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

materialscloud

en: Materials Cloud

epfl

display_name: epfl

marvel

display_name: marvel

materials-selection

display_name: materials-selection


$oid: OBSOLETE

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

materialscloud

approval_status: approved

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

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

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

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


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


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:
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


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: 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: 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)

materialscloud

en: Materials Cloud

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


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

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).

density-functional-theory

display_name: density-functional-theory

hybrid-functional

display_name: hybrid-functional

quantum-espresso

display_name: quantum-espresso


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

envi

en: Environment

oxygen-exchange

display_name: oxygen-exchange

surface-chemistry

display_name: surface-chemistry

work-function

display_name: work-function


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


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: Non-equilibrium nature of fracture determines the crack path

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: 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


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

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: Structurally and conformationally diverse databases are needed to train accurate neural networks or kernel-based potentials capable of exploring the complex free energy landscape of flexible functional organic molecules. Curating such databases for species beyond "simple" drug-like compounds or molecules comprised of well-defined building blocks (e.g., peptides) is challenging, as it requires thorough chemical space mapping and evaluation of both chemical and conformational diversity. Here, we introduce the OFF–ON (Organic Fragments From Organocatalysts that are Non-modular) database, a repository of 7,869 equilibrium and 67,457 non--equilibrium geometries of organic compounds and dimers aimed at describing conformationally flexible functional organic molecules, with an emphasis on photoswitchable organocatalysts. The relevance of this database is then demonstrated by training a Local Kernel Regression model on a low-cost semiempirical baseline and comparing it with a PBE0-D3 reference for several known catalysts, notably the free energy surfaces of exemplary photoswitchable organocatalysts. Our results demonstrate that the OFF–ON dataset offers reliable predictions for simulating the conformational behavior of virtually any (photoswitchable) organocatalyst or organic compound comprised of H, C, N, O, F, and S atoms, thereby opening a computationally feasible route to explore complex free energy surfaces in order to rationalize and predict catalytic behavior.

en: From organic fragments to photoswitchable catalysts: the off-on structural repository for transferable kernel-based potentials

materialscloud

en: Materials Cloud

free-energy

display_name: free-energy

photoswitchable-organocatalyst

display_name: photoswitchable-organocatalyst


en: Antiferromagnets are promising platforms for transduction and transmission of quantum information via magnons — the quanta of spin waves — and they offer advantages over ferromagnets in regard to dissipation, speed of response, and robustness to external fields. Recently, transduction was shown in a van der Waals antiferromagnets, where strong spin-exciton coupling enables readout of the amplitude and phase of coherent magnons by photons of visible light. This discovery shifts the focus of research to transmission, specifically to exploring the nonlocal interactions that enable magnon wave packets to propagate. Here we demonstrate that magnon propagation is mediated by the long-range dipole-dipole interaction. This coupling is an inevitable consequence of fundamental electrodynamics, and as such, will likely mediate the propagation of spin at long wavelengths in the entire class of van der Waals magnets currently under investigation. Successfully identifying the mechanism of spin propagation provides a set of optimization rules, as well as caveats, that are essential for any future applications of these promising systems.

en: Dipolar spin wave packet transport in a van der Waals antiferromagnet

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).

antiferromagnets

display_name: antiferromagnets

magnetostatic-spin-waves

display_name: magnetostatic-spin-waves

spin-transport

display_name: spin-transport

time-resolved-kerr-microscopy

display_name: time-resolved-kerr-microscopy


en: Here we report a resonant x-ray diffraction (RXD) study at the Cu L₃ edge on the multichiral system CsCuCl₃, exhibiting helical magnetic order in a chiral crystal structure. RXD is a powerful technique to disentangle electronic degrees of freedom due to its sensitivity to electric monopoles (charge), magnetic dipoles (spin), and electric quadrupoles (orbital). We characterize electric quadrupole moments around Cu ascribed to the unoccupied Cu 3d orbital, whose quantization axis is off the basal plane. Detailed investigation of magnetic reflections reveals additional sinusoidal modulations along the principal axis superimposed on the reported helical structure, i.e., a longitudinal conical (helical-butterfly) structure. The out-of-plane modulations imply significant spin-orbit interaction despite S=1/2 of Cu²⁺.

en: Conical spin order with chiral quadrupole helix in CsCuCl₃

envi

en: Environment

experimental

display_name: experimental

marvel

display_name: marvel


en:
Tin-lead halide perovskites with a bandgap near 1.2 electron-volt hold great promise for thin-film photovoltaics. However, the film quality of solution-processed Sn-Pb perovskites is compromised by the asynchronous crystallization behavior between Sn and Pb components, where the crystallization of Sn-based perovskites tends to occur faster than that of Pb. Here we show that the rapid crystallization of Sn is rooted in its stereochemically active lone pair, which impedes coordination between the metal ion and Lewis base ligands in the perovskite precursor. From this perspective, we introduce a noncovalent binding agent targeting the open metal site of coordinatively unsaturated Sn(II) solvates, thereby synchronizing crystallization kinetics and homogenizing Sn-Pb alloying. The resultant single-junction Sn-Pb perovskite solar cells achieve a certified power conversion efficiency of 24.13 per cent. The encapsulated device retains 90 per cent of the initial efficiency after 795 hours of maximum power point operation under simulated one-sun illumination.
We conducted DFT and AIMD simulations to study the structure and interactions of metal iodide-solvent ligand complexes. This archive contains the optimized atomic coordinates of PbI2/SnI2-ligands complexes and the initial and final configurations of AIMD trajectories.

en: Synchronized crystallization in tin-lead perovskite solar cells

halide-perovskite

display_name: halide-perovskite

lead-iodide

display_name: lead-iodide

tin-iodide

display_name: tin-iodide


en:
This data record contains the xyz-style files for 2'707 organic molecular crystals and their 3'202 molecular components. The crystals were initially taken directly from the Cambridge Structure Database, and the relaxations were computed and reported by [1]. This record contains an augmentation of a subset of this data, where we have identified the molecular constituents of each crystal, performed geometric relaxations using the same computational parameters, and identified the constituent functional groups. A full detail of methodology and provenance is included in the ESI of [2].
Each crystal and molecule has been relaxed using Quantum Espresso with the following parameters: the PBE exchange-correlation functional, the D2 dispersion correction, ultrasoft pseudopotentials with GIPAW reconstruction, and an equivalent plane-wave energy cutoff of 60 Ryd. We converged the energies within 1E-4 Ryd and forces below 1E-3 Ryd/Bohr, respectively, using MT-decoupling for the molecules to ensure no self-interaction. Furthermore, we compute the binding energy based on the lowest energy conformed represented in the dataset, ensuring comparability between crystals and co-crystals of similar stoichiometries without needing to obtain the global minimum conformation of each molecule.

en: Lattice energies and relaxed geometries for 2'707 organic molecular crystals and their 3'242 molecular components.

snsf

display_name: snsf

trinity-college

display_name: trinity-college


en: Verification and validation of methods and first-principles software are at the core of computational solid-state physics but are too rarely addressed. We compare four first-principles codes: Abinit, Quantum ESPRESSO, EPW, ZG, and three methods: (i) the Allen-Heine-Cardona theory using density functional perturbation theory (DFPT), (ii)  the Allen-Heine-Cardona theory using Wannier function perturbation theory (WFPT), and (iii) an adiabatic non-perturbative frozen-phonon method. For these cases, we compute the real and imaginary parts of the electron-phonon self-energy in diamond and BAs, including dipoles and quadrupoles when interpolating. We find excellent agreement between software that implements the same formalism as well as good agreement between the DFPT and WFPT methods. Importantly, we find that the Deybe-Waller term is momentum dependent which impacts the mass enhancement, yielding approximate results when using the Luttinger approximations. Finally, we compare the electron-phonon spectral functions between Abinit and EPW and find excellent agreement even away from the band edges.

en: Zero-point renormalization of the bandgap, mass enhancement, and spectral functions: Validation of methods and verification of first-principles codes

ab-initio

display_name: ab-initio

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

verification-and-validation

display_name: verification-and-validation

zero-point-renormalization

display_name: zero-point-renormalization


en:
Multi-band effects in superconducting heterostructures provide a rich playground for unconventional physics. We combine two complementary approaches based on density-functional theory (DFT) and effective low-energy model theory in order to investigate the proximity effect in a gold overlayer on the s-wave superconductor aluminium. We explain both theoretical approaches and intertwine the effective model and DFT analysis. This allows us to predict finite energy superconducting avoided crossings due to the interplay of the Rashba surface state of Au, and hybridization with the electronic structure of superconducting Al. We investigate the nature of the induced superconducting pairing and analyze their mixed singlet-triplet character. Our findings demonstrate the general recipes to explore material systems that exhibit novel finite-energy pairings.

This dataset accompanies a publication where the data is presented and discussed in detail.

en: Proximity-induced Cooper pairing at low and finite energies in the gold Rashba surface state

bogoliubov-de-gennes

display_name: bogoliubov-de-gennes

jukkr

display_name: jukkr

spin-orbit-coupling

display_name: spin-orbit-coupling

superconductivity

display_name: superconductivity


en: Multi-junction solar cells pose a particular modeling challenge, and advanced methods are needed to improve their efficiency and reduce their cost. We present here data about the I-V and P-V characteristics gotten using the electrical parameters obtained through an easy method to extract the electrical parameters of multi-junction solar cells using a single-diode model. The proposed technique is based solely on manufacturer data, and we solve the necessary mathematical equations numerically.

en: Curves data of a simple implicit method for parameters estimation of multi-junction solar cells

iv

display_name: iv

multiple-junction

display_name: multiple-junction

parameter-extraction-methods

display_name: parameter-extraction-methods

solar-energy

display_name: solar-energy


en:
A dataset of 35,608 materials with their topological properties is constructed by combining the density functional theory (DFT) results of Materiae and the Topological Materials Database. Thanks to this, machine-learning approaches are developed to categorize materials into five distinct topological types, with the XGBoost model achieving an impressive 85.2% classification accuracy. By conducting generalization tests on different sub-datasets, differences are identified between the original datasets in terms of topological types, chemical elements, unknown magnetic compounds, and feature space coverage. Their impact on model performance is analyzed.
Turning to the simpler binary classification between trivial insulators and nontrivial topological materials, three different approaches are also tested. Key characteristics influencing material topology are identified, with the maximum packing efficiency and the fraction of p valence electrons being highlighted as critical features.

en: Machine learning on multiple topological materials datasets

materialscloud

en: Materials Cloud

database

display_name: database

machine-learning

display_name: machine-learning

topological-materials

display_name: topological-materials


en: Efficient O₂ reduction to H₂O₂, vital for energy conversion and environmental cleanup, relies on precise control of heterogeneous catalysts interacting with reaction species. Through high-throughput density functional theory calculations, consisting of 369 single atom catalysts, we identified the polarized descriptor (electric dipole strength) on two-dimensional carbon materials, revealing insights into the catalytic effect of support polarization. Surprisingly, this descriptor exhibits advanced scaling relationships towards H₂O₂ synthesis, incorporating factors such as active metals, coordination environments, and surface curvatures, highlighting its widespread significance. Furthermore, it demonstrates reliable predictability for O₂ adsorption in dynamic water environments, with optimal reactivity observed within the range of -1.40 to -1.00 e·Å, as confirmed by dynamic and static simulations of the 2e- pathway of O₂ reduction. In essence, these findings offer valuable insights for the rational design of electrocatalysts tailored for selective O₂ reduction.

en: Scaling relations and dynamical predictiveness of electric dipole strength on 2e- ORR catalytic property

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).

density-functional-theory-calculations

display_name: density-functional-theory-calculations

electric-dipole-strength

display_name: electric-dipole-strength

oxygen-reduction-reaction

display_name: oxygen-reduction-reaction

support-polarization

display_name: support-polarization


en:
This study presents the initial implementation of the Fast INtention-Agnostic LEarning Server (FINALES) in a demonstration of a distributed Materials Acceleration Platform (MAP) including experimental and computational methods and a machine learning (ML)-based optimizer. In this demonstration, the optimizer was configured to minimize the density of the electrolyte solutions while maximizing the viscosity by exploiting experimental and computational results. The tenants (the units connected to FINALES in the MAP) are shortly described in the following:

- Autonomous Synthesis and Analysis of Battery electrolytes (ASAB) setup: an experimental tenant providing density and viscosity data using a densimeter of the type DMA 4100M and a viscometer of type Lovis 2000 both by Anton Paar Germany
- Molecular dynamics tenant: a computational tenant capable of providing radial distribution functions, diffusion coefficients, ionic conductivity, transference numbers, heat capacity and density data to the MAP
- Optimizer: the tenant guiding the optimization by processing the available data and generating requests for electrolyte formulations to be tested subsequently

This dataset accompanies the publication:
Vogler, M., Busk, J., Hajiyani, H., Jørgensen, P. B., Safaei, N., Castelli, I. E., Ramirez, F. F., Carlsson, J., Pizzi, G., Clark, S., Hanke, F., Bhowmik, A. & Stein, H. S. Brokering between tenants for an international materials acceleration platform. Matter 6, 2647–2665 (2023). DOI: https://doi.org/10.1016/j.matt.2023.07.016

en: FINALES (06/2022) – Electrolyte Optimization for Minimum Density and Maximum Viscosity

envi

en: Environment

battery-electrolyte

display_name: battery-electrolyte

big-map

display_name: big-map

conductivity

display_name: conductivity

density

display_name: density

materials-acceleration-platform-map

display_name: materials-acceleration-platform-map

polis

display_name: polis

radial-distribution-function-rdf

display_name: radial-distribution-function-rdf

viscosity

display_name: viscosity


en: Proximity-induced superconductivity in hybrid devices of topological insulators and superconductors offers a promising platform for the pursuit of elusive topological superconductivity and its anticipated applications, such as fault-tolerant quantum computing. To study and harness such hybrid devices, a key challenge is the realization of highly functional material interfaces with a suitable superconductor featuring 2e-periodic parity-conserving transport to ensure a superconducting hard-gap free of unpaired electrons, which is important for Majorana physics. A superconductor well-known for this characteristic is Al, however, its direct integration into devices based on tetradymite topological insulators has so far been found to yield non-transparent interfaces. By focusing on Bi₂Te₃-Al heterostructures, this study identifies detrimental interdiffusion processes at the interface through atomically resolved structural and chemical analysis, and showcase their mitigation by leveraging different interlayers – namely Nb, Ti, Pd, and Pt – between Bi₂Te₃ and Al. Through structural transformation of the interlayer materials (X) into their respective tellurides (XTe₂) atomically-sharp epitaxial interfaces are engineered and further characterized in low-temperature transport experiments on Al-X-Bi₂Te₃-X-Al Josephson junctions and in complementary density functional theory calculations. By demonstrating functional interfaces between Bi₂Te₃ and Al, this work provides key insights and paves the way for the next generation of sophisticated topological devices.

en: Engineering epitaxial interfaces for topological insulator – superconductor hybrid devices with Al electrodes

dft

display_name: dft

epitaxial-interfaces

display_name: epitaxial-interfaces

fleur

display_name: fleur

hybrid-devices

display_name: hybrid-devices

interface-engineering

display_name: interface-engineering

josephson-junctions

display_name: josephson-junctions

jukkr

display_name: jukkr

majorana-platform

display_name: majorana-platform

superconductors

display_name: superconductors

tmdc

display_name: tmdc

topological-insulator

display_name: topological-insulator

topological-superconductivity

display_name: topological-superconductivity


en: The nature of the gap observed at the zone border in the spin excitation spectrum of CrI₃ quasi-two-dimensional single crystals is still controversial. We perform first-principles calculations based on time-dependent density functional perturbation theory, which indicate that the observed gap results from a combination of spin-orbit and interlayer interaction effects. The former give rise to the anisotropic spin-spin interactions that are responsible for its very existence, while the latter determine both its displacement from the K point of the Brillouin zone, due to the in-plane lattice distortions induced by them, and an enhancement of its magnitude, in agreement with experiments and previous theoretical work based on a lattice model.

en: First-principles study of the gap in the spin excitation spectrum of the CrI₃ honeycomb ferromagnet

dirac-cone

display_name: dirac-cone

magnons

display_name: magnons

marvel

display_name: marvel

quantum-espresso

display_name: quantum-espresso

tddft

display_name: tddft


en:
Data-driven techniques are increasingly used to replace electronic-structure calculations of matter. In this context, a relevant question is whether machine learning (ML) should be applied directly to predict the desired properties or be combined explicitly with physically-grounded operations. We present an example of an integrated modeling approach, in which a symmetry-adapted ML model of an effective Hamiltonian is trained to reproduce electronic excitations from a quantum-mechanical calculation. The resulting model can make predictions for molecules that are much larger and more complex than those that it is trained on, and allows for dramatic computational savings by indirectly targeting the outputs of well-converged calculations while using a parameterization corresponding to a minimal atom-centered basis. Our results on a comprehensive dataset of hydrocarbons emphasize the merits of intertwining data-driven techniques with physical approximations, improving the transferability and interpretability of ML models without affecting their accuracy and computational efficiency, and providing a blueprint for developing ML-augmented electronic-structure methods.
Here we include the dataset, accompanying the paper linked below, of hydrocarbons including ethane, ethene, butadiene, hexane, hexatriene, isoprene, styrene, polyalkenes (dodecahexaene, tetradecaheptaene, hexadecaoctaene, octadecanonaene, eicosadecaene), aromatics (benzene, azulene, naphthalene, biphenyl), anthracene, beta-carotene, fullerene. We also provide scripts to generate the Fock and overlap matrices in this dataset. The code for machine learning can be found at the Software reference below.

en: Electronic excited states from physically-constrained machine learning

epfl

display_name: epfl

erc

display_name: erc

excited-states

display_name: excited-states

fiamma

display_name: fiamma

hamiltonian

display_name: hamiltonian

lifetimes

display_name: lifetimes

machine-learning

display_name: machine-learning


en: We study self-interaction effects in solvated and strongly-correlated cationic molecular clusters, with a focus on the solvated hydroxyl radical. To address the self-interaction issue, we apply the DC-r²SCAN method, with the auxiliary density matrix approach. Validating our method through simulations of bulk liquid water, we demonstrate that DC-r²SCAN maintains the structural accuracy of r²SCAN while effectively addressing spin density localization issues. Extending our analysis to solvated cationic molecular clusters, we find that the hemibonded motif in the [CH₃S∴CH₃SH]⁺ cluster is disrupted in the DC-r²SCAN simulation, in contrast to r²SCAN that preserves the (three-electron-two-center)-bonded motif. Similarly, for the [SH∴SH₂]⁺ cluster, r²SCAN restores the hemibonded motif through spin leakage, while DC-r²SCAN predicts a weaker hemibond formation influenced by solvent-solute interactions. Our findings demonstrate the potential of DC-r²SCAN combined with the auxiliary density matrix method to improve electronic structure calculations, providing insights into the properties of solvated cationic molecular clusters. This work contributes to the advancement of self-interaction corrected electronic structure theory and offers a computational framework for modeling condensed phase systems with intricate correlation effects.

en: Radicals in aqueous solution: Assessment of density-corrected SCAN functional

aqueous-hydroxyl-radical

display_name: aqueous-hydroxyl-radical

aqueous-sulfanyl-radical

display_name: aqueous-sulfanyl-radical

density-corrected-dft

display_name: density-corrected-dft

density-functional-theory

display_name: density-functional-theory

hydrogen-sulfide

display_name: hydrogen-sulfide

methanethiol

display_name: methanethiol


en: The poor ductility of hcp Mg is attributed to the low activity of non-basal slip systems and so activation of prismatic slip can aid ductility in rolled sheets by providing three additional  Burgers vector slip systems.  Experimental studies show that dilute additions of alloying elements such as Zn and Al leads to softening of prismatic slip at low temperatures but strengthening at higher temperatures.  Here, the role of solute strengthening of prismatic edge dislocations is investigated as a possible explanation for the higher-T strengthening.  Mg-Zn is studied using first-principles inputs in a parameter-free solute strengthening theory.  First-principles DFT is necessary to accurately assess the strong solute chemical interaction energies in the core of the compact edge dislocation.   Such calculations are subtle due to motion of the dislocation in the presence of the solute, and methods to obtain reliable results with acceptable computational cost are discussed.   While interaction energies of Zn in the prism edge core can be quite large (+/- 0.34 eV), the edge solute strengthening of prismatic slip in dilute Mg-Zn remains well below experiments at high temperatures.  However, the large difference (0.68 eV) in Zn/dislocation interaction energies across the core of the edge dislocation suggests strengthening by dynamic strain aging as an explanation for the higher-T strengthening.

en: Solute strengthening of prism edge dislocations in Mg alloys

dft

display_name: dft

edge-solute-strengthening

display_name: edge-solute-strengthening

mg-zn

display_name: mg-zn

prismatic-slip

display_name: prismatic-slip

solutedislocation-interaction-energy

display_name: solutedislocation-interaction-energy


en: The reactivity of silicates in aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of chemical reactions can provide insight at the molecular level, balancing accuracy and scale in reactive simulations in the condensed phase is a challenge. Here, we demonstrate how a machine-learning reactive interatomic potential can accurately capture silicate-water reactivity. The model was trained on a new dataset comprising 400,000 energies and forces of molecular clusters at the 𝜔-B97XD\def2-TVZP level. To ensure the robustness of the model, we introduce a new and general active learning strategy based on the attribution of the model uncertainty, that automatically isolates uncertain regions of bulk simulations to be calculated as small-sized clusters. Our trained potential is found to reproduce static and dynamic properties of liquid water and solid crystalline silicates, despite having been trained exclusively on cluster data. Furthermore, we utilize enhanced sampling simulations to recover the self-ionization reactivity of water accurately, and the acidity of silicate oligomers, and lastly study the silicate dimerization reaction in a water solution at neutral conditions and find that the reaction occurs through a flanking mechanism.

en: Learning a reactive potential for silica-water through uncertainty attribution

materialscloud

en: Materials Cloud

active-learning

display_name: active-learning

chemical-reactions

display_name: chemical-reactions

free-energy

display_name: free-energy

neural-network-potential

display_name: neural-network-potential

silicates

display_name: silicates


en: Low-crosslinked polymer networks have recently been found to behave auxetically when subjected to small tensions, that is, their Poisson's ratio ν becomes negative. In addition, for specific state points, numerical simulations revealed that diamond-like networks reach the limit of mechanical stability, exhibiting values of ν = −1, a condition that we define as hyper-auxeticity. This behavior is interesting per se for its consequences in materials science but is also appealing for fundamental physics because the mechanical instability is accompanied by evidence of criticality. In this work, we deepen our understanding of this phenomenon by performing a large set of equilibrium and stress–strain simulations in combination with phenomenological elasticity theory. The two approaches are found to be in good agreement, confirming the above results. We also extend our investigations to disordered polymer networks and find that the hyper-auxetic behavior also holds in this case, still manifesting a similar critical-like behavior as in the diamond one. Finally, we highlight the role of the number density, which is found to be a relevant control parameter determining the elastic properties of the system. The validity of the results under disordered conditions paves the way for an experimental investigation of this phenomenon in real systems, such as hydrogels.

en: Auxetic polymer networks: The role of crosslinking, density, and disorder

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).

auxetic-materials

display_name: auxetic-materials

elasticity

display_name: elasticity

hydrogels

display_name: hydrogels


en: The anharmonic infrared spectrum of adsorbed CO is simulated using density functional theory (DFT) to gain insight into the nature of Pd nanoparticles (NPs) supported on ceria. The authors systematically determine how the simulated infrared spectra are affected by CO coverage, NP size (0.5–1.5 nm), NP morphology (octahedral, icosahedral), and metal-support contact angle, by exploring a diversity of realistic models inspired by ab initio molecular dynamics.

en: Identifying the structure of supported metal catalysts using vibrational fingerprints from ab initio nanoscale models

envi

en: Environment

carbon-monoxide

display_name: carbon-monoxide

ceria

display_name: ceria

infrarred

display_name: infrarred

palladium

display_name: palladium

spectroscopy

display_name: spectroscopy


en: Transition metal oxides (e.g., cobalt oxides) often undergo a dynamic surface reconstruction under oxygen evolution reaction (OER) conditions to form the active state, which differs in response to the electrolyte pH. The resulting pH-dependency of OER activity is commonly observed but poorly understood. Herein, we demonstrate that operando X-ray absorption spectroscopy (XAS) characterization enables tracking of the Co oxidation transformation at different pH-directed (hydr)oxide/electrolyte interfaces. Combined with in situ electrochemical analyses, correlations between Co redox dynamics, flat band potential and Co oxidation transformations are established to explain the pH-dependency of OER activity. In alkaline environments, the low flat band potential allows a low-potential Co redox transformation, which in turns favors surface reconstruction. In neutral and acidic environments, an anodic shift of the Co redox transformation increases the OER overpotential, particularly in an acidic environment. The largest OER overpotential, in a neutral environment, is further attributable to the poor polarizability of Co atoms and the slowest Co oxidation transformation with respect to the change in applied potential (or OER current). These findings reveal that the Co oxidation transformation at the interface is the factor directly determining the pH-dependency of OER activity, therefore providing insight into designing efficient OER catalysts in different pH environments.

en: Oxidation of interfacial cobalt controls the pH-dependence of the oxygen evolution reaction

cobalt-oxides

display_name: cobalt-oxides

electrocatalytic-interface

display_name: electrocatalytic-interface

operando-x-ray-adsorption-spectroscopy

display_name: operando-x-ray-adsorption-spectroscopy

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


en:
We performed a computational study using Density Functional Theory calculations on a copper-graphene system. A global minima search was performed using the Minima Hopping algorithm to find multiple graphene isomers that can appear on different substrates. As a model of copper substrate, we used a 112 copper atom cluster and as a model of graphene flake, we used 40 carbon atoms on top of the copper surface. The system was placed in vacuum to guarantee no interaction between images.

The dataset contains coordinates of graphene flake isomers on crystalline and amorphous Cu substrates.

en: Comparative study of defects in graphene flake grown on amorphous and crystalline copper surfaces

copper

display_name: copper

density-functional-theory

display_name: density-functional-theory

graphene

display_name: graphene

graphene-growth

display_name: graphene-growth

metal-substrate

display_name: metal-substrate


en: Determining the atomic structure of a surface is essential for reliable simulations and in-depth exploration of chemical and atomic-scale physical processes. Using Ge(110) c(8×10) as a case study, this work employs Density Functional Theory (DFT) calculations to examine the role of vibrational entropy in surface reconstruction stability. The Ge(110) c(8×10) unit cell consists of interstitial-based pentamers (Universal Building Block model, UBB) interspersed with regions appearing in STM images as unreconstructed. DFT calculations predict that adding more pentamers lowers the surface energy, contradicting experimental findings. This discrepancy is resolved when vibrational entropy is accounted for and sur-face divacancies are introduced in addition to the UBB pentamers. These divacancies are similar to those proposed earlier in the Tetramer-Heptagonal and Tetragonal Ring (THTR) reconstruction model. The nearest neighbors of the vacancy sites are rebonded as on monatomic step edges. The differences in the vibrational entropy contributed by pentamers, divacancies, and unreconstructed surface stabilize Ge(110) c(8×10) reconstructions with the pentamer density observed experimentally. The presence of divacancies is conceptually consistent with the presence of monatomic steps in Ge(110) "16×2", the most stable reconstruction of this surface.

en: Ge(110) c(8×10) reconstructions stabilized by vibrations

dft

display_name: dft

pbe

display_name: pbe


en:
The presence of spin-orbit coupling or non-collinear magnetic spin states can have dramatic effects on the ground-state and spectral properties of materials, in particular on the band structure. Here, we develop non-collinear Koopmans-compliant functionals based on Wannier functions and density-functional perturbation theory, targeting accurate spectral properties in the quasiparticle approximation. Our non-collinear Koopmans-compliant theory involves functionals of four-component orbitals densities, that can be obtained from the charge and spin-vector densities of Wannier functions. We validate our approach on four emblematic non-magnetic and magnetic semiconductors where the effect of spin-orbit coupling goes from small to very large: the III-IV semiconductor GaAs, the transition-metal dichalcogenide WSe₂, the cubic perovskite CsPbBr₃, and the ferromagnetic semiconductor CrI₃.
The predicted band gaps are comparable in accuracy to state-of-the-art many-body perturbation theory and include spin-dependent interactions and screening effects that are missing in standard diagrammatic approaches based on the random phase approximation. While the inclusion of orbital- and spin-dependent interactions in many-body perturbation theory requires self-screening or vertex corrections, they emerge naturally in the Koopmans-functionals framework.

en: Spin-dependent interactions in orbital-density-dependent functionals: non-collinear Koopmans spectral functionals

metal-halide-perovskite

display_name: metal-halide-perovskite

non-collinear-magnetism

display_name: non-collinear-magnetism

snsf

display_name: snsf

spectral-functionals

display_name: spectral-functionals

spin-dependent-interactions

display_name: spin-dependent-interactions

spin-orbit-coupling

display_name: spin-orbit-coupling

spin-torque

display_name: spin-torque

transition-metal-dichalcogenide

display_name: transition-metal-dichalcogenide


en: In the pursuit of selective conversion of methane directly to methanol in the liquid phase, a common challenge is the concurrent formation of undesirable liquid oxygenates or combustion byproducts. However, we demonstrate that monometallic Pd-CeO2 catalysts, modified by carbon, created by a simple mechanochemical synthesis method exhibit 100% selectivity towards methanol at 75°C, using hydrogen peroxide as oxidizing agent. The solvent-free synthesis yields a distinctive Pd-iC-CeO2 interface, where interfacial carbon (iC) modulates metal-oxide interactions and facilitates tandem methane activation and peroxide decomposition, thus resulting in an exclusive methanol selectivity of 100% with a rate of 117 µmol/gcat at 75°C. Notably, solvent interactions of H2O2 (aq) were found to be critical for methanol selectivity through a DFT-simulated Eley-Rideal-like mechanism. This mechanism uniquely enables the direct conversion of methane into methanol via a solid-liquid-gas process.

en: From Methane to Methanol: Pd-iC-CeO2 Catalysts Engineered for High Selectivity via Mechano-Chemical Synthesis

eley-rideal-mechanism

display_name: eley-rideal-mechanism


en:
This record contains three datasets and the scripts used to generate figures in "Expanding density-correlation machine learning representations for anisotropic coarse-grained particles." This paper explores the theory and implementation of machine-learning descriptors for ellipsoidal bodies, extending the popular "Smooth Overlap of Atomic Positions" (SOAP) formalism. These case studies serve to demonstrate the different use cases of this technology.  The three datasets are:
- Generated configurations of nematic and smectic liquid crystal systems, with a range of orientational order, characterized by the nematic order parameter
- Dimers of (1, 1.5, 2) ellipsoids at different interaction cutoffs and rotations, with computed Gay-Berne type energies
- Crystalline configurations of planar benzene molecules, with energetics computed  using QuantumEspresso v7.046 using Perdew–Burke–Ernzerhof (PBE) pseudopotentials and cutoff parameters reported by Prandini et al.,  Grimme D3-dispersion correction, and a 3 × 3 Monkhorst–Pack k-point grid.

materialscloud

en: Materials Cloud

benzene

display_name: benzene

liquid-crystals

display_name: liquid-crystals

machine-learning

display_name: machine-learning

methods

display_name: methods

quantum-espresso

display_name: quantum-espresso


en:
In this work we study isomers of several representative small clusters to find principles for their stability. Our conclusions about the principles underlying the structure of clusters are based on a huge database of 44'000 isomers generated for 59 different clusters on the density functional theory level by Minima Hopping. We explore the potential energy surface of small neutral, anionic and cationic isomers, moving left to right across the third period of the periodic table and varying the number of atoms n and the cluster charge state q (X^q_n, with X={Na, Mg, Al, Si, Ge}, q=-1,0,1,2). We use structural descriptors such as bond lengths and atomic coordination numbers, the surface to volume ratios and the shape factor as well as electronic descriptors such as shell filling and hardness to detect correlations with the stability of clusters. The isomers of metallic clusters are found to be structure seekers with a strong tendency to adopt compact  shapes. However certain numbers of atoms can suppress the formation of a nearly spherical metallic clusters. Small non-metallic clusters typically also do not adopt compact spherical shapes for their lowest energy structures. In both cases spherical jellium models are not any more applicable. Nevertheless for many  structures, that have frequently a high degree of symmetry, the Kohn-Sham eigenvalues are bunched into shells and if the available electrons can completely fill such shells, a particularly stable structure can result. We call such a cluster whose shape gives rise to shells that can be completely filled by the number of available electrons an optimally matched cluster, since both the structure and the number of electrons must be special and match. In this way we can also explain the stability trends for covalent silicon and germanium cluster isomers, whose stability was previously explained by the presence of certain structural motifs. Thus we propose a unified framework to explain trends in the stability of isomers and to predict their structure for a wide range of small clusters.

This data record contains structure coordinates (compressed file all_minima_xyz_structures.tar.gz) of all minima found by the minima hopping method for all neutral and charged clusters, that are 43606 different structures. The python dictionary all_minima_names.npy stores all minima names. The python dictionary all_minima_data.npy stores all structural and electronic properties calculated for all minima. The jupyter notebook all_minima_data_analysis.ipynb helps the reading of the all_minima_names.npy and all_minima_data.npy python dictionaries.

en: Principles of isomer stability in small clusters

atomic-clusters

display_name: atomic-clusters

cscs

display_name: cscs


en:
We present SIESTA-BdG, an implementation of the simultaneous solution of the Bogoliubov-de Gennes (BdG) and Density Functional Theory (DFT) problem in SIESTA, a first-principles method and code for material simulations which uses pseudopotentials and a localized basis set. This unified approach describes both conventional and unconventional superconducting states, and enables a description of inhomogeneous superconductors and heterostructures. We demonstrate the validity, accuracy, and efficiency of SIESTA-BdG by computing physically relevant quantities (superconducting charge density, band structure, superconducting gap features, density of states) for conventional singlet (Nb, Pb) and unconventional (FeSe) superconductors. We find excellent agreement with experiments and results obtained within the KKR-BdG computational framework. SIESTA-BdG forms the basis for modelling quantum transport in superconducting devices and including - in an approximate fashion - the superconducting DFT potential of Oliveira, Gross, and Kohn.

This dataset contains the calculations performed on bulk Nb and the associated notebooks used to generate figures from this data.

en: Density functional Bogoliubov-de Gennes theory for superconductors implemented in the SIESTA code

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).

aiida

display_name: aiida

aiida-siesta

display_name: aiida-siesta

bogoliubov-de-gennes

display_name: bogoliubov-de-gennes

density-functional-theory

display_name: density-functional-theory

horizon-europe

display_name: horizon-europe

marie-curie-fellowship

display_name: marie-curie-fellowship

max

display_name: max

nb

display_name: nb

prace

display_name: prace

siesta

display_name: siesta

superconductivity

display_name: superconductivity


en: Phenalenyl (C₁₃H₉) is an open-shell spin-1/2 nanographene. Using scanning tunneling microscopy (STM) inelastic electron tunneling spectroscopy (IETS), covalently-bonded phenalenyl dimers have been shown to feature conductance steps associated with singlet-triplet excitations of a spin-1/2 dimer with antiferromagnetic exchange. In a recent work, we address the possibility of tuning the magnitude of the exchange interactions by varying the dihedral angle between the two molecules within a dimer. Theoretical methods, ranging from density functional theory calculations to many-body model Hamiltonians solved within different levels of approximation, are used to explain STM-IETS measurements of twisted phenalenyl dimers on a h-BN/Rh(111) surface. By means of first-principles calculations, we also propose strategies to induce sizable twist angles in surface-adsorbed phenalenyl dimers via functional groups, including a photoswitchable scheme. This record contains data that support the results discussed in the manuscript.

en: Conformational tuning of magnetic interactions in coupled nanographenes

envi

en: Environment

dmrg

display_name: dmrg

magnetic-nanographenes

display_name: magnetic-nanographenes

snsf

display_name: snsf

stmsts

display_name: stmsts


en:
Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is convenient from a computational perspective, enabling large-scale ML-driven simulations with a linear-scaling cost, and can also be used to deduce useful structure--property relations as they associate simple atomic motifs with complicated macroscopic properties. However, even though there exist practical justifications for these decompositions, only the global quantity is rigorously defined, and thus it is unclear to what extent the atomistic terms predicted by the model can be trusted.  Here, we introduce a quantitative metric, which we call the local prediction rigidity (LPR), to assess how robust the locally decomposed predictions of ML models are. We investigate the dependence of LPR on the details of model training, e.g. composition of the dataset, for several different problems ranging from simple toy models to real chemical systems. We present strategies to systematically enhance the LPR, which can be used to improve the robustness, interpretability, and transferability of the resulting atomistic ML models.
This repository contains datasets and Jupyter notebooks employed to corroborate the results of the above study.

en: Robustness of local predictions in atomistic machine learning models

epsrc

display_name: epsrc

erc

display_name: erc


en: This data presents the characteristics obtained using extracted parameters of multi- junction solar cells using a single diode triple-junction model. The proposed method combines analytical and numerical techniques to solve a nonlinear equation and determine the parameters, including the ideality factor, series resistance, shunt resistance, photocurrent, and saturation current, using manufacturer data and mathematical equations. The results show that the suggested approach achieves satisfactory performance and provide an accurate representation of the multi-junction circuit's parameters. Overall, this study provides a valuable contribution to the field of solar cell parameter extraction and offers insights for further research in this area.

en: Characteristics data for a new parameters extraction method of InGaP/GaAs/Ge multi-junction solar cell

i-v-characteristics

display_name: i-v-characteristics

multi-junction

display_name: multi-junction

pv-parameter-extraction

display_name: pv-parameter-extraction

solar-energy

display_name: solar-energy


en: The effect of hydrogen doping on the crystal structure and the electronic state in SmNiO₃ is investigated by means of density-functional theory with a combinatorial structure-generation approach. While 100% of hydrogen doping per Ni atom has been supposed to be responsible for the experimentally observed insulating phase, we found that 50% of hydrogen doping results in an outstandingly stable atomic structure showing the insulating property. The stable crystal structure shows the peculiar layered pattern of charge disproportionation of Ni²⁺ and Ni³⁺ valences together with the strong Jahn-Teller distortion that causes the eg orbital state splitting and opens the band gap.

en: Hydrogen-induced insulating state accompanied by inter-layer charge ordering in SmNiO₃

dft

display_name: dft

hydrogen-doping

display_name: hydrogen-doping


en: The phase change compound Ge₂Sb₂Te₅ (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases induced by Joule heating. The crystallization kinetics of GST225 is a key functional feature for the operation of these devices. We report here on the development of a machine-learned interatomic potential for GST225 that allowed us to perform large scale molecular dynamics simulations (over 10000 atoms for over 100 ns) to uncover the details of the crystallization kinetics in a wide range of temperatures of interest for the programming of the devices. The potential is obtained by fitting with a deep neural network (NN) scheme a large quantum-mechanical database generated within Density Functional Theory. The availability of a highly efficient and yet highly accurate NN potential opens the possibility to simulate phase change materials at the length and time scales of the real devices.

en: Unraveling the crystallization kinetics of the Ge₂Sb₂Te₅ phase change compound with a machine-learned interatomic potential

crystallization

display_name: crystallization

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potential

display_name: neural-network-potential

phase-change-materials

display_name: phase-change-materials

phase-change-memories

display_name: phase-change-memories


en: Fluctuations of electric fields can change the position of a gate-defined quantum dot in a semiconductor heterostructure. In the presence of magnetic field gradient, these stochastic shifts of electron's wavefunction lead to fluctuations of electron's spin splitting. The resulting spin dephasing due to charge noise limits the coherence times of spin qubits in isotopically purified Si/SiGe quantum dots. We investigate the spin splitting noise caused by such process caused by microscopic motion of charges at the semiconductor-oxide interface. We compare effects of isotropic and planar displacement of the charges, and estimate their densities and typical displacement magnitudes that can reproduce experimentally observed spin splitting noise spectra. We predict that for defect density of 10¹⁰ cm⁻², visible correlations between noises in spin splitting and in energy of electron's ground state in the quantum dot, are expected.

en: Correlations of spin splitting and orbital fluctuations due to 1/f charge noise in the Si/SiGe Quantum Dot

materialscloud

en: Materials Cloud

charge-noise

display_name: charge-noise

quantum-dots

display_name: quantum-dots

simulations

display_name: simulations


en: Recently a highly ordered Moiré dislocation lattice was identified at the interface between a SrTiO₃ (STO) thin film and the (LaAlO₃)₀.₃(Sr₂TaAlO₆)₀.₇ (LSAT) substrate. A fundamental understanding of the local ionic and electronic structure around the dislocation cores is crucial to further engineer the properties of these complex multifunctional heterostructures. Here we combine experimental characterization via analytical scanning transmission electron microscopy with results of molecular dynamics and density functional theory calculations to gain insights into the structure and defect chemistry of these dislocation arrays. Our results show that these dislocations lead to undercoordinated Ta/Al cations at the dislocation core, where oxygen vacancies can easily be formed, further facilitated by the presence of cation vacancies. The reduced Ti³⁺ observed experimentally at the dislocations by electron energy-loss spectroscopy are a consequence of both the structure of the dislocation itself, as well as of the electron-doping due to oxygen vacancy formation. Finally, the experimentally observed Ti diffusion into LSAT around the dislocation core occurs only together with cation-vacancy formation in LSAT or Ta diffusion into STO.

en: Combined theoretical and experimental study of the Moiré dislocation network at the SrTiO₃-(La,Sr)(Al,Ta)O₃ interface

complex-oxide-interface

display_name: complex-oxide-interface

dislocation

display_name: dislocation

point-defects

display_name: point-defects


en: Magnetostriction drives a rhombohedral distortion in the cubic rock salt antiferromagnet MnO at the Nèel temperature TN=118 K.  As an unexpected consequence we show that this distortion acts to localize the site of an implanted muon due to the accompanying redistribution of electron density. This lifts the degeneracy between equivalent sites, resulting in a single observed muon precession frequency.  Above TN, the muon instead becomes delocalized around a network of equivalent sites.  Our first-principles simulations based on Hubbard-corrected density-functional theory and molecular dynamics are consistent with our experimental data and help to resolve a long-standing puzzle regarding muon data on MnO, as well as having wider applicability to other magnetic oxides.

en: Magnetostriction-driven muon localisation in an antiferromagnetic oxide

materialscloud

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

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

dftuv

display_name: dftuv

experimental

display_name: experimental

marvel

display_name: marvel


en: We present an ab initio method to calculate the clamped Pockels tensor of ferroelectric materials from density-functional theory (DFT), the modern theory of polarization exploiting the electric-enthalpy functional, and automated first- and second-order finite-difference derivatives of the polarizations and the Hellmann-Feynman forces. Thanks to the functional-independent capabilities of our approach, we can determine the Pockels tensor of tetragonal barium titanate (BTO) beyond the local density approximation (LDA), with arbitrary exchange-correlation (XC) functionals, for example, PBEsol. The latter, together with RRKJ ultra-soft pseudo-potentials (PP) and a supercell exhibiting local titanium off-centering, enables us to stabilize the negative optical phonon modes encountered in tetragonal BTO when LDA and norm-conserving PP are combined. As a result, the correct value range of r51, the largest experimental Pockels coefficient of BTO, is recovered. We also reveal that r51 increases with decreasing titanium off-centering for this material. The lessons learned from the structural, dielectric, and vibrational investigations of BTO will be essential to design next-generation electro-optical modulators based on the Pockels effect.

en: Ab initio functional-independent calculations of the clamped Pockels tensor of tetragonal barium titanate

envi

en: Environment

ab-initio

display_name: ab-initio

aiida-vibroscopy

display_name: aiida-vibroscopy

barium-titanate

display_name: barium-titanate

density-functional-theory

display_name: density-functional-theory

electro-optics

display_name: electro-optics

imaginary-phonons

display_name: imaginary-phonons

pockels

display_name: pockels


en: Calcium carbonate (CaCO₃) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1 bar, with temperatures ranging from 300 to 2500 K, and at the constant temperature of 1600 K, with pressures ranging from 0 to 13 GPa. With increasing temperature, the transitions between calcite, CaCO₃-IV, and CaCO₃-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO₃-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO₃-IV transforms into CaCO₃-V. Through free energy analysis, we classified the latter transition as a continuous phase transition. At a temperature of 2000 K, a 'disordered CaCO₃' structure appears, characterized by low order within the calcium and carbonate sublattices and the free rotation of the carbonate ions. With increasing pressure, two calcium carbonate transformations were observed. At P = 2 GPa, the CaCO₃-V phase undergoes a phase transition into CaCO₃-IV, demonstrating that the model can describe the transition between these two phases as pressure- and temperature-driven. At P = 4.25 GPa, CaCO₃-IV undergoes a phase transition into the CaCO₃-Vb phase. This transition is classified as first-order based on free energy calculations.

en: Structural transitions of calcium carbonate by molecular dynamics simulation

calcium-carbonate

display_name: calcium-carbonate

high-pressure

display_name: high-pressure

high-temperature

display_name: high-temperature

metadynamics

display_name: metadynamics

molecular-dynamics

display_name: molecular-dynamics

phase-transitions

display_name: phase-transitions


en: The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as semiconducting systems. There are still open questions on the induced electronic re-distribution, including the formation of polarons. Indeed, to accurately reproduce the structural and electronic properties at the cuprous oxide surface, very large slab models and theoretical approaches that go beyond the standard generalized gradient corrected density functional theory are needed. In this work we investigate oxygen vacancies formed in proximity of a reconstructed Cu₂O(111) surface, where the outermost unsaturated copper atoms are removed, thus forming non-stoichiometric surface layers with copper vacancies. We address simultaneously surface and bulk properties by modelling a thick and symmetric slab, to find that hybrid exchange-correlation functionals are needed to describe the oxygen vacancy in this system. Our simulations show that the formation of oxygen vacancies is favoured in the sub-surface layer. Moreover, the oxygen vacancy leads to a splitting and left-shift of the shallow hole states in the gap, which are associated with the deficiency of copper at the surface. These findings suggest that surface electronic structure and reactivity are sensitive to the presence of oxygen vacancies, also when the latter are formed deeper within the film.

en: Understanding the role of oxygen-vacancy defects in Cu₂O(111) from first-principle calculations

hybrid-dft

display_name: hybrid-dft

oxygen-vacancy-defects

display_name: oxygen-vacancy-defects


en: High-performance n-type organic electrochemical transistors (OECTs) are essential for logic circuits and sensors. However, the performances of n-type OECTs lag far behind that of p-type ones. Conventional wisdom posits that the LUMO energy level dictates the n-type performance. Herein, we show that engineering the doped state is more critical for n-type OECT polymers. By balancing more charges to the donor moiety, we could effectively switch a p-type polymer to high-performance n-type material. Based on this concept, the polymer, P(gTDPP2FT), exhibits a record high n-type OECT performance with μC* of 54.8 F cm⁻¹ V⁻¹ s⁻¹, mobility of 0.35 cm² V⁻¹ s⁻¹, and response speed of τon/τoff = 1.75/0.15 ms. Calculations and comparison studies show that the conversion is primarily due to the more uniform charges, stabilized negative polaron, enhanced conformation, and backbone planarity at negatively charged states. Our work highlights the critical role of understanding and engineering polymers' doped states.

en: Switching p-type to high-performance n-type organic electrochemical transistors via doped state engineering

doped-state-engineering

display_name: doped-state-engineering

n-type

display_name: n-type

organic-electrochemical-transistor

display_name: organic-electrochemical-transistor


en: The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology. Dimensionality strongly affects these properties and has to be correctly accounted for in first-principles calculations. Here we develop and implement a formulation of density-functional and density-functional perturbation theory that is tailored for one-dimensional systems. A key ingredient is the inclusion of a Coulomb cutoff, a reciprocal-space technique designed to correct for the spurious interactions between periodic images in periodic-boundary conditions. This restores the proper one-dimensional open-boundary conditions, letting the true response of the isolated one-dimensional system emerge. In addition to total energies, forces and stress tensors, phonons and electron-phonon interactions are also properly accounted for. We demonstrate the relevance of the present method on a portfolio of realistic systems: BN atomic chains, BN armchair nanotubes, and GaAs nanowires. Notably, we highlight the critical role of the Coulomb cutoff by studying previously inaccessible polar-optical phonons and Fröhlich electron-phonon couplings. We also develop and apply analytical models to support the physical insights derived from the calculations and we discuss their consequences on electronic lifetimes. The present work unlocks the possibility to accurately simulate the linear response properties of one-dimensional systems, sheds light on the transition between dimensionalities and paves the way for further studies in several fields, including charge transport, optical coupling and polaritronics.

en: Density functional perturbation theory for one-dimensional systems: implementation and relevance for phonons and electron-phonon interactions

ab-initio

display_name: ab-initio

charge-transport

display_name: charge-transport

electron-phonon-coupling

display_name: electron-phonon-coupling

marvel

display_name: marvel

one-dimensional-materials

display_name: one-dimensional-materials

phonons

display_name: phonons


en: The deposited structure models of DNA adsorbed on prisitne PG/p-Si and metal (Au/W) doped PG/p-Si sheets, have been subjected to first principles calculations  based on DFT (PBE+vdW). The calculated binding affinity on PG and p-Si surface by M062X/6-31G* level of theory and adsorption energies by DFT predicts that PG has higher sensitivity towards DNA nucleic bases compared to p-Si with evident changes in their band structure properties.

en: 2D pentagonal-graphene and pentagonal-silicene sheets engineered for the detection of DNA nucleobases for genetic biomarker: A DFT study

materialscloud

en: Materials Cloud

dft

display_name: dft

electronic-structure

display_name: electronic-structure


en:
Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulators (TIs) Bi₂Te₃ and Bi₂Se₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian.
We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.

en: High-throughput magnetic co-doping and design of exchange interactions in topological insulators

co-doping

display_name: co-doping

jukkr

display_name: jukkr

magnetic-doping

display_name: magnetic-doping

quantum-anomalous-hall

display_name: quantum-anomalous-hall

topological-insulator

display_name: topological-insulator

topological-materials

display_name: topological-materials


en: We present a density functional theory study of the oxygen reduction reaction (ORR) on a single atom catalyst embedded in graphene, namely, TM-N₄-C (TM = Fe and Co), using the effective screening medium method combined with the reference interaction site model (ESM-RISM). It was found that Fe-N₄-C and Co-N₄-C show comparable ORR activities from the constant electrode potential simulations, in contrast to the results obtained using the constant (neutral) charge simulation, in which the superior performance of Co-N₄-C has been predicted. The constant potential method allows the variable charge and thus, resulting in a potential dependence of the reaction free energies different from that with the constant charge method in which the potential dependence is included as an ad hoc manner. We suggest the importance of the variable charge in the simulation of the electrochemical reaction, which is enabled by ESM-RISM.

en: Oxygen reduction reaction on single-atom catalysts from density functional theory calculations combined with an implicit solvation model

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).

density-functional-theory

display_name: density-functional-theory

implicit-solvation-model

display_name: implicit-solvation-model

oxygen-reduction-reaction

display_name: oxygen-reduction-reaction

single-atom-catalyst

display_name: single-atom-catalyst


en: We present a comprehensive vibrational analysis of hydrogen boride sheet through first-principles calculations, focusing on a variety of local structural configurations including surfaces, edges, and bilayer models - some of which contains vacancy and substitutional defects. A database of vibrational modes and simulated infrared spectra was constructed, revealing distinct spectral features that serve as characteristic fingerprints for different bonding environments. By analyzing mode distributions with respect to coordination environments, we identify the distinct contributions of terminal and bridging hydrogen atoms to specific spectral regions. The results show that structural modifications, such as interlayer stacking and edge termination, have a significant influence on vibrational characteristics, particularly in the intermediate and high frequency regions. The vibrational database enables the precise interpretation of infrared spectra and offers a reliable reference for model selection and peak analysis in both experimental and theoretical studies on hydrogen boride sheet and related materials. This archive contains the database compiled from this study, comprising (i) optimized structure files, (ii) energy and force datasets used to construct the Hessian matrix and (iii) the results from the vibrational analytics, such as simulated IR spectra and mode visualizations. The database was designed for maximum accessibility; consequently, all data are supplied in multiple standard formats.

en: Dataset for vibrational recognition of local structures in hydrogen boride sheets

envi

en: Environment

hydrogen-boride-sheets

display_name: hydrogen-boride-sheets

spectroscopy

display_name: spectroscopy

two-dimensional

display_name: two-dimensional


en:
Our study reveals how Gd adatoms and dimers on a superconducting Nb(110) surface induce Yu-Shiba-Rusinov (YSR) states, offering valuable insights into magnetic interactions of rare-earth atoms on superconducting surfaces. By engineering Gd dimers along the [1-10] and [001] directions, we uncover an indirect coupling between the Gd magnetic moments and the Nb substrate via their valence d electrons, leading to significant alterations in the YSR spectrum around the dimers. We further demonstrate the possibility for Néel-type spin-spiral ground states in chains of Gd atoms on Nb(110). These findings highlight the potential of 4f elements like Gd as a promising platform for controlling a spin-spiral ground state, a crucial prerequisite for realizing a topological superconductor that can host Majorana zero modes. The combination of theoretical modeling based on density functional theory, atomistic spin-dynamics simulations and experimental techniques, including scanning tunneling microscopy and spectroscopy, provides a comprehensive understanding of the coupling mechanisms and their impact on the electronic properties of these systems and establishes rare-earth magnets on Nb as a promising platform in the field.

This dataset collects the experimental and theoretical results of this work.

en: Rare-earth atoms on Nb(110) as a platform to engineer topological superconductivity

adatoms

display_name: adatoms

dftu

display_name: dftu

magnetism

display_name: magnetism

majorana-zero-mode

display_name: majorana-zero-mode

rare-earth

display_name: rare-earth

spin-dynamics

display_name: spin-dynamics

spin-spiral

display_name: spin-spiral

stm

display_name: stm

superconductivity

display_name: superconductivity

topological-superconductor

display_name: topological-superconductor