en: We present a combined theoretical and experimental investigation of the anti-symmetric Compton profile in LiNiPO4 as a possible probe for magneto-electric toroidal moments. Understanding as well as detecting such magneto-electric multipoles is an active area of research in condensed matter physics. Our calculations, based on density functional theory, indicate an anti-symmetric Compton profile in the direction of the ty toroidal moment in momentum space, with the computed anti-symmetric profile around four orders of magnitude smaller than the total profile. The difference signal that we measure is consistent with the computed profile, but of the same order of magnitude as the statistical errors and systematic uncertainties of the experiment. Our results motivate further theoretical work to understand the factors that influence the size of the anti-symmetric Compton profile, and to identify materials exhibiting larger effects.

materialscloud

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

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

en: Anti-symmetric Compton scattering in LiNiPO4: Towards a direct probe of the magneto-electric multipole moment

compton-scattering

display_name: compton-scattering

density-functional-theory

display_name: density-functional-theory

erc

display_name: erc

horizon-europe

display_name: horizon-europe

magneto-electric-toroidal-moment

display_name: magneto-electric-toroidal-moment


$oid: OBSOLETE

materialscloud

approval_status: approved

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


en: In this record we provide the data to support our recent finding on the intercalation of gold chloride underneath atomically precise graphene nanoribbons (GNRs). GNRs have a wide range of electronic properties that depend sensitively on their chemical structure. Several types of GNRs have been synthesized on metal surfaces through selective surface-catalyzed reactions. The resulting GNRs are adsorbed on the metal surface, which may lead to hybridization between the GNR orbitals and those of the substrate. This makes investigation of the intrinsic electronic properties of GNRs more difficult, and also rules out capacitive gating. In the manuscript where the data presented here is discussed, we demonstrate the formation of a dielectric gold chloride adlayer that can intercalate underneath GNRs on the Au(111) surface. The intercalated gold chloride adlayer electronically decouples the GNRs from the metal and leads to a substantial hole doping of the GNRs. Our results introduce an easily accessible tool in the in situ characterization of GNRs grown on Au(111) that allows for exploration of their electronic properties in a heavily hole-doped regime.

en: Electronic decoupling and hole-doping of graphene nanoribbons on metal substrates by chloride intercalation

dft

display_name: dft

electronic-properties

display_name: electronic-properties

marvel

display_name: marvel

on-surface-synthesis

display_name: on-surface-synthesis

stm

display_name: stm


en: Electrochemical systems are often simulated by using numerical methods based on finite element solution of differential equations. We developed a method to decrease the needed computational resources, based on the analytical solution of a part of the system: the obtained analytical equations are applied as boundary conditions to the finite element calculation. The part of the system that is analytically solved is the region of the diffuse double layer. We provide two COMSOL models: i) a 1d fully numerical calculation and ii) the same simulation performed with the semi-analytical method. For each model, we provide the .mph file (Comsol) and the .java file (Java+Comsol). We also provide examples of the resulting impedances and frequency responses of various parameters.

en: Numerical simulation of an electrochemical system and semi-analytical method

diffuse-double-layer

display_name: diffuse-double-layer

electrochemical-system

display_name: electrochemical-system

finite-element-method

display_name: finite-element-method

semi-analytical-solution

display_name: semi-analytical-solution


en:
The high-throughput molecular exploration and screening of organic electronic materials often starts with either a 'top-down' mining of existing repositories, or the 'bottom-up' assembly of fragments based on predetermined rules and known synthetic templates. In both instances, the datasets used are often produced on a case-by-case basis, and require the high-quality computation of electronic properties and extensive user input: curation in the top-down approach, and the construction of a fragment library and introduction of rules for linking them in the bottom-up approach. Both approaches are time-consuming and require significant computational resources. Here, we generate a top-down set named FORMED consisting of 117K synthesized molecules containing their optimized structures, associated electronic and topological properties and chemical composition, and use these structures as a vast library of molecular building blocks for bottom-up fragment-based materials design. A tool is developed to automate the coupling of these building block units based on their available Csp2-H bonds, thus providing a fundamental link between the two philosophies of dataset construction. Statistical models are trained on this dataset and a subset of the resulting hybrid top-down/bottom-up compounds (selected dimers), which enable on-the-fly prediction of key ground state (frontier molecular orbital gaps) and excited state (S1 and T1 energies) properties from molecular geometries with high accuracy across all known p-block organic compound space.
With access to ab initio-quality optical properties in hand, it is possible to apply this bottom-up pipeline using existing compounds as molecular building blocks to any materials design campaign. To illustrate this, we construct and screen over a million molecular candidates (predicted dimers) for efficient intramolecular singlet fission, the leading candidates of which provide insight into the structural features that may promote this multiexciton-generating process.

en: Data-driven discovery of organic electronic materials enabled by hybrid top-down/bottom-up design

crystal-structures

display_name: crystal-structures

donor-acceptor-copolymers

display_name: donor-acceptor-copolymers

optical-properties

display_name: optical-properties

organic-molecules

display_name: organic-molecules

photophysical-properties

display_name: photophysical-properties


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: We present a first-principles investigation of the structural, electronic, and magnetic properties of the pristine and Fe-doped α-MnO₂ using density-functional theory with extended Hubbard functionals. The onsite U and intersite V Hubbard parameters are determined from first principles and self-consistently using density-functional perturbation theory in the basis of Löwdin-orthogonalized atomic orbitals. Among the ferromagnetic and four types of antiferromagnetic (AFM) orderings for the pristine α-MnO₂ we find the C2-AFM spin configuration to be the most energetically favorable, in agreement with the experimentally observed AFM state. The computed lattice parameters, magnetic moments, and band gaps are overall in good agreement with the experimental ones when both the onsite and intersite Hubbard corrections are included. For the Fe-doped α-MnO₂ two types of doping are considered: Fe insertion in the 2 × 2 tunnels and partial substitution of Fe for Mn. The calculated formation energies show that Fe insertion is energetically favorable, in agreement with experiments. We find that both types of doping preserve the C2 AFM spin configuration of the host lattice. The oxidation state of Fe is found to be 2+ and 4+ in the case of the interstitial and substitutional doping, respectively, while the oxidation state of Mn is 4+ in both cases. This work opens a door for accurate studies of other Mn oxides and complex transition-metal compounds when the localization of 3d electrons occurs in the presence of strong covalent interactions with ligands.

en: Electronic structure and magnetism of pristine and Fe-doped α-MnO₂ from density-functional theory with extended Hubbard functionals

band-gap

display_name: band-gap

bond-angles

display_name: bond-angles

bond-length

display_name: bond-length

crystal-structure

display_name: crystal-structure

density-functional-theory

display_name: density-functional-theory

density-of-states

display_name: density-of-states

dftu

display_name: dftu

dftuv

display_name: dftuv

formation-energy

display_name: formation-energy

hubbard-parameters

display_name: hubbard-parameters

hubbard-projectors

display_name: hubbard-projectors

interstitial-doping

display_name: interstitial-doping

magnetic-moment

display_name: magnetic-moment

orthogonalized-atomic-orbitals

display_name: orthogonalized-atomic-orbitals

oxidation-state

display_name: oxidation-state

self-interactions

display_name: self-interactions

spin-configuration

display_name: spin-configuration

substitutional-doping

display_name: substitutional-doping


en: In the past decade we have witnessed the appearance of large databases of calculated material properties. These are most often obtained with the Perdew-Burke-Ernzerhof (PBE) functional of density-functional theory, a well established and reliable technique that is by now the standard in materials science. However, there have been recent theoretical developments that allow for an increased accuracy in the calculations. Here, we present a dataset of calculations for 175k solid-state materials obtained with two improved functionals: PBE for solids (that yields consistently better geometries than the PBE) and SCAN (probably the best all-around functional at the moment). Our results provide an accurate overview of the landscape of stable (and nearly stable) materials, and as such can be used for more reliable predictions of novel compounds. They can also be used for training machine learning models, or even for the comparison and benchmark of PBE, PBE for solids, and SCAN.

en: A new dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals

high-throughput

display_name: high-throughput

pbe-for-solids

display_name: pbe-for-solids

scan

display_name: scan


en: The catalytic oxidation of HCl by molecular oxygen (Deacon process) over ceria allows the recovery of molecular chlorine from omnipresent HCl waste produced in various industrial processes. In previous density functional theory (DFT) model calculations by Amrute et al. [J. Catal. 2012, 286, 287–297.], it was proposed that the most critical reaction step in this process is the displacement of tightly bound chlorine at a vacant oxygen position on the CeO2(111) surface (Clvac) toward a less strongly bound cerium on-top (Cltop) position. This step is highly endothermic by more than 2 eV. On the basis of a dedicated model study, namely the re-oxidation of a chlorinated single crystalline Clvac-CeO2−x(111)-(√3 × √3)R30° surface structure, we provide in-situ synchrotron-based spectroscopic data (high-resolution core level spectroscopy (HRCLS) and X-ray adsorption near edge structure (XANES)) for this oxygen-induced de-chlorination process. Combined with theoretical evidence from DFT calculations, the Clvac → Cltop displacement reaction is predicted to be induced by an adsorbed peroxo species (O22-), making the displacement step concerted and exothermic by only 0.6 eV with an activation barrier of only 1.04 eV. The peroxo species is shown to be important for the re-oxidation of Clvac-CeO2−x(111) and is considered essential for understanding the function of ceria in oxidation catalysis.

en: Critical step in the HCl oxidation reaction over single-crystalline CeO2−x(111): Peroxo-induced site change of strongly adsorbed surface chlorine

deacon-process

display_name: deacon-process

oxygen-induced-de-chlorination-process

display_name: oxygen-induced-de-chlorination-process

peroxo-surface-species

display_name: peroxo-surface-species

reduced-ceria

display_name: reduced-ceria


materialscloud

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

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


en: We present a first-principles investigation of the structural, electronic, and magnetic properties of the pristine and Fe-doped α-MnO₂ using density-functional theory with extended Hubbard functionals. The onsite U and intersite V Hubbard parameters are determined from first principles and self-consistently using density-functional perturbation theory in the basis of Löwdin-orthogonalized atomic orbitals. First, we analyze the pristine α-MnO₂ and show that the C2-AFM spin configuration is the most energetically favorable, in agreement with the experimentally observed antiferromagnetic state. For the Fe-doped α-MnO₂ two types of doping are considered: Fe insertion in the 2 × 2 tunnels and partial substitution of Fe for Mn. The calculated formation energies show that the experimentally observed Fe insertion is energetically favorable only when intersite Hubbard interactions are taken into account. Moreover, we find that both types of doping preserve the C2-AFM spin configuration of the host lattice only when Hubbard V corrections are included. The oxidation state of Fe is found to be +2 and +4 in the case of the interstitial and substitutional doping, respectively, while the oxidation state of Mn is +4 in both cases. This work opens a door for accurate studies of other Mn oxides and complex transition-metal compounds when the localization of 3d electrons occurs in the presence of strong covalent interactions with ligands.

en: Materials Cloud

en: Pivotal role of intersite Hubbard interactions in Fe-doped α-MnO₂

band-gap

display_name: band-gap

bond-angles

display_name: bond-angles

bond-length

display_name: bond-length

crystal-structure

display_name: crystal-structure

density-functional-theory

display_name: density-functional-theory

density-of-states

display_name: density-of-states

dftu

display_name: dftu

dftuv

display_name: dftuv


en: The mapped gaussian process (MGP) force-field used to elucidate the surface alloying of Cu-Zn. The force-field is made based on first-principles data by using machine-learning technique called Gaussian Process as implemented in FLARE package (https://github.com/mir-group/flare). Active and on-the-fly learning were employed to build the database efficiently. The simulation reveals atomistic details of the alloying process, i.e., the incorporation of deposited Zn adatoms to the Cu substrate. The surface alloying is found to start at upper and lower terraces near the step edge, which emphasize the role of steps and kinks in the alloying. The incorporation of Zn at the middle terrace was found at the later stage of the simulation.

en: The mapped gaussian process (MGP) force-field of Cu-Zn surface alloy

envi

en: Environment

cu-zn-surface

display_name: cu-zn-surface

first-principles

display_name: first-principles

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en:
The transport and optical properties of semiconducting transition metal dichalcogenides around room temperature are dictated by electron-phonon scattering mechanisms within a complex, spin-textured and multi-valley electronic landscape. The relative positions of the valleys are critical, yet they are sensitive to external parameters and very difficult to determine directly. We propose a first-principles model as a function of valley positions to calculate carrier mobility and Kerr rotation angles, and apply it to MoS₂, WS₂, MoSe₂, and WSe₂. The model brings valuable insights, as well as quantitative predictions of macroscopic properties for a wide range of carrier density. The doping-dependant mobility displays a characteristic peak, the height depending on the position of the valleys. In parallel, the Kerr rotation signal is enhanced when same spin-valleys are aligned, and quenched when opposite spin-valleys are populated. We provide guidelines to optimize and correlate these quantities with respect to experimental parameters, as well as the theoretical support for in situ characterization of the valley positions.
The dataset contains the necessary data, a jupyter notebook, a supporting python library, and a small app with a simple user interface to reproduce the results.

en: The impact of valley profile on the mobility and Kerr rotation of transition metal dichalcogenides

electron-phonon-coupling

display_name: electron-phonon-coupling

kerr-angle

display_name: kerr-angle

transport

display_name: transport


en:
The characterization of the atomic structure of disordered systems, such as amorphous, glasses and (bio)molecule in solution, is a fundamental step for most theoretical investigations. The properties of short- and medium-range local order structures are responsible for the electronic, optical and transport properties of these systems. Here, we present the BELLO open source code, a post-processing script-tool created for the automatic analysis and extraction of structural characteristics of disordered and amorphous systems. BELLO is agnostic to the code that generated single configurations or trajectories, it provides an intuitive access through a graphical user interface (GUI), and it requires minimal computational resources. Its capabilities include the calculation of the order parameter , the folded structure identification, and statistical analysis tools such as atomic coordination number and pair/angle-distribution functions. The working principles of the code are described and tested on ab initio molecular dynamics trajectories of amorphous chalcogenides.

The code is also on the GitHub repository
https://github.com/behnood-dianat/BELLO

en: BELLO: A post-processing tool for the local-order analysis of disordered systems

amorphous

display_name: amorphous

disorder

display_name: disorder

intersect

display_name: intersect

order

display_name: order

software

display_name: software


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

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

cscs

display_name: cscs

dft

display_name: dft

indenofluorene

display_name: indenofluorene

non-contact-atomic-force-microscopy

display_name: non-contact-atomic-force-microscopy

snsf

display_name: snsf

stm

display_name: stm


en: 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

experimental

display_name: experimental

magnetic-topological-insulator

display_name: magnetic-topological-insulator


en: In this record we provide data to support our recent findings related to carbon nanotube based quantum dots for tunable terahertz detection. Generating and detecting radiation in the technologically relevant range of the so-called terahertz gap (0.1–10 THz) is challenging because of a lack of efficient sources and detectors. Quantum dots in carbon nanotubes have shown great potential to build sensitive terahertz detectors, usually based on photon-assisted tunneling. A recently reported mechanism combining resonant quantum dot transitions and tunneling barrier asymmetries results in a narrow linewidth photocurrent response with a large signal-to-noise ratio under weak THz radiation. That device was sensitive to one frequency, corresponding to transitions between equidistant quantized states. In this work we show, using numerical simulations together with scanning tunneling spectroscopy studies of a defect-induced metallic zigzag single-walled carbon nanotube quantum dot, that breaking simultaneously various symmetries in metallic nanotube quantum dots of arbitrary chirality strongly relaxes the selection rules in the electric dipole approximation and removes energy degeneracies. This leads to a richer set of allowed optical transitions spanning frequencies from 1 THz to several tens of THz, for a ∼10 nm quantum dot. Based on these findings, we propose a terahertz detector device based on a metallic single-walled carbon nanotube quantum dot defined by artificial defects. Depending on its length and contacts transparency, the operating regimes range from a high-resolution gate-tunable terahertz sensor to a broadband terahertz detector. Our calculations indicate that the device is largely unaffected by temperatures up to 100 K, making carbon nanotube quantum dots with broken symmetries a promising platform to design tunable terahertz detectors that could operate at liquid nitrogen temperatures.

en: Metallic carbon nanotube quantum dots with broken symmetries as a platform for tunable terahertz detection

ab-initio

display_name: ab-initio

carbon-nanotubes

display_name: carbon-nanotubes

terahertz-detector

display_name: terahertz-detector


materialscloud

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

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


en: In the past decade we have witnessed the appearance of large databases of calculated material properties. These are most often obtained with the Perdew-Burke-Ernzerhof (PBE) functional of density-functional theory, a well established and reliable technique that is by now the standard in materials science. However, there have been recent theoretical developments that allow for an increased accuracy in the calculations. Here, we present a dataset of calculations for 175k solid-state materials obtained with two improved functionals: PBE for solids (that yields consistently better geometries than the PBE) and SCAN (probably the best all-around functional at the moment). Our results provide an accurate overview of the landscape of stable (and nearly stable) materials, and as such can be used for more reliable predictions of novel compounds. They can also be used for training machine learning models, or even for the comparison and benchmark of PBE, PBE for solids, and SCAN.

en: A new dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

pbe-for-solids

display_name: pbe-for-solids

scan

display_name: scan


en: Compared to isolated C₆₀³⁻ ions, characterized by a three-dimensional equipotential trough at the bottom of the lowest adiabatic potential energy surface (APES), the Jahn-Teller (JT) effect in cubic fullerides is additionally influenced by the interaction of JT distortions at C₆₀ sites with vibrational modes of the lattice. This leads to modification of JT stabilization energy and to the warping of the trough at each fullerene site, as well as to the interaction of JT distortions at different sites. Here we investigate these effects in three fcc fullerides with A = K, Rb, Cs and in Cs₃C₆₀ with bcc (A15) structure. DFT calculations of orbital vibronic coupling constants at C₆₀ sites and of phonon spectra have been done for fully ordered lattices (1 C₆₀/u.c.). Based on them the elastic response function for local JT distortions has been evaluated and the lowest APES investigated. To this end an expression for the latter as a function of trough coordinates of all sites has been derived. The results show that the JT stabilization energy slightly increases compared to an isolated C₆₀³⁻ and a warping of the trough of a few meV occurs. The interaction of JT distortions on nearest- and next-nearest-neighbor fullerene sites is of similar order of magnitude. These effects arise first of all due to the interaction of C₆₀ sites with the displacements of neighbor alkali atoms and are more pronounced in fcc fullerides than in the A15 compound. The results of this study support the picture of weakly hindered independent rotations of JT deformations at C₆₀ sites in cubic A₃C₆₀.

materialscloud

en: Materials Cloud

en: Jahn-Teller effect in the cubic fullerides A₃C₆₀

cubic-fullerides

display_name: cubic-fullerides

elastic-coupling

display_name: elastic-coupling

jahn-teller-effect

display_name: jahn-teller-effect

phonons

display_name: phonons


envi

en: Environment


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

machine-learning

display_name: machine-learning

neural-networks

display_name: neural-networks

potential-energy-surfaces

display_name: potential-energy-surfaces


en: In this record we provide data to support our recent findings related to the fabrication of [7]triangulene. Triangulene and its π-extended homologues constitute non-Kekulé polyradical frameworks with high-spin ground states, and are anticipated to be key components of organic spintronic devices. In our publication we report a combined in-solution and on-surface synthesis of the hitherto largest triangulene homologue, [7]triangulene (C78H24), consisting of twenty-eight benzenoid rings fused in a triangular fashion. We employ low-temperature scanning tunneling microscopy to confirm the chemical structure of individual molecules adsorbed on a Cu(111) surface. While neutral [7]triangulene in the gas phase is predicted to have an open-shell septet ground state; our scanning tunneling spectroscopy measurements, in combination with density functional theory calculations, reveal chemisorption of [7]triangulene on Cu(111) together with considerable charge transfer, resulting in a closed-shell state. Furthermore, substantial hybridization between the molecular orbitals of [7]triangulene is observed.

en: Synthesis and characterization of [7]triangulene

erc

display_name: erc

graphene-flagship

display_name: graphene-flagship

nanographene

display_name: nanographene

snsf

display_name: snsf

triangulene

display_name: triangulene


en: In the past decade we have witnessed the appearance of large databases of calculated material properties. These are most often obtained with the Perdew-Burke-Ernzerhof (PBE) functional of density-functional theory, a well established and reliable technique that is by now the standard in materials science. However, there have been recent theoretical developments that allow for an increased accuracy in the calculations. Here, we present the updated alexandria dataset of calculations for more than 415k solid-state materials obtained with two improved functionals: PBE for solids (that yields consistently better geometries than the PBE) and SCAN (probably the best all-around functional at the moment). Our results provide an accurate overview of the landscape of stable (and nearly stable) materials, and as such can be used for more reliable predictions of novel compounds. They can also be used for training machine learning models, or even for the comparison and benchmark of PBE, PBE for solids, and SCAN.

en: A new dataset of 415k stable and metastable materials calculated with the PBEsol and SCAN functionals

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

pbe-for-solids

display_name: pbe-for-solids

scan

display_name: scan


en: Hydrogen (H) embrittlement in multicomponent austenitic alloys is a serious limitation to their application in many environments. Recent experiments show that the High-Entropy Alloy (HEA) CoCrFeMnNi absorbs more H than 304 Stainless Steel but is less prone to embrittlement while the HEA CoCrFeNi is not embrittled under comparable conditions. As a first step toward understanding H embrittlement, here a comprehensive first-principles study of H absorption, surface, and fracture energies in the presence of H is presented for 304 Stainless Steel, 316 Stainless Steel, CoCrFeNi, and CoCrFeMnNi. A collinear paramagnetic model of the magnetic state is used, which is likely more realistic than previous proposed magnetic states. All alloys have a statistical distribution of H absorption sites. Hence, at low concentrations, H is effectively trapped in the lattice making it more difficult for H to segregate to defects or interfaces. Agreement with experimental H solubilities across a range of chemical potentials can be achieved with minor fitting of the average H absorption energy. The (111) surface energies for 0, 50, and 100% H surface coverage are very similar across all alloys. The fracture energies for two representative thermodynamic conditions are then determined. SS304 and CoCrFeNi are found to have the lowest fracture energies, but experiments suggest rather different embrittlement tendencies. These results indicate that differences in H embrittlement across these austenitic alloys are not due solely to differences in H absorption or H-reduced fracture energy, thus requiring more sophisticated concepts than those recently found successful for fcc Ni.

en: First principles study of the effect of hydrogen in austenitic stainless steels and high entropy alloys

complex-alloys

display_name: complex-alloys

h-absorption

display_name: h-absorption

hydrogen-embrittlement

display_name: hydrogen-embrittlement

surface-energy

display_name: surface-energy


en: The development of next generation perovskite-based optoelectronic devices relies critically on the understanding of the interaction between charge carriers and the polar lattice in out-of-equilibrium conditions. While it has become increasingly evident for CsPbBr3 perovskites that the Pb-Br framework flexibility plays a key role in their light-activated functionality, the corresponding local structural rearrangement has not yet been unambiguously identified. In this work, we demonstrate that the photoinduced lattice changes in the system are due to a specific polaronic distortion, associated with the activation of a longitudinal optical phonon mode at 18 meV by electron-phonon coupling, and we quantify the associated structural changes with atomic-level precision. Key to this achievement is the combination of time-resolved and temperature-dependent studies at Br K-edge and Pb L3-edge X-ray absorption with refined ab-initio simulations, which fully account for the screened core-hole final state effects on the X-ray absorption spectra. From the temporal kinetics, we show that carrier recombination reversibly unlocks the structural deformation at both Br and Pb sites. The comparison with the temperature-dependent XAS results rules out thermal effects as the primary source of distortion of the Pb-Br bonding motif during photoexcitation. Our work provides a comprehensive description of the CsPbBr3 perovskites photophysics, offering novel insights on the light-induced response of the system and its exceptional optoelectronic properties.

en: Quantifying photoinduced polaronic distortions in inorganic lead halide perovskites nanocrystals

electron-phonon-coupling

display_name: electron-phonon-coupling

frohilch-polarons

display_name: frohilch-polarons

halide-perovskites

display_name: halide-perovskites

marvel

display_name: marvel

time-dependent-x-ray-absorption

display_name: time-dependent-x-ray-absorption


materialscloud

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

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


en: Understanding the catalyst compositional and structural features that control selectivity is of uttermost importance to target desired products in chemical reactions. In this joint experimental–computational work, we leverage tailored Cu/ZnO precatalysts as a material platform to identify the intrinsic features of methane-producing and ethanol-producing CuZn catalysts in the electrochemical CO2 reduction reaction (CO2RR). Specifically, we find that Cu@ZnO nanocrystals, where a central Cu domain is decorated with ZnO domains, and ZnO@Cu nanocrystals, where a central ZnO domain is decorated with Cu domains, evolve into Cu@CuZn core@shell catalysts that are selective for methane (∼52%) and ethanol (∼39%), respectively. Operando X-ray absorption spectroscopy and various microscopy methods evidence that a higher degree of surface alloying along with a higher concentration of metallic Zn improve the ethanol selectivity. Density functional theory explains that the combination of electronic and tandem effects accounts for such selectivity. These findings mark a step ahead towards understanding structure–property relationships in bimetallic catalysts for the CO2RR and their rational tuning to increase selectivity towards target products, especially alcohols.

en: Elucidating the structure-dependent selectivity towards methane and ethanol of CuZn in the CO2 electroreduction using tailored Cu/ZnO precatalysts

cu

display_name: cu

cuzn

display_name: cuzn

dft

display_name: dft

epfl

display_name: epfl

erc

display_name: erc


snsf

display_name: snsf


en: This dataset, consisting of 29 videos, has been used for the publication 'High-Throughput Activity Screening and Sorting of Single Catalyst Particles with a Droplet Microreactor Using Dielectrophoresis': "A droplet microreactor has been developed for fluorescence activated sorting of catalyst particles using dielectrophoresis. Fluid Catalytic Cracking (FCC) particles stained with styrene derivatives are analyzed with the developed analytical platform and sorted based on catalytic activity. Highly active and low-to-moderately active catalyst particles are sorted out, using 4-fluorostyrene or 4-methoxystyrene as a probe respectively. The FCC particles are encapsulated in liquid droplets, where the fluorescent FCC particles activate the dielectrophoretic sorter, and are sorted within 200 ms."

en: High-throughput activity screening and sorting of single catalyst particles with a droplet microreactor using dielectrophoresis

dielectrophoretic-sorting

display_name: dielectrophoretic-sorting

experimental

display_name: experimental

fluid-catalytic-cracking-catalyst

display_name: fluid-catalytic-cracking-catalyst


materialscloud

en: Materials Cloud


en:
In order to identify novel substrate materials, we developed a high-throughput bond breaking algorithm. This algorithm takes a three-dimensional crystal as input, systematically breaks bonds, and checks if the bonding network has been reduced to two periodic directions. We apply this algorithm to Materials Project database and identify 4,693 symmetrically unique cleaved surfaces across 2,133 crystals. We then characterize the thermodynamic stability of these cleaved surfaces using the DFT software VASP, characterizing 3,991 surfaces as potential substrates with energy comparable to the experimentally used substrates (0001) AlN, ZnO, and CdS.

This repository contains the structure files, setting files, pseudopotential choices, bulk precursor structure and MaterialsProject ID, and thermodynamic data for the substrates considered in this work.

en: Computational synthesis of substrates by crystal cleavage

envi

en: Environment

high-throughput

display_name: high-throughput

lattice-matching

display_name: lattice-matching

substrate

display_name: substrate

vasp

display_name: vasp


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

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: By combining metal nodes and organic linkers, an  infinite number of metal organic frameworks (MOFs) can be designed in silico. When making new databases of such hypothetical MOFs, we need to assure that they not only contribute towards the growth of the count of structures but also add different chemistry to existing databases. In this work, we designed a database of ~20,000 hypothetical MOFs which are diverse in terms of their chemical design space—metal nodes, organic linkers, functional groups and pore geometries. Using Machine Learning techniques, we visualized and quantified the diversity of these structures. We then assessed the usefulness of diverse structures by evaluating their performance, using grand-canonical Monte Carlo simulations, in two important environmental applications---post combustion carbon capture and hydrogen storage. We find that many of these structures perform better than widely used benchmark materials such as Zeolite-13X (for post combustion carbon capture) and MOF-5 (for hydrogen storage).

en: Diversifying databases of metal organic frameworks for high-throughput computational screening

diversity

display_name: diversity

machine-learning

display_name: machine-learning

metal-organic-frameworks

display_name: metal-organic-frameworks

molecular-simulations

display_name: molecular-simulations


erc

display_name: erc


en: The quantum effect of light nuclei in materials is usually considered as lattice vibration and zero-point motion (ZPM) from an ab initio perspective. Here we start from full-quantized particles and take the muon as an example, considering the two-body quantized system of the muon and the electrons within Two-Component Density Functional Theory, which can calculate the related two-body wave functions directly and automatically taking into account the quantum effect of the muon. This is an attempt to reveal the quantum effect of light nuclei in materials from a different respect. It is tested in some metallic systems (Fe-bcc, Co-fcc, Co-hcp) and some non-metallic systems (NaF, CaF₂, diamond), we finally find this fundamental method agrees better with experiments and shows good potential for further such study.

en: Two-component density functional theory study of quantized muons in solids

casino-quantum-monte-carlo

display_name: casino-quantum-monte-carlo

quantum-espresso

display_name: quantum-espresso


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

ab-initio

display_name: ab-initio

molecular-dynamics

display_name: molecular-dynamics


materialscloud

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

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


en:
A comprehensive description of photo-chemical processes in materials, comprising spin-forbidden processes such as intersystem crossing and phosphorescence, implies to take into account spin-orbit coupling. We present an efficient implementation of a perturbative spin-orbit coupling correction for the Tamm-Dancoff approximation of linear-response time-dependent density functional theory within a mixed Gaussian and plane waves framework relying on spin-orbit coupling corrected pseudopotentials. The implementation is validated for a benchmark set of small aromatic molecules, with mean errors in excitation energies and spin-orbit coupling matrix elements being in the range of 0.1 - 0.6 eV and 1.0 to 13.8 cm⁻¹ in comparison to density functional theory and density functional theory multi-reference configuration interaction reference results. Computational timings are given for a bismuth-containing metal-organic framework.
The data in this record are supplementary data to the manuscript linked below.

en: Perturbative spin-orbit couplings for the simulation of extended framework materials

spin-orbit-coupling

display_name: spin-orbit-coupling


en: This entry provides original trajectories of on-the-fly probability enhanced sampling (OPES) and of molecular dynamics simulations and images of nudged-elastic band (NEB) calculation. Jupyter notebooks are provided for a NEB profile, NEB collective variables, free energy surface of the OPES simulations, hole transfer of the OPES simulations, proton transfer mechanisms of of the OPES simulations, water density profiles of MD simulations, radial distribution functions of MD simulations, reweight of Bi-O bonds of OPES simulations, coordination numbers of surface Bi atoms and hydrogen-bond analysis of proton transfer.

en: Data and analyses for first proton-coupled electron transfer of water oxidation at the BiVO₄-water interface

machine-learning-potentials

display_name: machine-learning-potentials

on-the-fly-probability-sampling

display_name: on-the-fly-probability-sampling

opes

display_name: opes

proton-couple-electron-transfer

display_name: proton-couple-electron-transfer

reweighting

display_name: reweighting


materialscloud

en: Materials Cloud


en: Unlocking the potential of topological order within many-body spin systems has long been a central pursuit in the realm of quantum materials. Despite extensive efforts, the quest for a versatile platform enabling site-selective spin manipulation, essential for tuning and probing diverse topological phases, has persisted. Here, we utilize on-surface synthesis to construct spin-1/2 alternating-exchange Heisenberg (AH) chains with antiferromagnetic couplings J1 and J2 by covalently linking Clar's goblets -- nanographenes each hosting two antiferromagnetically-coupled unpaired electrons. In a recent work, utilizing scanning tunneling microscopy, we exert atomic-scale control over the spin chain lengths, parities and exchange-coupling terminations, and probe their magnetic response by means of inelastic tunneling spectroscopy. Our investigation confirms the gapped nature of bulk excitations in the chains, known as triplons. Besides, the triplon dispersion relation is successfully extracted from the spatial variation of tunneling spectral amplitudes. Furthermore, depending on the parity and termination of chains, we observe varying numbers of in-gap S=1/2 edge spins, enabling the determination of the degeneracy of distinct topological ground states in the thermodynamic limit-either 1, 2, or 4. By monitoring interactions between these edge spins, we identify the exponential decay of spin correlations. Our experimental findings, corroborated by theoretical calculations, present a phase-controlled many-body platform, opening promising avenues toward the development of spin-based quantum devices. The record contains data and codes that support the results discussed in the manuscript.

en: Tunable topological phases in nanographene-based spin-½ alternating-exchange Heisenberg chains

magnetic-nanographene

display_name: magnetic-nanographene

spin-chian

display_name: spin-chian

topological-phase-transition

display_name: topological-phase-transition


envi

en: Environment


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

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

amorphous

display_name: amorphous

chalcogenides

display_name: chalcogenides

device-to-materials

display_name: device-to-materials

electronic-structure

display_name: electronic-structure

intersect

display_name: intersect

openmodel

display_name: openmodel

selectors

display_name: selectors


en:
The high-throughput molecular exploration and screening of organic electronic materials often starts with either a 'top-down' mining of existing repositories, or the 'bottom-up' assembly of fragments based on predetermined rules and known synthetic templates. In both instances, the datasets used are often produced on a case-by-case basis, and require the high-quality computation of electronic properties and extensive user input: curation in the top-down approach, and the construction of a fragment library and introduction of rules for linking them in the bottom-up approach. Both approaches are time-consuming and require significant computational resources. Here, we generate a top-down set named FORMED consisting of 117K synthesized molecules containing their optimized structures, associated electronic and topological properties and chemical composition, and use these structures as a vast library of molecular building blocks for bottom-up fragment-based materials design. A tool is developed to automate the coupling of these building block units based on their available Csp2-H bonds, thus providing a fundamental link between the two philosophies of dataset construction. Statistical models are trained on this dataset and a subset of the resulting hybrid top-down/bottom-up compounds (selected dimers), which enable on-the-fly prediction of key ground state (frontier molecular orbital gaps) and excited state (S1 and T1 energies) properties from molecular geometries with high accuracy across all known p-block organic compound space.
With access to ab initio-quality optical properties in hand, it is possible to apply this bottom-up pipeline using existing compounds as molecular building blocks to any materials design campaign. To illustrate this, we construct and screen over a million molecular candidates (predicted dimers) for efficient intramolecular singlet fission, the leading candidates of which provide insight into the structural features that may promote this multiexciton-generating process.

en: Data-driven discovery of organic electronic materials enabled by hybrid top-down/bottom-up design

crystal-structures

display_name: crystal-structures

donor-acceptor-copolymers

display_name: donor-acceptor-copolymers

marvel

display_name: marvel

optical-properties

display_name: optical-properties

organic-molecules

display_name: organic-molecules

photophysical-properties

display_name: photophysical-properties


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

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

atoms

display_name: atoms

density-functional-theory

display_name: density-functional-theory

hartree-fock

display_name: hartree-fock

high-precision

display_name: high-precision

hybrids

display_name: hybrids


en: We mine from the literature experimental data on the CO2 electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict Faradaic Efficiencies for 11 CO2RR products, as a function of the applied voltage at which the reaction takes place, and the relative amounts of non equivalent surface sites, distinguished according to their nominal coordination. A satisfactory model accuracy is found only when discriminating data according to their provenance. On one hand, this result points at a qualitative agreement across reported experimental CO2RR  trends for single-crystal surfaces with well-defined terminations. On the other, this finding hints at the presence of differences in nominally identical catalysts and/or CO2RR measurements, which result in quantitative disagreement between experiments.

en: What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO2 reduction? A data-driven retrospective

catalysis

display_name: catalysis

cu

display_name: cu

gaussian-process

display_name: gaussian-process


en: Two-dimensional topological insulators are characterized by an insulating bulk and conductive edge states protected by the nontrivial topology of the bulk electronic structure. They remain robust against moderate disorder until Anderson localization occurs and destroys the topological phase. Interestingly, disorder can also induce a topological phase—known as a topological Anderson insulator—starting from an otherwise pristine trivial phase. While topological invariants are generally regarded as global quantities, we argue that space-resolved topological markers can act as local order parameters, revealing the role of fluctuations and correlations in the local topology under Anderson disorder and vacancies. With this perspective, we perform numerical simulations of disorder-driven topological phase transitions in the Haldane and Kane-Mele models, using supercells with both open and periodic boundary conditions. We find that short-scale fluctuations of topological markers vanish upon coarse-graining, except at the topological phase transition, where their correlation length peaks and large-scale fluctuations remain.

materialscloud

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

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

en: Fluctuations and correlations of local topological order parameters in disordered two-dimensional topological insulators

anderson-disorder

display_name: anderson-disorder

fluctuations-and-correlations

display_name: fluctuations-and-correlations

haldane-model

display_name: haldane-model

kane-mele-model

display_name: kane-mele-model

local-topology

display_name: local-topology

topological-order-parameters

display_name: topological-order-parameters

vacancies

display_name: vacancies


en: Ideal magnetic frustration forms the basis for the emergence of exotic quantum spin states that are entirely nonmagnetic. Such singlet spin states are the defining feature of the Shastry-Sutherland model, and of its faithful materials realization in the quantum antiferromagnet SrCu₂(BO₃)₂. To address these states on ultrafast timescales, despite their lack of any microscopic order parameter, we introduce a nonlinear magnetophononic mechanism to alter the quantum spin dynamics by driving multiple optical phonon modes coherently and simultaneously. We apply intense terahertz pulses to create a nonequilibrium modulation of the magnetic interactions that breaks the ideal frustration of SrCu₂(BO₃)₂, such that previously forbidden physics can be driven in a coherent manner. Specifically, this driving populates a purely magnetic excitation, the singlet branch of the two-triplon bound state, by resonance with the difference frequency of two pumped phonons. Our results demonstrate how light-driven phonons can be used for the ultrafast and selective manipulation of interactions in condensed matter, even at frequencies far from those of the pump spectrum, offering valuable additional capabilities for the dynamical control of quantum many-body phenomena.

en: Ultrafast frustration-breaking and magnetophononic driving of singlet excitations in a quantum magnet

magnetophononic

display_name: magnetophononic

quantum-magnetic-materials

display_name: quantum-magnetic-materials

snsf

display_name: snsf

strongly-correlated-electrons

display_name: strongly-correlated-electrons

tera-hertz-pump-and-probe

display_name: tera-hertz-pump-and-probe


en: The resolution of proton solid-state NMR spectra is usually limited by broadening arising from dipolar interactions between spins. Magic-angle spinning alleviates this broadening by inducing coherent averaging. However, even the highest spinning rates experimentally accessible today are not able to completely remove dipolar interactions. Here, we introduce a deep learning approach to determine pure isotropic proton spectra from a two-dimensional set of magic-angle spinning spectra acquired at different spinning rates. Applying the model to 8 organic solids yields high-resolution 1H solid-state NMR spectra with isotropic linewidths in the 50-400 Hz range.

materialscloud

en: Materials Cloud

en: Pure isotropic proton NMR spectra in solids using deep learning

machine-learning

display_name: machine-learning

nmr

display_name: nmr

resolution

display_name: resolution


envi

en: Environment


en: Predicting the thermal conductivity of glasses from first principles has hitherto been a prohibitively complex problem. In fact, past works have highlighted challenges in achieving computational convergence with respect to length and/or time scales using either the established Allen-Feldman or Green-Kubo formulations, endorsing the concept that atomistic models containing thousands of atoms — thus beyond the capabilities of first-principles calculations — are needed to describe the thermal conductivity of glasses. In addition, these established formulations either neglect anharmonicity (Allen-Feldman) or miss the Bose-Einstein statistics of atomic vibrations (Green Kubo), thus leaving open the question on the relevance of these effects. Here, we present a first-principles formulation to address the thermal conductivity of glasses above the plateau, which can account comprehensively for the effects of structural disorder, anharmonicity, and quantum Bose-Einstein statistics. The protocol combines the Wigner formulation of thermal transport with convergence-acceleration techniques, and is validated in vitreous silica using both first-principles calculations and a quantum-accurate machine-learned interatomic potential. We show that models of vitreous silica containing less than 200 atoms can already reproduce the thermal conductivity in the macroscopic limit and that anharmonicity negligibly affects heat transport in vitreous silica. We discuss the microscopic quantities that determine the trend of the conductivity at high temperature, highlighting the agreement of the calculations with experiments in the temperature range above the plateau where radiative effects remain negligible (50<∼T <∼450 K).

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

atomic-vibrations

display_name: atomic-vibrations

first-principles

display_name: first-principles

thermal-transport

display_name: thermal-transport

vitreous-silica

display_name: vitreous-silica


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

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


en:
MXenes represent one of the largest class of 2D materials with promising applications in many fields and their properties tunable by the surface group composition. Raman spectroscopy is expected to yield rich information about the surface composition, but the interpretation of measured spectra has proven challenging. The interpretation is usually done via comparison to simulated spectra, but there are large discrepancies between the experimental and earlier simulated spectra. In this work, we develop a computational approach to simulate Raman spectra of complex materials that combines machine-learning force-field molecular dynamics and reconstruction of Raman tensors via projection to pristine system modes. The approach can account for the effects of finite temperature, mixed surfaces, and disorder. We apply our approach to simulate Raman spectra of titanium carbide MXene and show that all these effects must be included in order to properly reproduce the experimental spectra, in particular the broad features. We discuss the origin of the peaks and how they evolve with surface composition, which can then be used to interpret experimental results.

This record contains input files for MLFF training and production runs, information on the training set (atomic structures, energies and forces) and some of the molecular dynamics trajectories used to obtain Raman spectra.

en: Raman spectra of 2D titanium carbide MXene from machine-learning force field molecular dynamics

molecular-dynamics

display_name: molecular-dynamics

raman-spectroscopy

display_name: raman-spectroscopy


en: The electronic, optical, and magnetic properties of graphene nanoribbons (GNRs) can be engineered by controlling their edge structure and width with atomic precision through bottom-up fabrication based on molecular precursors. This approach offers a unique platform for all-carbon electronic devices but requires careful optimization of the growth conditions to match structural requirements for successful device integration, with GNR length being the most critical parameter. In a recent work we study, the growth, characterization, and device integration of 5-atom wide armchair GNRs (5-AGNRs), which are expected to have an optimal bandgap as active material in switching devices. 5-AGNRs are obtained via on-surface synthesis under ultrahigh vacuum conditions from Br- and I-substituted precursors. It is shown that the use of I-substituted precursors and the optimization of the initial precursor coverage quintupled the average 5-AGNR length. This significant length increase allowed the integration of 5-AGNRs into devices and the realization of the first field-effect transistor based on narrow bandgap AGNRs that shows switching behavior at room temperature. The study highlights that the optimized growth protocols can successfully bridge between the sub-nanometer scale, where atomic precision is needed to control the electronic properties, and the scale of tens of nanometers relevant for successful device integration of GNRs. The record contains data supporting the results presented in the publication

en: Growth optimization and device integration of narrow-bandgap graphene nanoribbons

dft

display_name: dft

fet

display_name: fet

graphene-nanoribbons

display_name: graphene-nanoribbons

grapheneflagship

display_name: grapheneflagship

gw

display_name: gw

marvel

display_name: marvel

raman

display_name: raman


en: In this record we provide the data to support our recent finding on the synthesis of edge-extended zigzag graphene nanoribbons. Graphene nanoribbons (GNRs) have gained significant attention in nanoelectronics due to their potential for precise tuning of electronic properties through variations in edge structure and ribbon width. However, the synthesis of GNRs with highly sought‐after zigzag edges (ZGNRs), critical for spintronics and quantum information technologies, remains challenging. In the manuscript where the data presented here is discussed, a design motif for synthesizing a novel class of GNRs termed edge‐extended ZGNRs is presented. This motif enables the controlled incorporation of edge extensions along the zigzag edges at regular intervals. The synthesis of a specific GNR instance—a 3‐zigzag‐rows‐wide ZGNR—with bisanthene units fused to the zigzag edges on alternating sides of the ribbon axis is successfully demonstrated. The resulting edge‐extended 3‐ZGNR is comprehensively characterized for its chemical structure and electronic properties using scanning probe techniques, complemented by density functional theory calculations. The design motif showcased in the manuscript opens up new possibilities for synthesizing a diverse range of edge‐extended ZGNRs, expanding the structural landscape of GNRs and facilitating the exploration of their structure‐dependent electronic properties.

en: On‐surface synthesis of edge‐extended zigzag graphene nanoribbons

density-functional-theory

display_name: density-functional-theory

on-surface-synthesis

display_name: on-surface-synthesis

snsf

display_name: snsf


materialscloud

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

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


en: The CO₂ hydrogenation reaction to produce methanol holds great significance as it contributes to achieving a CO₂-neutral economy. Previous research identified isolated Cu⁺ species doping the oxide surface of a Cu-MgO-Al₂O₃ mixed oxide derived from a hydrotalcite precursor as the active site in CO₂ hydrogenation, stabilizing monodentate formate species as a crucial intermediate in methanol synthesis. In this work, we present a molecular-level understanding of how surface water and hydroxyl groups play a crucial role in facilitating spontaneous CO₂ activation at Cu⁺ sites and the formation of monodentate formate species. The computational evidence has been experimentally validated by comparing the catalytic performance of the Cu-MgO-Al₂O₃ catalyst with hydroxyl groups against its hydrophobic counterpart, where hydroxyl groups are blocked using an esterification method. Our work highlights the synergistic effect between doped Cu⁺ ions and adjacent hydroxyl groups, both of which serve as key parameters in regulating methanol production via CO₂ hydrogenation. By elucidating the specific roles of these components, we contribute to advancing the understanding of the underlying mechanisms and provide valuable insights for optimizing methanol synthesis processes.

en: Water and Cu⁺ synergy in selective CO₂ hydrogenation to methanol over Cu/MgO catalysts

computational-chemistry

display_name: computational-chemistry

copper

display_name: copper

heterogeneous-catalysis

display_name: heterogeneous-catalysis

methanol

display_name: methanol

mgo

display_name: mgo


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

electronic-structure

display_name: electronic-structure

manganese-oxide

display_name: manganese-oxide

many-body-perturbation-theory

display_name: many-body-perturbation-theory

vertex-corrections

display_name: vertex-corrections


materialscloud

en: Materials Cloud


en: Here, we develop a self-assembly technique to synthesize 1-nm-thick rutile-structured high-entropy oxides (RuIrFeCoCrO₂) from naked metal ions assembly and oxidation at air-molten salt interface. The RuIrFeCoCrO₂ only requires an overpotential of 185 mV at 10 m A cm⁻² and maintains the high activity for over 1000 hours in an acidic electrolyte via the adsorption evolution mechanism. In this dataset, we calculated the desolvation coefficient (D) of various cations in aqueous solution and molten salt. In molten salt, the corresponding D for metal ions is higher by several orders of magnitude compared to that in water, which allows metal ions to become freely moving ions. We also conducted DFT calculations to gain insight to the structural stability and reaction mechanism of this HEO. The results show that the reaction mechanism changes from LOM (RuO₂) to AEM (RuIrFeCoCrO₂).

en: Atomically thin high-entropy oxides via naked metal ion self-assembly for proton exchange membrane electrolysis

envi

en: Environment

dft

display_name: dft

electrocatalysis

display_name: electrocatalysis

high-entropy-oxides

display_name: high-entropy-oxides


en: Using density-functional theory, we demonstrate that the formal layer charges of the metallic samarium nickelate electrode influence the spontaneous ferroelectric polarization of the barium titanate in SmNiO₃/BaTiO₃ capacitors. We find that, despite the metallic screening of SmNiO₃, the spontaneous polarization of BaTiO₃ always aligns with the layer polarization of the SmNiO₃ formal charges. We also find zero critical thickness for the ferroelectricity in BaTiO₃ in this orientation. The opposite polarization direction is highly disfavored for thin BaTiO₃ slabs but becomes less unstable with increasing slab thickness. We construct a simple electrostatic model that allows us both to study the behavior for thicker BaTiO₃ and SmNiO₃ slabs and to extract the influence of various material parameters on the behavior. We mimic a metal-insulator transition in the SmNiO₃ by varying the metallic screening length, which we find influences the stability of the ferroelectric polarization. Our results show that layer charges in the metal electrodes strongly influence the properties of ferroelectric capacitors and can even provide new ways to control them.

en: Interplay of metallicity, ferroelectricity and layer charges in SmNiO₃/BaTiO₃ superlattices

ferroelectricity

display_name: ferroelectricity

polar-discontinuity

display_name: polar-discontinuity


en: Harnessing the most advanced capabilities of quantum technologies will require the ability to control macroscopic quantum states of matter. Quantum magnetic materials provide a valuable platform for realizing highly entangled many-body quantum systems, and have been used to investigate phenomena ranging from quantum phase transitions (QPTs) to fractionalization, topological order and the entanglement structure of the quantum wavefunction. Although multiple studies have controlled their properties by static applied pressures or magnetic fields, dynamical control at the fundamental timescales of their magnetic interactions remains completely unexplored. However, major progress in the technology of ultrafast laser pulses has enabled the dynamical modification of electronic properties, and now we demonstrate the ultrafast control of quantum magnetism. This we achieve by a magnetophononic mechanism, the driving of coherent lattice displacements to produce a resonant excitation of the quantum spin dynamics. Specifically, we apply intense terahertz laser pulses to excite a collective spin state of the quantum antiferromagnet SrCu2(BO3)2 by resonance with the nonlinear mixing frequency of the driven phonons that modulate the magnetic interactions. Our observations indicate a universal mechanism for controlling nonequilibrium quantum many-body physics on timescales many orders of magnitude faster than those achieved to date.

en: Nonlinear quantum magnetophononics in SrCu2(BO3)2

magnetophononic

display_name: magnetophononic

marvel

display_name: marvel

quantum-magnetic-materials

display_name: quantum-magnetic-materials

strongly-correlated-electrons

display_name: strongly-correlated-electrons

tera-hertz-pump-and-probe

display_name: tera-hertz-pump-and-probe


en: Ideal magnetic frustration forms the basis for the emergence of exotic quantum spin states that are entirely nonmagnetic. Such singlet spin states are the defining feature of the Shastry-Sutherland model, and of its faithful materials realization in the quantum antiferromagnet SrCu₂(BO₃)₂. To address these states on ultrafast timescales, despite their lack of any microscopic order parameter, we introduce a nonlinear magnetophononic mechanism to alter the quantum spin dynamics by driving multiple optical phonon modes coherently and simultaneously. We apply intense terahertz pulses to create a nonequilibrium modulation of the magnetic interactions that breaks the ideal frustration of SrCu₂(BO₃)₂, such that previously forbidden physics can be driven in a coherent manner. Specifically, this driving populates a purely magnetic excitation, the singlet branch of the two-triplon bound state, by resonance with the difference frequency of two pumped phonons. Our results demonstrate how light-driven phonons can be used for the ultrafast and selective manipulation of interactions in condensed matter, even at frequencies far from those of the pump spectrum, offering valuable additional capabilities for the dynamical control of quantum many-body phenomena.

en: Ultrafast frustration-breaking and magnetophononic driving of singlet excitations in a quantum magnet

snsf

display_name: snsf


en: In this paper, we present a workflow that is designed to work without manual intervention to efficiently predict, by using molecular simulations, the thermodynamic data that is needed to design a carbon capture process. We developed a procedure that does not rely on fitting of the adsorption isotherms. From molecular simulations, we can obtain accurate data for both, the pure component isotherms as well as the mixture isotherms. This allowed us to make a detailed comparison of the different methods to predict the mixture isotherms. All approaches rely on an accurate description of the pure component isotherms and a model to predict the mixture isotherms. As we are interested in low CO₂ concentrations, it is essential that these models correctly predict the low pressure limit, i.e., give a correct description of the Henry regime. Among the equations that describe this limit correctly, the dual-site Langmuir (DSL) model is often used for the pure components and the extended DSL (EDSL) for the mixtures. An alternative approach, which avoids describing the pure component isotherms with a model, is to numerically integrate the pure component isotherms in the context of IAST.  In this work we compare these two methods. In addition, we show that the way these data are fitted for DSL can significantly impact the ranking of materials, in particular for capture processes with low concentration of CO₂ in the feed stream.

en: Towards a robust evaluation of nanoporous materials for carbon capture applications

dual-site-langmuir-dsl

display_name: dual-site-langmuir-dsl

ideal-adsorbed-solution-theory-iast

display_name: ideal-adsorbed-solution-theory-iast

metal-organic-frameworks-mofs

display_name: metal-organic-frameworks-mofs

temperature-swing-adsorption-tsa

display_name: temperature-swing-adsorption-tsa


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

materialscloud

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

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

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

catalystelectrolyte-interface

display_name: catalystelectrolyte-interface

electrochemical-impedance-spectroscopy

display_name: electrochemical-impedance-spectroscopy

frequency-dispersion-of-capacitance

display_name: frequency-dispersion-of-capacitance

interfacial-capacitance

display_name: interfacial-capacitance

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


en: The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations that are relevant to extend this approach beyond density functional theory (DFT), in order to automate many-body perturbation theory (MBPT) calculations. Notably, a novel algorithm pursuing the goal of an efficient and robust convergence procedure for GW and BSE simulations is provided, together with its implementation in a fully automated framework. This is accompanied by an automatic GW band interpolation scheme based on maximally-localized Wannier functions, aiming at a reduction of the computational burden of quasiparticle band structures while preserving high accuracy. The proposed developments are validated on a set of representative semiconductor and metallic systems.

en: Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

aiida

display_name: aiida

aiida-yambo

display_name: aiida-yambo

automated-many-body-perturbation-theory

display_name: automated-many-body-perturbation-theory

big-map

display_name: big-map

bse

display_name: bse

first-principles

display_name: first-principles

gw

display_name: gw

high-throughput

display_name: high-throughput

max

display_name: max

yambo-code

display_name: yambo-code


materialscloud

en: Materials Cloud

marvel

display_name: marvel


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

thermal-barrier-coating

display_name: thermal-barrier-coating

thermal-transport

display_name: thermal-transport


envi

en: Environment


en: The urgent need for clean energy coupled with the exceptional promise of hydrogen (H) as a clean fuel is driving development of new metals resistant to hydrogen embrittlement. Experiments on new fcc high entropy alloys present a paradox: these alloys absorb more H than Ni or SS304 (austenitic 304 stainless steel) while being more resistant to embrittlement. Here, a new theory of embrittlement in fcc metals is presented based on the role of H in driving an intrinsic ductile-to-brittle transition at a crack tip. The theory quantitatively predicts the H concentration at which a transition to embrittlement occurs in good agreement with experiments for SS304, SS316L, CoCrNi, CoNiV, CoCrFeNi, and CoCrFeMnNi. The theory rationalizes why CoNiV is the alloy most resistant to embrittlement and why SS316L is more resistant than the high entropy alloys CoCrFeNi and CoCrFeMnNi, which opens a path for the computationally guided discovery of new embrittlement-resistant alloys.

en: Mechanism and prediction of hydrogen embrittlement in fcc stainless steels and high entropy alloys

fracture

display_name: fracture

high-entropy-alloys

display_name: high-entropy-alloys

hydrogen-embrittlement

display_name: hydrogen-embrittlement

snsf

display_name: snsf


en: A robust framework for generating adsorption isotherms to screen materials for carbon capture

dual-site-langmuir-dsl

display_name: dual-site-langmuir-dsl

ideal-adsorbed-solution-theory-iast

display_name: ideal-adsorbed-solution-theory-iast

metal-organic-frameworks-mofs

display_name: metal-organic-frameworks-mofs

temperature-swing-adsorption-tsa

display_name: temperature-swing-adsorption-tsa


en: Crystal-graph attention networks have emerged recently as remarkable tools for the prediction of thermodynamic stability and materials properties from unrelaxed crystal structures. Previous networks trained on two million materials exhibited, however, strong biases originating from underrepresented chemical elements and structural prototypes in the available data. We tackled this issue computing additional data to provide better balance across both chemical and crystal-symmetry space. Crystal-graph networks trained with this new data show unprecedented generalization accuracy, and allow for reliable, accelerated exploration of the whole space of inorganic compounds. We applied this universal network to performed machine-learning assisted high-throughput materials searches including 2500 binary and ternary prototypes and spanning about 1 billion compounds. After validation using density-functional theory, we uncover in total 19512 additional materials on the convex hull of thermodynamic stability and around 150000 compounds with a distance of less than 50 meV/atom from the hull. Here we include the DCGAT-1, DCGAT-2, and DCGAT-3 datasets used in this work.

en: Large-scale machine-learning-assisted exploration of the whole materials space

crystal-graph-attention-networks

display_name: crystal-graph-attention-networks

density-functional-theory

display_name: density-functional-theory


high-throughput

display_name: high-throughput


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

solute-strengthening

display_name: solute-strengthening

twinning

display_name: twinning


en: Many relationships important to civil engineering depend on surface roughness (morphology). Examples are the bond strength between concrete layers, the adhesion of a wheel to the pavement, the angle of friction in the soil in contact with a wall surface, and many other cases when we deal with a material with a surface having the characteristics of a Gaussian field. Based on scans of the natural concrete surfaces subjected to different smoothing processes, theoretical models were made. The observed features of the models were grouped into 25 categories belonging to the spherical semivariogram model. Each category is described by two parameters: range (with discrete domain 0.01, 0.04, 0.08, 0.16, 0.32) and upper limits (also with discrete domain 1, 2, 4 , 8, 16) with zero trend. For all combinations of range-limit pairs, homogeneous Gaussian random fields satisfying the spatial dependence of the category were generated in R software by using the RandomFields library. In the final step, the Blender rendering software was used. 1,000 images were taken for each category type using constant angle lighting and moving the camera over the generated surface. Users can download a set of 25,000 images to build or verify the surface classifier. The generated 25 types of surfaces are also provided.

en: Shadow-light images of simulated 25 classes of surface roughness for automatic classification

civil-engineering

display_name: civil-engineering

classification

display_name: classification

concrete

display_name: concrete

deep-learning

display_name: deep-learning

machine-learning

display_name: machine-learning

shadow-light-images

display_name: shadow-light-images

virtual-modeling

display_name: virtual-modeling


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).