atom is sp³ bound to a hydrogen atom — has not been achieved so far, in spite of numerous experimental attempts. Here, we obtain an unprecedented level of hydrogenation (~90% of sp³ bonds) by exposing fully free-standing nano porous samples — constituted by single to few veils of smoothly rippled graphene — to atomic hydrogen in ultra-high-vacuum. Such a controlled hydrogenation of high-quality and high-specific-area samples converts the original conductive graphene into a wide gap semiconductor, with the valence band maximum (VBM) ~3.5 eV below the Fermi level, as monitored by photoemission spectro-microscopy and confirmed by theoretical predictions. In fact, the calculated band structure unequivocally identifies the achievement of a stable, double-side fully hydrogenated configuration, with no trace of pi states and a gap opening in excellent agreement with the experimental results.

en: Materials Cloud

en: Gap opening in double-sided highly hydrogenated free-standing graphene

big-map

display_name: big-map

density-functional-theory

display_name: density-functional-theory

first-principles

display_name: first-principles

graphane

display_name: graphane

gw-approximation

display_name: gw-approximation

hydrogenated-graphene

display_name: hydrogenated-graphene

max

display_name: max

nanoporous-graphene

display_name: nanoporous-graphene

spectromicroscopy

display_name: spectromicroscopy

yambo-code

display_name: yambo-code


envi

en: Environment


en:
The creation and maintenance of crystallographic data repositories is one of the greatest data-related achievements in chemistry. Platforms such as the Cambridge Structural Database host what is likely the most diverse collection of synthesizable molecules. If properly mined, they could be the basis for the large-scale exploration of new regions of the chemical space using quantum chemistry (QC). However, it is currently challenging to retrieve all the necessary information for QC based exclusively on the available structural data, especially for transition metal complexes. To solve this shortcoming, we present  cell2mol, a software that interprets crystallographic data and retrieves the connectivity and total charge of molecules, including the oxidation state (OS) of metal atoms. We prove that  cell2mol outperforms other popular methods at assigning the metal OS, while offering a much more comprehensive interpretation of the unit cell, and we make publicly available reliable QC-ready databases totaling 31k transition metal complexes and 13k ligands, encompassing incomparable chemical diversity.

This record contains the aforementioned database of crystallographic structures after interpretation using the cell2mol software. The database spans 8 different transition metals (Fe, Mn, Ru, Re, Cr, Co, Ni, Cu; named from 1 to 8) and contains over 31000 different transition metal complexes and 13000 unique ligands, but also contains the interpreted contents of the entire unit cells in terms of discrete chemical species with well-defined charges and connectivities. Details can be found in the README.txt file and an exemplary script is provided for usage. The cell2mol code can be obtained in https://github.com/lcmd-epfl/cell2mol.

en: cell2mol: encoding chemistry to interpret crystallographic data

crystal

display_name: crystal

experimental

display_name: experimental


en: Hydrogen boride (HB) sheets are metal-free two-dimensional materials comprising boron and hydrogen in a 1:1 stoichiometric ratio. In spite of the several advancements, the fundamental interactions between HB sheets and discrete molecules remain unclear. Here, we report the adsorption of CO2 and its conversion to CH4 and C2H6 using hydrogen-deficient HB sheets. Although fresh HB sheets did not adsorb CO2, hydrogen-deficient HB sheets reproducibly physisorbed CO2 at 297 K. The adsorption followed the Langmuir model with a saturation coverage of 2.4 × 10−4 mol g−1 and a heat of adsorption of approximately 20 kJ mol−1, which was supported by density functional theory calculations. When heated in a CO2 atmosphere, hydrogen-deficient HB began reacting with CO2 at 423 K. The detection of CH4 and C2H6 as CO2 reaction products in a moist atmosphere indicated that hydrogen-deficient HB promotes C–C coupling and CO2 conversion reactions. Our findings highlight the application potential of HB sheets as catalysts for CO2 conversion.

en: Carbon dioxide adsorption and conversion to methane and ethane on hydrogen boride sheets

carbon-dioxide

display_name: carbon-dioxide

ethane

display_name: ethane

hydrogen-boride

display_name: hydrogen-boride

methane

display_name: methane

two-dimensional

display_name: two-dimensional


en: Maximally localized Wannier functions (MLWFs) are widely used to construct first-principles tight-binding models that accurately reproduce the electronic structure of materials. Recently, robust and automated approaches to generate these MLWFs have emerged, leading to natural sets of atomic-like orbitals that describe both the occupied states and the lowest lying unoccupied ones (when the latter can be meaningfully described by bonding/anti-bonding combinations of localized orbitals). For many applications, it is important to instead have MLWFs that describe only certain target manifolds separated in energy between them — the occupied states, the empty states, or certain groups of bands. Here, we start from the full set of MLWFs describing simultaneously all the target manifolds, and then mix them using a combination of parallel transport and maximal localization to construct orthogonal sets of MLWFs that fully and only span the desired target submanifolds. The algorithm is simple and robust, and it is applied to some paradigmatic but non-trivial cases (the valence and conduction bands of silicon, the top valence band of MoS₂, the 3d and t2g/eg bands of SrVO₃ and to a mid-throughput study of 77 insulators.

en: Automated mixing of maximally localized Wannier functions into target manifolds

manifold-optimization

display_name: manifold-optimization

marvel

display_name: marvel

snsf

display_name: snsf

wannier-functions

display_name: wannier-functions

wannier-interpolation

display_name: wannier-interpolation

wannierization

display_name: wannierization


en:
We develop an accurate nanoelectronic modeling approach for realistic three-dimensional topological insulator nanostructures and investigate their low-energy surface-state spectrum. Starting from the commonly considered four-band k·p bulk model Hamiltonian for the Bi₂Se₃ family of topological insulators, we derive new parameter sets for Bi₂Se₃, Bi₂Te₃ and Sb₂Te₃. We consider a fitting strategy applied to ab initio band structures around the Γ point that ensures a quantitatively accurate description of the low-energy bulk and surface states, while avoiding the appearance of unphysical low-energy states at higher momenta, something that is not guaranteed by the commonly considered perturbative approach. We analyze  the effects that arise in the low-energy spectrum of topological surface states due to band anisotropy and electron-hole asymmetry, yielding Dirac surface states that naturally localize on different side facets. In the thin-film limit, when surface states hybridize through the bulk, we resort to a thin-film model and derive thickness-dependent model parameters from ab initio calculations that show good agreement with experimentally resolved band structures, unlike the bulk model that neglects relevant many-body effects in this regime. Our versatile modeling approach offers a reliable starting point for accurate simulations of realistic topological material-based nanoelectronic devices.
This dataset contains the data used in the corresponding publication.

en: Low-energy modeling of three-dimensional topological insulator nanostructures

dft

display_name: dft

effective-hamiltonian

display_name: effective-hamiltonian

kp-low-energy-model

display_name: kp-low-energy-model

tight-binding

display_name: tight-binding

topological-insulator

display_name: topological-insulator


en: Charge density wave (CDW) orders in vanadium-based kagome metals have recently received tremendous attention, yet their origin remains a topic of debate. The discovery of ScV₆Sn₆, a bilayer kagome metal featuring an intriguing √3 x √3 x 3 CDW order, offers a novel platform to explore the underlying mechanism behind the unconventional CDW. Here, we combine high-resolution angle-resolved photoemission spectroscopy, Raman scattering and density functional theory to investigate the electronic structure and phonon modes of ScV₆Sn₆. We identify topologically nontrivial surface states and multiple van Hove singularities (VHSs) in the vicinity of the Fermi level, with one VHS aligning with the in-plane component of the CDW vector near the K ̅ point. Additionally, Raman measurements indicate a strong electron-phonon coupling, as evidenced by a two-phonon mode and new emergent modes. Our findings highlight the fundamental role of lattice degrees of freedom in promoting the CDW in ScV₆Sn₆.

en: Phonon promoted charge density wave in topological kagome metal ScV₆Sn₆

arpes-raman-stm-dft

display_name: arpes-raman-stm-dft

nccr-marvel

display_name: nccr-marvel


en:
Materials that can host Majorana zero modes gained a lot of attention in recent years due to the possibility to engineer topologically protected quantum computing platforms. Promising candidates are heterostructures of topological insulators and superconductors. Here we present density-functional-theory-based calculations for Pd-doped Bi₂Te₃ and Pd(Bi,Te)x (x=1,2) in order to shed light on the superconducting properties in the self-formed superconducting phase when Pd is deposited on top of the topological insulator Bi₂Te₃.
This dataset accompanies a joint experiment/theory publication and publishes the related density functional theory calculations for:
- relaxed geometries for Pd intercalation in the Bi₂Te₃ vdW gap
- electronic structure of PdTe and PdTe₂ compared to alloy phases of Pd(Bi,Te) and Pd(Bi,Te)₂, collectively referred to as "xPBT"
- calculations for the superconducting state of xPBT phases within the Kohn-Sham Bogoliubov-de Gennes method

en: Pd-doping of Bi₂Te₃ and superconductivity of Pd(Bi,Te)x from density functional theory

density-functional-theory

display_name: density-functional-theory

majorana

display_name: majorana

superconductivity

display_name: superconductivity

topological-materials

display_name: topological-materials


materialscloud

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

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


en: Fracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till mid-2022. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 148, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also records the factors influential to fracture. Examples are material processing history, phase structure, grain size, uniaxial tensile properties such as yield strength and elongation, and testing conditions.

en: Dataset for fracture and impact toughness of high-entropy alloys

fracture-toughness

display_name: fracture-toughness

high-entropy-alloys

display_name: high-entropy-alloys

impact-energy

display_name: impact-energy

impact-toughness

display_name: impact-toughness


en: We study the water dehydrogenation reaction at the BiVO₄(010)-water interface by combining nudged-elastic-band calculations and electronic structure calculations at the hybrid functional level. We investigate the pathway and the kinetic barrier for the adiabatic reaction going from the hole polaron localized in BiVO₄ to the dehydrogenation of the adsorbed water molecule at the interface. The reaction is found to involve the H2O•⁺ radical cation as intermediate, to have a kinetic barrier of 0.7 eV, and to be initiated by the electron transfer. The calculated kinetic barrier is in good agreement with experiment and is consistent with the slow hole transfer kinetics observed at the surface of BiVO₄. To characterize the structural changes occurring during this process, we analyze the O-H distances for three relevant water molecules. We also examine the Wannier functions around the O atom of the adsorbate involved in the reaction to reveal the changes in the electronic structure during the hole hopping. The projected density of states of the lowest unoccupied molecular orbitals allows us to identify the atomic orbitals that are primarily involved in the reaction. We expect that the proposed reaction mechanism generally holds when the surface coverage is dominated by molecularly adsorbed water.

materialscloud

en: Materials Cloud

en: Oxygen evolution at the BiVO₄-water interface: mechanism of the water dehydrogenation reaction

marvel

display_name: marvel

metal-oxide

display_name: metal-oxide

water-dehydrogenation-reaction

display_name: water-dehydrogenation-reaction


envi

en: Environment


en: Neural networks (NNs) often assign high confidence to their predictions, even for points far out-of-distribution, making uncertainty quantification (UQ) a challenge. When they are employed to model interatomic potentials in materials systems, this problem leads to unphysical structures that disrupt simulations, or to biased statistics and dynamics that do not reflect the true physics. Differentiable UQ techniques can find new informative data and drive active learning loops for robust potentials. However, a variety of UQ techniques, including newly developed ones, exist for atomistic simulations and there are no clear guidelines for which are most effective or suitable for a given case. In this work, we examine multiple UQ schemes for improving the robustness of NN interatomic potentials (NNIPs) through active learning. In particular, we compare incumbent ensemble-based methods against strategies that use single, deterministic NNs: mean-variance estimation, deep evidential regression, and Gaussian mixture models. We explore three datasets ranging from in-domain interpolative learning to more extrapolative out-of-domain generalization challenges: rMD17, ammonia inversion, and bulk silica glass. Performance is measured across multiple metrics relating model error to uncertainty. Our experiments show that none of the methods consistently outperformed each other across the various metrics. Ensembling remained better at generalization and for NNIP robustness;  MVE only proved effective for in-domain interpolation, while GMM was better out-of-domain; and evidential regression, despite its promise, was not the preferable alternative in any of the cases. More broadly, cost-effective, single deterministic models cannot yet consistently match or outperform ensembling for uncertainty quantification in NNIPs.

en: Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles

adversarial-sampling

display_name: adversarial-sampling

ammonia

display_name: ammonia

neural-network-interatomic-potentials

display_name: neural-network-interatomic-potentials

silica-glass

display_name: silica-glass

single-deterministic-neural-networks

display_name: single-deterministic-neural-networks

uncertainty-quantification

display_name: uncertainty-quantification


en: On-surface synthesis has emerged as a powerful strategy to fabricate unprecedented forms of atomically precise graphene nanoribbons (GNRs). However, the on-surface synthesis of zigzag GNRs (ZGNR) has met with only limited success. In the paper where the data are discussed, we report the synthesis and on-surface reactions of 2,7-dibromo-9,9'-bianthryl as the precursor towards π-extended ZGNRs. Characterization by scanning tunneling microscopy and high-resolution noncontact atomic force microscopy clearly demonstrated the formation of anthracene-fused ZGNRs. Unique skeletal rearrangements were also observed, which could be explained by intramolecular Diels-Alder cycloaddition. Theoretical calculations of the electronic properties of the anthracene-fused ZGNRs revealed spin-polarized edge-states and a narrow bandgap of 0.20 eV.

en: On-surface synthesis of anthracene-fused zigzag graphene nanoribbons from 2,7-dibromo-9,9'-bianthryl reveals unexpected ring rearrangements

graphene-nanoribbons

display_name: graphene-nanoribbons

on-surface-synthesis

display_name: on-surface-synthesis


en:
Hubbard-corrected density-functional theory has proven to be successful in addressing self-interaction errors in 3D magnetic materials. However, the effectiveness of this approach for 2D magnetic materials has not been extensively explored. Here, we use PBEsol+U and its extensions PBEsol+U+V to investigate the electronic, structural, and vibrational properties of 2D antiferromagnetic FePS₃ and ferromagnetic CrI₃, and compare the monolayers with their bulk counterparts. Hubbard parameters (on-site U and inter-site V) are computed self-consistently using density-functional perturbation theory, thus avoiding any empirical assumptions. We show that for FePS₃ the Hubbard corrections are crucial in obtaining the experimentally observed insulating state with the correct crystal symmetry, providing also vibrational frequencies in good agreement with Raman experiments. While empirical U can lead to an unstable ground-state (i.e. imaginary phonons), the system remains stable through the self-consistent process of calculating Hubbard parameters.
For ferromagnetic CrI₃, we discuss how a straightforward application of Hubbard corrections worsens the results and introduces a spurious separation between spin-majority and minority conduction bands. Promoting the Hubbard U to be a spin-resolved parameter — that is, applying different (first-principles) values to the spin-up and spin-down manifolds — recovers a more physical picture of the electronic bands and delivers the best comparison with experiments.

en: On-site and inter-site Hubbard corrections in magnetic monolayers: The case of FePS₃ and CrI₃

cscs

display_name: cscs

dft

display_name: dft

dftu

display_name: dftu

dftuv

display_name: dftuv

epfl

display_name: epfl

first-principles

display_name: first-principles

hubbard

display_name: hubbard

quantum-espresso

display_name: quantum-espresso


en: Oxides containing metals or semimetals from the p-block of the periodic table, e.g., indium oxide or antimony oxide, are of interest as transparent conductors and light absorbers for solar energy conversion due to the tunability of their electronic conductivity and optical absorption. Comparatively, these oxides have found limited applications in solar-to-hydrogen photocatalysis primarily due to their high electronegativity, which impedes electron transfer for converting protons into hydrogen. We have shown recently that inserting s-block metal cations into p-block oxides is effective at lowering electronegativities while affording further control of band gaps. Here, we explain the origins of this dual tunability by demonstrating the mediator role of s-block metal cations in modulating orbital hybridization while not contributing to frontier electronic states. From this result, we carry out a comprehensive computational study of 109 ternary oxides of s- and p-block metal elements as candidate photocatalysts for solar hydrogen generation. We downselect the most desirable materials using band gaps and band edges obtained from Hubbard-corrected density-functional theory with Hubbard parameters computed entirely from first principles, evaluate the stability of these oxides in aqueous conditions, and characterize experimentally four of the remaining materials, synthesized with high phase uniformity, to critically assess the accuracy of the computational models. We thus propose nine oxide semiconductors, including CsIn₃O₅, Sr₂In₂O₅, and KSbO₂ which, to the extent of our literature review, have not been previously considered as water-splitting photocatalysts. This record contains the data for the simulations discussed in our manuscript.

en: Ternary oxides of s- and p-block metals for photocatalytic solar-to-hydrogen conversion

marvel

display_name: marvel

photocatalysis

display_name: photocatalysis


en: We study the electronic and optical properties of the hydrogen boride sheet by using the many-body perturbation theory with the perturbative GW (G₀W₀) approximation. It was found that the hydrogen boride sheet shows a semimetallic electronic structure, supporting the previous theoretical study based on the semilocal density functional theory calculations. It was also found that the optical spectrum calculated based on the quasiparticle energies agrees well with the experiments. This work suggests that G₀W₀ approximation may be useful for predicting precise electronic and optical properties of the hydrogen boride sheet and its derivatives.

en: Electronic and optical properties of the hydrogen boride sheet from the many-body perturbation theory

density-functional-theory

display_name: density-functional-theory

hydrogen-boride

display_name: hydrogen-boride

many-body-perturbation-theory

display_name: many-body-perturbation-theory

nanosheet

display_name: nanosheet

two-dimensional

display_name: two-dimensional


materialscloud

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

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


en: One key bottleneck of solid-state NMR spectroscopy is that ¹H NMR spectra of organic solids are often very broad due to the presence of a strong network of dipolar couplings. We have recently suggested a new approach to tackle this problem. More specifically, we parametrically mapped errors leading to residual dipolar broadening into a second dimension and removed them in a correlation experiment. In this way pure isotropic proton (PIP) spectra were obtained that contain only isotropic shifts and provide the highest ¹H NMR resolution available today in rigid solids. Here, using a deep-learning method, we extend the PIP approach to a second dimension, and for samples of L-tyrosine hydrochloride and ampicillin we obtain high resolution ¹H-¹H double-quantum/single-quantum dipolar correlation and spin-diffusion spectra with significantly higher resolution than the corresponding spectra at 100 kHz MAS, allowing the identification of previously overlapped isotropic correlation peaks.

en: Two-dimensional pure isotropic proton solid state NMR

machine-learning

display_name: machine-learning

nmr

display_name: nmr

resolution

display_name: resolution


en: The GW approach produces highly accurate quasiparticle energies, but its application to large systems is computationally challenging, which can be largely attributed to the difficulty in computing the inverse dielectric matrix. To address this challenge, we develop a machine learning approach to efficiently predict density-density response functions (DDRF) in materials. For this, an atomic decomposition of the DDRF is introduced as well as the neighbourhood density-matrix descriptor both of which transform in the same way under rotations. The resulting DDRFs are then used to evaluate quasiparticle energies via the GW approach. This technique is called the ML-GW approach. To assess the accuracy of this method, we apply it to hydrogenated silicon clusters and find that it reliably reproduces HOMO-LUMO gaps and quasiparticle energy levels. The accuracy of the predictions deteriorates when the approach is applied to larger clusters than those included in the training set. These advances pave the way towards GW calculations of complex systems, such as disordered materials, liquids, interfaces and nanoparticles.

en: Accelerating GW calculations through machine learned dielectric matrices

ab-initio

display_name: ab-initio

dft

display_name: dft


en: Existing, classical interatomic potentials for bcc iron predict contradicting crack-tip mechanisms (i.e. cleavage, dislocation emission, phase transition) for the same crack systems, thus leaving the crack propagation mechanism in bcc iron unclear. In this work, we develop a Gaussian approximation potential (GAP) by extending a DFT database for ferromagnetic bcc iron to include highly distorted primitive bcc cells and surface separation, along with small crack-tip configurations that are identified by means of a fully automated active learning workflow. Our GAP (referred to as Fe-GAP22) predicts crack propagation within 8 meV/atom accuracy. The fully automated, active learning workflow is made publicly available on GitHub. With the newly developed Fe-GAP22, we find that in absence of other defects around the crack tip (e.g. nanovoids, dislocations), the static (T=0K) crack-tip mechanism is cleavage, thus settling the contradictions in the literature. Our work also highlights the need for multi-scale modelling to predict fracture at finite temperatures and finite strain rates.

materialscloud

en: Materials Cloud

en: Atomistic fracture in bcc iron revealed by active learning of Gaussian approximation potential

bcc-iron

display_name: bcc-iron

fracture

display_name: fracture

gaussian-approximation-potential

display_name: gaussian-approximation-potential


envi

en: Environment


en: AuNi is a classic long-studied fcc alloy combining a very "large" atom (Au) and a very "small" atom (Ni), and the large atomic size misfits suggest very high strengthening. Here, AuNi is used as a model alloy for the testing of new strengthening theories in random alloys that include the effects of both size misfits and solute–solute interactions. Experimentally, AuNi samples are fabricated, characterized, and tested, and show no segregation after annealing at 900 °C and a very high yield strength of 769 MPa. Theoretically, the main inputs to the theory (alloy lattice and elastic constants, solute misfit volumes, energy fluctuations associated with slip in the presence of solute–solute interactions) are extracted from experiments or computed using first-principles DFT. The parameter-free prediction of the yield strength is 809 MPa, in very good agreement with experiments. Solute–solute interactions enhance the strength only moderately (13%), demonstrating that the strengthening is dominated by the solute misfit contribution. Various aspects of the full theory are discussed, the general methodology is presented in an easy-to-apply analytic framework, and a new analysis for strengthening in alloys with zero misfits but non-zero solute–solute interactions is presented. These results provide support for the theories and point toward applications to many fcc complex concentrated alloys.

en: Solute misfit and solute interaction effects on strengthening: A case study in AuNi

auni

display_name: auni

misfit-volume

display_name: misfit-volume

solute-strengthening-theory

display_name: solute-strengthening-theory

stacking-fault-energy

display_name: stacking-fault-energy

yield-strength

display_name: yield-strength


marvel

display_name: marvel


en: The temperature-dependent properties of the aqueous electron have been extensively studied using mixed quantum-classical simulations in a wide range of thermodynamic conditions based on one-electron pseudopotentials. While the cavity model appears to explain most of the physical properties of the aqueous electron, only a non-cavity model has so far been successful in accounting for the temperature dependence of the absorption spectrum. Here, we present an accurate and efficient description of the aqueous electron under various thermodynamic conditions by combining hybrid functional-based molecular dynamics, machine learning techniques, and multiple time-step methods. Our advanced simulations accurately describe the temperature dependence of the absorption maximum in the presence of cavity formation. Specifically, our work reveals that the red shift of the absorption maximum results from an increasing gyration radius with temperature, rather than from global density variations as previously suggested.

en: Temperature dependent properties of the aqueous electron

ab-initio-molecular-dynamics

display_name: ab-initio-molecular-dynamics

aqueous-electron

display_name: aqueous-electron

hybrid-functional

display_name: hybrid-functional


machine-learning

display_name: machine-learning


en: Topological data analysis based on persistent homology has been applied to the molecular dynamics simulation for the fast ion-conducting phase (α-phase) of AgI, to show its effectiveness on the ion-migration mechanism analysis. Time-averaged persistence diagrams of α-AgI, which quantitatively records the shape and size of the ring structures in the given atomic configurations, clearly showed the emergence of the four-membered rings formed by two Ag and two I ions at high temperatures. They were identified as common structures during the Ag ion migration. The averaged potential energy change due to the deformation of four-membered ring agrees well with the activation energy calculated from the conductivity Arrhenius plot. The concerted motion of two Ag ions via the four-membered ring was also successfully extracted from molecular dynamics simulations by our approach, providing the new insight into the specific mechanism of the concerted motion.

en: Topological data analysis of superionic conductor silver iodide

ion-migration

display_name: ion-migration

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

persistence-diagram

display_name: persistence-diagram


en: Fracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till mid-2022. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 148, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also records the factors influential to fracture. Examples are material processing history, phase structure, grain size, uniaxial tensile properties such as yield strength and elongation, and testing conditions.

en: Dataset for fracture and impact toughness of high-entropy alloys

fracture-toughness

display_name: fracture-toughness

high-entropy-alloys

display_name: high-entropy-alloys

impact-energy

display_name: impact-energy

impact-toughness

display_name: impact-toughness


en: We present an approach for the calculation of the Z2 topological invariant in non-crystalline two-dimensional quantum spin Hall insulators. While topological invariants were originally mathematically introduced for crystalline periodic systems, and crucially hinge on tracking the evolution of occupied states through the Brillouin zone, the introduction of disorder or dynamical effects can break the translational symmetry and imply the use of larger simulation cells, where the k-point sampling is typically reduced to the single Γ-point. Here, we introduce a single-point formula for the spin Chern number that enables to adopt the supercell framework, where a single Hamiltonian diagonalisation is performed. Our single-point approach allows to calculate the spin Chern number even when the spin operator does not commute with the Hamiltonian, as in the presence of Rashba spin-orbit coupling. This archive entry contains the results of the single-point calculations of the topological invariant on the tight-binding Kane-Mele model for large supercells (up to 7200 sites). Convergence tests as function of the supercell size are reported, both in the pristine case and in presence of Anderson disorder. Single-point calculations of the spin Chern number are carried out over the entire phase diagram of the Kane-Mele model. The study of topological phase transitions due to disorder is performed in terms of single-point spin Chern number by averaging over several realisations of the Anderson disorder in the supercell.

materialscloud

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

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

en: Single-point spin Chern number in a supercell framework

anderson-disorder

display_name: anderson-disorder

kane-mele-model

display_name: kane-mele-model

spin-chern-number

display_name: spin-chern-number

supercell-framework

display_name: supercell-framework

topological-insulators

display_name: topological-insulators


en: Recent neutron-diffraction experiments in honeycomb CrI₃ quasi-2D ferromagnets have evinced the existence of a gap at the Dirac point in their spin-wave spectra. The existence of this gap has been attributed to strong in-plane Dzyaloshinskii-Moriya or Kitaev (DM/K) interactions and suggested to set the stage for topologically protected edge states to sustain non-dissipative spin transport. We perform state-of-the-art simulations of the spin-wave spectra in monolayer CrI₃, based on time-dependent density-functional perturbation theory (TDDFpT) and fully accounting for spin-orbit couplings (SOC) from which DM/K interactions ultimately stem. While our results are in qualitative agreement with experiments, the computed TDDFpT magnon gap at the Dirac point is found to be 0.47 meV, roughly six times smaller than the most recent experimental estimates, so questioning that intralayer anisotropies alone can explain the observed gap. Lattice-dynamical calculations, performed within density-functional perturbation theory (DFpT), indicate that a substantial degeneracy and a strong coupling between vibrational and magnetic excitations exist in this system, providing a possible additional gap-opening mechanism in the spin-wave spectra. To pursue this path, we introduce an interacting magnon-phonon Hamiltonian featuring a linear coupling between lattice and spin fluctuations, enabled by the magnetic anisotropy induced by SOC. Upon determination of the relevant interaction constants by DFpT and supercell calculations, this model allows us to propose magnon-phonon interactions as an important microscopic mechanism responsible for the enhancement of the gap in the range of ≈4meV around the Dirac point of the CrI₃ monolayer.

en: Magnon-phonon interactions enhance the gap at the Dirac point in the spin-wave spectra of CrI₃ two-dimensional magnets

dfpt

display_name: dfpt

magnon-phonon-coupling

display_name: magnon-phonon-coupling

magnons

display_name: magnons

marvel

display_name: marvel

phonons

display_name: phonons

quantum-espresso

display_name: quantum-espresso

tddft

display_name: tddft


en:
Super-resolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer scale. An interesting feature of this method is the possibility of monitoring microgel response to temperature changes in situ. However, when performing advanced microscopy experiments, interactions between the particle and the environment can be important. Often microgels are deposited on a substrate, since they have to remain still for several minutes during the experiment. In the publication associated with this data, we use direct stochastic optical reconstruction microscopy (dSTORM) and advanced coarse-grained molecular dynamics simulations to investigate how individual microgels anchored on hydrophilic and hydrophobic surfaces undergo their volume phase transition with temperature. We find that, in the presence of a hydrophilic substrate, the structure of the microgel is unperturbed and the resulting density profiles quantitatively agree with simulations performed under bulk conditions. Instead, when a hydrophobic surface is used, the microgel spreads at the interface and an interesting competition between the two hydrophobic strengths, monomer–monomer vs monomer–surface, comes into play at high temperatures.
The data deposited on the Materials Cloud Archive contains the initial microgel configuration in LAMMPS read format, the calculated radii and the density profiles under the different temperatures and surfaces.

en: Probing temperature responsivity of microgels and its interplay with a solid surface by super-resolution microscopy and numerical simulations

cineca-iscra

display_name: cineca-iscra

experimental

display_name: experimental

microgels

display_name: microgels

molecular-dynamics

display_name: molecular-dynamics

volume-phase-transition

display_name: volume-phase-transition


materialscloud

en: Materials Cloud


en: We present an inexpensive first-principles approach for describing quantum paraelectricity that combines density functional theory (DFT) treatment of the electronic subsystem with quantum mechanical treatment of the ions through solution of the single-particle Schrödinger equation with the DFT-calculated potential. Using BaTiO3, SrTiO3, and KTaO3 as model systems, we show that the approach can straightforwardly distinguish between ferroelectric, paraelectric, and quantum paraelectric materials, based on simple quantities extracted from standard density functional and density functional perturbation theories. We calculate the influence of isotope substitution and strain on quantum paraelectric behavior and find that, while complete replacement of oxygen-16 by oxygen-18 has a surprisingly small effect, experimentally accessible strains can induce large changes. Finally, we collect the various choices for the phonon mass that have been introduced in the literature. We ide tify those that are most physically meaningful by comparing them with our results that avoid such a choice through the use of mass-weighted coordinates.

en: Ferroelectric, quantum paraelectric, or paraelectric? Calculating the evolution from BaTiO3 to SrTiO3 to KTaO3 using a single-particle quantum mechanical description of the ions

envi

en: Environment

dft

display_name: dft

ferroelectricity

display_name: ferroelectricity

quantum-paraelectricity

display_name: quantum-paraelectricity


en: Metal surfaces have long been known to reconstruct, significantly influencing their structural and catalytic properties. Many key mechanistic aspects of these subtle transformations remain poorly understood due to limitations of previous simulation approaches. Using active learning of Bayesian machine-learned force fields trained from ab initio calculations, we enable large-scale molecular dynamics simulations to describe the thermodynamics and time evolution of the low-index mesoscopic surface reconstructions of Au (e.g., the Au(111)-`Herringbone,' Au(110)-(1x2)-`Missing-Row,' and Au(100)-`Quasi-Hexagonal' reconstructions). This capability yields direct atomistic understanding of the dynamic emergence of these surface states from their initial facets, providing previously inaccessible information such as nucleation kinetics and a complete mechanistic interpretation of reconstruction under the effects of strain and local deviations from the original stoichiometry. We successfully reproduce previous experimental observations of reconstructions on pristine surfaces and provide quantitative predictions of the emergence of spinodal decomposition and localized reconstruction in response to strain at non-ideal stoichiometries. A unified mechanistic explanation is presented of the kinetic and thermodynamic factors driving surface reconstruction. Furthermore, we study surface reconstructions on Au nanoparticles, where characteristic (111) and (100) reconstructions spontaneously appear on a variety of high-symmetry particle morphologies. The training data, MLFF, and subsequent simulations are provided for reproducibility.

en: Low-index mesoscopic surface reconstructions of Au surfaces using Bayesian force fields

density-functional-theory

display_name: density-functional-theory

machine-learning

display_name: machine-learning

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Cobalt-based oxides are active electrocatalysts for the oxygen evolution reaction (OER) in alkaline electrolytes. However, their OER activity at near-neutral pHs is generally low and more active OER catalysts at neutral pHs are desired for practical applications. Herein, La0.2Sr0.8CoO3–δ, La0.2Sr0.8Co0.8Fe0.2O3–δ, La0.5Sr1.5CoO4–δ and CoOx catalysts were prepared by the flame spray synthesis method and their surface was functionalized by a dry phosphate incorporation process. Small amount of P was incorporated on the surface of the catalyst (in the range of ppm). All the samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and soft and hard X-ray absorption spectroscopy (XAS) before and after the functionalization process. The electrocatalytic activity towards OER of the different nanoparticle catalysts was investigated in electrolytes with different pH values (pH = 7, 12.5, 13, and 13.5).

en: The role of phosphate functionalization on the oxygen evolution reaction activity of cobalt-based oxides at different pH values

alkaline-water-electrolysis

display_name: alkaline-water-electrolysis

neutral-ph

display_name: neutral-ph

phosphate-ion-functionalization

display_name: phosphate-ion-functionalization


en: Fracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till mid-2022. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 148, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also records the factors influential to fracture. Examples are material processing history, phase structure, grain size, uniaxial tensile properties such as yield strength and elongation, and testing conditions.

fracture-toughness

display_name: fracture-toughness

high-entropy-alloys

display_name: high-entropy-alloys

impact-energy

display_name: impact-energy

impact-toughness

display_name: impact-toughness


en: Magnet/superconductor hybrids (MSHs) hold the promise to host emergent topological superconducting phases. Both one-dimensional (1D) and two-dimensional (2D) magnetic systems in proximity to s-wave superconductors have shown evidence of gapped topological superconductivity with zero-energy end states and chiral edge modes. Recently, it was proposed that the bulk transition-metal dichalcogenide 4Hb-TaS2 is a gapless topological nodal-point superconductor (TNPSC). However, there has been no experimental realization of a TNPSC in a MSH system yet. In our work we present the discovery of TNPSC in antiferromagnetic (AFM) monolayers on top of an s-wave superconductor. Our calculations show that the topological phase is driven by the AFM order, resulting in the emergence of a gapless time-reversal invariant topological superconducting state. Using low-temperature scanning tunneling microscopy we observe a low-energy edge mode, which separates the topological phase from the trivial one, at the boundaries of antiferromagnetic islands. As predicted by the calculations, we find that the relative spectral weight of the edge mode depends on the edge's atomic configuration. Our results establish the combination of antiferromagnetism and superconductivity as a novel route to design 2D topological quantum phases. This record contains tight binding calculations results and a combination of STM images and tunneling spectroscopy data supporting our work.

en: Antiferromagnetism-driven two-dimensional topological nodal-point superconductivity

nodal-point-superconductivity

display_name: nodal-point-superconductivity

scaning-tunneling-microscopy

display_name: scaning-tunneling-microscopy

topological-quantum-materials

display_name: topological-quantum-materials


materialscloud

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

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


en: The search for new high-temperature alloys that can enable higher-efficiency/lower-emissions power generation has accelerated with the discovery of body-centered cubic (bcc) refractory High Entropy Alloys (HEAs). These many-component, non-dilute alloys in the Cr-Mo-W-V-Nb-Ta-Ti-Zr-Hf-Al family hold the potential for combining high strength and thermodynamic stability at high temperature with low density and room-temperature ductility, but searching the immense compositional space is daunting. Here, very recent theories and expanded thermodynamic tools are used to guide the discovery of new alloys satisfying the required suite of properties. We present the dataset we generated in search for such alloys, including 5-component equicomposition alloys, as well as new quinary and quarternary alloys in the Hf-Mo-Nb-Ta-Ti space having even better overall properties (high strength, high strength retention, good ductility, light weight and single phase).

en: Theory-guided design of high-strength, high-melting point, ductile, low-density, single-phase BCC high entropy alloys

epfl

display_name: epfl

marvel

display_name: marvel

materials-selection

display_name: materials-selection


en: Halide perovskites (HPs) are widely viewed as promising photovoltaic and light-emitting materials for their suitable band gaps in the visible spectrum. Density functional theory (DFT) calculations employing (semi)local exchange-correlation functionals usually underestimate the band gaps for these systems. Accurate descriptions of the electronic structures of HPs often demand higher-order levels of theory such as the Heyd-Scuseria-Ernzerhof (HSE) hybrid density functional and GW approximations that are much more computationally expensive than standard DFT. Here, we investigate three representative types of HPs, ABX3 halide perovskites, vacancy-ordered double perovskites (VODPs), and bond disproportionated halide perovskites (BDHPs), using DFT+U+V with onsite U and intersite V Hubbard parameters computed self-consistently without a priori assumption. The inclusion of Hubbard corrections improves the band gap prediction accuracy for all three types of HPs to a similar level of advanced methods. Moreover, the self-consistent Hubbard U is a meaningful indicator of the true local charge state of multivalence metal atoms in HPs. The inclusion of the intersite Hubbard V is crucial to properly capture the hybridization between valence electrons on neighboring atoms in BDHPs that have breathing-mode distortions of halide octahedra. In particular, the simultaneous convergence of both Hubbard parameters and crystal geometry enables a band gap prediction accuracy superior to HSE for BDHPs but at a fraction of the cost. Our work highlights the importance of using self-consistent Hubbard parameters when dealing with HPs that often possess intricate competitions between onsite localization and intersite hybridization.

en: Onsite and intersite electronic correlations in the Hubbard model for halide perovskites

band-gap

display_name: band-gap

dftuv

display_name: dftuv

halide-perovskite

display_name: halide-perovskite


en: We present a potential explanation for the strain-induced metal-insulator transition that has recently been observed in thin films of SrCrO₃ using density-functional theory (DFT) and its extension to DFT+U. Our calculations show that the unstrained system exhibits a C-type antiferromagnetically ordered ground state, which is near to a Jahn-Teller instability, given realistic values of the Hubbard U parameter. However, the significant energy overlap between the higher-lying dxy band and the dxz/dyz band works against the JT distortion's. When epitaxially strained, this overlap is reduced by the lowering of the dxyband relative to dxz/dyz as the system gets closer to the nominal integer filling. The degeneracy between the dxz and dyz orbitals is subsequently lifted by the JT distortion, opening a gap in the electronic band structure.

en: Evidence for Jahn-Teller-driven metal-insulator transition in strained SrCrO₃ from first principles calculations

dftu

display_name: dftu

jahn-teller-effect

display_name: jahn-teller-effect

orbital-order

display_name: orbital-order


materialscloud

en: Materials Cloud


en: The concept of order in disordered materials is the key to controlling the mechanical, electrical, and chemical properties of amorphous compounds widely exploited in industrial applications and daily life. Rather, it is far from being understood. Here, we propose a multi-technique numerical approach to study the order/disorder of amorphous materials on both the short- and the medium-range scale. We combine the analysis of the disorder level based on chemical and physical features with their geometrical and topological properties, defining a previously unexplored interplay between the different techniques and the different order scales. We applied this scheme to amorphous GeSe and GeSeTe chalcogenides, showing a modulation of the internal disorder as a function of the stoichiometry and composition: Se-rich systems are less ordered than Ge-rich systems at the short- and medium-range length scales. The present approach can be easily applied to more complex systems containing three or more atom types without any a priori knowledge about the system chemical–physical features, giving a deep insight into the understanding of complex systems.

en: Multi-technique approach to unravel the (dis)order in amorphous materials

amorphous

display_name: amorphous

chalcogenides

display_name: chalcogenides

disorder

display_name: disorder

intersect

display_name: intersect

molecular-dynamics

display_name: molecular-dynamics

openmodel

display_name: openmodel


envi

en: Environment


en: The magnetic, noncollinear parametrization of Dudarev's DFT+U method is generalized to fully-relativistic ultrasoft pseudopotentials. We present the definition of the DFT+U total energy functional, and the calculation of forces and stresses in the case of orthogonalized atomic orbitals defining the localised Hubbard manifold, where additional contributions arising from the derivative of the inverse square root of the overlap matrix appear. We further extend the perturbative calculation of the Hubbard U parameters within density-functional perturbation theory to the noncollinear relativistic case, by exploiting an existing and recently developed theoretical approach that takes advantage of the time-reversal operator to solve a second Sternheimer equation. We validate and apply the new scheme by studying the electronic structure and the thermodynamics of the binary compounds EuX (where X = O, S, Se, Te is a chalcogen atom), as representative simple crystals, and of the pyrochlore Cd2Os2O7, representative of a more structurally complex oxide.

en: Noncollinear DFT+U and Hubbard parameters with fully-relativistic ultrasoft pseudopotentials

first-principles

display_name: first-principles

quantum-espresso

display_name: quantum-espresso


en: Motivated by the recent experimental discovery of strongly surface-plane-dependent superconductivity at surfaces of KTaO₃ single crystals, we calculate the electron-phonon coupling strength, λ, of doped KTaO₃ along the reciprocal-space high-symmetry directions. Using the Wannier-function approach implemented in the EPW package, we calculate λ across the experimentally covered doping range and compare its mode-resolved distribution along the [001], [110] and [111] directions. We find that the electron-phonon coupling is strongest in the optical modes around the Γ point, with some distribution to higher k values in the [001] direction. The electron-phonon coupling strength as a function of doping has a dome-like shape in all three directions, and is largest in the [001] direction and weakest in the [111] direction. This is in contrast to the experimentally measured critical temperatures, which are highest for the (111) plane, pointing to a non-BCS character of the superconductivity. The strong localization of λ in the soft optical modes around Γ suggests an importance of ferroelectric soft-mode fluctuations.

en: First-principles calculation of electron-phonon coupling in doped KTaO₃

ab-initio

display_name: ab-initio

electron-phonon-coupling

display_name: electron-phonon-coupling


en:
Machine-learned interatomic potentials are fast becoming an indispensable tool in computational materials science. One approach is the ephemeral data-derived potential (EDDP), which was designed to accelerate atomistic structure prediction. The EDDP is simple and cost-efficient. It relies on training data generated in small unit cells and is fit using a lightweight neural network, leading to smooth interactions which exhibit the robust transferability essential for structure prediction. Here, we present a variety of applications of EDDPs, enabled by recent developments of the open-source EDDP software. New features include interfaces to phonon and molecular dynamics codes, as well as deployment of the ensemble deviation for estimating the confidence in EDDP predictions. Through case studies ranging from elemental carbon and lead to the binary scandium hydride and the ternary zinc cyanide, we demonstrate that EDDPs can be trained to cover wide ranges of pressures and stoichiometries, and used to evaluate phonons, phase diagrams, superionicity, and thermal expansion. These developments complement continued success in accelerated structure prediction.
This record provides the data associated with the different case studies demonstrating the uses of ephemeral data-derived potentials in the article "Developments and Further Applications of Ephemeral Data Derived Potentials".

en: Developments and further applications of ephemeral data derived potentials

hydrides

display_name: hydrides

machine-learned-interatomic-potentials

display_name: machine-learned-interatomic-potentials

metal-organic-frameworks

display_name: metal-organic-frameworks

phase-diagram

display_name: phase-diagram

phonons

display_name: phonons

superionicity

display_name: superionicity


materialscloud

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

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


en: The crystal structure of a material is essentially determined by the nature of its chemical bonding. Consequently, the atomic coordination intimately correlates with the degree of ionicity or covalency of the material. Based on this principle, materials with similar chemical compositions can be successfully categorized into different coordination groups. However, counterexamples recently emerged in complex ternary compounds. For instance, strongly covalent IB-IIIA-VIA₂ compounds, such as AgInS₂, prefer tetrahedrally coordinated structure (TCS), while strongly ionic IA-VA-VIA₂ compounds, such as NaBiS₂, would favor octahedrally coordinated structure (OCS). One naturally expects that IB-VA-VIA₂ compounds with intermediate ionicity or covalency, such as AgBiS₂, should then have a mix-coordinated structure (MCS) consisting of covalent AgS₄ tetrahedra and ionic BiS₆ octahedra. Surprisingly, only OCS was observed experimentally for AgBiS₂. To resolve this puzzle, we perform first-principles studies of the phase stabilities of ternary compounds at finite temperatures. We find that AgBiS₂ indeed prefers MCS at the ground state, in agreement with the typical expectation, but under experimental synthesis conditions disordered OCS becomes energetically more favorable because of its low mixing energy and high configurational entropy. This dataset includes structural information for the MCS and OCS configurations of ABX₂ compounds, along with the principal input data used for each calculation.

en: Dataset of disorder-stabilized unfavorable coordination in complex ABX₂ compounds

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

vasp

display_name: vasp


en: Motivated by the recent experimental discovery of strongly surface-plane-dependent superconductivity at surfaces of KTaO3 single crystals, we calculate the electron-phonon coupling strength, λ, of doped KTaO3 along the reciprocal-space high-symmetry directions. Using the Wannier-function approach implemented in the EPW package, we calculate λ across the experimentally covered doping range and compare its mode-resolved distribution along the [001], [110] and [111] reciprocal-space directions. We find that the electron-phonon coupling is strongest in the optical modes around the Γ point, with some distribution to higher k values in the [001] direction. The electron-phonon coupling strength as a function of doping has a dome-like shape in all three directions and its integrated total is largest in the [001] direction and smallest in the [111] direction, in contrast to the experimentally measured trends in critical temperatures. This disagreement points to a non-BCS character of the superconductivity. Instead, the strong localization of λ in the soft optical modes around Γ suggests an importance of ferroelectric soft-mode fluctuations, which is supported by our findings that the mode-resolved λ values are strongly enhanced in polar structures. The inclusion of spin-orbit coupling has negligible influence on our calculated mode-resolved λ values.


en: A detailed understanding of how molecules interact with two-dimensional materials, particularly concerning energy level alignment and charge transfer processes, is essential to incorporate functional molecular films into next-generation 2D material-organic hybrid devices. One of the major challenges in integrating molecular films in field-effect transistors is facilitating ambipolar charge transport, which is often hindered by the large electronic gap of the organic layers. In a recent work we compare the adsorption site-dependent energy level alignment of C60, C70, and C84 fullerenes induced by the spatial variation of the electrostatic surface potential of the h-BN/Rh(111) Moiré superstructure. As the size of the fullerenes increases, the HOMO-LUMO gap shrinks. In the case of C84, we find an intrinsic charge transfer from the substrate to the fullerenes adsorbed in the Moiré pore centers, rendering them negatively charged. The electric field effect-induced charging of neutral fullerenes and discharging of intrinsically negatively charged fullerenes are investigated using scanning tunneling spectroscopy, non-contact atomic force microscopy, and Kelvin probe force spectroscopy. Our findings show that on metal-supported h-BN, the LUMO level of C84 is sufficiently close to the Fermi energy that it can be neutral or 1e− negatively charged depending on slight variations of the electrostatic potential. The findings propose a path to make ambipolar charge transfer accessible and efficient by circumventing the need to overcome the fullerenes' electronic gap. This record contain data that support the results discussed in our work.

en: Ambipolar charge transfer of larger fullerenes enabled by the modulated surface potential of h-BN/Rh(111)

ambipolar-charge-transfer

display_name: ambipolar-charge-transfer

cscs

display_name: cscs

fullerenes

display_name: fullerenes

intermolecular-interactions

display_name: intermolecular-interactions

non-contact-atomic-force-microscopy

display_name: non-contact-atomic-force-microscopy

organic-hybrid-electronics

display_name: organic-hybrid-electronics

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy

snsf

display_name: snsf


ab-initio

display_name: ab-initio


en: In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We observe that all the range-separated hybrid functionals that correctly describe the long-range dielectric screening significantly improve from standard hybrid functionals such as PBE0 and HSE06. Among this group, the choice of the short-range Fock exchange fraction and the screening length can further reduce the predicted error. We then propose a universal expression for the selection of the inverse screening parameter as a function of the short-range and long-range Fock exchange fractions, which results in a mean absolute error as small as 0.15 eV for band gap prediction.

en: Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

density-functional-theory

display_name: density-functional-theory

hybrid-functional

display_name: hybrid-functional

quantum-espresso

display_name: quantum-espresso


materialscloud

en: Materials Cloud


en: This dataset includes all data presented in the figures of the main manuscript: XPS work function changes, ab-initio calculated work functions, O2p band center shifts, Densities of state for LSC and PCO, i-PLD results for LSC, LSF, STF and PCO, Densities of state for adsorbed O2 on differently decorated PCO surfaces. In this work, we investigated surface dipole changes which were induced by modification of mixed conducting surfaces with binary oxides via pulsed laser deposition.

en: Engineering surface dipoles on mixed conducting oxides with ultra-thin oxide decoration layers

oxygen-exchange

display_name: oxygen-exchange

surface-chemistry

display_name: surface-chemistry

work-function

display_name: work-function


envi

en: Environment


en: This dataset includes all the atomic coordinates of the optimized computational models from electronic structure calculations reported in the manuscript. In this work, we highlight that single-site noble metal dopants on the Cu surface can influence C–O bond dissociation in a key selectivity-determining intermediate (e.g., oxygen-bound *CH₂CHO), which in turn direct the post-C–C coupling pathways to ethylene versus ethanol. Combining theoretical and experimental analyses, we demonstrate that the favorability of C–O bond scission is controlled by the oxygen affinity of the metal dopant on the Cu catalyst. We find that the selectivity ratio of ethylene-to-ethanol displays a volcano relationship with respect to the oxygen binding strength on the doped surfaces.

en: Directing CO₂ electroreduction pathways for selective C₂ product formation using single-site doped Cu catalysts

selectivity

display_name: selectivity

single-site-doped-catalysts

display_name: single-site-doped-catalysts


en: Accurate first-principles predictions of the structural, electronic, magnetic, and electrochemical properties of cathode materials can be key in the design of novel efficient Li-ion batteries. Spinel-type cathode materials LixMn2O4 and LixMn1.5Ni0.5O4 are promising candidates for Li-ion battery technologies, but they present serious challenges when it comes to their first-principles modeling. Here, we use density-functional theory with extended Hubbard functionals - DFT+U+V with on-site U and inter-site V Hubbard interactions - to study the properties of these transition-metal oxides. The Hubbard parameters are computed from first-principles using density-functional perturbation theory. We show that while U is crucial to obtain the right trends in properties of these materials, V is essential for a quantitative description of the structural and electronic properties, as well as the Li-intercalation voltages. This work paves the way for reliable first-principles studies of other families of cathode materials without relying on empirical fitting or calibration procedures.

en: Unraveling the effects of inter-site Hubbard interactions in spinel Li-ion cathode materials

dftu

display_name: dftu

dftuv

display_name: dftuv

extended-hubbard-functionals

display_name: extended-hubbard-functionals

li-ion-batteries

display_name: li-ion-batteries

lithium-intercalation-voltage

display_name: lithium-intercalation-voltage

marvelosp

display_name: marvelosp

spinel-cathode-materials

display_name: spinel-cathode-materials


cscs

display_name: cscs


en: Perovskite oxynitrides are, due to their reduced band gap compared to oxides,  promising materials for photocatalytic applications. They are most commonly synthesized from {110} layered Carpy-Galy (A₂B₂O₇) perovskites via thermal ammonolysis, i.e. the exposure to a flow of ammonia at elevated temperature. The conversion of the layered oxide to the non-layered oxynitride must involve a complex combination of nitrogen incorporation, oxygen removal and ultimately structural transition by elimination of the interlayer shear plane. Despite the process being commonly used, little is known about the microscopic mechanisms and hence factors that could ease the conversion. Here we aim to derive such insights via density functional theory calculations of the defect chemistry of the oxide and the oxynitride as well as the oxide's surface chemistry. Our results point to the crucial role of surface oxygen vacancies in forming clusters of NH₃ decomposition products and in incorporating N, most favorably substitutionally at the anion site. N then spontaneously diffuses away from the surface, more easily parallel to the surface and in interlayer regions, while diffusion perpendicular to the interlayer plane is somewhat slower. Once incorporation and diffusion lead to a local N concentration of about 70 % of the stoichiometric oxynitride composition, the nitridated oxide spontaneously transforms to a nitrogen-deficient oxynitride.

en: Conversion of La₂Ti₂O₇ to LaTiO₂N via ammonolysis: An ab-initio investigation

ammonolysis

display_name: ammonolysis

defects

display_name: defects

marvel

display_name: marvel

oxynitride

display_name: oxynitride

snsf

display_name: snsf


materialscloud

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

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


en: Even though fracture in solids can be rationalized in continuum mechanics, local processes such as the path selection and the formation of facets and kinks along the crack edges cannot be resolved in this framework. The problem is addressed by developing a high-fidelity neural network-based force field NN-F3. An active-learning approach is taken to capture the high strain and non-equilibrium nature of the crack tips in 2D crystals such as graphene and h-BN, which has not been satisfactorily addressed by existing empirical and machine-learning force fields. Atomistic simulations using NN-F3 resolve spatial complexities from lattice-scale kinks to sample-scale crack patterns, which are discussed directly with continuum mechanics predictions and experimental observation. The results show that kinking or deflection of the cracks defines the roughness of cleaved edges and is explained by the alternation of the stress intensity factors. We also find that the selection of crack paths cannot be determined by the anisotropy in the energies of relaxed edges as widely referred to in the literature. The distortion and undercoordination of the cleaved edges play critical roles in the fracture process, which have to be incorporated into the models to predict the crack paths. Measures of fracture toughness are extracted from the fracture patterns, the critical stress intensity factors, or the energies of edges in the intermediate, unrelaxed states.

en: Crack path selection in 2D crystals

fracture-anisotropy

display_name: fracture-anisotropy

fracture-mechanics

display_name: fracture-mechanics

graphene

display_name: graphene

machine-learning

display_name: machine-learning

neural-newrok-force-field

display_name: neural-newrok-force-field


en: Local processes during fracture, such as the selection of crack paths and the formation of facets and kinks along the paths, are non-equilibrium and discrete in nature and cannot be resolved in the framework of continuum thermodynamics. Atomistic models using existing empirical or machine-learning force fields also fail to offer satisfactory solutions. The problem is addressed here by developing a high-fidelity neural network-based force field (NN-F³) following an active-learning approach that covers the space spanned by strain states up to material failure and the non-equilibrium, intermediate states of atomic-level structures during cracking. Atomistic simulations using NN-F³ identify spatial complexities from lattice-scale kinks to sample-scale crack patterns in 2D crystals such as graphene and h-BN. The selection of crack paths is found to be associated with alternation in the stress intensity factors and anisotropy in the fracture toughness, which defines the roughness of cleaved edges. We find that the non-uniform lattice distortion and undercoordination of cleaved edges at the crack front play critical roles in the fracture process, which cannot be described by the energy densities of relaxed edges as widely used in the literature. Instead, the fracture patterns, the critical stress intensity factors corresponding to the lattice kinks, and the energy densities of edges in the intermediate, unrelaxed states offer reasonable measures for the fracture toughness and its anisotropy, which can be determined from experiments or simulations with the atomic-level resolution and well explain the experimental observation.

en: Non-equilibrium nature of fracture determines the crack path


en: A high-fidelity neural network-based force field (NN-F³) is developed to cover the space of strain states up to material failure and the non-equilibrium, intermediate nature of fracture. Simulations of fracture in 2D crystals using NN-F³ reveal spatial complexities from lattice-scale kinks to sample-scale patterns. We find that the fracture resistance cannot be captured by the energy densities of relaxed edges as used in the literature. Instead, the fracture patterns, critical stress intensity factors at the kinks, and energy densities of edges in the intermediate, unrelaxed states offer reasonable measures for the fracture toughness and its anisotropy.


en: The recent development of ultra-fast MAS (>100 kHz) provides new opportunities for structural characterization in solids. Here we use NMR crystallography to validate the structure of verinurad, a microcrystalline active pharmaceutical ingredient. To do this, we take advantage of 1H resolution improvement at ultra-fast MAS and use solely 1H-detected experiments and machine learning methods to assign all the experimental proton and carbon chemical shifts. This framework provides a new tool for elucidating chemical information from crystalline samples with limited sample volume and yields remarkably faster acquisition times compared to 13C-detected experiments, without the need to employ dynamic nuclear polarization.

en: Crystal structure validation of verinurad via proton-detected ultra-fast MAS NMR and machine learning

nmr-crystallography

display_name: nmr-crystallography

solid-state-nmr

display_name: solid-state-nmr

verinurad

display_name: verinurad


materialscloud

en: Materials Cloud


en: We show that hematite, 𝛼-Fe₂O₃, below its Morin transition, has a ferroic ordering of rank-5 magnetic triakontadipoles on the Fe ions. In the absence of spin-orbit coupling, these are the lowest-order ferroically aligned magnetic multipoles, and they give rise to the g-wave non-relativistic spin splitting in hematite. We find that the ferroically ordered magnetic triakontadipoles result from the simultaneous antiferroic ordering of the charge hexadecapoles and the magnetic dipoles, providing a route to manipulating the magnitude and the sign of the magnetic triakontadipoles as well as the spin splitting. Furthermore, we find that both the ferroic ordering of the magnetic triakontadipoles and many of the spin-split features persist in the weak ferromagnetic phase above the Morin transition temperature.

en: Non-relativistic ferromagnetotriakontadipolar order and spin splitting in hematite

erc

display_name: erc

multipoles

display_name: multipoles


envi

en: Environment


en: Since the preliminary work of Anisimov and co-workers, the Hubbard corrected DFT+U functional has been used for predicting properties of correlated materials by applying on-site effective Coulomb interactions to specific orbitals. However, the determination of the Hubbard U parameter has remained under intense discussion despite the multitude of approaches proposed. Here, we define a selection criterion based on the use of polaronic defect states for the enforcement of the piecewise linearity of the total energy upon electron occupation. A good agreement with results from piecewise-linear hybrid functionals is found for the electronic and structural properties of polarons, including the formation energies. The values of U determined in this way are found to give a robust description of the polaron energetics upon variation of the considered state. In particular, we also address a polaron hopping pathway, finding that the determined value of U leads to accurate energetics without requiring a configurational-dependent U. It is emphasized that the selection of U should be based on physical properties directly associated with the orbitals to which U is applied, rather than on more global properties such as band gaps and band widths.  For comparison, we also determine U through a well-established linear-response scheme finding noticeably different values of U and consequently different formation energies. Possible origins of these discrepancies are discussed. As case studies, we consider the self-trapped electron in BiVO₄, the self-trapped hole in MgO, the Li-trapped hole in MgO, and the Al-trapped hole in 𝛼-SiO₂.

en: Hubbard U through polaronic defect states

density-functional-theory

display_name: density-functional-theory

dftu

display_name: dftu

hybrid-functionals

display_name: hybrid-functionals

polarons

display_name: polarons

self-interaction

display_name: self-interaction


en: We establish the sign of the linear magnetoelectric (ME) coefficient, α, in chromia, Cr₂O₃. Cr₂O₃ is the prototypical linear ME material, in which an electric (magnetic) field induces a linearly proportional magnetization (polarization), and a single magnetic domain can be selected by annealing in combined magnetic (H) and electric (E) fields. Opposite antiferromagnetic domains have opposite ME responses, and which antiferromagnetic domain corresponds to which sign of response has previously been unclear. We use density functional theory (DFT) to calculate the magnetic response of a single antiferromagnetic domain of Cr₂O₃ to an applied in-plane electric field at 0 K. We find that the domain with nearest neighbor magnetic moments oriented away from (towards) each other has a negative (positive) in-plane ME coefficient, α⊥, at 0 K. We show that this sign is consistent with all other DFT calculations in the literature that specified the domain orientation, independent of the choice of DFT code or functional, the method used to apply the field, and whether the direct (magnetic field) or inverse (electric field) ME response was calculated. Next, we reanalyze our previously published spherical neutron polarimetry data to determine the antiferromagnetic domain produced by annealing in combined E and H fields oriented along the crystallographic symmetry axis at room temperature. We find that the antiferromagnetic domain with nearest-neighbor magnetic moments oriented away from (towards) each other is produced by annealing in (anti-)parallel E and H fields, corresponding to a positive (negative) axial ME coefficient, α∥, at room temperature. Since α⊥ at 0 K and α∥ at room temperature are known to be of opposite sign, our computational and experimental results are consistent. This dataset contains the input data to reproduce the calculation of the magnetoelectric effect as plotted in Fig. 3 of the manuscript, for Elk, Vasp, and Quantum Espresso.

en: On the sign of the linear magnetoelectric coefficient in Cr₂O₃

dft

display_name: dft

horizon-europe

display_name: horizon-europe

magnetoelectric

display_name: magnetoelectric


en:
The development of novel double-hybrid density functionals offers new levels of accuracy, and is leading to fresh insights into the fundamental properties of matter. Hartree–Fock exact exchange and correlated wave function methods such as MP2 and direct RPA are usually required to build such functionals. Their high computational cost is a concern, and their application to large and periodic systems is therefore limited. In this work, low-scaling methods for HFX, SOS-MP2 and direct RPA energy gradients are developed and implemented in the CP2K software package. The use of the resolution-of-the-identity approximation with a short range metric and atom-centered basis functions lead to sparsity, allowing for sparse tensor contractions to take place. These operations are efficiently performed with the newly developed DBT and DBM libraries, which scale to hundreds of GPU nodes. The resulting methods, RI-HFX, SOS-MP2 and dRPA, were benchmarked on large supercomputers. They exhibit favorable sub-cubic scaling with system size, good strong scaling performance, and GPU acceleration up to a factor of 3. These developments will allow for double-hybrid level calculations of large and periodic condensed phase systems to take place on a more regular basis.

This record contains all CP2K input and output files used for the paper.

en: Sparse tensor based nuclear gradients for periodic Hartree–Fock and low-scaling correlated wave function methods in the CP2K software package: A massively parallel and GPU accelerated implementation.

correlated-wave-function

display_name: correlated-wave-function

gpu

display_name: gpu

hartree-fock

display_name: hartree-fock

hpc

display_name: hpc

low-scaling

display_name: low-scaling

nuclear-gradients

display_name: nuclear-gradients

rpa

display_name: rpa

sparse-tensors

display_name: sparse-tensors


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).