en: Machine learning potentials have become an important tool for atomistic simulations in many fields, from chemistry via molecular biology to materials science. Most of the established methods, however, rely on local properties and are thus unable to take global changes in the electronic structure into account, which result from long-range charge transfer or different charge states. In this work we overcome this limitation by introducing a fourth-generation high-dimensional neural network potential that combines a charge equilibration scheme employing environment-dependent atomic electronegativities with accurate atomic energies. The method, which is able to correctly describe global charge distributions in arbitrary systems, yields much improved energies and substantially extends the applicability of modern machine learning potentials. This is demonstrated for a series of systems representing typical scenarios in chemistry and materials science that are incorrectly described by current methods, while the fourth-generation neural network potential is in excellent agreement with electronic structure calculations.

en: A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer

dft

display_name: dft

machine-learning-potentials

display_name: machine-learning-potentials

non-local-charge-transfer

display_name: non-local-charge-transfer

snsf

display_name: snsf


$oid: OBSOLETE

en: There is much current work on metallic glasses (MGs). The field is making rapid advances and has opened up questions of fundamental scientific interest. Metallic glasses are known to suffer from poor formability. Among other methods of improving the mechanical properties of MGs, introducing deformable crystalline phases into MGs is beneficial for enhancing the plastic compliance of MGs. The definition of the principal phase transformations (on heating and on cooling) underlying the feasibility of such a method is the focus of the deposited in situ high-energy XRD data carried out at Deutsches Elektronen-Synchrotron DESY, Hamburg, Germany. This archive entry contains the temporal evolution of the equilibrium and metastable phases on flash-annealing (heating and cooling) and during containerless solidification via electromagnetic levitation with an unprecedented timescale of ~4 ms.

en: In situ high-energy X-ray diffraction of a CuZr-based metallic glass

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

containerless-solidification

display_name: containerless-solidification

electromagnetic-levitation

display_name: electromagnetic-levitation

metallic-glasses

display_name: metallic-glasses

phase-transformation-mechanisms

display_name: phase-transformation-mechanisms

synchrotron-xrd

display_name: synchrotron-xrd


en:
The EPW (Electron-Phonon coupling using Wannier functions) software is a Fortran90 code that uses density-functional perturbation theory and maximally localized Wannier functions for computing
electron-phonon couplings and related properties in solids accurately and efficiently. The EPW v4 program can be used to compute electron and phonon self-energies, linewidths, electron-phonon scattering
rates, electron-phonon coupling strengths, transport spectral functions, electronic velocities, resistivity, anisotropic superconducting gaps and spectral functions within the Migdal-Eliashberg theory. The
code now supports spin-orbit coupling, time-reversal symmetry in non-centrosymmetric crystals, polar materials, and k and q-point parallelization. Considerable effort was dedicated to optimization and
parallelization, achieving almost a ten times speedup with respect to previous releases. A computer test farm was implemented to ensure stability and portability of the code on the most popular compilers
and architectures. Since April 2016, version 4 of the EPW code is fully integrated in and distributed with the Quantum ESPRESSO package, and can be downloaded through at https://gitlab.com/QEF/q-e

en: EPW: Electron-phonon coupling, transport and superconducting properties using maximally localized Wannier functions

electron-phonon-coupling

display_name: electron-phonon-coupling

electronic-transport

display_name: electronic-transport

prace

display_name: prace

superconductivity

display_name: superconductivity

wannier-functions

display_name: wannier-functions


en: We present a scheme to extract the adsorption energy, adsorbate interaction parameter and the saturation coverage from temperature programmed desorption (TPD) experiments. We propose that the coverage dependent adsorption energy can be fit using a functional form including the configurational entropy and linear adsorbate-adsorbate interaction terms. As one example of this scheme, we analyze TPD of CO desorption on Au(211) and Au(310) surfaces. We determine that under atmospheric CO pressure, the steps of both facets adsorb between 0.4-0.9 ML coverage of CO*. We compare this result against energies obtained from five density functionals, RPBE, PBE, PBE-D3, RPBE-D3 and BEEF-vdW. We find that the energies and equilibrium coverages from RPBE-D3 and PBE are closest to the values determined from the TPD. This dataset contains all the DFT calculations run using AiiDA.

en: How to extract adsorption energies, adsorbate-adsorbate interaction parameters, and saturation coverages from temperature programmed desorption experiments

benchmark

display_name: benchmark

catalysis

display_name: catalysis


en: Blending organic molecules to tune their energy levels is currently investigated as an approach to engineer the bulk and interfacial optoelectronic properties of organic semiconductors. It has been proven that the ionization energy (IE) and electron affinity (EA) can be equally shifted in the same direction by electrostatic effects controlled by blending similar halogenated derivatives with different energetics. Here, we show that the energy gap of organic semiconductors can be tuned by blending as well. We use oligothiophenes with different numbers of thiophene rings as example and investigate their structure and electronic properties. Photoelectron spectroscopy and inverse photoelectron spectroscopy show tunability of the single-particle gap, with the optical gaps showing similar, but smaller effects. Theoretical analysis shows that this tuning is mainly caused by a change in the dielectric constant with blend ratio. Further studies will explore the practical impact of this energy-level engineering strategy in optoelectronic devices.

en: Band gap engineering in blended organic semiconductor films based on dielectric interactions

dielectric-interactions

display_name: dielectric-interactions

energy-level-tuning

display_name: energy-level-tuning

photoelectron-spectroscopy

display_name: photoelectron-spectroscopy

theoretical-simulations

display_name: theoretical-simulations


en: Variations of volume plasmon energy of both ribbon and bulk FeMo14C15B6Erx (x=0-2) metallic glasses were measured as a function of the temperature in an analytical transmission electron microscope using valence electron energy loss spectroscopy (VEELS). The plasmon energy was found to decrease with increasing temperature, due not only to thermal expansion but also to chemical reordering in the glasses. The chemical reordering stimulates a specific solute cluster formation; M23(C, B)6 solute clusters began to form above about 200°C in both ribbon and bulk FeMo14C15B6Erx (x=0, 0.5, 1) metallic glasses. The formation of the M23(C, B)6 solute clusters was only found above 400°C in the ribbon FeMo14C15B6Er2 metallic glass, indicating inhibition of the M23(C, B)6 solute clusters occurred owing to the formation of Er-(C, B) complexes/clusters. The Er-(C, B) complexes/clusters were formed in the cooling process of the sample fabrication. In contrast to the ribbon sample, the formation of the M23(C, B)6 solute clusters did not occur in the bulk FeMo14C15B6Er2 metallic glass during heating. The amount of the Er-(C, B) complexes/clusters in the bulk sample was larger than that in the ribbon sample because of the slow cooling rate in the bulk sample fabrication. Because the solute carbon and boron atoms were mostly consumed by the formation of Er-(C, B) complexes/clusters in the bulk FeMo14C15B6Er2 metallic glass, the formation of M23(C, B)6 solute clusters was suppressed. This study demonstrates that chemical reordering during the relaxation of metallic glasses can be detected by the VEELS, providing valuable insight into the relaxation stage of metallic glass during heating.

en: Plasmon energy changes in FeMo14C15B6Erx (x=0-2) bulk metallic glass during in-situ heating

bulk-metallic-glass

display_name: bulk-metallic-glass

chemical-reordering

display_name: chemical-reordering

electron-energy-loss-spectroscopy

display_name: electron-energy-loss-spectroscopy

experimental

display_name: experimental

in-situ-heating

display_name: in-situ-heating

volume-plasmon

display_name: volume-plasmon


en: The solar water splitting process assisted by semiconductor photocatalysts attracts growing research interests worldwide for the production of hydrogen as a clean and sustainable energy carrier. Due to their optical and electrical properties several oxynitride materials show great promise for the fabrication of efficient photocatalysts for solar water splitting. This study reports a comparative investigation of particle- and thin films-based photocatalysts using three different oxynitride materials. The absolute comparison of the photoelectrochemical activities favors the particle-based electrodes due to the better absorption properties and larger electrochemical surface area. However, thin films surpass the particle-based photoelectrodes due to their more suitable morphological features that improve the separation and mobility of the photo-generated charge carriers. Our analysis identifies what specific insights into the properties of materials can be achieved with the two complementary approaches.

en: Oxynitride thin films versus particle-based photoanodes: a comparative study for photoelectrochemical solar water splitting

marvel

display_name: marvel

oxynitride-photoanode

display_name: oxynitride-photoanode

pulsed-laser-deposition

display_name: pulsed-laser-deposition

solar-fuel

display_name: solar-fuel

solar-water-splitting

display_name: solar-water-splitting


en:
Selector devices are indispensable components of large-scale nonvolatile memory and neuromorphic array systems. Besides the conventional silicon transistor, two-terminal ovonic threshold switching (OTS) devices with much higher scalability are currently the most industrially favored selector technology. Despite industrial confidence in OTS selectors, current devices rely heavily on intricate control of material stoichiometry and generally suffer from toxic and complex dopants to remedy the intrinsic demerits of the principal functioning materials. Here, we report on a selector with a large drive current density of 34 MA/cm2 and a ~106 high nonlinearity, realized in an environment-friendly and earth-abundant sulfide binary semiconductor, GeS. Both experiments and first-principles calculations have revealed Ge pyramid-dominated network and high density of near-valence band trap states in amorphous GeS. The high drive current capacity is associated with the strong Ge-S covalency and the high nonlinearity could arise from the synergy of the mid-gap traps assisted electronic transition and local Ge-Ge chain growth as well as locally enhanced bond alignment under high electric field. Besides the superior selector function, we have also demonstrated stochastic integrate-and-fire neuron behavior using GeS device, providing an intriguing opportunity for all-chalcogenide neuromorphic electronics.
The source data underlying Figs. 1c-e, Figs. 2a–e, and Figs. 3b, d, f are provided as a Source Data file.

en: Ultrahigh drive current and large selectivity in GeS selector

ges

display_name: ges

ots

display_name: ots

phase-change-memory

display_name: phase-change-memory

selector

display_name: selector


en: An advanced modeling approach is presented to shed light on the thermal transport properties of van der Waals materials (vdWMs) composed of single-layer transition metal dichalcogenides (TMDs) stacked on top of each other with a total or partial overlap only in the middle region. It relies on the calculation of dynamical matrices from first principles and on their usage in a phonon quantum transport simulator. We observe that vibrations are transferred microscopically from one layer to the other along the overlap region which acts as a filter selecting out the states that can pass through it. Our work emphasizes the possibility of engineering heat flows at the nanoscale by carefully selecting the TMD monolayers that compose vdWMs.

en: Ab initio modeling of thermal transport through van der Waals materials

cscs

display_name: cscs

snsf

display_name: snsf

thermal-properties

display_name: thermal-properties

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides

van-der-waals-materials

display_name: van-der-waals-materials


en:
The record contains the data supporting our recent findings on asymmetric azide-alkyne Huisgen cycloaddition on chiral metal surfaces:
Achieving fundamental understanding of enantioselective heterogeneous synthesis is marred by the permanent presence of multitudinous arrangements of catalytically active sites in real catalysts. We address this issue by using structurally comparatively simple, well‐defined, and chiral intermetallic PdGa{111} surfaces as catalytic substrates. We demonstrate the impact of chirality transfer and ensemble effect for the thermally activated azide‐alkyne Huisgen cycloaddition between 3‐(4‐azidophenyl)propionic acid and 9‐ethynylphenanthrene on these threefold symmetric intermetallic surfaces under ultrahigh vacuum conditions. Specifically, we encounter a dominating ensemble effect for this reaction as on the Pd3‐terminated PdGa{111} surfaces no stable heterocoupled structures are created, while on the Pd1‐terminated PdGa{111} surfaces, the cycloaddition proceeds regioselectively. Moreover, we observe chirality transfer from the substrate to the reaction products, as they are formed enantioselectively on the Pd1‐terminated PdGa{111} surfaces. Our results evidence a determinant ensemble effect and the immense potential of PdGa as asymmetric heterogeneous catalyst.

en: Asymmetric azide‐alkyne Huisgen cycloaddition on chiral metal surfaces

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).

ab-initio-simulations

display_name: ab-initio-simulations

asymmetric-heterogeneous-catalysis

display_name: asymmetric-heterogeneous-catalysis

azidealkyne-huisgen-cycloaddition

display_name: azidealkyne-huisgen-cycloaddition

experimental

display_name: experimental

onsurface-synthesis

display_name: onsurface-synthesis


en: Koopmans-compliant functionals provide an orbital-density-dependent framework for an accurate evaluation of spectral properties; they are obtained by imposing a generalized piecewise-linearity condition on the total energy of the system with respect to the occupation of any orbital. In crystalline materials, due to the orbital-density-dependent nature of the functionals, minimization of the total energy to a ground state provides a set of minimizing variational orbitals that are localized and thus break the periodicity of the underlying lattice. Despite this, we show that Bloch symmetry can be preserved and it is possible to describe the electronic states with a band-structure picture, thanks to the Wannier-like character of the variational orbitals. We also present a method to unfold and interpolate the electronic bands from supercell (Γ-point) calculations, which enables us to calculate full band structures with Koopmans-compliant functionals. The results obtained for a set of benchmark semiconductors and insulators show very good agreement with state-of-the-art many-body perturbation theory and experiments, underscoring the reliability of these spectral functionals in predicting band structures.

en: Bloch's theorem in orbital-density-dependent functionals: Band structures from Koopmans spectral functionals

materialscloud

en: Materials Cloud

envi

en: Environment

dft

display_name: dft

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

koopmans-functionals

display_name: koopmans-functionals

marvelosp

display_name: marvelosp

orbital-density-dependent

display_name: orbital-density-dependent

photoemission-spectra

display_name: photoemission-spectra


en: This record contains the results of the first experimental investigation of the change in the electron dynamics across the topological phase transition from the type-II Weyl semimetal phase of MoTe2 to the trivial phase. By using the capability of time-resolved ARPES to access the unoccupied density of states, we succeed in transiently populating the Weyl points, which are otherwise above the Fermi level and out of the reach of conventional ARPES. We observe a bottleneck in the electron dynamics when the Weyl points annihilate and gaps are opened in the high-temperature trivial phase. This interpretation is supported by the observation that, in the "sister" compound WTe2 the dynamics is not affected by the change in temperature, and it is always much slower, thus reflecting the larger energy separation between the valence and conduction band.

en: Enhanced ultrafast relaxation rate in the Weyl semimetal phase of MoTe2 measured by time- and angle-resolved photoelectron spectroscopy

electron-dynamics

display_name: electron-dynamics

erc

display_name: erc

marvel

display_name: marvel

topological-phase-transition

display_name: topological-phase-transition

type-ii-weyl-semimetal

display_name: type-ii-weyl-semimetal


en: This repository contains the scripts that were used to run the calculations that present a new biasing technique, the Adaptive Topography of Landscape for Accelerated Sampling (ATLAS). The techinque is implemented in plumed-2.0 and the input file are included in the repository, as well as a few scripts to postprocess the calculations and reproduce the plots presented in the paper

en: Global free-energy landscapes as a smoothly joined collection of local maps

enhanced-sampling

display_name: enhanced-sampling

epfl

display_name: epfl

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics

snsf

display_name: snsf


en: Organic photodetectors have promising applications in low-cost imaging, health monitoring and near infrared sensing. Recent research on organic photodetectors based on donor-acceptor systems has resulted in narrow-band, flexible and biocompatible devices, of which the best reach external photovoltaic quantum efficiencies approaching 100%. However, the high noise spectral density of these devices limits their specific detectivity to around 10^13 Jones in the visible and several orders of magnitude lower in the near-infrared, severely reducing performance. Here, we show that the shot noise, proportional to the dark current, dominates the noise spectral density, demanding a comprehensive understanding of the dark current. We demonstrate that, in addition to the intrinsic saturation current generated via charge-transfer states, dark current contains a major contribution from trap-assisted generated charges and decreases systematically with decreasing concentration of traps. By modeling the dark current of several donor-acceptor systems, we reveal the interplay between traps and charge-transfer states as source of dark current and show that traps dominate the generation processes, thus being the main limiting factor of organic photodetectors detectivity.

en: Reverse dark current in organic photodetectors and the major role of traps as source of noise

dark-current

display_name: dark-current

detectivity

display_name: detectivity

organic-photodetectors

display_name: organic-photodetectors

traps

display_name: traps


en: The formation of large polarons has been proposed as reason for the high defect tolerance, low mobility, low charge carrier trapping and low nonradiative recombination rates of lead halide perovskites. Recently, direct evidence for large-polaron formation has been reported from a 50% effective mass enhancement in angle-resolved photoemission of CsPbBr₃ over theory for the orthorhombic structure. We present in-depth band dispersion measurements of CsPbBr₃ and GW calculations which lead to almost identical effective masses at the valence band maximum of 0.203+/-0.016 m₀ in experiment and 0.217 m₀ in orthorhombic theory. We argue that the effective mass can be explained solely on the basis of electron-electron correlation and large polaron formation cannot be concluded from photoemission data.

en: Is there a polaron signature in angle-resolved photoemission of CsPbBr₃?

large-polaron

display_name: large-polaron


en: We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive supercells of the traditional linear-response approach; instead, unit cells are used with monochromatic perturbations that significantly reduce the computational cost of determining Hubbard parameters. HP is an open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, HP is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing Hubbard parameters self-consistently for the phospho-olivine LixMn0.5Fe0.5PO4 (x=0, 0.5, 1) and by highlighting the accuracy of predictions of the geometry and Li intercalation voltages.

en: HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

cscs

display_name: cscs

density-functional-perturbation-theory

display_name: density-functional-perturbation-theory

hubbard-parameters

display_name: hubbard-parameters

linear-response-theory

display_name: linear-response-theory

marvelosp

display_name: marvelosp

open-science

display_name: open-science

open-source-software

display_name: open-source-software

quantum-espresso

display_name: quantum-espresso

self-interaction-corrections

display_name: self-interaction-corrections

transition-metal-compounds

display_name: transition-metal-compounds


en: Sustainability combined with high energy density prospects makes Fe-based oxides attractive as cathodes for calcium rechargeable batteries. This work presents a DFT evaluation of the CaFe2+nO4+n (0 < n < 3) family, for which both the average intercalation voltage and the theoretical specific capacity decrease with the increasing n value. The term n = 1/4, Ca4Fe9O17, meets the most appealing characteristics: a calculated average voltage of 4.16 V, a theoretical specific capacity of 230 mA h g−1 and the lowest energy barrier for Ca migration so far predicted for an existing oxide (0.72 eV). To overcome the previously reported synthesis difficulties, we employed a novel synthesis procedure in sealed quartz tubes followed by quenching in water. The XRD and SAED patterns of the prepared Ca4Fe9O17 powder reveal a certain degree of stacking defects along the c axis. Attempts to deinsert Ca ions from Ca4Fe9O17 by chemical means (NO2BF4 in ACN) and in electrochemical Ca cells were unsuccessful, although some hints of oxidation are observed in Li cells with the LP30 electrolyte. The suitability of Ca4Fe9O17 as a Ca cathode is pending further studies utilizing Ca-electrolytes with high anodic stability.

en: Appraisal of calcium ferrites as cathodes for calcium rechargeable batteries: DFT, synthesis, characterization and electrochemistry of Ca4Fe9O17

batteries

display_name: batteries

calcium

display_name: calcium

cathode-material

display_name: cathode-material

ferrites

display_name: ferrites


en: A current goal driving alloy development is the identification of alloy compositions for high temperature applications but with the additional requirement of sufficient ductility at ambient temperatures. Multicomponent, single-phase, polycrystalline High Entropy Alloys (HEAs) have recently emerged as a new class of metal alloys, and some refractory bcc HEAs composed mainly of Nb, V, Ta, Cr, Mo, and/or W show excellent strength retention up to very high temperatures but low ductility at room temperature (RT). Here, it is postulated that the macroscopic ductility in bcc elements and alloys is determined by the intrinsic competition between brittle cleavage and ductile dislocation emission mechanisms at an atomistically sharp crack. The stress intensities K_Ic for cleavage and K_Ie for emission are evaluated within Linear Elastic Fracture Mechanics and validated by atomistic simulations on model alloys. A RT ductility criterion based on K_Ie/K_Ic for critical crack orientations is proposed based on the elemental metals and is then applied to HEAs. Agreement with experimental trends in ductility vs. composition across a range of existing HEAs is demonstrated. The analysis is then extended across large composition spaces of the Mo-Nb-Ta-V-W and Mo-Nb-Ti alloy families, identifying new compositions with the potential for RT ductility.

en: A ductility criterion for bcc high entropy alloys

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).

bcc

display_name: bcc

fracture

display_name: fracture

high-entropy-alloys

display_name: high-entropy-alloys

intrinsic-ductility

display_name: intrinsic-ductility

snsf

display_name: snsf


en: Mg-Al mixed metal oxides (MMOs), derived from the decomposition of layered double hydroxides (LDHs), have been purposed as a material for CO2 capture of industrial plant emissions. In order to aid in the design and optimization of these materials for CO2 capture at 200 °C, we have used the combination of solid-state nuclear magnetic resonance (ssNMR) and density functional theory (DFT) to characterize the CO2 gas sorption products and determine the various sorption sites in the Mg-Al MMOs. Comparison of DFT cluster calculations with 13C chemical shift of the chemisorbed products indicates that mono and bi-dentate carbonate are formed at the Mg-O site with an adjacent Al substitution of an Mg atom, while bicarbonate is formed at Mg-OH sites without adjacent Al substitution. Quantitative 13C NMR shows an increase in the relative amount of strongly basic sites, where the monodentate carbonate product is formed, with increasing Al mole % in the MMO. This detailed understanding of the various basic Mg-O sites presents in the MMO material, and the formation of the carbonate, bidentate carbonate and bicarbonate chemisorbed species yields new insight into the mechanism of CO2 adsorption at 200 °C which can further aid in the design and capture capacity optimization of the materials.

en: Characterization of chemisorbed species and active adsorption sites in Mg-Al mixed metal oxides for high temperature CO2 capture

materialscloud

en: Materials Cloud

carbon-capture

display_name: carbon-capture

dft

display_name: dft

epfl

display_name: epfl

marvel

display_name: marvel

nmr

display_name: nmr


en:
The resolving power of solid-state nuclear magnetic resonance (NMR) crystallography depends heavily on the accuracy of the computational prediction of NMR chemical shieldings of candidate structures, which are usually taken to be local minima in the potential energy surface.
To test the limits of this approximation, we perform a systematic study of the role of finite-temperature and quantum nuclear fluctuations on 1H, 13C, and 15N chemical shieldings in molecular crystals -- considering the paradigmatic examples of the different polymorphs of benzene, glycine, and succinic acid.
We find the effect of quantum fluctuations to be comparable in size to the typical errors of predictions of chemical shieldings for static nuclei with respect to experimental measurements, and to improve the match between experiments and theoretical predictions, translating to more reliable assignment of the NMR spectra to the correct candidate structure.
Thanks to the use of integrated machine-learning models trained on both first-principles configurational energies and chemical shieldings, the accurate sampling of thermal and quantum fluctuations of the structures can be achieved at an affordable cost, setting a new standard for the calculations that underlie solid-state structural determination by NMR.

This archive contains the machine-learning potentials and shielding models, sample inputs, and scripts to reproduce the results discussed in the manuscript. It further contains the reference data and scripts to reconstruct the shielding models.

en: The importance of nuclear quantum effects for NMR crystallography

envi

en: Environment

first-principles-gipaw-dft

display_name: first-principles-gipaw-dft

machine-learning

display_name: machine-learning

molecular-crystals

display_name: molecular-crystals

nmr-chemical-shielding

display_name: nmr-chemical-shielding

nuclear-quantum-effects

display_name: nuclear-quantum-effects


en: Skutterudites are crystals with a cagelike structure that can be augmented with filler atoms ("rattlers"), usually leading to a reduction in thermal conductivity that can be exploited for thermoelectric applications. Here, we leverage the recently introduced Wigner formulation of thermal transport to elucidate the microscopic physics underlying heat conduction in skutterudites, showing that filler atoms can drive a crossover from the Boltzmann to the Wigner regimes of thermal transport, i.e., from particlelike conduction to wavelike tunneling. At temperatures where the thermoelectric efficiency of skutterudites is largest, wavelike tunneling can become comparable to particlelike propagation. We define a Boltzmann deviation descriptor able to differentiate the two regimes and relate the competition between the two mechanisms to the materials' chemistry, providing a design strategy to select rattlers and identify optimal compositions for thermoelectric applications.

en: Crossover from Boltzmann to Wigner thermal transport in thermoelectric skutterudites

phonons

display_name: phonons

thermal-conductivity

display_name: thermal-conductivity

thermoelectrics

display_name: thermoelectrics


en: On-surface synthesis is a rapidly developing field involving chemical reactions on well-defined solid surfaces to access the synthesis of low-dimensional organic nanostructures which cannot be achieved via traditional solution chemistry. On-surface reactions critically depend on a high degree of chemoselectivity in order to achieve an optimum balance between the target structure and possible side products. In this record we provide data for the calculations that support a work that we recently published. In the published manuscript, we demonstrate the synthesis of graphene nanoribbons with a large unit cell based on steric hindrance-induced complete chemoselectivity as revealed by scanning probe microscopy measurements and density functional theory calculations. Our results disclose that combined molecule-substrate van der Waals interactions and intermolecular steric hindrance promote a selective aryl-aryl coupling, giving rise to high-quality uniform graphene nanostructures. The established coupling strategy has been used to synthesize two types of graphene nanoribbons with different edge topologies inducing a pronounced variation of the electronic energy gaps. The demonstrated chemoselectivity is representative of n-anthryl precursor molecules and may be further exploited to synthesize graphene nanoribbons with novel electronic, topological and magnetic properties with implications for electronic and spintronic applications.

en: Steering on-surface reactions through molecular steric hindrance and molecule-substrate van der Waals interactions

aiidalab

display_name: aiidalab

graphene-nanoribbons

display_name: graphene-nanoribbons

on-surface-synthesis

display_name: on-surface-synthesis

scanning-probe-microscopy

display_name: scanning-probe-microscopy


en:
The potential profile and the energy level offset of core/shell heterostructured nanocrystals (h-NCs) determine the photophysical properties and the charge transport characteristics of h-NC solids. However, limited material choices for heavy metal-free III-V/II-VI h-NCs pose challenges in comprehensive control of the potential profile. Herein, we present an approach to such control by steering dipole densities at the interface of III-V/II-VI h-NCs. The controllable heterovalency at the interface is responsible for interfacial dipole densities that result in the vacuum-level shift, providing an additional knob for the control of optical and electrical characteristics of h-NCs. The synthesis of h-NCs with atomic precision allows us to correlate interfacial dipole moments with the nanocrystals' photochemical stability and optoelectronic performance.

The description was referred to the abstract of the original paper. All numerical data of the main figures in the articles are included in this data repository.
In particular, each tab of the data file indicates each panel in the main figures.
Please refer to the main research article.

en: Interface polarization in heterovalent core/shell nanocrystals

experimental

display_name: experimental

heterostructured-nanocrystal

display_name: heterostructured-nanocrystal

interface-polarization

display_name: interface-polarization


en: Magnetic topological insulators (TIs) promise a wealth of applications in spin-based technologies, relying on the novel quantum phenomena provided by their topological properties. Particularly promising is the (MnBi₂Te₄)(Bi₂Te₃)n layered family of established intrinsic magnetic TIs that can flexibly realize various magnetic orders and topological states. High tunability of this material platform is enabled by manganese–pnictogen intermixing, whose amounts and distribution patterns are controlled by synthetic conditions. Positive implication of the strong intermixing in MnSb₂Te₄ is the interlayer exchange coupling switching from antiferromagnetic to ferromagnetic, and the increasing magnetic critical temperature. On the other side, intermixing also implies atomic disorder which may be detrimental for applications. Here we employ nuclear magnetic resonance and muon spin spectroscopy, sensitive local probe techniques, to scrutinize the impact of the intermixing on the magnetic properties of (MnBi₂Te₄)(Bi₂Te₃)n and MnSb₂Te₄. Our measurements not only confirm the opposite alignment between the Mn magnetic moments on native sites and antisites in the ground state of MnSb₂Te₄, but for the first time directly show the same alignment in (MnBi₂Te₄)(Bi₂Te₃)n with n = 0, 1 and 2. Moreover, for all compounds, we find the static magnetic moment of the Mn antisite sublattice to disappear well below the intrinsic magnetic temperature, leaving a homogeneous magnetic structure undisturbed by the intermixing. Our findings provide microscopic understanding of the crucial role played by Mn–Bi intermixing in (MnBi₂Te₄)(Bi₂Te₃)n and offer pathways to optimizing the magnetic gap in its surface states. The data contained in this archive consists of both the µSR and NMR experimental data including DFT calculations for the muon and hyperfine coupling interactions, all required to reproduce the results and figures presented in this article.

en: Different ordering temperature of the Mn antisite sublattice in the intrinsic magnetic topological insulators of the MnBi₂Te₄ family

cationic-intermixing

display_name: cationic-intermixing

magnetic-topological-insulator

display_name: magnetic-topological-insulator


en:
**Data for Properties of α-Brass Nanoparticles. 1. Neural Network Potential Energy Surface**
Jan Weinreich, Anton Römer, Martín Leandro Paleico, and Jörg Behler

53 841 reference structures of alpha brass (less 40 % Zn) with following split
 - 4009 brass clusters
 - 8492 molten brass bulk structures
 - 8964 copper slabs, and 16 878 brass slabs
 - 5377 copper bulk structures
 - 10 121 brass bulk structures have been included.

53 841 total energies and 8 903 340 force components. The ranges of values for the energies and force components to be fitted have a width of about 2 eV/atom and 15 eV/Å, respectively. However, some structures may have slightly higher Zn content as discussed in Fig 3 (https://arxiv.org/abs/2001.10906)

The archive contains an easily usable npz file as well as the original input.data file used to fit the potential energy surface. Additionally a Jupyter notebook describes in great detail how the data was converted to the npz format and how to read the data e.g. for subsequent use with python. In addition an example VASP calculation was added to provide detailed information about how the reference data was calculated with DFT.

DETAILS:
- DFT PB VASP-5.3 target accuracy of the total energy few meV/atom
- Convergence tests with respect to the number of k-points showed that in order to fulfill this criterion a k-point grid of 12 × 12 × 12 is needed for a conventional four-atom copper fcc unit cell with a lattice constant of about 3.63 Å along with a plane wave cutoff energy of 500 eV and projector augmented wave potentials.(61,63)
- Larger systems have been calculated using an adapted k-point grid corresponding to the same k-point density. The Γ-point centered k-point grids have been constructed employing the Monkhorst–Pack scheme. For surface calculations, 4–14 layer slabs with a total vacuum thickness of at least 8 Å have been used.
- In the case of cluster calculations, which have also been treated in a periodic setup, the periodic images of the clusters have been separated by at least 8 Å in all three spatial directions. The convergence of very large clusters with diameters of d ≈ 22 Å, which have been used to include specific atomic environments in the data set, has been extensively tested and we found that using the Γ-point only is sufficient to reach the required convergence level.

en: Properties of α-brass nanoparticles. 1. Neural network potential energy surface

alloys

display_name: alloys

brass

display_name: brass

database

display_name: database

dft

display_name: dft

neural-networks

display_name: neural-networks

potential-energy-surfaces

display_name: potential-energy-surfaces


en: Through the use of the piecewise-linearity condition of the total energy, we correct the self-interaction for the study of polarons by constructing nonempirical functionals at the semilocal level of theory. We consider two functionals, the γDFT and the μDFT functionals, both of which are based on the addition of a weak local  potential to the semilocal Hamiltonian to enforce the piecewise-linearity condition. We show that the resulting polaron properties are in good agreement with reference hybrid functional calculations. This supports the use of semilocal functionals for calculating polaron properties.

en: Nonempirical semilocal density functionals for correcting the self-interaction of polaronic states

materialscloud

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

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

density-functional-theory

display_name: density-functional-theory

piecewise-linearity

display_name: piecewise-linearity

polarons

display_name: polarons

self-interaction

display_name: self-interaction


en: Charge-transfer-to-solvent states in aqueous halides are ideal systems for studying the electron-transfer dynamics to the solvent involving a complex interplay between electronic excitation and solvent polarization. Despite extensive experimental investigations, a full picture of the charge-transfer-to-solvent dynamics has remained elusive. Here, we visualise the intricate interplay between the dynamics of the electron and the solvent polarization occurring in this process. Through the combined use of ab initio molecular dynamics and machine learning methods, we investigate the structure, dynamics and free energy as the excited electron evolves through the charge-transfer-to-solvent process, which we characterize as a sequence of states denoted charge-transfer-to-solvent, contact-pair, solvent-separated, and hydrated electron states, depending on the distance between the iodine and the excited electron. Our assignment of the charge-transfer-to-solvent states is supported by the good agreement between calculated and measured vertical binding energies. Our results reveal the charge transfer process in terms of the underlying atomic processes and mechanisms.

en: Dynamics of the charge transfer to solvent process in aqueous iodide

materialscloud

en: Materials Cloud

ab-initio

display_name: ab-initio

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en: Using vertex-corrected quasiparticle self-consistent GW schemes, we address the electronic structure of two manganese dioxide polymorphs, α-MnO₂ and β-MnO₂. In particular, we determine the fundamental band gaps, the macroscopic dielectric constants, the magnetic moments of the Mn atoms, the band structures and the associated densities of states. Additionally, we obtain the imaginary component of the dielectric function ε₂(𝜔) from the solution of the  Bethe–Salpeter equation. For β-MnO₂, we record overall good agreement when comparing the density of states with XPS/BIS spectra and the dielectric function ε₂(𝜔) with optical response spectra. Applied to α-MnO₂, whose pristine bulk structure is poorly characterized, our work provides a prediction at the same level of theory. The quality of the achieved description is further supported by comparisons with experimental spectra of nanostructured and doped variants. This study demonstrates that state-of the-art GW methods successfully account for key electronic-structure features of MnO₂ polymorphs.

en: Electronic structure of α-MnO₂ and β-MnO₂ through GW with vertex corrections

envi

en: Environment

electronic-structure

display_name: electronic-structure

gw

display_name: gw

manganese-oxide

display_name: manganese-oxide

many-body-perturbation-theory

display_name: many-body-perturbation-theory

vertex-corrections

display_name: vertex-corrections


en: Alloys based on lanthanum phosphate (LaPO₄) are often employed as thermal barrier coatings, due to their low thermal conductivity and structural stability over a wide temperature range. To enhance the thermal-insulation performance of these alloys, it is essential to comprehensively understand the fundamental physics governing their heat conduction. Here, we employ the Wigner formulation of thermal transport in conjunction with first-principles calculations to elucidate how the interplay between anharmonicity and compositional disorder determines the thermal properties of La1-xGdxPO₄ alloys, and discuss the fundamental physics underlying the emergence and coexistence of particle-like and wave-like heat-transport mechanisms. Our predictions for microscopic vibrational properties (temperature-dependent Raman spectrum) and for macroscopic thermal conductivity are validated against experiments. Finally, we leverage these findings to devise strategies to optimize the performance of thermal barrier coatings.

en: First-principles characterization of thermal conductivity in LaPO₄-based alloys

alloys

display_name: alloys

anharmonicity-and-disorder

display_name: anharmonicity-and-disorder

first-principles

display_name: first-principles

thermal-barrier-coating

display_name: thermal-barrier-coating

thermal-transport

display_name: thermal-transport


en: Twinning in fcc High Entropy Alloys (HEAs) has been implicated as a possible mechanism for hardening that enables enhanced ductility. Here, a theory for the twinning stress is developed analogous to recent theories for yield stress. Specifically, the stress to move a twin dislocation, i.e an fcc partial dislocation moving along a pre-existing twin boundary, through a random multicomponent alloy is determined. A reduced elasticity theory is then introduced in which atoms interact with the twin dislocation pressure field and the twin boundary. The theory is applied to NiCoCr using results from both interatomic potentials and elasticity theory. Results are also used to predict the increased stress for the motion of (i) a single partial dislocation leaving a trailing stacking fault and (ii) adjacent partial dislocations involved in twin nucleation. Increased strength is predicted for all processes involved in the nucleation and growth of fcc twins. Comparison to single-crystal experiments at room temperature then suggests that twinning is controlled by twin nucleation, with reasonable quantitative agreement. When solute/fault interactions are neglected, the theory shows that twinning and lattice flow stresses are related. The theory also provides insight into how other dilute solute additions could suppress twinning, as found experimentally.

en: Theory of twin strengthening in fcc high entropy alloys

random-alloys

display_name: random-alloys

snsf

display_name: snsf

solute-strengthening

display_name: solute-strengthening

twinning

display_name: twinning


en: The recently discovered layered kagome metals AV₃Sb₅ (A=K, Rb, Cs) exhibit diverse correlated phenomena, which are intertwined with a topological electronic structure with multiple van Hove singularities (VHSs) in the vicinity of the Fermi level. As the VHSs with their large density of states enhance correlation effects, it is of crucial importance to determine their nature and properties. Here, we combine polarization-dependent angle- resolved photoemission spectroscopy with density functional theory to directly reveal the sublattice properties of 3d-orbital VHSs in CsV₃Sb₅. Four VHSs are identified around the M point and three of them are close to the Fermi level, with two having sublattice-pure and one sublattice-mixed nature. Remarkably, the VHS just below the Fermi level displays an extre- mely flat dispersion along MK, establishing the experimental discovery of higher-order VHS. The characteristic intensity modulation of Dirac cones around K further demonstrates the sublattice interference embedded in the kagome Fermiology. The crucial insights into the electronic structure, revealed by our work, provide a solid starting point for the understanding of the intriguing correlation phenomena in the kagome metals AV₃Sb₅.

en: Rich nature of Van Hove singularities in Kagome superconductor CsV₃Sb₅

arpes-dft

display_name: arpes-dft

nccr-marvel

display_name: nccr-marvel

vhss

display_name: vhss


en: Body-centered-cubic (BCC) high entropy alloys (HEAs) can show exceptionally high strength up to high temperatures. Mechanistic theories are needed to guide alloy discovery within the immense multicomponent HEA compositional space. Here, two new theories for strengthening as controlled by screw and edge dislocations, respectively, are applied to predict the yield stresses of a range of BCC alloys over a wide range of temperatures. Results show that the screw theory, with one fitting parameter, can capture experiments in many dilute and non-dilute alloys while the parameter-free edge theory agrees with experiments in non-dilute alloys having a sufficiently large misfit parameter. These results indicate a transition in single-phase alloy strengthening from traditional screw dominance to edge dominance with increasing misfit that is enabled in complex non-dilute alloys. These results point to the use of the edge theory to guide design of high-temperature alloys in the non-dilute range.

en: Screw vs. edge dislocation strengthening in body-centered-cubic high entropy alloys and implications for guided alloy design

alloy-discovery

display_name: alloy-discovery

bcc

display_name: bcc

high-entropy-alloys

display_name: high-entropy-alloys


en: Recent theory proposes that edge dislocations in random body-centered cubic (BCC) high entropy alloys have high barriers for motion, conveying high strengths up to high temperatures. Here, the energy barriers for edge motion are computed for two model alloys, NbTaV and MoNbTaW as represented by interatomic potentials, using the Nudged Elastic Band method and compared to theoretical predictions. The average magnitude of the barriers and the average spacing of the barriers along the glide direction agree well with the analytical theory, with no adjustable parameters. The evolution of the barriers versus applied stress is modeled, and the mean strength is in reasonable agreement with the predicted zero-temperature strength. These findings validate the analytic theory. A reduced analytic model based on solute misfit volumes is then applied to Hf-Mo-Nb-Ta-Ti-Zr and Mo-Nb-Ta-Ti-V-W alloys, rationalizing the observed significant strength increases at room temperature and 1000 ∘C upon addition of solutes with large misfit into a base alloy. The analytic theory for edge motion is thus a powerful validated tool for guiding alloy selection.

en: High energy barriers for edge dislocation motion in body-centered cubic high entropy alloys

atomistic-models

display_name: atomistic-models


en: The electronic density of states (DOS) provides information regarding the distribution of electronic energy levels in a material, and can be used to approximate its optical and electronic properties and therefore guide computational material design. Given its usefulness and relative simplicity, it has been one of the first electronic properties used as target for machine-learning approaches going beyond interatomic potentials. A subtle but important point, well-appreciated in the condensed matter community but usually overlooked in the construction of data-driven models, is that for bulk configurations the absolute energy reference of single-particle energy levels is ill-defined. Only energy differences matter, and quantities derived from the DOS are typically independent on the absolute alignment. We introduce an adaptive scheme that optimizes the energy reference of each structure as part of the training process, and show that it consistently improves the quality of ML models compared to traditional choices of energy reference, for different classes of materials and different model architectures. On a practical level, we trace the improved performance to the ability of this self-aligning scheme to match the most prominent features in the DOS. More broadly, we believe that this work highlights the importance of incorporating insights on the nature of the physical target into the definition of the architecture and of the appropriate figures of merit for machine-learning models, that translate in better transferability and overall performance.

en: Adaptive energy reference for machine-learning models of the electronic density of states

materialscloud

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

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

density-of-states

display_name: density-of-states

electronic-structure

display_name: electronic-structure

epfl

display_name: epfl

erc

display_name: erc

machine-learning

display_name: machine-learning

marvel

display_name: marvel


en: We present an ab initio modeling framework to simulate Majorana transport in 2D semiconducting materials, paving the way for topological qubits based on 2D nanoribbons. By combining density-functional-theory and quantum transport calculations, we show that the signature of Majorana bound states (MBSs) can be found in 2D material systems as zero-energy modes with peaks in the local density-of-states. The influence of spin-orbit coupling and external magnetic fields on Majorana transport is studied for two relevant 2D materials, WSe2 and PbI2. To illustrate the capabilities of the proposed ab initio platform, a device structure capable of hosting MBSs is created from a PbI2 nanoribbon and carefully investigated. These results are compared to InSb nanowires and used to provide design guidelines for 2D topological qubits.

en: Ab initio modeling framework for Majorana transport in 2D materials: towards topological quantum computing

materialscloud

en: Materials Cloud

ab-initio

display_name: ab-initio

majorana

display_name: majorana

quantum-transport

display_name: quantum-transport


en: Crystalline defects can modify quantum interactions in solids, causing unintuitive, even favourable, properties such as quantum Hall effect or superconducting vortex pinning. Here we present another example of this notion—an unexpected unidirectional Kondo scattering in single crystals of 2H-NbS2. This manifests as a pronounced low-temperature enhancement in the out-of-plane resistivity and thermopower below 40 K, hidden for the in-plane charge transport. The anomaly can be suppressed by the c-axis-oriented magnetic field, but is unaffected by field applied along the planes. The magnetic moments originate from layers of 1T-NbS2, which inevitably form during the growth, undergoing a charge-density-wave reconstruction with each superlattice cell (David-star-shaped cluster of Nb atoms) hosting a localized spin. Our results demonstrate the unique and highly anisotropic response of a spontaneously formed Kondo-lattice heterostructure, intercalated in a layered conductor.

en: Unidirectional Kondo scattering in layered NbS2

envi

en: Environment

first-principles-calculation

display_name: first-principles-calculation

vasp

display_name: vasp


en: Polyelectrolyte complexes (PECs), formed via the self-assembly of oppositely charged polysaccharides, are highly valued for their biocompatibility, biodegradability, and hydrophilicity, offering significant potential for biotechnological applications. However, the complex nature and lack of insight at a molecular level into polyelectrolytes conformation and aggregation often hinders the possibility of achieving an optimal control of PEC systems, limiting their practical applications. To address this problem, an in-depth investigation of PECs microscopic structural organization is required. In this work, for the first time, a hybrid approach that combines experimental techniques with atomistic molecular dynamics simulations is used to elucidate, at a molecular level, the mechanisms underlying the aggregation and structural organization of complexes formed by gellan and chitosan, i.e. PECs commonly used in food technology. This combined analysis reveals a two-step complexation process: gellan initially self-assembles into a double-helix structure, subsequently surrounded and stabilized by chitosan via electrostatic interactions. Furthermore, these results show that complexation preserves the individual conformation and intrinsic functionality of both polyelectrolytes, thereby ensuring the efficacy of the PECs in biotechnological applications.

en: Unveiling the self-assembly process of gellan-chitosan complexes through a combination of atomistic simulations and experiments

chitosan

display_name: chitosan

gellan

display_name: gellan

gels

display_name: gels

polyelectrolyte-complexes

display_name: polyelectrolyte-complexes

polysaccharides

display_name: polysaccharides


en: Doping and compositing are two universal design strategies used to engineer the electronic state of a material and mitigate its disadvantages. These two strategies have been extensively applied to the design of efficient electrocatalysts for water splitting. Using cobalt oxide (CoO) as a model catalyst, we prove that the oxygen evolution reaction (OER) performance could be progressively improved, first by Fe-doping to form Fe-CoO solid solution, and further by the addition of CeO2 to produce a Fe-CoO/CeO2 composite. X-ray adsorption spectroscopy (XAS) reveals that distinct electronic interactions are induced by the processes of doping and compositing. Fe-doping of CoO can break down the structural symmetry in the pristine material, changing the electronic structure of both Co and O species at the surface and decreasing the flat-band potential (Vfb). In comparison, subsequent compositing of Fe-CoO with CeO2 induces negligible electronic changes in the as-synthesized Fe-CoO (as seen in ex-situ characterizations), but significantly modifies the oxidative transformations of both Co and Fe under OER conditions. Our spectroscopic investigations reveal that Fe-doping and CeO2 compositing play different roles in modifying the electronic properties of CoO in its pristine state and during OER catalysis, respectively, in return, providing useful guidance for the design of more efficient electrocatalysts using these two strategies.

en: Spectroscopic investigations of complex electronic interactions by elemental doping and material compositing of cobalt oxide for enhanced oxygen evolution reaction activity

compositing

display_name: compositing

doping

display_name: doping

electronic-interaction

display_name: electronic-interaction

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction

x-ray-adsorption-spectroscopy

display_name: x-ray-adsorption-spectroscopy


en:
Two-dimensional (2D) materials have been a central focus of recent research because they host a variety of properties, making them attractive both for fundamental science and for applications. It is thus crucial to be able to identify accurately and efficiently if bulk three-dimensional (3D) materials are formed by layers held together by weak binding energy and, thus, can be potentially exfoliated into 2D materials. In this work, we develop a machine-learning (ML) approach that, combined with a fast preliminary geometrical screening, is able to efficiently identify potentially exfoliable materials. Starting from a combination of descriptors for crystal structures, we work out a subset of them that are crucial for accurate predictions. Our final ML model, based on a random forest classifier, has a very high recall of 98%. Using a SHapely Additive exPlanations (SHAP) analysis, we also provide an intuitive explanation of the five most important variables of the model. Finally, we compare the performance of our best ML model with a deep neural network architecture using the same descriptors.
To make our algorithms and models easily accessible, we publish an online tool on the Materials Cloud portal that only requires a bulk 3D crystal structure as input. Our tool thus provides a practical yet straightforward approach to assess whether any 3D compound can be exfoliated into 2D layers.

en: Machine-learning accelerated identification of exfoliable two-dimensional materials

binding-energy

display_name: binding-energy

crystal-structure

display_name: crystal-structure

exfoliation

display_name: exfoliation

online-tool

display_name: online-tool

two-dimensional

display_name: two-dimensional


en: As exemplified by the growing interest in the quantum anomalous Hall effect, the research on topology as an organizing principle of quantum matter is greatly enriched from the interplay with magnetism. In this vein, we present a combined electrical and thermoelectrical transport study on the magnetic Weyl semimetal EuCd₂As₂. Unconventional contribution to the anomalous Hall and anomalous Nernst effects were observed both above and below the magnetic transition temperature of EuCd₂As₂, indicating the existence of significant Berry curvature. EuCd₂As₂ represents a rare case in which this unconventional transverse transport emerges both above and below the magnetic transition temperature in the same material. The transport properties evolve with temperature and field in the antiferromagnetic phase in a different manner than in the paramagnetic phase, suggesting different mechanisms to their origin. Our results indicate EuCd₂As₂ is a fertile playground for investigating the interplay between magnetism and topology, and potentially a plethora of topologically nontrivial phases rooted in this interplay. This record contains the raw data for this manuscript [Physical Review Letters 126, 076602 (2021)].

en: Unconventional transverse transport above and below the magnetic transition temperature in Weyl semimetal EuCd₂As₂

anomalous-hall-effect

display_name: anomalous-hall-effect

anomalous-nernst-effect

display_name: anomalous-nernst-effect

experimental

display_name: experimental

magnetic-weyl-semimetal

display_name: magnetic-weyl-semimetal

topological-spin-texture

display_name: topological-spin-texture


en: We use a data-driven approach to study the magnetic and thermodynamic properties of van der Waals (vdW) layered materials. We investigate monolayers of the form A2B2X6, based on the known material Cr2Ge2Te6, using density functional theory (DFT) calculations and determine their magnetic properties, such as magnetic order and magnetic moment. We also examine formation energies and use them as a proxy for chemical stability.

en: Data-driven studies of magnetic two-dimensional materials

machine-learning

display_name: machine-learning

magnetic-materials

display_name: magnetic-materials

two-dimensional-materials

display_name: two-dimensional-materials


en:
Despite their incredible performance, it is well reported that deep neural networks tend to be overoptimistic about their prediction confidence. Finding effective and efficient calibration methods for neural networks is therefore an important endeavour towards better uncertainty quantification in deep learning. In this manuscript, we introduce a novel calibration technique named expectation consistency (EC), consisting of a post-training rescaling of the last layer weights by enforcing that the average validation confidence coincides with the average proportion of correct labels. First, we show that the EC method achieves similar calibration performance to temperature scaling (TS) across different neural network architectures and data sets, all while requiring similar validation samples and computational resources. However, we argue that EC provides a principled method grounded on a Bayesian optimality principle known as the Nishimori identity. Next, we provide an asymptotic characterization of both TS and EC in a synthetic setting and show that their performance crucially depends on the target function. In particular, we discuss examples where EC significantly outperforms TS.
This record provides the code for the paper "Expectation consistency for calibration of neural networks".

en: Expectation consistency for calibration of neural networks (code)

materialscloud

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

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

neural-networks

display_name: neural-networks

temperature-scaling

display_name: temperature-scaling

uncertainty-quantification

display_name: uncertainty-quantification


en: We propose Landau levels as a probe for the topological character of electronic bands in two-dimensional moiré superlattices. We consider two configurations of twisted double bilayer graphene (TDBG) that have very similar band structures, but show different valley Chern numbers of the flat bands. These differences between the AB-AB and AB-BA configurations of TDBG clearly manifest as different Landau level sequences in the Hofstadter butterfly spectra calculated using the tight-binding model. The Landau level sequences are explained from the point of view of the distribution of orbital magnetization in momentum space that is governed by the rotational C2 and time-reversal T symmetries. Our results can be readily extended to other twisted graphene multilayers and h-BN/graphene heterostructures thus establishing the Hofstadter butterfly spectra as a powerful tool for detecting the nontrivial valley band topology.

en: Landau levels as a probe for band topology in graphene moiré superlattices

materialscloud

en: Materials Cloud

band-topology

display_name: band-topology

landau-level

display_name: landau-level

moire-superlattice

display_name: moire-superlattice

twisted-double-bilayer-graphene

display_name: twisted-double-bilayer-graphene


en: High Entropy Alloys (HEAs) are a new broad class of near-random solid solution alloys that can possess some impressive mechanical and physical properties including high stability against grain growth (i.e. low grain boundary (GB) mobility). Here, it is shown that an initially flat GB in an HEA can become spontaneously rough, driven by natural local compositional fluctuations. Roughening lowers the total GB energy and thus can inhibit migration. A parameter-free theoretical framework is developed to demonstrate the energetics and size scales of the roughening in terms of solute/GB interaction energies and GB disconnection energies. Above a critical level of solute/GB interactions, a planar GB is predicted to roughen down to the scale of the GB periodic unit. A similar theory for 1D GBs (minimum periodic length in one direction) is also developed since such geometries are common in atomistic simulations. Specific predictions are made for the symmetric tilt boundaries Σ17 [100] (530) and Σ5 [100] (310) in a model CoCuFeNi alloy and atomistic simulations demonstrate roughening consistent with the theory. Analysis of the stresses needed to drive migration shows how migration can be inhibited or enhanced, rationalizing variations in mobility of GBs in HEAs.

en: Theory of spontaneous grain boundary roughening in high entropy alloys

envi

en: Environment

grain-boundaries

display_name: grain-boundaries

high-entropy-alloys

display_name: high-entropy-alloys

pinning

display_name: pinning

spontaneous-roughening

display_name: spontaneous-roughening


en: The screening arising from many-body excitations is a crucial quantity for describing ab-sorption and inelastic X-ray scattering (IXS) of materials. Similarly, the electron screening plays a critical role in state-of-the-art approaches for determining the fundamental band gap. However, ab initio studies of the screening in liquid water have remained limited. Here, we use a combined analysis based on the Bethe-Salpeter equation and time-dependent density functional theory. We first show that absorption spectra at near-edge energies are insufficient to assess the accuracy by which the screening is described. Next, when the energy range under scrutiny is extended, we instead find that the IXS spectra are highly sensitive and allow for the selection of the optimal theoretical scheme. This leads to good agreement with experiment over a large range of transferred energies and momenta, and enables establishing the elusive fundamental band gap of liquid water at 9.3 eV.

en: Many-body screening effects in liquid water

dft

display_name: dft

epfl

display_name: epfl

mbpt

display_name: mbpt

snsf

display_name: snsf

water

display_name: water


en:
The uploaded archive provides a ML-ready data set extracted from the juHemd database (see references) augmented with supplemental data for atomic descriptors. Descriptors provided in this data set include structural, magnetic, atomic quantities as well as derived (summed) quantities. In total, 118 possible descriptors are included of which 12 are DFT generated. For each simulation type (LDA/GGA) there is also a data set cleaned from DFT data available.

After data cleaning and preprocessing we extracted 387 LDA calculated magnetic Heusler structures as well as 408 GGA structures which have a full structural and magnetic data set. As we only aim at magnetic compounds, we chose to filter out compounds from the original JuHemd which have at least 0.1 Bohr magneton as total absolute magnetic moment. For each data file there is an existing descriptor file naming all the descriptors included in the data set.

en: ML-ready Curie temperatures and descriptors extracted from the JuHemd database

critical-temperature

display_name: critical-temperature

curie-temperature

display_name: curie-temperature

density-functional-theory

display_name: density-functional-theory

electronic-structure

display_name: electronic-structure

heusler-alloy

display_name: heusler-alloy

judft

display_name: judft

kkr

display_name: kkr

machine-learning

display_name: machine-learning

magnetic

display_name: magnetic

magnetic-phase-transition

display_name: magnetic-phase-transition

magnetic-structure

display_name: magnetic-structure

max

display_name: max

monte-carlo

display_name: monte-carlo


en: CeO₂ greatly enhances the electrocatalytic oxygen evolution reaction (OER) activity of CoOx, though the enhancement mechanism beyond this synergy is yet to be understood. Here, operando hard X-ray adsorption spectroscopy (hXAS) is applied to monitor the Co K edge and Ce L₃ edge in CoOx/CeO₂ to shed light on the evolution of the Co and Ce oxidation states during OER. In addition, ex situ soft XAS (sXAS) characterizations provide information on the irreversible surface-specific transformations of the Co L₃ edge as well as of the O K edge. Combining the operando and ex situ spectroscopic characterizations with comprehensive electrochemical analyses, we confirm CeO₂ is not the active center for the OER. However, coupling CeO₂ with CoOx introduces significant modifications in the Co and O species at the CoOx surface and alters the flat band potential (Efb), leading to more favorable Co oxidation state transformations during OER and possibly modifying the preferential reaction pathway. This work establishes the connections between electronic structures, Co oxidation state and the OER reaction mechanism for CoOx/CeO₂ composites electrodes.

en: Operando tracking the interactions between CoOx and CeO₂ during oxygen evolution reaction

co-oxidation

display_name: co-oxidation

co-redox

display_name: co-redox

operando-xas

display_name: operando-xas

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


en: We present ab initio calculations of hidden magnetoelectric multipolar order in Cr₂O₃ and its iron-based analogue, α-Fe₂O₃. We show the presence of hidden antiferroically-ordered magnetoelectric multipoles in both the prototypical magnetoelectric material Cr₂O₃, and centrosymmetric α-Fe₂O₃, which has the same crystal structure as Cr₂O₃, but a different magnetic dipolar ordering. In turn, we predict anti-magnetoelectric effects, in which local magnetic dipole moments are induced in opposite directions under the application of an external electric field, to create an additional antiferromagnetic ordering. We confirm the predicted induced moments using first-principles calculations. Our results demonstrate the existence of hidden magnetoelectric multipoles leading to local linear magnetoelectric responses even in centrosymmetric materials, where a net bulk linear magnetoelectric effect is forbidden by symmetry.  This archive contains input files and some output files necessary for creating all the data discussed in our paper with the title: Hidden orders and (anti-)Magnetoelectric Effects in Cr₂O₃ and α-Fe₂O₃.

en: Hidden orders and (anti-)magnetoelectric effects in Cr₂O₃ and α-Fe₂O₃

erc

display_name: erc

magnetoelectricity

display_name: magnetoelectricity

multipoles

display_name: multipoles


en:
Metal-organic frameworks (MOF) and covalent organic frameworks (COFs) are promising nanocarriers for targeted drug delivery. For their uptake and release, non-covalent interactions between the framework and the drugs play a fundamental role. However, an in-depth understanding of how different functional groups affect these interactions is still lacking. Using a multilevel approach combining molecular docking and density functional theory, we show in the publication associated with this data how computational modeling can be exploited to gain information on the interplay between functionalization and drug delivery features. We find that functional groups significantly impact the strength of the host-guest interactions. Moreover, the interaction strength qualitatively correlates with drug release data from experimental literature, providing a link between framework structure and release properties. The results of our study facilitate the customization of non-covalent interactions between MOFs/COFs and drugs and give direction on how to rationally design nanocarriers for sustaining the drug release in the body over longer times.
The data deposited on the Materials Cloud Archive contains the inputs and outputs of the molecular docking and DFT simulations.

en: Engineering host-guest interactions in organic framework materials for drug delivery

covalent-organic-frameworks

display_name: covalent-organic-frameworks

dft

display_name: dft

drug-delivery

display_name: drug-delivery

metal-organic-frameworks

display_name: metal-organic-frameworks


en: An ab initio  study of the coupled electrons and phonon transport properties of MoS2-hBN devices. A comparison of the device characteristics when hBN is treated as a perfectly insulating, non vibrating layer and one where it is included in the DFT together with MoS2.

en: Influence of the hBN dielectric layers on the quantum transport properties of MoS2 transistors.

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).

ab-initio

display_name: ab-initio

quantum-transport

display_name: quantum-transport

thermal-properties

display_name: thermal-properties


en: This dataset includes the full computational workflows of a proof-of-concept study of various possible mechanisms (standard and bifunctional ones) for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) on exfoliated NiOOH as electrocatalyst, including active edge sites (M5) and hydrogen acceptor sites in the same model system. Furthermore, explicit water is included in the model to describe the equilibration of the M-OOH species to M-OOH/eq, a crucial step that enables a bifunctional route to be operative. Additionally, different single Fe-dopant positions (M1, M2, M3, M4, M5, M6 and M7) are considered and four different reaction schemes (S1, S2, S3 and S4) are studied for the OER and the reverse ORR process. The results are relevant in alkaline conditions, where the studied model systems are stable. Certain Fe-dopant positions result in active Ni-edge sites with very low overpotentials provided that water is present within the model system.

en: Oxygen evolution and reduction on Fe‑doped NiOOH

materialscloud

en: Materials Cloud

electrochemical-overpotential

display_name: electrochemical-overpotential

mixed-metal-oxyhydroxides

display_name: mixed-metal-oxyhydroxides

oxygen-reduction-reaction

display_name: oxygen-reduction-reaction


en:
Uncertainty quantification is a central challenge in reliable and trustworthy machine learning. Naive measures such as last-layer scores are well-known to yield overconfident estimates in the context of overparametrized neural networks. Several methods, ranging from temperature scaling to different Bayesian treatments of neural networks, have been proposed to mitigate overconfidence, most often supported by the numerical observation that they yield better calibrated uncertainty measures. In this work, we provide a sharp comparison between popular uncertainty measures for binary classification in a mathematically tractable model for overparametrized neural networks: the random features model. We discuss a trade-off between classification accuracy and calibration, unveiling a double descent like behavior in the calibration curve of optimally regularized estimators as a function of overparametrization. This is in contrast with the empirical Bayes method, which we show to be well calibrated in our setting despite the higher generalization error and overparametrization.
This record provides the code to reproduce the numerical experiments of the related paper "On double-descent in uncertainty quantification in overparametrized models".

en: On double-descent in uncertainty quantification in overparametrized models (code)

envi

en: Environment

neural-networks

display_name: neural-networks

numerical-simulation

display_name: numerical-simulation

uncertainty-quantification

display_name: uncertainty-quantification


en: We present evidence of a strong circular photon drag effect (PDE) in topological insulators (TIs) through the observation of threefold rotationally symmetric helicity-dependent topological photocurrents using THz spectroscopy in epitaxially-grown Bi₂Se₃ with reduced crystallographic twinning. We establish how twinned domains introduce competing nonlinear optical (NLO) responses inherent to the crystal structure that obscure geometry-sensitive optical processes through the introduction of a spurious mirror symmetry. Minimizing the twinning defect reveals strong NLO response currents whose magnitude and direction depend on the alignment of the excitation to the crystal axes and follow the threefold rotational symmetry of the crystal. Notably, photocurrents arising from helical light reverse direction for left/right circular polarizations and maintain a strong azimuthal dependence—a result uniquely attributable to the circular PDE, where the photon momentum acts as an applied in-plane field stationary in the laboratory frame. Our results demonstrate new levels of control over the magnitude and direction of photocurrents in TIs and that the study of single-domain films is crucial to reveal hidden phenomena that couple topological order and crystal symmetries.

en: Emergence of threefold symmetric helical photocurrents in epitaxial low twinned Bi₂Se₃

electronic-structure

display_name: electronic-structure

experimental

display_name: experimental

photon-drag-effect

display_name: photon-drag-effect

spectroscopy

display_name: spectroscopy

terahertz

display_name: terahertz

topological-materials

display_name: topological-materials


en: Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

en: High-throughput computation of Raman spectra from first principles

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

raman-tensors

display_name: raman-tensors


en: Physics-inspired molecular representations are the cornerstone of similarity-based learning applied to solve chemical problems. Despite their conceptual and mathematical diversity, this class of descriptors shares a common underlying philosophy: they all rely on the molecular information that determines the form of the electronic Schrödinger equation. Existing representations take the most varied forms, from non-linear functions of atom types and positions to atom densities and potential, up to complex quantum chemical objects directly injected into the ML architecture. In this work, we present the Spectrum of Approximated Hamiltonian Matrices (SPAᴴM) as an alternative pathway to construct quantum machine learning representations through leveraging the foundation of the electronic Schrödinger equation itself: the electronic Hamiltonian. As the Hamiltonian encodes all quantum chemical information at once, SPAᴴM representations not only distinguish different molecules and conformations, but also different spin, charge, and electronic states. As a proof of concept, we focus here on efficient SPAᴴM representations built from the eigenvalues of a hierarchy of well-established and readily-evaluated "guess" Hamiltonians. These SPAᴴM representations are particularly compact and efficient for kernel evaluation and their complexity is independent of the number of different atom types in the database

en: SPAᴴM: the spectrum of approximated hamiltonian matrices representations

epfl

display_name: epfl

erc

display_name: erc

guess-hamiltonians

display_name: guess-hamiltonians

machine-learning

display_name: machine-learning

molecular-representation

display_name: molecular-representation

snsf

display_name: snsf

spahm

display_name: spahm


en:
We show that, contrary to popular assumptions, predictions from machine learning potentials built upon high-dimensional atom-density representations almost exclusively occur in regions of the representation space which lie outside the convex hull defined by the training set points. We then propose a perspective to rationalise the domain of robust extrapolation and accurate prediction of atomistic machine learning potentials in terms of the probability density induced by training points in the representation space.
The data here contained can be used to reproduce all results and graphs shown in the article. We also include the trajectory files for the Au13 dataset we generate by running molecular dynamics simulations of an Au nanoparticle containing 13 atoms at temperatures of 50K, 100K, 200K, 300K, and 400K. Details regarding the generation of such dataset can be found in the supplementary information file for the article.

en: On the robust extrapolation of high-dimensional machine learning potentials

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Hydroxyapatite (HA, Ca10PO4(OH)2) is a widely explored material in the experimental domain of biomaterials science, because of its resemblance with natural bone minerals. Specifically, in the bioceramic community, HA doped with multivalent cations (e.g., Mg+2, Fe+2, Sr+2, etc.) has been extensively investigated in the last few decades. Experimental research largely established the critical role of dopant content on the changes in mechanical and biocompatibility properties. The plethora of experimental measurements of mechanical response on doped HA is based on compression or indentation testing of polycrystalline materials. Such measurements, as well as computational predictions of me,  on single crystalline (doped) HA are scarce. On that premise, the present study aims to build atomistic models of Fe2+-doped HA, a model system, with varying Fe content (10, 20, 30, and 40 mol%) and to explore their uniaxial tensile response by means of molecular dynamics (MD) simulation, together with the calculation of IR spectrum. In the equilibrated unit cell structures, Ca(1) sites were found to be energetically favourable for Fe2+ substitution. The local distribution of Fe2+ ions significantly affect the atomic partial charge distribution and chemical symmetry surrounding the functional groups. These signatures are reflected in the significant decrease in the intensity of IR peaks and are found in the Fe-doped HA, together with peak splitting because of the symmetry change in the crystal structure. Another important objective of this work is to computationally predict the mechanical response of doped HA in their single crystal format. An interesting observation is that the elastic anisotropy of undoped HA was not compromised with Fe-doping. Tensile strength (TS) is systematically reduced in doped HA with Fe+2 dopant content and a decrease in TS with temperature can be attributed to the increased thermal agitation of atoms at elevated temperatures. The physics of the tensile response was rationalized in terms of the strain dependent changes in covalent/ionic framework (Ca-P distance, P-O bond strain, O-P-O angular strain, O-H bond distance). Further, the dynamic changes in covalent bond network were energetically analyzed by calculating the changes in O-H and P-O bond vibrational energy. Summarizing, the current work develops our foundational understanding of the atomistic phenomena involved in the phase stability and tensile response of Fe-doped HA single crystals.

en: In silico study on probing atomistic insight into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals

hydroxyapatite

display_name: hydroxyapatite

iron-doping

display_name: iron-doping

md-simulation

display_name: md-simulation

mechanical-response

display_name: mechanical-response


en: We present a first-principles method to calculate electron-phonon coupling elements in atomic systems, and showcase its application to the evaluation of the phonon-limited mobility of n-type single-layer MoS₂. The method combines a density functional theory (DFT) plane-wave supercell approach with a real-space maximally localized Wannier basis. It enables the calculation of electronic structure, phonon displacements with their corresponding frequencies, and real-space electron-phonon coupling elements on the same footing, without the need for density functional perturbation theory (DFPT) or Wannier interpolation. We report a low-field, intrinsic mobility of 274 cm²/Vs at room temperature for MoS₂, and highlight its dependence on carrier density and temperature. In addition, we compare our findings to the latest available modeling data and put them in perspective with the experimentally measured values. Based on these observations, the mobilities presented in this work appear to be compatible with experimental results, when taking into account other scattering sources. Hence, the proposed approach provides a reliable framework for mobility calculations that can be extended towards large-scale device simulations.

en: Electron-phonon calculations using a wannier-based supercell approach: applications to the monolayer MoS₂ mobility

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).

ab-initio

display_name: ab-initio

carrier-transport

display_name: carrier-transport

dft

display_name: dft

electron-mobility

display_name: electron-mobility

electron-phonon-coupling

display_name: electron-phonon-coupling


en: Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics. However, low carrier mobility in 2DM transistors driven by phonon scattering remains a critical challenge. To address this issue, we propose the controlled introduction of localized tensile strain as an effective mean to inhibit electron-phonon scattering in 2DM. Strain is achieved by conformally adhering the 2DM via van-der-Waals forces to a dielectric layer previously nanoengineered with a gray-tone topography. Our results show that monolayer MoS₂ FETs under tensile strain achieve an 8-fold increase in on-state current, reaching mobilities of 185 cm²/Vs at room temperature, in good agreement with theoretical calculations. The present work on nanotopographic grayscale surface engineering and the use of high-quality dielectric materials has the potential to find application in the nanofabrication of photonic and nanoelectronic devices. Here we report the main data and codes needed to reproduce the theoretical findings of this work.

en: Deterministic grayscale nanotopography to engineer mobilities in strained MoS₂ FETs

materialscloud

en: Materials Cloud

density-functional-theory

display_name: density-functional-theory

first-principles

display_name: first-principles

transport

display_name: transport


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

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

envi

en: Environment

dftdmft

display_name: dftdmft

dftu

display_name: dftu

hartree-fock

display_name: hartree-fock

marvel

display_name: marvel


en: The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT). However, running large simulation cells with DFT is computationally demanding, while simulations of small cells are often plagued with non-physical effects that are a consequence of the system's finite size. Therefore, one is often forced to use empirical models that describe the physics of the material in terms of effective interaction terms, that are fitted using the results from DFT, to perform simulations that do not suffer from finite size effects. In this study we use a machine-learning (ML) potential trained on DFT, in combination with accelerated sampling techniques, to converge the thermodynamic properties of Barium Titanate (BTO) with first-principles accuracy and a full atomistic description. Our results indicate that the predicted Curie temperature depends strongly on the choice of DFT functional and system size, due to the presence of emergent long-range directional correlations in the local dipole fluctuations. Our findings demonstrate how the combination of ML models and traditional bottom-up modeling allow one to investigate emergent phenomena with the accuracy of first-principles calculations and the large size and time scales afforded by empirical models.

en: Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

dielectric-correlations

display_name: dielectric-correlations

ferroelectrics

display_name: ferroelectrics

finite-size-effects

display_name: finite-size-effects

hybrid-dft-ml

display_name: hybrid-dft-ml

machine-learning-potentials

display_name: machine-learning-potentials

metadynamics

display_name: metadynamics

phase-transitions

display_name: phase-transitions

sinergia

display_name: sinergia

snsf

display_name: snsf


en: Dimensionality provides a clear fingerprint on the dispersion of infrared-active, polar-optical phonons. For these phonons, the local dipoles parametrized by the Born effective charges drive the LO-TO splitting of bulk materials; this splitting actually breaks down in two-dimensional materials. Here, we develop the theory for one-dimensional (1D) systems -nanowires, nanotubes, and atomic and polymeric chains. Combining an analytical model with the implementation of density-functional perturbation theory in 1D boundary conditions, we show that the dielectric splitting in the dispersion relations collapses as x²log(x) at the zone center. The dielectric properties and the radius of the 1D materials are linked by the present work to these red shifts, opening infrared and Raman characterization avenues.

en: Infrared-active phonons in one-dimensional materials and their spectroscopic signatures

ab-initio

display_name: ab-initio

one-dimensional-materials

display_name: one-dimensional-materials

phonons

display_name: phonons

raman

display_name: raman