en: Due to presence of magnetic field gradient needed for coherent spin control, dephasing of single-electron spin qubits in silicon quantum dots is often dominated by 1/f charge noise. We investigate theoretically fluctuations of ground state energy of an electron in gated quantum dot in realistic Si/SiGe structure. We assume that the charge noise is caused by motion of charges trapped at the semiconductor-oxide interface. We consider a realistic range of trapped charge densities, ρ∼10¹⁰ cm⁻², and typical lenghtscales of isotropically distributed displacements of these charges, δr≤1 nm, and identify pairs (ρ,δr) for which the amplitude and shape of the noise spectrum is in good agreement with spectra reconstructed in recent experiments on similar structures.

en: Simulation of 1/f charge noise affecting a quantum dot in a Si/SiGe structure

materialscloud

en: Materials Cloud

charge-noise

display_name: charge-noise

quantum-dots

display_name: quantum-dots

simulation

display_name: simulation


$oid: OBSOLETE

en: Contact-Electro-Catalysis is an emerging catalytic principle that takes advantage of exchanges of electrons occurring through contact electrification events at solid-liquid interfaces to initiate or drive the catalysis of redox reactions. In this publication, the authors have proven the ability of various polymer insulators to catalyze the reduction of a wide variety of metal ions in aqueous solution, in both aerobic and anaerobic conditions. This property of the dielectric polymers was employed to design a 1-step method to selectively extract gold from e-waste leachates. In anaerobic conditions, the rate of the reactions increase due to the absence of competition form oxygen for the electrons. The influence of metal ions in solution on the distance between O₂ and the polymer chain of polytetrafluoroethylene was evaluated, as well as the resulting adsorption energy. The effect of tacticity on the ability of polymers such as PP to perform the contact-electro-catalytic reduction of oxygen was also evaluated. The files in this repository contains the position of the atoms before and after relaxation in all cases that were used to conduct the calculations.

en: Reduction of precious metal ions in aqueous solutions by contact-electro-catalysis

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

catalysis

display_name: catalysis

contact-electrification

display_name: contact-electrification

contact-electro-catalysis

display_name: contact-electro-catalysis

vasp

display_name: vasp


en: Several methods have been developed to improve the predictions of density functional theory (DFT) in the case of strongly correlated electron systems. Out of these approaches, DFT+U, which corresponds to a static treatment of the local interaction, and DFT combined with dynamical mean field theory (DFT+DMFT), which considers local fluctuations, have both proven incredibly valuable in tackling the description of materials with strong local electron-electron interactions. While it is in principle known that the Hartree-Fock (HF) limit of the DFT+DMFT approach should recover DFT+U, demonstrating this equivalence in practice is challenging, due to the very different ways in which the two approaches are generally implemented. In this work, we introduce a way to perform DFT+U calculations in QE using Wannier functions as calculated by Wannier90, which allows us to use the same Hubbard projector functions both in DFT+U and in DFT+DMFT. We benchmark these DFT+U calculations against DFT+DMFT calculations where the DMFT impurity problem is solved within the HF approximation. Considering a number of prototypical materials including NiO, MnO, LaMnO₃, and LuNiO₃, we establish the sameness of the two approaches. Finally, we showcase the versatility of our approach by going beyond the commonly used atomic orbital-like projectors by performing DFT+U calculations for VO₂ using a special set of bond-centered Wannier functions.

en: Explicit demonstration of the equivalence between DFT+U and the Hartree-Fock limit of DFT+DMFT

dftdmft

display_name: dftdmft

dftu

display_name: dftu

hartree-fock

display_name: hartree-fock

marvel

display_name: marvel


en: Graphene nanoribbons (GNRs), nanometer-wide strips of graphene, have garnered significant attention due to their tunable electronic and magnetic properties arising from quantum confinement. A promising approach to manipulate their electronic characteristics involves substituting carbon with heteroatoms, such as nitrogen, with different effects predicted depending on their position. In a recent publication, we present the extension of the edges of 7-atom-wide armchair graphene nanoribbons (7-AGNRs) with pyridine rings, achieved on a Au(111) surface via on-surface synthesis. High-resolution structural characterization confirms the targeted structure, showcasing the pre-dominant formation of carbon-nitrogen (C-N) bonds (over 90% of the units) during growth. This favored bond formation pathway is elucidated and confirmed through density functional theory (DFT) simulations. Furthermore, an analysis of the electronic properties reveals a reduction of the band gap of the GNR, accompanied by the presence of nitrogen-localized states. Our results underscore the successful formation of C-N bonds on the metal surface, providing insights for designing new GNRs that incorporate substitutional nitrogen atoms to precisely control their electronic properties. The record contains data that support the findings described in the publication.

en: Preferential graphitic-nitrogen formation in pyridine-extended graphene nanoribbons

aiidalab

display_name: aiidalab

cscs

display_name: cscs

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

nitrogen-doping

display_name: nitrogen-doping

stm

display_name: stm


en: Accurate descriptions of intermolecular interactions are of great importance in simulations of molecular liquids. We present an electronic structure method that combines the accuracy of the Harris functional approach with the computational efficiency of approximately linear-scaling density functional theory (DFT). The proposed method allows for simulations with accuracies close to the Kohn-Sham DFT reference. Embedded in the CP2K program package, the method is designed to enable ab initio molecular dynamics simulations of molecular solutions for system sizes of several thousands of atoms. As example of production applications we applied the method to molecular dynamics simulations in the isobaric-isothermal ensemble of the binary mixtures cyclohexane-methanol and toluene-methanol at different molar fractions of methanol. This record contains all CP2K input files necessary for the MD simulations, as well as 30ps trajectory files, and benchmark data of the energy correction.

en: A variational formulation of the Harris functional as correction to approximate Kohn-Sham density functional theory

cyclohexane

display_name: cyclohexane

harris-functional

display_name: harris-functional

isobaric-isothermal-ensemble

display_name: isobaric-isothermal-ensemble

linear-scaling-dft

display_name: linear-scaling-dft

methanol

display_name: methanol

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

snsf

display_name: snsf

subsystem-dft

display_name: subsystem-dft

toluene

display_name: toluene


en: Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where --- instead of comparing against real, many-electron systems --- we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has analytical solutions for particular strengths of its harmonic confining potential. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom across a range of confining potential strengths. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.

en: Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom

electronic-structure

display_name: electronic-structure

hookes-atom

display_name: hookes-atom

koopmans-spectral-functionals

display_name: koopmans-spectral-functionals

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals


en: Garnets, known since the early stages of human civilization, have found important applications in modern technologies including magnetorestriction, spintronics, lithium batteries, etc. The overwhelming majority of experimentally known garnets are oxides, while explorations (experimental or theoretical) for the rest of the chemical space have been limited in scope.  A key issue is that the garnet structure has a large primitive unit cell, requiring an enormous amount of computational resources. To perform a comprehensive search of the complete chemical space for new garnets, we combine recent progress in graph neural networks with high-throughput calculations. We apply the machine learning model to identify the potential (meta-)stable garnet systems before systematic density-functional calculations to validate the predictions. In this way, we discover more than 600 ternary garnets with distances to the convex hull below 100~meV/atom with a variety of physical and chemical properties. This includes sulfide, nitride and halide garnets. This record includes the results of 15742 vasp calculations of the ternary garnets investigated. All calculations were performed using the PBE functional.

en: Machine learning guided high-throughput search of non-oxide garnets

density-functional-theory

display_name: density-functional-theory

garnets

display_name: garnets

vasp

display_name: vasp


en: We use piecewise-linear functionals to study the polaron energy landscape and hopping rates in 𝜷-Ga₂O₃, which we adopt as an example of an anisotropic material hosting multiple polaronic states. We illustrate various functionals for polaron localization, including a hybrid functional and two types of semilocal functionals, and discuss how to ensure the piecewise linearity condition. Then, we determine the formation energies of stable polarons, and show that single-site and multi-site polaronic states can be found in close energetic competition. We calculate the hyperfine and superhyperfine parameters associated with each polaron, and discuss the comparison with experiment. Next, we perform nudged-elastic-band calculations to determine energy landscapes and hole transfer rates of all first-nearest-neighbor polaron hoppings. We show that when the piecewise linearity condition is ensured polaron properties are robust upon variation of the functional adopted, including formation energies, energy barriers, and charge transfer rates. This supports the use of semilocal functionals for calculating polaron transport properties.

en: Polaron hopping through piecewise-linear functionals

dftu

display_name: dftu

gammadft

display_name: gammadft

hybrid-functionals

display_name: hybrid-functionals

piecewise-linearity

display_name: piecewise-linearity

polaron-hopping

display_name: polaron-hopping

polarons

display_name: polarons

self-interaction

display_name: self-interaction


en: Transition-metal-based kagome materials at van Hove filling are a rich frontier for the investigation of novel topological electronic states and correlated phenomena. To date, in the idealized two-dimensional kagome lattice, topologically Dirac surface states (TDSSs) have not been unambiguously observed, and the manipulation of TDSSs and van Hove singularities (VHSs) remains largely unexplored. Here, we reveal TDSSs originating from a Z2 bulk topology and identify multiple VHSs near the Fermi level (EF) in magnetic kagome material GdV6Sn6. Using in situ surface potassium deposition, we successfully realize manipulation of the TDSSs and VHSs. The Dirac point of the TDSSs can be tuned from above to below EF, which reverses the chirality of the spin texture at the Fermi surface. These results establish GdV6Sn6 as a fascinating platform for studying the nontrivial topology, magnetism, and correlation effects native to kagome lattices. They also suggest potential application of spintronic devices based on kagome materials.

en: Tunable topological Dirac surface states and van Hove singularities in kagome metal GdV6Sn6

materialscloud

en: Materials Cloud

arpesdft

display_name: arpesdft

nccr-marvel

display_name: nccr-marvel

tdsss-and-vhss

display_name: tdsss-and-vhss


en:
Interfacing a topological insulator (TI) with an s-wave superconductor (SC) is a promising material platform that offers the possibility to realize a topological superconductor through which Majorana-based topologically protected qubits can be engineered. In our computational study of the prototypical SC/TI interface between Nb and Bi₂Te₃, we identify the benefits and possible bottlenecks of this potential Majorana material platform. Bringing Nb in contact with the TI film induces charge doping from the SC to the TI, which shifts the Fermi level into the TI conduction band. For thick TI films, this results in band bending leading to the population of trivial TI quantum-well states at the interface. In the superconducting state, we uncover that the topological surface state experiences a sizable superconducting gap-opening at the SC/TI interface, which is furthermore robust against fluctuations of the Fermi energy. We also show that the trivial interface state is only marginally proximitized, potentially obstructing the realization of Majorana-based qubits in this material platform.
This dataset contains the data for the DFT-based calculations for interfaces between the s-wave superconductor Nb and the topological insulator Bi₂Te₃ which is discussed in the publication referenced below.

en: Dataset of proximity induced superconductivity in a topological insulator

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).

bogoliubov-de-gennes

display_name: bogoliubov-de-gennes

superconductivity

display_name: superconductivity

topological-materials

display_name: topological-materials

topological-superconductor

display_name: topological-superconductor


en: Nuclear magnetic resonance (NMR) chemical shifts are a direct probe of local atomic environments and can be used to determine the structure of solid materials. However, the substantial computational cost required to predict accurate chemical shifts is a key bottleneck for NMR crystallography. We recently introduced ShiftML, a machine-learning model of chemical shifts in molecular solids, trained on minimum-energy geometries of materials composed of C, H, N, O, and S that provides rapid chemical shift predictions with density functional theory (DFT) accuracy. Here, we extend the capabilities of ShiftML to predict chemical shifts for both finite temperature structures and more chemically diverse compounds, while retaining the same speed and accuracy. For a benchmark set of 13 molecular solids, we find a root-mean-squared error of 0.47 ppm with respect to experiment for 1H shift predictions (compared to 0.35 ppm for explicit DFT calculations), while reducing the computational cost by over four orders of magnitude.

en: A machine learning model of chemical shifts for chemically and structurally diverse molecular solids

envi

en: Environment

machine-learning

display_name: machine-learning

snsf

display_name: snsf


en:
With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.

en: Characterization of single in situ prepared interfaces composed of niobium and a selectively-grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

density-functional-theory

display_name: density-functional-theory

experiment

display_name: experiment

majorana

display_name: majorana

transport

display_name: transport


en:
We present a sulfur K-edge X-ray absorption near-edge structure (XANES) database of 18 crystalline and 48 amorphous Lithium-Phosphorous-Sulfur (LPS) compounds. The database contains a total of 2681 XANES spectra of symmetrically inequivalent absorbing S sites. Structures were taken from Materials Cloud entry 2022.17 (archive.materialscloud.org/record/2022.17) and were originally generated by systematically removing Li, P and S atoms from known crystal structures using an evolutionary algorithm and an artificial neural network based interatomic potential. The details of this procedure can be found in Guo et al. (see references below). From this data set, low-energy structures were selected for spectral simulations. The excited electron and core hole method as implemented in VASP 6.2.1 was used to compute the XANES spectra for each symmetrically inequivalent Sulfur atom. The details of the VASP simulations can be found in the associated manuscript.

Acknowledgements: We acknowledge financial support by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Contract No. DE-SC0012704. These results used the computational resources of the Center for Functional Nanomaterials and the Scientific Data and Computing Center, a component of the Computational Science Initiative, at Brookhaven National Laboratory under the Contract No. DE-SC0012704. We also acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010.

en: Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

amorphous-lps

display_name: amorphous-lps

lps

display_name: lps

vasp

display_name: vasp

x-ray-absorption-spectroscopy

display_name: x-ray-absorption-spectroscopy


en: Charge transport plays a crucial role in manifold potential applications of two-dimensional materials, including field effect transistors, solar cells, and transparent conductors. At most operating temperatures, charge transport is hindered by scattering of carriers by lattice vibrations. Assessing the intrinsic phonon-limited carrier mobility is thus of paramount importance to identify promising candidates for next-generation devices. Here we provide a framework to efficiently compute the  drift and Hall carrier mobility of two-dimensional materials through the Boltzmann transport equation by relying on a Fourier-Wannier interpolation. Building on a recent formulation of long-range contributions to dynamical matrices and phonon dispersions [Phys. Rev. X 11, 041027 (2021)], we extend the approach to electron-phonon coupling including the effect of dynamical dipoles and quadrupoles. We identify an unprecedented contribution associated with the Berry connection that is crucial to preserve the Wannier-gauge covariance of the theory. This contribution is not specific to 2D crystals, but also concerns the 3D case, as we demonstrate via an application to bulk SrO. We showcase our method on a wide selection of relevant monolayers ranging from SnS₂ to MoS₂, graphene, BN, InSe, and phosphorene. We also discover a non-trivial temperature evolution of the Hall hole mobility in InSe whereby the mobility increases with temperature above 150~K due to the mexican-hat electronic structure of the InSe valence bands. Overall, we find that dynamical quadrupoles are essential and can impact the carrier mobility in excess of 75%.

en: Long-range electrostatic contribution to the electron-phonon couplings and mobilities of two-dimensional and bulk materials

ab-initio

display_name: ab-initio

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

marvel

display_name: marvel


en: This database contains the neural network potential (NNP) model and training data for aqueous ZnCl₂ solutions from 1 m to 30 m. The NNP model can be used to compute total energies and atomic forces, with one of its major applications being large-scale molecular dynamics (MD) simulations. The model was trained using DeePMD-kit v2.2.1, with training data generated through an active learning approach implemented in DP-GEN. The energies and forces in the training set were obtained from density functional theory (DFT) calculations using the SCAN exchange-correlation functional performed using Quantum ESPRESSO. Further details on the ab initio calculation procedures and model training methodology are available in the associated manuscript (see reference below).

en: Resolving the solvation structure and transport properties of aqueous zinc electrolytes from salt-in-water to water-in-salt using neural network potential

deepmd

display_name: deepmd

neural-network-potential

display_name: neural-network-potential

water

display_name: water

water-in-salt

display_name: water-in-salt


en: Organic solvents are widely used in polymer synthesis, despite their use lengthening purification steps and generating chemical waste. All-dry synthesis techniques, such as initiated Chemical Vapour Deposition (iCVD) polymerization, eliminate the use of solvents, however, only a narrow palette of material properties is accessible. Inspired by the principles of solvent engineering in solution synthesis, we report a strategy to broaden this palette by vapour-phase complexing (namely, vapour-phase solvation) mediated by hydrogen-bonding. Broad ranges of polymer chain length, as well as the mechanical strength and variety of film surface morphology are demonstrating using this strategy. We further achieve an unprecedented solvation modality; more specifically, interfacial solvation. The molecular interactions, locations of solvation, and kinetics of the coupled solvation-adsorption-polymerization process are investigated using molecular dynamic simulations and experimental validation of a theoretical kinetic model. The strategy can be applied to various methacrylate and vinyl monomers. Solvation in all-dry polymerization offers a new degree of freedom in polymer design and synthesis with improved environmental benignness, pointing to accelerated discovery of polymer thin films by simply introducing active solvents in the vapour phase. Here we provided the code for data processing to the result of the molecular dynamic simulation.

en: Engineering solvation in initiated Chemical Vapor Deposition (iCVD) for process-property control

icvd

display_name: icvd

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

polymer-thin-film

display_name: polymer-thin-film


en: Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages.

en: A bridge between trust and control: Computational workflows meet automated battery cycling

materialscloud

en: Materials Cloud

aurora

display_name: aurora

battery

display_name: battery

big-map

display_name: big-map

cycling

display_name: cycling

premise

display_name: premise

robot

display_name: robot

workflow

display_name: workflow


en: Understanding the phononic origin of the infrared dielectric properties of yttria (Y₂O₃) and other rare-earth sesquioxides (RE₂O₃) is a fundamental task in the search of appropriate RE₂O₃ materials that serve particular infrared optical applications. We herein investigate the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, Ho, Lu) using DFT-based phonon calculations and Lorentz oscillator model. The abundant IR-active optical phonon modes that are available for effective absorption of photons result in high reflectance of RE₂O₃, among which four IR-active modes originated from large distortions of REO₆ octahedra are found to contribute dominantly to the phonon dielectric constants. Particularly, the present calculation method by considering one-phonon absorption process is demonstrated with good reliability in predicting the infrared dielectric parameters of RE₂O₃ at the far-infrared as well as the vicinity of mid-infrared region, and the potential cutoff frequency/wavelength of its applicability is disclosed as characterized by the maximum frequency of IR-active longitudinal phonon modes. The results deepen the understanding on infrared dielectric properties of RE₂O₃, and aid the computational design of materials with appropriate infrared properties.

en: Phononic origin of the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, Ho, Lu) compounds

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).

infrared

display_name: infrared

phonon

display_name: phonon

sesquioxides

display_name: sesquioxides


en:
Singlet fission has shown potential for boosting the power conversion efficiency of solar cells, but the scarcity of suitable molecular materials hinders its implementation. We introduce an uncertainty-controlled genetic algorithm (ucGA) based on ensemble machine learning predictions from different molecular representations that concurrently optimizes excited state energies, synthesizability, and singlet exciton size for the discovery of singlet fission materials. We show that uncertainty in the model predictions can control how far the genetic optimization moves away from previously known molecules.
Running the ucGA in an exploitative setup performs local optimization on variations of known singlet fission scaffolds, such as acenes. In an explorative mode, hitherto unknown candidates displaying excellent excited state properties for singlet fission are generated. We suggest a class of heteroatom-rich mesoionic compounds as acceptors for charge-transfer mediated singlet fission. When included in larger conjugated donor-acceptor systems, these units exhibit strong localization of the triplet state, favorable diradicaloid character and suitable triplet energies for exciton injection into semiconductor solar cells. As the proposed candidates are composed of fragments from synthesized molecules, they are likely synthetically accessible.

en: Inverse design of singlet fission materials with uncertainty-controlled genetic optimization

envi

en: Environment

genetic-algorithm

display_name: genetic-algorithm

inverse-design

display_name: inverse-design

machine-learning

display_name: machine-learning

singlet-fission

display_name: singlet-fission

uncertainty-quantification

display_name: uncertainty-quantification


en: The AV₃Sb₅ kagome superconductors series are of intense interest due to their diverse and intricate properties. The breaking of time-reversal symmetry (TRS) in the normal state of these superconductors stands as a significant feature, yet the extent to which this effect can be tuned remains uncertain. Here, we employ a unique low-energy muon spin rotation technique combined with local field numerical analysis to study the TRS breaking response as a function of depth from the surface in single crystals of RbV₃Sb₅ with charge order and Cs(V0.86Ta0.14)₃Sb₅ without charge order. In the bulk (specifically above 30 nm from the sur face) of RbV₃Sb₅, we have detected a notable increase in the internal field width experienced by the muon ensemble. This increase occurs within the charge ordered state. Intriguingly, the muon spin relaxation rate is significantly enhanced near the surface of RbV₃Sb₅ (specifically within a depth range of 30-40 nm from the surface), and this effect commences at temperatures significantly higher than the onset of charge order. Conversely, in Cs(V0.86Ta0.14)₃Sb₅, which lacks charge order, we do not observe a similar enhancement in the internal field width, neither in the bulk nor at the surface. These observations indicate a strong connection between charge order and TRS breaking on one hand, and on the other hand, suggest that TRS breaking can be manipulated to occur prior to long-range charge order. This research offers compelling evidence for depth-dependent magnetism in AV₃Sb₅ superconductors in the presence of charge order. Such findings are likely to illuminate the intricate microscopic mechanisms that underpin the TRS breaking phenomena in these materials.

en: Depth-dependent time reversal symmetry breaking response in the charge-ordered kagome material RbV₃Sb₅

dft

display_name: dft

kagome-metal

display_name: kagome-metal

muon-spin-spectroscopy

display_name: muon-spin-spectroscopy


en: Singlet fission (SF) is a two-step process in which a singlet splits into two triplets throughout the so-called correlated triplet-pair (1TT) state. Intramolecular SF (iSF) materials in particular, have attracted growing interest as they can be easily implemented in single junction solar cells and boost their power conversion efficiency. Still, the potential of iSF materials such as polymers and oligomers for photovoltaic applications has been partially hindered by their ability to go beyond the 1TT intermediate and generate free triplets, which mechanism remains poorly understood. In this work, the main aspects governing the 1TT dissociation in donor-acceptor copolymers and the key features that optimize this process are exposed. First, we show that both thermodynamics and kinetics play a crucial role in the intramolecular triplet-pair separation and second, we uncover the inherent flexibility of the donor unit as the fundamental ingredient to optimize them simultaneously. Overall, these results provide a better understanding of the intramolecular 1TT dissociation process and establish a new paradigm for the development of novel iSF active materials.

en: Optimizing the thermodynamics and kinetics of the triplet-pair dissociation in donor-acceptor copolymers for intramolecular singlet fission

donor-acceptor-copolymers

display_name: donor-acceptor-copolymers

electronic-structure

display_name: electronic-structure

epfl

display_name: epfl

marie-curie-fellowship

display_name: marie-curie-fellowship


en: Extensive machine-learning assisted research has been dedicated to predicting band gaps for perovskites, driven by their immense potential in photovoltaics. Yet, the effectiveness is often hampered by the lack of high-quality band-gap datasets, particularly for perovskites involving d orbitals. In this work, we consistently calculate a large dataset of band gaps with a high level of accuracy, which is rigorously validated by experimental and state-of-the-art GW band gaps. Leveraging this achievement, our machine-learning derived descriptor exhibits exceptional universality and robustness, proving effectiveness not only for single and double, halide and oxide perovskites regardless of the underlying atomic structures, but also for hybrid organic-inorganic perovskites. With this approach, we comprehensively explore up to 15,659 materials, unveiling 14 unreported lead-free perovskites with suitable band gaps for photovoltaics. Notably, MASnBr₃, FA₂SnGeBr₆, MA₂AuAuBr₆, FA₂AuAuBr₆, FA₂InBiCl₆, FA₂InBiBr₆, and Ba₂InBiO₆ stand out with direct band gaps, small effective masses, low exciton binding energies, and high stabilities.

en: High-quality data enabling universality of band-gap descriptor and discovery of photovoltaic perovskites

band-gap-descriptor

display_name: band-gap-descriptor

high-quality-dataset

display_name: high-quality-dataset

hybrid-functional

display_name: hybrid-functional

photoboltaic-perovskites

display_name: photoboltaic-perovskites


en: The reliable ab-initio description of strongly correlated materials is a long-sought capability in condensed matter physics. The GW+EDMFT method is a promising scheme, which provides a self-consistent description of correlations and screening, and does not require user-provided parameters. In order to test the reliability of this approach we apply it to the experimentally well characterized perovskite compound Ca₂RuO₄, in which a temperature-dependent structural deformation drives a paramagnetic metal-insulator transition. Our results demonstrate that the nonlocal polarization and self-energy components introduced by GW are essential for setting the correct balance between interactions and bandwidths, and that the GW+EDMFT scheme produces remarkably accurate predictions of the electronic properties of this strongly correlated material.

en: Fully ab-initio electronic structure of Ca₂RuO₄

first-principles

display_name: first-principles

gw-method

display_name: gw-method

snsf

display_name: snsf

strongly-correlated-systems

display_name: strongly-correlated-systems


en: Melt post-condensation, thermal, and thermo-oxidative degradation of a cyclo-aliphatic polyamide were studied through time-resolved rheometry (TRR). The implemented TRR elucidates structural changes occurring during two concurrent phenomena, namely melt post-condensation and thermal/thermo-oxidative degradation, during the time sweep in a parallel plate rheometer. TRR measurements were conducted on neat polyamide under nitrogen (inert/non-oxidative) and air (oxidative) environment at 3 % strain amplitude and a range of frequencies between 0.1 and 100 rad/sec for two hours. At temperatures of 260, 270, and 275 °C, a dual-stage time-dependent growth in viscoelastic properties was observed under an oxidative environment. Thermo-oxidative degradation of polyamide melt 270 °C was shown to occur from the exposed sample edge, continuing inwards, effectively reducing the radius of the unoxidized polymer melt by 6.4 %. A modeling approach using MATLAB is presented to interpret and differentiate the rheological behavior of edge oxidized gel and bulk polymer within the volume of the sample melt. The code removes the effects of the strain limiter and the edge gelation from experimental measurements in predicting the material properties.

en: Predicting the influence of edge oxidation in parallel-plate rheometry

edge-oxidation

display_name: edge-oxidation

experimental

display_name: experimental

matlab

display_name: matlab


en:
Prediction of microstructure evolution during material processing is essential to control the material properties. Simulation tools for microstructure evolution prediction based on physical concepts are computationally expensive and time-consuming. Therefore, they are not practical when either there is an urgent need for microstructure morphology during the process, or there is a need to generate big microstructure datasets. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. We propose a Predictive Recurrent Neural Network (PredRNN) model for the microstructure prediction, which extends the inner-layer transition function of memory states in LSTMs to spatiotemporal memory flow. As a case study, we used a dataset from spinodal decomposition simulation of FeCrCo alloy created by the phase-field method for training and predicting future microstructures by previous observations. The results show that the trained network predicts quantitatively accurate microstructure morphologies while it is several orders of magnitude faster than the phase field method.
The trained model aims to generate future material microstructures by learning from the historical microstructures, where the visual dynamics are believed to have modular structures that can be learned with compositional subsystems. A PredRNN (https://github.com/thuml/predrnn-pytorch) model was trained to predict Fe-Cr-Co microstructures evolution during the spinodal decomposition.

en: Spatiotemporal prediction of microstructure evolution with predictive recurrent neural network

materialscloud

en: Materials Cloud

phase-field-spinodal-decomposition

display_name: phase-field-spinodal-decomposition


en: We present the NaviCatGA package, a versatile genetic algorithm capable of optimizing molecular catalyst structures using well-suited fitness functions to achieve a set of targeted properties. The flexibility and generality of this tool are demonstrated with two examples: i) Ligand optimization and exploration for Ni-catalyzed aryl-ether cleavage manipulating SMILES and using a fitness function derived from molecular volcano plots, ii) multiobjective (i.e., activity/selectivity) optimization of bipyridine N.N'-dioxide Lewis basic organocatalysts for the asymmetric propargylation of benzaldehyde from 3D molecular fragments. We show that evolutionary optimization, enabled by NaviCatGA, is an efficient way of accelerating catalyst discovery that bypasses combinatorial scaling issues and incorporates compelling chemical constraints.

en: Genetic optimization of homogeneous catalysts

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).

catalysis

display_name: catalysis

homogeneous-catalysis

display_name: homogeneous-catalysis

optimization

display_name: optimization

organocatalysis

display_name: organocatalysis

volcano-plot

display_name: volcano-plot


en: Prismatic slip of the screw  dislocation in magnesium at temperatures ≳ 150 K is understood to be governed by double-cross-slip of the stable basal screw through the unstable prism screw and back to the basal screw, with the activation energy controlled by the formation energy of two basal-basal kinks. However, atomistic studies of the double-kink process predict activation energies roughly twice those derived experimentally. Here, a new mechanism of prism glide is proposed, analyzed theoretically, and demonstrated qualitatively and quantitatively via direct molecular dynamics (MD) simulations. The new mechanism is intrinsically 3d, and involves the nucleation of a single kink at the junction where a 3d prismatic dislocation loop transitions from the basal screw segment to non-screw prismatic character. The relevant kink energies are calculated using recently-developed Neural-Network Potentials (NNPs) for Mg that show good agreement versus DFT for basal and prism  dislocations, enabling a parameter-free analytic model for the activation barrier. Direct MD simulations show both operation of the precise proposed mechanism and a stress-dependent activation barrier that agrees reasonably with the analytic model. Predictions of dislocation velocity compare very well with in-situ TEM data, and macroscopic strength versus temperature can also be understood. Overall, the new intrinsically 3d mechanism for dislocation glide due to single kink nucleation rather than double-kink nucleation explains key features of the prismatic slip in Mg and may have broader applicability in other metals where kink nucleation processes control thermally-activated flow.

en: Mechanism of thermally-activated prismatic slip in Mg

envi

en: Environment

magnesium

display_name: magnesium

marvel

display_name: marvel

neural-network-potential

display_name: neural-network-potential

prismatic-slip

display_name: prismatic-slip


en: Weyl nodes can be classified into zero-dimensional (0D) Weyl points, 1D Weyl nodal lines, and 2D Weyl nodal surfaces (WNS), which possess finite Chern numbers. Up to date, the largest Chern number of WPs identified in Weyl semimetals is 4, which is thought to be a maximal value for linearly crossing points in solids. On the other hand, whether the Chern numbers of nonzero-dimensional linear crossing Weyl nodal objects have one upper limit is still an open question. In this work, combining angle-resolved photoemission spectroscopy with density-functional theory calculations, we show that the chiral crystal AlPt hosts a cube-shaped charged WNS which is formed by the linear crossings of two singly degenerate bands. Different from conventional Weyl nodes, the cube-shaped nodal surface in AlPt is enforced by nonsymmorphic chiral symmetries and time-reversal symmetry rather than accidental band crossings, and it possesses a giant Chern number |C|=26. Moreover, our results and analysis prove that there is no upper limit for the Chern numbers of such kind of 2D Weyl nodal object. This record includes the data in the related paper Phys. Rev. B 105, 115118 – Published 14 March 2022.

en: Giant Chern number of a Weyl nodal surface without upper limit

giant-chern-number

display_name: giant-chern-number

unpaired-weyl-point

display_name: unpaired-weyl-point

weyl-nodal-surface

display_name: weyl-nodal-surface

weyl-nodal-wall

display_name: weyl-nodal-wall


en: Magnetic materials can display many solutions to the electronic-structure problem, corresponding to different local or global minima of the energy functional. In Hartree-Fock or density-functional theory different single-determinant solutions lead to different magnetizations, ionic oxidation states, hybridizations, and inter-site magnetic couplings. The vast majority of these states can be fingerprinted through their projection on the atomic orbitals of the magnetic ions. We have devised an approach that provides an effective control over these occupation matrices, allowing us to systematically explore the landscape of the potential energy surface. We showcase the emergence of a complex zoology of self-consistent states; even more so when semi-local density-functional theory is augmented - and typically made more accurate - by Hubbard corrections. Such extensive explorations allow to robustly identify the ground state of magnetic systems, and to assess the accuracy (or not) of current functionals and approximations

en: The energy landscape of magnetic materials

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

openmodel

display_name: openmodel


en:
Quantum spin Hall insulators (QSHIs) are a class of topological materials that has been extensively studied during the past decade. One of their distinctive features is the presence of a finite band gap in the bulk and gapless, topologically protected edge states that are spin-momentum locked. These materials are characterized by a Z₂ topological order where, in the 2D case, a single topological invariant can be even or odd for a trivial or a topological material, respectively. Thanks to their interesting properties, such as the realization of dissipationless spin currents, spin pumping and spin filtering, they are of great interest in the field of electronics, spintronics and quantum computing. In this work we perform an high-throughput screening of QSHI starting from a set of 783 2D exfoliable materials (603 after removing materials with lanthanides), recently identified from a systematic screening of the ICSD, COD, and MPDS databases (MC2D). In this screening we identify 4 Z₂ topological insulators, 3 of which already known in the literature, and 7 direct gap metals with the potential of becoming QSHIs under a reasonable external perturbation.

All the data are also displayed in the dedicated DISCOVER section "2D topological insulators" https://www.materialscloud.org/discover/2dtopo/dashboard/ptable

en: A complementary screening for quantum spin Hall insulators in 2D exfoliable materials

dft

display_name: dft

quantum-espresso

display_name: quantum-espresso

quantum-spin-hall

display_name: quantum-spin-hall

topological-insulator

display_name: topological-insulator


en: In contrast to inorganic quantum wells, hybrid quantum wells (HQWs) based on metal-organic semiconductors are characterized by relatively soft lattices, in which excitonic states can strongly couple to lattice phonons. Therefore, understanding the lattice's impact on exciton dynamics is essential for harnessing the optoelectronic potential of HQWs. Beyond 2D metal halide perovskites, layered metal-organic chalcogenides (MOCs) are an air-stable, underexplored material class hosting room-temperature excitons that could be exploited as photodetectors, light emitting devices, and ultrafast photoswitches. Here, we elucidate the role of phonons in the optical transitions of the prototypical MOC [AgSePh]∞. Impulsive stimulated Raman scattering (ISRS) allows us to detect coherent exciton oscillations driven by Fröhlich interaction with low-energy optical phonons. Steady state absorption and Raman spectroscopies reveal a strong exciton-phonon coupling (Huang-Rhys parameter ~1.7) and its anharmonicity, manifested as non-trivial temperature-dependent Stokes shift. Our ab initio calculations support these observations, hinting at an anharmonic behavior of the low-energy phonons < 200 cm⁻¹. Our results untangle complex exciton-phonon interactions in MOCs, establishing an ideal testbed for room-temperature many-body phenomena.

en: Anharmonic exciton-phonon coupling in metal-organic chalcogenides hybrid quantum wells

exciton-phonon-coupling

display_name: exciton-phonon-coupling

metal-organic-chalcogenides

display_name: metal-organic-chalcogenides

raman-spectroscopy

display_name: raman-spectroscopy


en:
Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional formulation. These functionals address two fundamental issues with density functional theory (DFT). First, while Kohn-Sham eigenvalues can loosely mirror experimental quasiparticle energies, they are not meant to reproduce excitation energies and there is formally no connection between the two (except for the HOMO for the exact functional). Second, (semi-)local DFT deviates from the expected piecewise linear behavior of the energy as a function of the total number of electrons. This can make eigenvalues an even poorer proxy for quasiparticle energies and, together with the absence of the exchange-correlation derivative discontinuity, contributes to DFT's underestimation of band gaps. By enforcing a generalized piecewise linearity condition to the entire electronic manifold, Koopmans functionals yield molecular orbital energies and solids-state band structures with comparable accuracy to many-body perturbation theory but at greatly reduced computational cost and preserving a functional formulation. This paper introduces "koopmans", an open-source package that contains all of the code and workflows needed to perform Koopmans functional calculations without requiring expert knowledge. The theory and algorithms behind Koopmans functionals are summarized, and it is shown how one can easily use the koopmans package to obtain reliable spectral properties of molecules and materials.

This archive contains files that accompany the article of the same name.

en: koopmans: an open-source package for accurately and efficiently predicting spectral properties with Koopmans functionals

charged-excitations

display_name: charged-excitations

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

koopmans-spectral-functionals

display_name: koopmans-spectral-functionals

marvel

display_name: marvel

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals

snsf

display_name: snsf


en: In the past decade, quantum diffusion Monte Carlo (DMC) has been demonstrated to successfully predict the energetics and properties of a wide range of molecules and solids by numerically solving the electronic many-body Schrödinger equation. We show that when coupled with quantum machine learning (QML) based surrogate methods the computational burden can be alleviated such that QMC shows clear potential to undergird the formation of high quality descriptions across chemical space. We discuss three crucial approximations necessary to accomplish this: The fixed node approximation, universal and accurate references for chemical bond dissociation energies, and scalable minimal amons set based QML (AQML) models. Numerical evidence presented includes converged DMC results for over one thousand small organic molecules with up to 5 heavy atoms used as amons, and 50 medium sized organic molecules with 9 heavy atoms to validate the AQML predictions. Numerical evidence collected for 𝛥-AQML models suggests that already modestly sized QMC training data sets of amons suffice to predict total energies  with near chemical accuracy throughout chemical space. In this archive, we present DMC energies for over one thousand small organic molecules with up to 5 heavy atoms, and 50 medium sized organic molecules with 9 heavy atoms, as well as energies computed at cheaper levels of theory such as HF, DFT, MP2 and CCSD(T).

en: Fixed node diffusion Monte Carlo energies for over one thousand small organic molecules

materialscloud

en: Materials Cloud

chemical-space

display_name: chemical-space

quantum-machine-learning

display_name: quantum-machine-learning

quantum-monte-carlo

display_name: quantum-monte-carlo


en: Thin film organic photovoltaics (OPVs) aspire to extract solar energy in a green, high efficiency, and cost-effective pathway, offering a sustainable solution to energy and ecosystem. We take the effort of developing low ecological harmful solvent processing of OPV devices and mini-modules, to strengthen the environmental benefits of OPV. New formula utilizing safer solvents enhanced with additives affords an optimal laboratory device efficiency of 20% as well as superior operational and thermal stability. Mini-module shows an efficiency up to 17.6% in upscaled processing, representing the highest performance for green solvent OPV development. Suitable nanoscaled phase separation is obtained in together with a micron-scale surface wrinkle pattern from the new developed processing strategy. Thus efficient photon-to-electron conversion at nano-interfaces and light extraction in broader receiving angles is achieved, which allows for more flexible installation geometries in building-integrated applications.

en: Organic solar cells with eco-friendly preparation to achieve an efficiency of 20%

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).

long-term-lifetime

display_name: long-term-lifetime

organic-solar-cells

display_name: organic-solar-cells

sustainability

display_name: sustainability


en: A key strategy to design environmental barrier coatings focuses on doping multiple rare-earth principal components into β-type rare-earth disilicates (RE2Si2O7) to achieve versatile property optimization. However, controlling the phase formation capability of (nRExi)2Si2O7 remains a crucial challenge, due to the complex polymorphic phase competitions and evolutions led by different RE3+ combination. Herein, by fabricating twenty-one model (REI0.25REII0.25REIII0.25REIV0.25)2Si2O7 compounds, we find that their formation capability can be evaluated by the ability to accommodate configurational randomness of multiple RE3+ cations in β-type lattice while preventing the β-to-γ polymorphic transformation. The phase formation and stabilization are controlled by the average RE3+ radius and the deviations of different RE3+ combinations. Subsequently, based on high-throughput density-functional-theory calculations, we propose that the configurational entropy of mixing is a reliable descriptor to predict the phase formation of β-type (nRExi)2Si2O7. The results may accelerate the design of (nRExi)2Si2O7 materials with tailored compositions and controlled polymorphic phases.

en: Phase formation capability and compositional design of β-phase multiple rare-earth principal component disilicates

envi

en: Environment

density-functional-theory

display_name: density-functional-theory

environmental-barrier-coating

display_name: environmental-barrier-coating

experimental

display_name: experimental

high-entropy-ceramics

display_name: high-entropy-ceramics

phase-formation

display_name: phase-formation

rare-earth-disilicate

display_name: rare-earth-disilicate


en:
The widespread application of machine learning (ML) to the chemical sciences is making it very important to understand how the ML models learn to correlate chemical structures with their properties, and what can be done to improve the training efficiency whilst guaranteeing interpretability and transferability. In this work, we demonstrate the wide utility of prediction rigidities, a family of metrics derived from the loss function, in understanding the robustness of ML model predictions. We show that the prediction rigidities allow the assessment of the model not only at the global level, but also on the local or the component-wise level at which the intermediate (e.g. atomic, body-ordered, or range-separated) predictions are made. We leverage these metrics to understand the learning behavior of different ML models, and to guide efficient dataset construction for model training. We finally implement the formalism for a ML model targeting a coarse-grained system to demonstrate the applicability of the prediction rigidities to an even broader class of atomistic modeling problems.
This record contains all the data used for the analyses conducted in the associated work published in Faraday Discussions.

en: Prediction rigidities for data-driven chemistry

machine-learning

display_name: machine-learning

ml-model-robustness

display_name: ml-model-robustness

prediction-rigidity

display_name: prediction-rigidity

uncertainty-quantification

display_name: uncertainty-quantification


en: Augmented plane wave methods enable an efficient description of atom-centered or localized features of the electronic density, circumventing high energy cutoffs and thus prohibitive computational costs of pure plane wave formulations. To complement existing implementations for ground-state properties and excitation energies, we present the extension of the Gaussian and augmented plane wave method to excited-state nuclear gradients within the Tamm–Dancoff approximation of time-dependent density functional theory and its implementation in the CP2K program package. Benchmarks for a test set of 35 small molecules demonstrate that maximum errors in the nuclear forces for excited states of singlet and triplet spin multiplicity are smaller than 0.1 eV/Å. The method is furthermore applied to the calculation of the zero-phonon line of defective hexagonal boron nitride. This spectral feature is reproduced with an error of 0.6 eV in comparison to GW–Bethe–Salpeter reference computations and 0.4 eV in comparison to experimental measurements. Accuracy assessments and applications thus demonstrate the potential use of the outlined developments for large-scale applications on excited-state properties of extended systems. The data in this record are supplementary data to the published article with DOI 10.1021/acs.jctc.4c00614.

en: Excited-state forces with the Gaussian and augmented plane wave method for the Tamm–Dancoff approximation of time-dependent density functional theory

augmented-plane-wave-methods

display_name: augmented-plane-wave-methods

gaussian-basis-sets

display_name: gaussian-basis-sets


en: Complex oxide functionality, such as ferroelectricity, magnetism or superconductivity is often achieved in epitaxial thin-film geometries. Oxygen vacancies tend to be the dominant type of defect in these materials but a fundamental understanding of their stability and electronic structure has so far mostly been established in the bulk or strained bulk, neglecting interfaces and surfaces present in a thin-film geometry. We investigate here, via density functional theory calculations, oxygen vacancies in the model system of a SrMnO3 (SMO) thin film grown on a SrTiO3 (STO) (001) substrate. Structural and electronic differences compared to bulk SMO result mainly from undercoordination at the film surface. The changed crystal field leads to a depletion of subsurface valence-band states and transfer of this charge to surface Mn atoms, both of which strongly affect the defect chemistry in the film. The result is a strong preference of oxygen vacancies in the surface region compared to deeper layers. Finally, for metastable oxygen vacancies in the substrate, we predict a spatial separation of the defect from its excess charge, the latter being accommodated in the film but close to the substrate boundary. These results show that surface and interface effects lead to significant differences in stability and electronic structure of oxygen vacancies in thin-film geometries compared to the (strained) bulk.

en: Surface and interface effects in oxygen deficient SrMnO3 thin films grown on SrTiO3

crystal-field

display_name: crystal-field

cscs

display_name: cscs

interface

display_name: interface

oxygen-vacancy

display_name: oxygen-vacancy

snsf

display_name: snsf

surface

display_name: surface

thin-film

display_name: thin-film


en: In the upcoming process to overcome the limitations of the standard von Neumann architecture, synaptic electronics is gaining a primary role for the development of in-memory computing. In this field, Ge-based compounds have been proposed as switching materials for nonvolatile memory devices and for selectors. By employing the classical molecular dynamics, we study the structural features of both the liquid states at 1500 K and the amorphous phase at 300 K of Ge-rich and Se-rich chalcogenides binary Ge_x Se_1–x systems in the range 0.4 ≤ x ≤ 0.6. The simulations rely on a model of interatomic potentials where ions interact through steric repulsion, as well as Coulomb and charge–dipole interactions given by the large electronic polarizability of Se ions. Our results indicate the formation of temperature-dependent hierarchical structures with short-range local orders and medium-range structures, which vary with the Ge content. Our work demonstrates that nanosecond-long simulations, not accessible via ab initio techniques, are required to obtain a realistic amorphous phase from the melt. Our classical molecular dynamics simulations are able to describe the profound structural differences between the melt and the glassy structures of GeSe chalcogenides. These results open to the understanding of the interplay between chemical composition, atomic structure, and electrical properties in switching materials.

en: Hierarchical short- and medium-range order structures in amorphous Ge_x Se_1–x for selectors applications

amorphous

display_name: amorphous

chalcogenides

display_name: chalcogenides

intersect

display_name: intersect

molecular-dynamics

display_name: molecular-dynamics


en: The α/β interface is central to the microstructure and mechanical properties of titanium alloys. We investigate the structure, thermodynamics and migration of the coherent and semicoherent Ti α/β interfaces as a function of temperature and misfit strain via molecular dynamics (MD) simulations, thermodynamic integration and an accurate, DFT-trained Deep Potential. The structure of an equilibrium semicoherent interface consists of an array of steps, an array of misfit dislocations, and coherent terraces. Analysis determines the dislocation and step (disconnection) array structure and habit plane. The MD simulations show the detailed interface morphology dictated by intersecting disconnection arrays. The steps are shown to facilitate α/β interface migration, while the misfit dislocations lead to interface drag; the drag mechanism is different depending on the direction of interface migration. These results are used to predict the nature of α phase nucleation on cooling through the α-β phase transition.

en: Coherent and semicoherent interfaces in titanium: structure, thermodynamics, migration

free-energy

display_name: free-energy

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

titanium-interfaces

display_name: titanium-interfaces


en: Organic semiconductors with high-spin ground states are fascinating because they could enable fundamental understanding on the spin-related phenomenon in light element and provide opportunities for organic magnetic and quantum materials. Although high-spin ground states have been observed in some quinoidal type small molecules or doped organic semiconductors, semiconducting polymers with high-spin at their neutral ground state are rarely reported. Here we report three high-mobility semiconducting polymers with different spin ground states. We show that polymer building blocks with small singlet-triplet energy gap (ΔES-T) could enable small ΔES-T gap and increase the diradical character in copolymers. We demonstrate that the electronic structure, spin density, and solid-state interchain interactions in the high-spin polymers are crucial for their ground states. Polymers with a triplet ground state (S = 1) could exhibit doublet (S = 1/2) behavior due to different spin distributions and solid-state interchain spin-spin interactions. Besides, these polymers showed outstanding charge transport properties with high hole/electron mobilities and can be both n- and p-doped with superior conductivities. Our results demonstrate a rational approach to high-mobility semiconducting polymers with different spin ground states.

en: High-mobility semiconducting polymers with different spin ground states

materialscloud

en: Materials Cloud

high-mobility-polymers

display_name: high-mobility-polymers

high-spin-materials

display_name: high-spin-materials

organic-semiconductor

display_name: organic-semiconductor


en:
Despite the high promise of Li-metal-based batteries, its commercialization has been hampered due to the formation of dendrites that lead to mechanical instability,
energy loss and eventual internal short circuits. The provided dataset consists of the phase-field simulation results for investigating the effect of applied overpotential and operating temperature on dendrite growth. These data are used for elucidating the correlation of overpotential and temperature with the surface modulation during electrodeposition. The simulation cell consists of a Li metal anode and 1M LiPF6 in EC:DMC (1:1), and the electrodeposition process was simulated under the applied overpotential ranging from 0.30 V to 0.44 V with a 0.02 V increment at temperatures from 268 K and 333 K with a 5 K increment. The data contains order parameter, chemical potential and overpotential. The supplied Python script can compute the surface tortuosity, average and maximum Li heights and dendrite height at a given temperature, overpotential and time step.

en: Phase-field investigation of lithium electrodeposition under different applied overpotentials and operating temperatures

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).

anode

display_name: anode

big-map

display_name: big-map

dendrites

display_name: dendrites

interfaces

display_name: interfaces

lithium

display_name: lithium

phase-field

display_name: phase-field


en: The heat capacity of a material is a fundamental property that is of significant practical importance. For example, in a carbon capture process, the heat required to regenerate a solid sorbent is directly related to the heat capacity of the material. However, for most materials suitable for carbon capture applications the heat capacity is not known, and thus the standard procedure is to assume the same value for all materials. In this work, we developed a machine-learning approach to accurately predict the heat capacity of these materials, i.e., zeolites, metal-organic frameworks, and covalent-organic frameworks. The accuracy of our prediction is confirmed with novel experimental data. Finally, for a temperature swing adsorption process that captures carbon from the flue gas of a coal-fired power plant, we show that for some materials the energy requirement is reduced by as much as a factor of two using the correct heat capacity.

en: A data-science approach to predict the heat capacity of nanoporous materials

envi

en: Environment

heat-capacity

display_name: heat-capacity

machine-learning

display_name: machine-learning

mof

display_name: mof

snsf

display_name: snsf

thermal-properties

display_name: thermal-properties

zeolite

display_name: zeolite


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

en: Quantum phase diagram of high-pressure hydrogen

high-pressure-hydrogen

display_name: high-pressure-hydrogen


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

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

batteries

display_name: batteries

generalised-convex-hull

display_name: generalised-convex-hull

minima-search

display_name: minima-search


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

en: Fermi energy determination for advanced smearing techniques

fermi-energy

display_name: fermi-energy

insulators

display_name: insulators

intersect

display_name: intersect

marvel

display_name: marvel

semiconductors

display_name: semiconductors

smearing

display_name: smearing


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

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

high-throughput

display_name: high-throughput

wannier-functions

display_name: wannier-functions

wannierization

display_name: wannierization


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

en: Platinum nanoparticles under oxidizing conditions

oxygen-adsorption

display_name: oxygen-adsorption

platinum-nanocatalyst

display_name: platinum-nanocatalyst

platinum-nanoparticle

display_name: platinum-nanoparticle

pressure-temperature-phase-diagram

display_name: pressure-temperature-phase-diagram


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

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

materialscloud

en: Materials Cloud

electronic-structure

display_name: electronic-structure

magnetism

display_name: magnetism

rare-earth-nickelates

display_name: rare-earth-nickelates


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

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

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).

big-map

display_name: big-map

density-functional-theory

display_name: density-functional-theory

first-principles

display_name: first-principles

graphane

display_name: graphane

gw-approximation

display_name: gw-approximation

hydrogenated-graphene

display_name: hydrogenated-graphene

max

display_name: max

nanoporous-graphene

display_name: nanoporous-graphene

spectromicroscopy

display_name: spectromicroscopy

yambo-code

display_name: yambo-code


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

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

en: cell2mol: encoding chemistry to interpret crystallographic data

envi

en: Environment

crystal

display_name: crystal

experimental

display_name: experimental

marvel

display_name: marvel


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

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

carbon-dioxide

display_name: carbon-dioxide

ethane

display_name: ethane

hydrogen-boride

display_name: hydrogen-boride

methane

display_name: methane

two-dimensional

display_name: two-dimensional


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

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

manifold-optimization

display_name: manifold-optimization

snsf

display_name: snsf

wannier-functions

display_name: wannier-functions

wannier-interpolation

display_name: wannier-interpolation

wannierization

display_name: wannierization


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

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

dft

display_name: dft

effective-hamiltonian

display_name: effective-hamiltonian

kp-low-energy-model

display_name: kp-low-energy-model

tight-binding

display_name: tight-binding

topological-insulator

display_name: topological-insulator


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

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

arpes-raman-stm-dft

display_name: arpes-raman-stm-dft

nccr-marvel

display_name: nccr-marvel


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

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

density-functional-theory

display_name: density-functional-theory

majorana

display_name: majorana

superconductivity

display_name: superconductivity

topological-materials

display_name: topological-materials


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

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

materialscloud

en: Materials Cloud

marvel

display_name: marvel

metal-oxide

display_name: metal-oxide

water-dehydrogenation-reaction

display_name: water-dehydrogenation-reaction


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

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

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).

graphene-nanoribbons

display_name: graphene-nanoribbons

on-surface-synthesis

display_name: on-surface-synthesis


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

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

envi

en: Environment

cscs

display_name: cscs

dftu

display_name: dftu

dftuv

display_name: dftuv

epfl

display_name: epfl

first-principles

display_name: first-principles

hubbard

display_name: hubbard

quantum-espresso

display_name: quantum-espresso