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

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

low-scaling-algorithm

display_name: low-scaling-algorithm

method-development

display_name: method-development

tddft

display_name: tddft

xas

display_name: xas


$oid: OBSOLETE

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

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

materialscloud

approval_status: approved

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

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

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

graphene

display_name: graphene

mid-infrared

display_name: mid-infrared

plasmon

display_name: plasmon

tunable-emission

display_name: tunable-emission


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

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

coordinate-bond

display_name: coordinate-bond

er-sb-te

display_name: er-sb-te

experimental

display_name: experimental

hierarchical-melt

display_name: hierarchical-melt

phase-change-memory

display_name: phase-change-memory


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

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

aluminum-oxide

display_name: aluminum-oxide

amorphous

display_name: amorphous

neural-network-potential

display_name: neural-network-potential


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

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

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

density-functional-theory

display_name: density-functional-theory

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


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

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

amorphous-materials

display_name: amorphous-materials

charge-transport

display_name: charge-transport

epfl

display_name: epfl

erc

display_name: erc

reorganization-energy

display_name: reorganization-energy

replica-exchange-molecular-dynamics

display_name: replica-exchange-molecular-dynamics

triphenylamine

display_name: triphenylamine


en: We present our resonant X-ray diffraction work to study the antiferromagnetic spin canting perpendicular to the hexagonal planes of the archetypal type-I multiferroic YMnO₃. We find the x-ray diffraction spectral shape at the Mn L2,3 edges change as a function of temperature below TN for this material. Using a combination of phenomenological arguments and computations using the DFT-based FDMNES code, we attribute the difference spectra to be a result of interference of scattered amplitudes from the canted magnetic dipole and higher-order magnetoelectric multipoles.

en: Antiferromagnetic spin canting and magnetoelectric multipoles in h-YMnO₃

dft

display_name: dft

marvel

display_name: marvel

snsf

display_name: snsf


en: The nature of the liquid–solid interface determines the characteristics of a variety of physical phenomena, including catalysis, electrochemistry, lubrication, and crystal growth. Most of the established models for crystal growth are based on macroscopic thermodynamics, neglecting the atomistic nature of the liquid–solid interface. Here, experimental observations and molecular dynamics simulations are employed to identify the 3D nature of an atomic‐scale ordering of liquid Ga in contact with solid GaAs in a nanowire growth configuration. An interplay between the liquid ordering and the formation of a new bilayer is revealed, which, contrary to the established theories, suggests that the preference for a certain polarity and polytypism is influenced by the atomic structure of the interface. The conclusions of this work open new avenues for the understanding of crystal growth, as well as other processes and systems involving a liquid–solid interface.

en: 3D ordering at the liquid–solid polar interface of nanowires

gaas

display_name: gaas

gallium-arsenide

display_name: gallium-arsenide

machine-learning-potential

display_name: machine-learning-potential

molecular-dynamics-simulations

display_name: molecular-dynamics-simulations

nanowire

display_name: nanowire

ordering-at-the-interface

display_name: ordering-at-the-interface


en: Progress in the development of rechargeable Ca-ion batteries demands the discovery of potential cathode materials. Transition metal oxides are interesting candidates due to their theoretical high energy densities, but with the drawback of a low Ca mobility. Previous computational/experimental investigations associate the electrochemical inactivity of various oxides (CaMO3-perovskite, CaMn2O4-post-spinel and CaV2O5) to high energy barriers for Ca migration. The introduction of oxygen and/or Ca vacancies in ternary transition metal oxides is a likely way to reshape the local topology and hence improve the Ca diffusivity. In this work, the energy barriers for Ca migration are calculated and discussed for (i) oxygen-deficient perovskites within the related Ca2Fe2O5-brownmillerite and Ca2Mn2O5 structures, and (ii) tunnel CaMn4O8, a derivative of the CaMn2O4-marokite with Ca vacancies.

en: DFT investigation of Ca mobility in reduced-perovskite and oxidized-marokite oxides

calcium-batteries

display_name: calcium-batteries

marokite

display_name: marokite

perovskite

display_name: perovskite

post-spinel

display_name: post-spinel


en: Photoelectrochemical solar water splitting is a promising approach to convert solar energy into sustainable hydrogen fuel using semiconductor electrodes. Due to their visible light absorption properties, oxynitrides have shown to be attractive photocatalysts for this application. In this study, the influence of the preparation method of CaNbO2N particles on their morphological and optical properties, and thereby their photoelectrochemical performance, is investigated. The best performing CaNbO2N photoanode is produced by ammonolysis of Nb enriched calcium niobium oxide. The enhanced photoactivity arises from an enlarged surface area and superior visible light absorption properties. The photoactivity of this photoanode was further enhanced by photodeposition of Co-Pi co-catalyst and by atomic layer deposition of an Al2O3 overlayer. A photocurrent density of 70 mA at 1.23 V vs RHE was achieved. The observed enhancement of the photoelectrochemical performance after Co-Pi/Al2O3 deposition is the combined effect of the improved kinetics of oxygen evolution due to the Co-Pi co-catalyst and the reduced surface recombination of the photogenerated carriers at the Al2O3 surface layer.

en: Improved photoelectrochemical water splitting of CaNbO2N photoanodes by Co-Pi photodeposition and surface passivation

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).

computational-screening

display_name: computational-screening

photoelectrochemical-water-splitting

display_name: photoelectrochemical-water-splitting

surface-passivation

display_name: surface-passivation


en: Electron–electron interactions play an important role in graphene and related systems and can induce exotic quantum states, especially in a stacked bilayer with a small twist angle. For bilayer graphene where the two layers are twisted by the 'magic angle', flat band and strong many-body effects lead to correlated insulating states and superconductivity. In contrast to monolayer graphene, the band structure of untwisted bilayer graphene can be further tuned by a displacement field, providing an extra degree of freedom to control the flat band that should appear when two bilayers are stacked on top of each other. Here, we report the discovery and characterization of displacement field-tunable electronic phases in twisted double bilayer graphene. We observe insulating states at a half-filled conduction band in an intermediate range of displacement fields. Furthermore, the resistance gap in the correlated insulator increases with respect to the in-plane magnetic fields and we find that the g factor, according to the spin Zeeman effect, is ~2, indicating spin polarization at half-filling. These results establish twisted double bilayer graphene as an easily tunable platform for exploring quantum many-body states.

en: Correlated states in twisted double bilayer graphene

materialscloud

en: Materials Cloud

envi

en: Environment

correlated-states

display_name: correlated-states

cscs

display_name: cscs

epfl

display_name: epfl

tdbg

display_name: tdbg

twisted-double-bilayer-graphene

display_name: twisted-double-bilayer-graphene


en: Electron-phonon (e-ph) interactions are pervasive in condensed matter, governing phenomena such as transport, superconductivity, charge-density waves, polarons, and metal-insulator transitions. First-principles approaches enable accurate calculations of e-ph interactions in a wide range of solids. However, they remain an open challenge in correlated electron systems (CES), where density functional theory often fails to describe the ground state. Therefore reliable e-ph calculations remain out of reach for many transition metal oxides, high-temperature superconductors, Mott insulators, planetary materials, and multiferroics. Here we show first-principles calculations of e-ph interactions in CES, using the framework of Hubbard-corrected density functional theory (DFT+U) and its linear response extension (DFPT+U), which can describe the electronic structure and lattice dynamics of many CES. We showcase the accuracy of this approach for a prototypical Mott system, CoO, carrying out a detailed investigation of its e-ph interactions and electron spectral functions. While standard DFPT gives unphysically divergent and short-ranged e-ph interactions, DFPT+U is shown to remove the divergences and properly account for the long-range Fröhlich interaction, allowing us to model polaron effects in a Mott insulator. Our work establishes a broadly applicable and affordable approach for quantitative studies of e-ph interactions in CES, a novel theoretical tool to interpret experiments in this broad class of materials.

en: Ab initio electron-phonon interactions in correlated electron systems

afosr

display_name: afosr

dftu

display_name: dftu

doe

display_name: doe

electron-phonon-coupling

display_name: electron-phonon-coupling

epsrc

display_name: epsrc

first-principles-calculations

display_name: first-principles-calculations

jcap

display_name: jcap

kfas

display_name: kfas

lattice-dynamics

display_name: lattice-dynamics

marvel

display_name: marvel

nersc

display_name: nersc

nffa

display_name: nffa

nsf

display_name: nsf

phonons

display_name: phonons

polarons

display_name: polarons

snsf

display_name: snsf

transition-metal-oxides

display_name: transition-metal-oxides

wannier-function-methods

display_name: wannier-function-methods


en: The implementation of ultrasoft pseudopotentials into time-dependent density-functional perturbation theory is detailed for both the Sternheimer approach and the Liouville-Lanczos (LL) method, and equations are presented in the scalar relativistic approximation for periodic solids with finite momentum transfer q. The LL method is applied to calculations of the electron energy loss (EEL) spectrum of face-centered cubic bulk Au both at vanishing and finite q. Our study reveals the richness of the physics underlying the various contributions to the density fluctuation in gold. In particular, our calculations suggest the existence in gold of two quasiseparate 5d and 6s electron gasses, each one oscillating with its own frequency at, respectively, 5.1 eV and 10.2 eV. We find that the contribution near 2.2 eV comes from 5d to 6s interband transitions modified by the intraband contribution to the real part of the dielectric function, which we call a mixed excitation.

en: Electron energy loss spectroscopy of bulk gold with ultrasoft pseudopotentials and the Liouville-Lanczos method

dft

display_name: dft

eels

display_name: eels

eu-max

display_name: eu-max

genci

display_name: genci

gold

display_name: gold

interband-transitions

display_name: interband-transitions

intraband-transitions

display_name: intraband-transitions

liouville-lanczos-method

display_name: liouville-lanczos-method

loss-function

display_name: loss-function

marvelosp

display_name: marvelosp

mixed-excitations

display_name: mixed-excitations

plasmons

display_name: plasmons

quantum-espresso

display_name: quantum-espresso

sternheimer-equations

display_name: sternheimer-equations

tddft

display_name: tddft


en: Rechargeable lithium-ion batteries dominate the consumer electronics and electric vehicle markets. However, concerns on Li availability have prompted the development of alternative high energy density electrochemical energy storage systems. Rechargeable batteries based on a Ca metal anode can exhibit advantages in terms of energy density, safety and cost. The development of rechargeable Ca metal batteries requires the identification of suitable high specific energy cathode materials. This work focuses on Ca-bearing minerals because they represent stable and abundant compounds. Suitable minerals should contain a transition metal able of being reversibly reduced and oxidized, which points to several major classes of silicates and carbonates: olivine (CaFeSiO4; kirschsteinite), pyroxene (CaFe/MnSi2O6; hedenbergite and johannsenite, respectively), garnet (Ca3Fe/Cr2Si3O12; andradite and uvarovite, respectively), amphibole (Ca2Fe5Si8O22(OH)2; ferroactinolite) and double carbonates (CaMn(CO3)2; kutnahorite and CaFe(CO3)2; ankerite). This work discusses their electrode characteristics based on crystal chemistry analysis and density functional theory (DFT) calculations. The results indicate that upon Ca deintercalation, compounds such as pyroxene, garnet and double carbonate minerals could display high theoretical energy densities (ranging from 780 to 1500 Wh/kg) with moderate structural modifications. As a downside, DFT calculations indicate a hampered Ca mobility in their crystal structures. The overall analysis then disregards olivine, garnet, pyroxene, amphibole and double carbonates as structural types for future Ca-cathode materials design.

en: Analysis of minerals as electrode materials for Ca-based rechargeable batteries

batteries

display_name: batteries

electrode-materials

display_name: electrode-materials

geochemistry

display_name: geochemistry

minerals

display_name: minerals


en: Cif files of relaxed "derived" copper surfaces from Cu2O, Cu2S, Cu3N, and Cu3P using EMT and published in J Gauthier, JH Stenlid, F Abild-Pedersen, M Head-Gordon, AT Bell, ACS Energy Letters, "The role of roughening to enhance selectivity to C2+ products during CO2 electroreduction on copper" (2021). These structures were used to evaluate the effect of roughening on catalytic selectivity of copper in electrochemcial CO2 reduction into valuable products such as fuels and commodity chemicals.

en: Atomic structures of 100nm x 100nm large oxide-, nitride-, sulfide-, and phosphide-derived copper surfaces

atomic-coordinates

display_name: atomic-coordinates

copper

display_name: copper

surface-structure

display_name: surface-structure


en: Density-functional theory is widely used to predict the physical properties of materials. However, it usually fails for strongly correlated materials. A popular solution is to use the Hubbard corrections to treat strongly correlated electronic states. Unfortunately, the exact values of the Hubbard U and J parameters are initially unknown, and they can vary from one material to another. In this semi-empirical study, we explore the U and J parameter space of a group of iron-based compounds to simultaneously improve the prediction of physical properties (volume, magnetic moment, and bandgap). We used a Bayesian calibration assisted by Markov chain Monte Carlo sampling for three different exchange-correlation functionals (LDA, PBE, and PBEsol). We found that LDA requires the largest U correction. PBE has the smallest standard deviation and its U and J parameters are the most transferable to other iron-based compounds. Lastly, PBE predicts lattice parameters reasonably well without the Hubbard correction.

en: Exploring DFT+U parameter space with a Bayesian calibration assisted by Markov chain Monte Carlo sampling

bayesian-calibration

display_name: bayesian-calibration

dftu

display_name: dftu

markov-chain-monte-carlo

display_name: markov-chain-monte-carlo

mcmc

display_name: mcmc


en:
Reticular chemistry provides materials designers with a practically infinite playground on different length scales. However, the space of all plausible materials for a given application is so large that it cannot be explored using a brute-force approach. One promising approach to guide the design and discovery of materials is machine learning, which typically involves learning a mapping of structures onto properties from data.
To advance the data-driven materials discovery of metal-organic frameworks (MOFs) for gas storage and separation applications we provide a dataset of diverse gas separation properties (CO2, CH4, H2, N2, O2 isotherms); H2S, H2O, Kr, Xe Henry coefficients (computed using grand canonical Monte-Carlo with classical force fields) as well as parasitic energy for carbon capture from natural gas and a coal-fired power plant (computed using a simple process model) for the relaxed structures in the QMOF dataset with their DDEC charges.

en: Gas adsorption and process performance data for MOFs

aiida

display_name: aiida

erc

display_name: erc

marvel

display_name: marvel

mof

display_name: mof

nanoporous

display_name: nanoporous


en: Accurate computational predictions of band gaps are of practical importance to the modeling and development of semiconductor technologies, such as (opto)electronic devices and photoelectrochemical cells. Among available electronic-structure methods, density-functional theory (DFT) with the Hubbard U correction (DFT+U) applied to band edge states is a computationally tractable approach to improve the accuracy of band gap predictions beyond that of DFT calculations based on (semi)local functionals. At variance with DFT approximations, which are not intended to describe optical band gaps and other excited-state properties, DFT+U can be interpreted as an approximate spectral-potential method when U is determined by imposing the piecewise linearity of the total energy with respect to electronic occupations in the Hubbard manifold (thus removing self-interaction errors in this subspace), thereby providing a (heuristic) justification for using DFT+U to predict band gaps. However, it is still frequent in the literature to determine the Hubbard U parameters semiempirically by tuning their values to reproduce experimental band gaps, which ultimately alters the description of other total-energy characteristics. Here, we present an extensive assessment of DFT+U band gaps computed using self-consistent ab initio U parameters obtained from density-functional perturbation theory to impose the aforementioned piecewise linearity of the total energy. The study is carried out on 20 compounds containing transition-metal or p-block (group III-IV) elements, including oxides, nitrides, sulfides, oxynitrides, and oxysulfides. By comparing DFT+U results obtained using nonorthogonalized and orthogonalized atomic orbitals as Hubbard projectors, we find that the predicted band gaps are extremely sensitive to the type of projector functions and that the orthogonalized projectors give the most accurate band gaps, in satisfactory agreement with experimental data. This work demonstrates that DFT+U may serve as a useful method for high-throughput workflows that require reliable band gap predictions at moderate computational cost.

en: Extensive benchmarking of DFT+U calculations for predicting band gaps

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).

band-gap

display_name: band-gap

hubbard-correction

display_name: hubbard-correction

lowdin-orthogonalization

display_name: lowdin-orthogonalization

marvelosp

display_name: marvelosp

self-interaction

display_name: self-interaction

snsf

display_name: snsf


en: The dataset contains the result of 48 Nudged Elastic Band calculations of Li(2-x)VO2F diffusion barriers in the format of Atomic Simulation Environment (ASE) trajectories. The NEB was performed with VASP, using projector augmented-wave (PAW) method to describe electron-ion interaction. The disordered rock salt cells were created using a 3 x 4 x 4 supercell containing 96 atoms (in case of no vacancies). PBE is used as XC functional while a rotationally invariant Hubbard U correction was applied to the d orbital of V with a U value of 3.25 eV. See more details in the paper.

en: On-the-fly assessment of diffusion barriers of disordered transition metal oxyfluorides using local descriptors

materialscloud

en: Materials Cloud

big-map

display_name: big-map

fet-open

display_name: fet-open

lirichfcc

display_name: lirichfcc

lithium-diffusion

display_name: lithium-diffusion

machine-learning

display_name: machine-learning

nudged-elastic-band

display_name: nudged-elastic-band


en: C2N is an ordered two-dimensional carbon nitride with a high density (1.7 × 10^14 cm−2) of 3.1 Å-sized nanopores, making it promising for high-flux gas sieving for energy-efficient He and H2 purification. Herein, we discuss the accurate calculation of potential energy surfaces for He, H2, N2, and CO2 across C2N nanopores, to characterize the gas-sieving potential of C2N. We compare the potential energy surface derived from density-functional theory calculations using five commonly used van der Waals (vdW) approximations. While all five functionals point that the C2N nanopore yields He/N2 and H2/N2 selectivities over 1000, adsorption energies and energy barriers vary remarkably depending on the approximation chosen. To make progress, we compare the calculations against the results from the adiabatic connection fluctuation dissipation theory, with random-phase approximation, known to be accurate in capturing vdW interactions. The comparison indicates that the interaction energy is less accurate with vdW density functional theory. On the other hand, more empirical corrections work reasonably well, a finding that we also confirm for another carbon nitride lattice, poly(triazine imide). Overall, we recommend these for screening carbon nitride materials for gas separation, but also comparing functionals with higher-order approaches when dealing with different materials.

en: Gas transport across carbon nitride nanopores: a comparison of van der Waals functionals against the random-phase approximation

envi

en: Environment

carbon-nitrides

display_name: carbon-nitrides

cscs

display_name: cscs

density-functional-theory

display_name: density-functional-theory

epfl

display_name: epfl

nanoscale-transport

display_name: nanoscale-transport

random-phase-approximation

display_name: random-phase-approximation

van-der-waals-approximations

display_name: van-der-waals-approximations


en: elphbolt is a modern Fortran (2018 standard) code for efficiently solving the coupled electron-phonon Boltzmann transport equations from first principles. Using results from density functional and density functional perturbation theory as inputs, it can calculate the effect of the non-equilibrium phonons on the electronic transport (phonon drag) and non-equilibrium electrons on the phononic transport (electron drag) in a fully self-consistent manner and obeying the constraints mandated by thermodynamics. It can calculate the lattice, charge, and thermoelectric transport coefficients for the temperature gradient and electric fields, and the effect of the mutual electron-phonon drag on these transport properties. The code fully exploits the symmetries of the crystal and the transport-active window to allow the sampling of extremely fine electron and phonon wave vector meshes required for accurately capturing the drag phenomena. The coarray feature of modern Fortran, which offers native and convenient support for parallelization, is utilized. The code is compact, readable, well-documented, and extensible by design.

en: The elphbolt ab initio solver for the coupled electron-phonon Boltzmann transport equations

ab-initio

display_name: ab-initio

boltzmann-transport

display_name: boltzmann-transport

electron-drag

display_name: electron-drag

electron-phonon-coupling

display_name: electron-phonon-coupling

electron-transport

display_name: electron-transport

intersect

display_name: intersect

phonon-drag

display_name: phonon-drag

phonon-transport

display_name: phonon-transport

thermoelectricity

display_name: thermoelectricity


en:
This repository has the input files and a guide to recreate the data from "The importance of reference frame for pressure at the liquid-vapour interface" (https://arxiv.org/abs/2107.00499). It requires the Flowmol code to be downloaded and built from https://github.com/edwardsmith999/flowmol (it should work with the latest version but the paper was generated from commit c4a52d434053d676c0281449b0fce7112116fd54 or the persistent version linked to DOI https://doi.org/10.5281/zenodo.4639546). The included README.txt file outlines how to do this. The input files are also included on the Github repository. The summarised data is also included as a Python pickle (summary.p) with scripts to produce all plots from the paper. This data, which shows the profile going through a liquid vapour interface, can be analysed in Python.

The abstract for the article, which explains the importance of this data, is as follows: The local pressure tensor is non-unique, a fact which has generated confusion and debate in the seventy years since the seminal work by Irving Kirkwood. This non-uniqueness is normally attributed to the interaction path between molecules, especially in the interfacial-science community. In this work we reframe this discussion of non-uniqueness in terms of the location, or reference frame, used to measure the pressure. By using a general mathematical description of the liquid-vapour interface, we obtain a reference frame that moves with the interface through time, providing a new insight into the pressure. We compare this instantaneous moving reference frame with the fixed Eulerian one. Through this process, we show the requirement that normal pressure balance at the moving surface is satisfied by surface fluxes, however an additional corrective term based on surface curvature is required for the average pressure in a volume. We make the case that a focus on the path of integration is the cause of much of the confusion in the literature. Using an explicit reference frame with a more general derivation of pressure clarifies some of the issues of uniqueness in the pressure tensor and provides a pressure tensor which is defined at any instant in time and valid away from thermodynamic equilibrium.

flowmol

display_name: flowmol

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

python-pickle

display_name: python-pickle

software-input-files

display_name: software-input-files


en: Within the framework of many-body perturbation theory integrated with density functional theory (DFT), a novel defect-subspace projection GW method, the so-called p-GW, is proposed. By avoiding the periodic defect interference through open boundary self-energies, we show that the p-GW can efficiently and accurately describe quasi-particle correlated defect levels in two-dimensional (2D) monolayer MoS₂. By comparing two different defect states originating from sulfur vacancy and adatom to existing theoretical and experimental works, we show that our GW correction to the DFT defect levels is precisely modelled. Based on these findings, we expect that our method can provide genuine trap states for various 2D transition-metal dichalcogenide (TMD) monolayers, thus enabling the study of defect-induced effects on the device characteristics of these materials via realistic simulations.

en: Efficient and accurate defect level modelling in monolayer MoS₂ via GW+DFT with open boundary conditions

dft

display_name: dft

gw

display_name: gw

marvel

display_name: marvel

negf

display_name: negf


en: On-surface synthesis serves as a powerful approach to construct π-conjugated carbon nanostructures that are not accessible by conventional wet chemistry. Nevertheless, this method has been limited by the types and numbers of available on-surface transformations. While the majority of successful cases exploit thermally triggered dehalogenative carbon–carbon coupling and cyclodehydrogenation, rearrangement of appropriate functional moieties has received limited research attention. In a recent work, we describe the unprecedented interchain coupling and thermally induced skeleton rearrangement  of (dihydro)indeno[2,1-b]fluorene (IF) polymers on an Au(111) surface under ultrahigh vacuum conditions, leading to different ladder polymers as well as fully fused graphene nanoribbon segments containing pentagonal and heptagonal rings. Au-coordinated nanoribbons are also observed. All structures are unambiguously characterized by high-resolution scanning probe microscopy. The results provide an avenue to fabricating a wider variety of π-conjugated polymers and carbon nanostructures comprising nonhexagonal rings as well as rarely explored organometallic nanoribbons. This record contains data of the calculations that support our results.

en: On-surface interchain coupling and skeletal rearrangement of indenofluorene polymers

cscs

display_name: cscs

indenofluorene

display_name: indenofluorene

non-contact-atomic-force-microscopy

display_name: non-contact-atomic-force-microscopy

snsf

display_name: snsf

stm

display_name: stm


en: The choice of the ideal material employed in selector devices is a tough task both from the theoretical and experimental side, especially due to the lack of a synergistic approach between techniques able to correlate specific material properties with device characteristics. Using a material-to-device multiscale technique, a reliable protocol for an efficient characterization of the active traps in amorphous GeSe chalcogenide is proposed. The resulting trap maps trace back the specific features of materials responsible for the measured findings, and connect them to an atomistic description of the sample. The metrological approach can be straightforwardly extended to other materials and devices, which is very beneficial for an efficient material-device codesign and the optimization of novel technologies.

en: Device-to-materials pathway for electron traps detection in amorphous GeSe-based selectors

amorphous

display_name: amorphous

chalcogenides

display_name: chalcogenides

device-to-materials

display_name: device-to-materials

electronic-structure

display_name: electronic-structure

intersect

display_name: intersect

openmodel

display_name: openmodel

selectors

display_name: selectors


en: We present a numerical tool for solving the non-relativistic Kohn-Sham problem for spherically-symmetric atoms. It treats the Schrödinger equation as an integral equation relying heavily on convolutions. The solver supports different types of exchange-correlation functionals including screened and long-range corrected hybrids. We implement a new method for treating range separation based on the complementary error function kernel. The present tool is applied in spin-restricted non-relativistic total energy calculations of atoms. A comparison with ultra-precise reference data[Cinal, JOMC 58, 1571 (2020)] shows a 14-digit agreement for Hartree-Fock results. We provide further benchmark data obtained with 5 different exchange-correlation functionals: VWN5 (the local-density approximation), PBE (the generalized gradient approximation), PBE0 and B3LYP (hybrids with a Fock exchange) and LC-BLYP (hybrid with a long-range corrected exchange).

en: Total energies of atoms from integral-equation radial solver

atoms

display_name: atoms

density-functional-theory

display_name: density-functional-theory

hartree-fock

display_name: hartree-fock

high-precision

display_name: high-precision

hybrids

display_name: hybrids


en: Predicting the thermal conductivity of glasses from first principles has hitherto been a very complex problem. The established Allen-Feldman and Green-Kubo approaches employ approximations with limited validity--the former neglects anharmonicity, the latter misses the quantum Bose-Einstein statistics of vibrations--and require atomistic models that are very challenging for first principles methods. Here, we present a protocol to determine from first-principles the thermal conductivity k(T) of glasses above the plateau (i.e., above the temperature-independent region appearing almost without exceptions in the k(T) of all glasses at cryogenic temperatures). The protocol combines the Wigner formulation of thermal transport with convergence-acceleration techniques, and accounts comprehensively for the effects of structural disorder, anharmonicity, and Bose-Einstein statistics. We validate this approach in vitreous silica, showing that models containing less than 200 atoms can already reproduce k(T) in the macroscopic limit. We discuss the effects of anharmonicity and the mechanisms determining the trend of k(T) at high temperature, reproducing experiments at temperatures where radiative effects remain negligible.

en: Thermal conductivity of glasses: first-principles theory and applications

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).

atomic-vibrations

display_name: atomic-vibrations

first-principles

display_name: first-principles

thermal-transport

display_name: thermal-transport

vitreous-silica

display_name: vitreous-silica


en: Electrochemical impedance spectroscopy (EIS) is the widely used technique to monitor the electrical properties of a catalyst under electrocatalytic conditions. Although it is extensively used for research in electrocatalysis, its effectiveness and power have not been fully harnessed to elucidate complex interfacial processes. Herein, we use the frequency dispersion parameter, n, which is extracted from EIS measurements, to describe the dispersion characteristics of capacitance and interfacial properties of Co3O4 under alkaline oxygen evolution reaction (OER) conditions. We first prove the n-value is sensitive to the interfacial electronic changes associated with Co redox processes and surface reconstruction. The n-value decreases by increasing the specific/active surface area of the catalysts. We further modify the interfacial properties by changing different components, i.e., replacing the proton with deuterium, adding ethanol as a new oxidant, and changing the cation in the electrolyte. Intriguingly, the n-value can identify different influences on the interfacial process from proton transfer, the decrease and carbon-poisoning of oxidized Co species, and the interfacial water structure. These findings convey that the frequency dispersion of capacitance is a convenient and useful method to uncover the interfacial properties under electrocatalytic conditions, which helps to advance the understanding of the interface-activity relationship.

en: Uncovering the catalyst/electrolyte interfacial process by frequency dispersion of capacitance

materialscloud

en: Materials Cloud

catalystelectrolyte-interface

display_name: catalystelectrolyte-interface

electrochemical-impedance-spectroscopy

display_name: electrochemical-impedance-spectroscopy

frequency-dispersion-of-capacitance

display_name: frequency-dispersion-of-capacitance

interfacial-capacitance

display_name: interfacial-capacitance

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


en: Determining ab-initio potential dependent energetics are critical to investigating mechanisms for electrochemical reactions. While methodology for evaluating reaction thermodynamics is established, simulation techniques for the corresponding kinetics is still a major challenge owing to a lack of potential control, finite cell size effects or computational expense. In this work, we develop a model which allows for computing electrochemical activation energies from just a handful of Density Functional Theory (DFT) calculations. The sole input into the model are the atom centered forces obtained from DFT calculations performed on a homogeneous grid composed of varying field-strengths. We show that the activation energies as a function of the potential obtained from our model are consistent for different super-cell sizes and proton concentrations for a range of electrochemical reactions. This record contains output files from all the DFT calculations needed to reproduce the figures in the manuscript.

en: Force-based method to determine the potential dependence in electrochemical barriers

envi

en: Environment

electrochemical-barriers

display_name: electrochemical-barriers

electrochemical-kinetics

display_name: electrochemical-kinetics

proton-electron-transfer-reactions

display_name: proton-electron-transfer-reactions


en: The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)heating of batteries. The reason for this lies in the complexity of the calculations: on one hand, the diffusion of ionic charge carriers makes lattice methods formally unsuitable due to the lack of equilibrium atomic positions needed for normal-mode expansion. On the other hand, the prohibitive cost of large-scale molecular dynamics (MD) simulations of heat transport in large systems at ab initio levels has hindered the use of MD-based methods. In this work, we leverage recently developed machine-learning potentials targeting different ab initio functionals (PBEsol, r2SCAN, PBE0) and a state-of-the-art formulation of the Green-Kubo theory of heat transport in multicomponent systems to compute the thermal conductivity of a promising solid-state-electrolyte, Li3PS4, in all its polymorphs (α, β and γ). By comparing MD estimates with lattice methods on the low-temperature, non-diffusive γ-Li3PS4, we highlight strong anharmonicities and negligible nuclear quantum effects, hence further justifying MD-based methods even for non-diffusive phases. Finally, for the ion-conducting α and β phases, where the multicomponent Green-Kubo MD approach is mandatory, our simulations indicate a weak temperature dependence of the thermal conductivity, a glass-like behavior due to the effective local disorder characterizing these Li-diffusing phases.

en: Thermal transport of Li₃PS₄ solid electrolytes with ab initio accuracy

epfl

display_name: epfl

lab-cosmo

display_name: lab-cosmo

machine-learning

display_name: machine-learning

marvel

display_name: marvel

max

display_name: max

snsf

display_name: snsf

solid-state-electrolytes

display_name: solid-state-electrolytes

swissuniversities

display_name: swissuniversities


en:
We propose a variational algorithm to study the real time dynamics of quantum systems as a ground-state problem on quantum devices. The method is based on the original proposal of Feynman and Kitaev to encode time into a register of auxiliary qubits.
We prepare the Feynman-Kitaev Hamiltonian acting on the composed system as a qubit operator and find an approximate ground state using the Variational Quantum Eigensolver. We apply the algorithm to the study of the dynamics of a transverse field Ising chain with an increasing number of spins and time steps, proving a favorable scaling in terms of the number of two qubit gates.
Through numerical experiments, we investigate its robustness against hardware noise, showing that the method can be use to evaluate dynamical properties of quantum systems and detect the presence of dynamical quantum phase transitions by measuring Loschmidt echoes.
The scripts provided implement the algorithm both in Python, using the Qiskit library, and in Julia, using the Yao.jl package.
Moreover, we included the data to reproduce the figures of the manuscript without running the simulations.

en: Variational dynamics as a ground-state problem on a quantum computer

quantum-computing

display_name: quantum-computing

quantum-simulation

display_name: quantum-simulation

real-time-evolution

display_name: real-time-evolution


en: Dehydrogenation reactions are key steps in many metal-catalyzed chemical processes and in the on-surface synthesis of atomically precise nanomaterials. The principal role of the metal substrate in these reactions is undisputed, but the role of metal adatoms remains, to a large extent, unanswered, particularly on gold substrates. In a recent publication, we discuss their importance by studying the surface-assisted cyclodehydrogenation on Au(111) as an ideal model case. We choose a polymer theoretically predicted to give one of two cyclization products depending on the presence or absence of gold adatoms. Scanning probe microscopy experiments observe only the product associated with adatoms. We challenge the prevalent understanding of surface-assisted cyclodehydrogenation, unveiling the catalytic role of adatoms and their effect on regioselectivity. The study adds new perspectives to the understanding of metal catalysis and the design of on-surface synthesis protocols for novel carbon nanomaterials. The record contains data for the CP2K-based calculations that support the results.

en: The role of metal adatoms in a surface-assisted cyclodehydrogenation reaction on a gold surface

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

on-surface-synthesis

display_name: on-surface-synthesis

stm

display_name: stm


en: With the recent advances in machine learning for quantum chemistry, it is now possible to predict the chemical properties of compounds and to generate novel molecules. Existing generative models mostly use a string- or graph-based representation, but the precise three-dimensional coordinates of the atoms are usually not encoded. First attempts in this direction have been proposed, where autoregressive or GAN-based models generate atom coordinates. Those either lack a latent space in the autoregressive setting, such that a smooth exploration of the compound space is not possible, or cannot generalize to varying chemical compositions. We propose a new approach to efficiently generate molecular structures that are not restricted to a fixed size or composition. Our model is based on the variational autoencoder which learns a translation-, rotation-, and permutation-invariant low-dimensional representation of molecules. Our experiments yield a mean reconstruction error below 0.05 Angstrom, outperforming the current state-of-the-art methods by a factor of four, and which is even lower than the spatial quantization error of most chemical descriptors. The compositional and structural validity of newly generated molecules has been confirmed by quantum chemical methods in a set of experiments.

en: 3DMolNet: a generative network for molecular structures

generative-model

display_name: generative-model

molecules-discovery

display_name: molecules-discovery

three-dimensional-structures

display_name: three-dimensional-structures


en: We unveil the nature of the structural disorder in bottom-up zigzag graphene nanoribbons along with its effect on the magnetism and electronic transport on the basis of scanning probe microscopies and first-principles calculations. We find that edge-missing m-xylene units emerging during the cyclodehydrogenation step of the on-surface synthesis are the most common point defects. These "bite" defects act as spin-1 paramagnetic centers, severely disrupt the conductance spectrum around the band extrema, and give rise to spin-polarized charge transport. We further show that the electronic conductance across graphene nanoribbons is more sensitive to "bite" defects forming at the zigzag edges than at the armchair ones. Our work establishes a comprehensive understanding of the low-energy electronic properties of disordered bottom-up graphene nanoribbons.

en: Edge disorder in bottom-up zigzag graphene nanoribbons: implications for magnetism and quantum electronic transport

cscs

display_name: cscs

defects

display_name: defects

electronic-transport

display_name: electronic-transport

gnr

display_name: gnr

magnetism

display_name: magnetism

onr

display_name: onr


en: Time-dependent density functional theory has become state-of-the-art for describing photophysical and photochemical processes in extended materials due to its affordable cost. The inclusion of exact exchange was shown to be essential for the correct description of the long-range asymptotics of electronic interactions and thus a well-balanced description of valence, Rydberg and charge-transfer excitations. Several approaches for an efficient treatment of exact exchange have been established for the ground state, while implementations for excited-state properties are rare. Furthermore, the high computational costs required for excited-state properties in comparison to ground-state computations often hinder large-scale applications on periodic systems with hybrid functional accuracy. We therefore propose two approximate schemes for improving computational efficiency for the treatment of exact exchange. Within the auxiliary density matrix method (ADMM), exact exchange is estimated using a relatively small auxiliary basis and the introduced basis-set incompleteness error is compensated by an exchange density functional correction term. Benchmark results for a test set of 35 molecules demonstrate that the mean absolute error introduced by ADMM is smaller than 0.3 pm for excited-state bond lengths and in the range of 0.02 - 0.07 eV for vertical excitation, adiabatic excitation and fluorescence energies. Computational timings for a series of covalent-organic frameworks demonstrate that a speed-up of at least one order of magnitude can be achieved for ES geometry optimizations in comparison to conventional hybrid functionals. The second method is to use a semi-empirical tight binding approximation for both Coulomb and exchange contributions to the excited-state kernel. This simplified Tamm-Dancoff approximation (sTDA) achieves an accuracy comparable to approximated hybrid density functional theory when referring to highly accurate coupled-cluster reference data. We find that excited-state bond lengths deviate by 1.1 pm on average and mean absolute errors in vertical excitation, adiabatic excitation and fluorescence energies are in the range of 0.2 - 0.5 eV. In comparison to ADMM-approximated hybrid functional theory, sTDA accelerates the computation of broad-band excitation spectra by one order of magnitude, suggesting its potential use for large-scale screening purposes.

en: Excited-state properties for extended systems: efficient hybrid density functional methods

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).

excited-state-properties

display_name: excited-state-properties

hybrid-density-functional-theory

display_name: hybrid-density-functional-theory

marie-curie-fellowship

display_name: marie-curie-fellowship

marvel

display_name: marvel

theoretical-spectroscopy

display_name: theoretical-spectroscopy


en: Computational searches for new materials are naturally turning from binary systems, to ternary and other multicomponent systems, and beyond. Here, we select the industrially-relevant metals Ti and Al and report the results of an extensive structure prediction study on the ternary titanium-carbon-oxygen (Ti-C-O) and aluminium-carbon-oxygen (Al-C-O) systems. We map out for the first time the full phase stability of Ti-C-O and Al-C-O compounds using first-principles calculations, through simple, effcient and highly parallel random structure searching in conjunction with techniques based on complex network theory. This record contains the crystal structures used to generate our ternary convex hulls for these systems. We provide input files for the CASTEP density-functional theory code, crystallographic '.res' files of the relaxed structures, and CASTEP output files showing atomic positions and forces calculated during relaxation.

en: Navigating the Ti-C-O and Al-C-O ternary systems through theory-driven discovery

materialscloud

en: Materials Cloud

carbonate-minerals

display_name: carbonate-minerals

density-functional-theory

display_name: density-functional-theory

structure-prediction

display_name: structure-prediction

ternary-systems

display_name: ternary-systems


en:
Two different heat-transport mechanisms are discussed in solids: in crystals, heat carriers propagate and scatter like particles, as described by Peierls' formulation of Boltzmann transport equation for phonon wavepackets; in glasses, instead, carriers behave wave-like, diffusing via a Zener-like tunneling between quasi-degenerate vibrational eigenstates, as described by the Allen-Feldman equation. Recently, it has been shown that these two conduction mechanisms emerge as limiting cases from a unified transport equation, which describes on an equal footing solids ranging from crystals to glasses; moreover, in materials with intermediate characteristics the two conduction mechanisms coexist, and it is crucial to account for both. Here, we discuss the theoretical foundations of such transport equation as is derived from the Wigner phase-space formulation of quantum mechanics, elucidating how the interplay between disorder, anharmonicity, and the quantum Bose-Einstein statistics of atomic vibrations determines thermal conductivity. This Wigner formulation argues for a preferential phase convention for the dynamical matrix in the reciprocal Bloch representation and related off-diagonal velocity operator's elements; such convention is the only one yielding a conductivity which is invariant with respect to the non-unique choice of the crystal's unit cell and is size-consistent. We rationalize the conditions determining the crossover from particle-like to wave-like heat conduction, showing that phonons below the Ioffe-Regel limit (i.e. with a mean free path shorter than the interatomic spacing) contribute to heat transport due to their wave-like capability to interfere and tunnel. Finally, we show that the present approach overcomes the failures of the Peierls-Boltzmann formulation for materials with ultralow or glass-like thermal conductivity, with case studies of materials for thermal barrier coatings and thermoelectric energy conversion.

Here, we release the crystal structures, interatomic force constants, and computational parameters needed to reproduce the results discussed in the article "Wigner formulation of thermal transport in solids" (arXiv preprint, 2021) by M. Simoncelli, N. Marzari, and F. Mauri.

envi

en: Environment

anharmonicity

display_name: anharmonicity

phonons

display_name: phonons

thermal-conductivity

display_name: thermal-conductivity

wigner-heat-transport-equation

display_name: wigner-heat-transport-equation


en:
The electronic structure, interatomic bonding, and mechanical properties of two supercell models of Ni-based super alloys are calculated by using ab initio density functional theory methods. The alloys are in the face centered cubic lattice having 864 atoms and eleven elements: Haynes282 (Ni₄₄₄Cr₂₀₂Co₇₉Al₅₆Ti₂₅Mo₂₅Fe₁₂Mn₃Si₅C₁₂B) and Inconel740 (Ni₃₇₃Cr₂₄₆Co₁₅₃Al₃₃Ti₂₁Nb₆MoFe₆
Mn₃Si₁₇C₅). These multi-component alloys have very complex electronic structure, bonding and partial charge distributions depending on the composition and strength of local bonding environment. We employ the novel concept of total bond order density (TBOD) and its partial components (PBOD) to ascertain the internal cohesion that controls the intricate balance between the propensity of metallic bonding between Ni, Cr and Co, and the strong bonds with C and Al. We find Inconel740 has slightly stronger mechanical properties than Haynes282. Comparison with more conventional high entropy alloys with equal components are discussed.

en: Ab initio simulation of structure and properties in Ni-based superalloys Haynes282 and Inconel740

effective-charge

display_name: effective-charge


en: Predicting the electrical properties of organic molecular crystals (OMCs) is challenging due to their complex crystal structures and electron-phonon (e-ph) interactions. Charge transport in OMCs is conventionally categorized into two limiting regimes – band transport, characterized by weak e-ph interactions, and charge hopping due to localized polarons formed by strong e-ph interactions. However, between these two limiting cases there is a less well understood intermediate regime where polarons are present but transport does not occur via hopping. Here we show a many-body first-principles approach that can accurately predict the carrier mobility in OMCs in the intermediate regime and shed light on its microscopic origin. Our approach combines a finite-temperature cumulant method to describe strong e-ph interactions with Green-Kubo transport calculations. We apply this parameter-free framework to naphthalene crystal, demonstrating electron mobility predictions within a factor of 1.5–2 of experiment between 100–300 K. Our analysis reveals that electrons couple strongly with both inter- and intramolecular phonons in the intermediate regime, as evidenced by the formation of a broad polaron satellite peak in the electron spectral function and the failure of the Boltzmann transport equation (BTE). Our study advances quantitative modeling of charge transport in complex organic crystals. This dataset contains input and output files required to reproduce the BTE results presented in our work.

en: Intermediate polaronic charge transport in organic crystals from a many-body first-principles approach

boltzmann-equation

display_name: boltzmann-equation

carrier-mobility

display_name: carrier-mobility

charge-transport

display_name: charge-transport

electron-phonon-coupling

display_name: electron-phonon-coupling

electron-phonon-scattering-rate

display_name: electron-phonon-scattering-rate

first-principles-calculations

display_name: first-principles-calculations

molecular-crystal

display_name: molecular-crystal

naphthalene

display_name: naphthalene

organic-crystal

display_name: organic-crystal

polaron

display_name: polaron


en:
We developed a general framework for hybrid quantum-classical computing of molecular and periodic embedding calculations based on an orbital space separation of the fragment and environment degrees of freedom. We show its potential by presenting a specific implementation of periodic range-separated DFT coupled to a quantum circuit ansatz, whereby the variational quantum eigensolver and the quantum equation-of-motion approach are used to obtain the low-lying spectrum of the embedded fragment Hamiltonian.
Application of this scheme to study strongly correlated molecular systems and localized electronic states in materials is showcased through the accurate prediction of the optical properties for the neutral oxygen vacancy in magnesium oxide (MgO). Despite some discrepancies in absorption predictions, the method demonstrates competitive performance with state-of-the-art ab initio approaches, particularly evidenced by the accurate prediction of the photoluminescence emission peak.

en: A general framework for active space embedding methods: applications in quantum computing

marvelqs

display_name: marvelqs

qiskit-nature

display_name: qiskit-nature

quantum-embedding

display_name: quantum-embedding

quantum-simulation

display_name: quantum-simulation


en:
Resonant inelastic X-ray scattering (RIXS) can probe localized excitations at selected atoms in materials, including particle-hole transitions from valence to the conduction bands. These transitions are governed by fundamental prop- erties of the corresponding Bloch wave-functions, including orbital and mag- netic degrees of freedom, and quantum geometric properties such as the Berry curvature. In particular, orbital angular momentum (OAM), which is closely linked to the Berry curvature, can exhibit a nontrivial momentum dependence. We demonstrate how information on such OAM textures can be extracted from the circular dichroism in RIXS. Based on accurate modeling with first-principles treatment of the key ingredient – the light-matter interaction – we simulate dichroic RIXS spectra for the prototypical transition metal dichalcogenide MoSe₂ and the two-dimensional topological insulator 1T′-MoS₂ . Guided by an in- tuitive picture for the optical selection rules, we discuss how the momentum- dependent OAM manifests itself in the dichroic RIXS signal if one controls the momentum transfer. Our calculations are performed for typical experimental geometries and parameter regimes, and demonstrate the possibility of observ- ing the predicted circular dichroism in forthcoming experiments. Thus, our work establishes a new avenue to observing Berry curvature and topological states in quantum materials.

The simulated RIXS spectra and the scripts to generate the plots in this work are available in this archive.

en: Probing magnetic orbitals and Berry curvature with circular dichroism in resonant inelastic X-ray scattering

marvel

display_name: marvel

quantum-espresso

display_name: quantum-espresso

two-dimensional

display_name: two-dimensional

wannier-functions

display_name: wannier-functions


en: The electronic properties and optical response of ice and water are intricately shaped by their molecular structure, including the quantum mechanical nature of hydrogen atoms. Despite numerous former studies, a comprehensive understanding of nuclear quantum effects (NQE) on the electronic structure of water and ice at finite temperatures remains elusive. Here, we utilize molecular simulations that harness efficient machine-learning potentials and many-body perturbation theory to assess how NQEs impact the electronic bands of water and hexagonal ice. By comparing path-integral and classical simulations, we find that NQEs lead to a larger renormalization of the fundamental gap of ice, compared to that of water, ultimately yielding similar bandgaps in the two systems, consistent with experimental estimates. Our calculations suggest that the increased quantum mechanical delocalization of protons in ice, relative to water, is a key factor leading to the enhancement of NQEs on the electronic structure of ice.

en: Nuclear quantum effects on the electronic structure of water and ice

electronic-structure

display_name: electronic-structure

molecular-dynamics

display_name: molecular-dynamics

nuclear-quantum-effects

display_name: nuclear-quantum-effects

water

display_name: water


en: The study of magnetism in transition metals is a cornerstone in understanding complex electronic and magnetic interactions in condensed matter systems. Among transition metal elements, body-centered cubic (bcc) chromium stands out because of its spin-density wave (SDW) ground state, posing a long-standing challenge for density functional theory (DFT). Conventional functionals, such as the generalized-gradient approximation (GGA) and the local-density approximation (LDA), fail to predict this experimentally observed incommensurate SDW as the ground state. In this study, we present a comprehensive DFT analysis of bcc Cr employing GGA and a variety of meta-GGA functionals. We evaluated total energies, structural parameters, and magnetic properties across a wide range of SDW wave vectors. Our results show that all meta-GGA functionals overestimate the local magnetic moments and enhance the nodal magnetic frustration, destabilizing the SDW state relative to the commensurate antiferromagnetic (AF) configuration. Tao-Perdew-Staroverov-Scuseria (TPSS) yields results closest to those of the GGA, thus providing the most adequate description of bcc Cr among the meta-GGA functionals. These results emphasize the need for the further development of non-local or hybrid functionals tailored for complex magnetic systems.

en: A first-principles study of bcc chromium beyond the generalized gradient approximation (GGA)

chromium

display_name: chromium

dft

display_name: dft

magnetism

display_name: magnetism

spin-density-waves

display_name: spin-density-waves


en: A catalyst possessing a broad substrate scope, in terms of both turnover and enantioselectivity, is sometimes called "general". Despite their great utility in asymmetric synthesis, truly general catalysts are difficult or expensive to discover via traditional high-throughput screening and are, therefore, rare. Existing computational tools accelerate the evaluation of reaction conditions from a pre-defined set of experiments to identify the most general ones, but cannot generate entirely new catalysts with enhanced substrate breadth. For these reasons, we report an inverse design strategy based on the open-source genetic algorithm NaviCatGA and on the OSCAR database of organocatalysts to simultaneously probe the catalyst and substrate scope and optimize generality as primary target. We apply this strategy to the Pictet–Spengler condensation, for which we curate a database of 820 reactions, used to train statistical models of selectivity and activity. Starting from OSCAR, we define a combinatorial space of millions of catalyst possibilities, and perform evolutionary experiments on a diverse substrate scope that is representative of the whole chemical space of tetrahydro-β-carboline products. While privileged catalysts emerge, we show how genetic optimization can address the broader question of generality in asymmetric synthesis, extracting structure–performance relationships from the challenging areas of chemical space.

en: A genetic optimization strategy with generality in asymmetric organocatalysis as primary target

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

enantioselectivity

display_name: enantioselectivity

generality

display_name: generality

genetic-optimization

display_name: genetic-optimization

machine-learning

display_name: machine-learning

nccr-catalysis

display_name: nccr-catalysis

organic-molecules

display_name: organic-molecules

organocatalysis

display_name: organocatalysis


en:
In a recent preprint, entitled: "Development of a machine learning interatomic potential for exploring pressure-dependent kinetics of phase transitions in Germanium", we presented a novel Neural-Network (NN)  interatomic potential for Ge. We recall that Ge phases different from the cubic-diamond one are of particular interest for applications. Hexagonal Ge, for instance, displays superior optical properties. It is therefore important to investigate how, exploiting pressure, Ge can be transformed into different allotropes. In order to build a potential tackling kinetics of pressure-induced phase transformations, several kinetic paths (mainly sampled using the solid-state Nudged Elastic Band method) were added to the database, following a suitable active-learning procedure. Energies, forces, and stressed relative to the various configurations were computed ab initio using VASP with the PBE functional. The NN potential was trained using the Deep Potential Molecular Dynamic package (DeePMDkit). The potential greatly reproduces the relative stability of several Ge phases and yields at least a semi-quantitative description of the energetics along complex phase-transformation paths.
In the present archive, we provide the full potential for use in LAMMPS and ASE, together with the full database produced using VASP.

en: A NN-Potential for phase transformations in Ge

materialscloud

en: Materials Cloud

deepmd

display_name: deepmd

germanium

display_name: germanium

neural-network

display_name: neural-network

phase-transitions

display_name: phase-transitions


en: We calculate the screened electron-electron interaction for the charge-disproportionated insulator CaFeO₃ using the constrained random-phase approximation (cRPA). While in many correlated materials, the formation of a Mott-insulating state is driven by a large local Coulomb repulsion, represented by the Hubbard U, several cases have been identified more recently where U is strongly screened and instead the Hund's interaction J dominates the physics. Our results confirm a strong screening of the local Coulomb repulsion U in CaFeO₃ whereas J is much less screened and can thus stabilize a charge-disproportionated insulating state. This is consistent with the case of the rare-earth nickelates where similar behavior has been demonstrated. In addition, we validate some common assumptions used for parametrizing the local electron-electron interaction in first-principles calculations based on density-functional theory (DFT), assess the dependence of the interaction on the choice of correlated orbitals, and discuss the use of the calculated interaction parameters in DFT+U calculations of CaFeO₃. Our work also highlights certain limitations for the direct use of cRPA results in DFT-based first-principles calculations, in particular for systems with strong entanglement between the correlated and uncorrelated bands.

en: Calculation of screened Coulomb interaction parameters for the charge-disproportionated insulator CaFeO₃

envi

en: Environment

charge-disproportionation

display_name: charge-disproportionation

constrained-random-phase-approximation

display_name: constrained-random-phase-approximation

metal-insulator-transition

display_name: metal-insulator-transition

perovskite

display_name: perovskite


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

neural-network-potential

display_name: neural-network-potential

water

display_name: water

water-in-salt

display_name: water-in-salt


en:
We use a combination of symmetry analysis, phenomenological modeling, and first-principles density functional theory to explore the interplay between the magnetic ground state and the detailed atomic structure in the hexagonal rare-earth manganites. We find that the magnetic ordering is sensitive to a breathing mode distortion of the Mn and O ions in the ab plane, which is described by the K1 mode of the high-symmetry structure. Our density functional calculations of the magnetic interactions indicate that this mode particularly affects the single-ion anisotropy and the interplanar symmetric exchanges. By extracting the parameters of a magnetic model Hamiltonian from our first-principles results, we develop a phase diagram to describe the magnetic structure as a function of the anisotropy and exchange interactions. This in turn allows us to explain the dependence of the magnetic ground state on the identity of the rare-earth ion and on the K1 mode.
The attached files contain VASP input files and bash scripts for running all the DFT calculations in the manuscript.

en: Influence of the triangular Mn-O breathing mode on magnetic ordering in multiferroic hexagonal manganites

ab-initio

display_name: ab-initio

dftu

display_name: dftu

erc

display_name: erc

marvel

display_name: marvel


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

first-principles

display_name: first-principles

infrared

display_name: infrared

phonon

display_name: phonon

sesquioxides

display_name: sesquioxides


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

singlet-fission

display_name: singlet-fission


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: 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

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).

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

materialscloud

en: Materials Cloud

free-energy

display_name: free-energy

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

titanium-interfaces

display_name: titanium-interfaces


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

envi

en: Environment

manifold-optimization

display_name: manifold-optimization

marvel

display_name: marvel

snsf

display_name: snsf

wannier-functions

display_name: wannier-functions

wannier-interpolation

display_name: wannier-interpolation

wannierization

display_name: wannierization


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

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

selectivity

display_name: selectivity

single-site-doped-catalysts

display_name: single-site-doped-catalysts


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

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

ammonolysis

display_name: ammonolysis

defects

display_name: defects

oxynitride

display_name: oxynitride


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

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

erc

display_name: erc

multipoles

display_name: multipoles


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

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

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

correlated-wave-function

display_name: correlated-wave-function

gpu

display_name: gpu

hartree-fock

display_name: hartree-fock

hpc

display_name: hpc

low-scaling

display_name: low-scaling

nuclear-gradients

display_name: nuclear-gradients

rpa

display_name: rpa

sparse-tensors

display_name: sparse-tensors


en: Electrosynthesis of urea from CO2 and NOX provides an exceptional opportunity for human society, given the increasingly available renewable energy. To raise the overall electrosynthesis efficiency, the most critical reaction step for such electrosynthesis, C-N coupling, needs to be significantly improved. The C-N coupling can only happen at a narrow potential window, generally in the low overpotential region, and a fundamental understanding of the C-N coupling is needed for further development of this strategy. In this regard, we performed ab initio Molecular Dynamics (AIMD) simulations to reveal the origin of C-N coupling under a small electrode potential window with both the dynamic nature of water as a solvent, and the electrode potentials considered. We explored the key reaction networks for urea formation on Cu(100) surface in neutral electrolytes. Our work shows excellent agreement with experimentally observed selectivity under different potentials on the Cu electrode. We discovered that the *NH and *CO are the key precursors for C-N bonds formation at low overpotential, while at high overpotential the C-N coupling occurs between adsorbed *NH and solvated CO. These insights provide vital information for future spectroscopic measurements and enable us to design new electrochemical systems for more value-added chemicals.

en: Mechanism of C-N bonds formation in electrocatalytic urea production revealed by ab initio molecular dynamics simulation

aimd

display_name: aimd

electrocatalysis

display_name: electrocatalysis

nox-reduction

display_name: nox-reduction


en:
In the past few years, the theory of thermal transport in amorphous solids has been substantially extended beyond the Allen-Feldman model. The resulting formulation, based on the Green-Kubo linear response or the Wigner-transport equation, bridges this model for glasses with the traditional Boltzmann kinetic approach for crystals. The computational effort required by these methods usually scales as the cube of the number of atoms, thus severely limiting the size range of computationally affordable glass models. Leveraging hydrodynamic arguments, we show how this issue can be overcome through a simple formula to extrapolate a reliable estimate of the bulk thermal conductivity of glasses from finite models of moderate size. We showcase our findings for realistic models of paradigmatic glassy materials.
This repository contains example inputs to compute the hydrodynamic extrapolation of the thermal conductivity of glasses.
Explicit examples are for amorphous silicon. Optimized atomic configurations are provided also for amorphous silica and silicon carbide.

en: Hydrodynamic finite-size scaling of the thermal conductivity in glasses

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).

amorphous-solids

display_name: amorphous-solids

glasses

display_name: glasses

max

display_name: max

size-effects

display_name: size-effects

thermal-transport

display_name: thermal-transport