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


$oid: OBSOLETE

materialscloud

approval_status: approved

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

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

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


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.

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.

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


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: 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: Materials Cloud

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

envi

en: Environment


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


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 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: 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

dft

display_name: dft

electrocatalysis

display_name: electrocatalysis

high-entropy-oxides

display_name: high-entropy-oxides


materialscloud

en: Materials Cloud


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


envi

en: Environment


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.

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 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).

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


materialscloud

en: Materials Cloud


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

envi

en: Environment

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


en: Pure magnesium (Mg) is an attractive metal for structural applications due to its low density, but also has low ductility and low fracture toughness. Dilute alloying of Mg with rare earth elements in small amounts improves the ductility, but the effects of alloying on fracture are not well-established. Here, the intrinsic fracture of a model Mg-3at%Y solid solution alloy is studied using a combination of anisotropic linear elastic fracture mechanics and atomistic simulations applied to a comprehensive set of crack configurations under mode I loading. The competition between brittle cleavage and ductile dislocation emission at the crack tip in Mg is improved slightly by alloying, because local fluctuations of the random solutes enable dislocation emission rather than cleavage fracture for a number of configurations where the differences in critical load for cleavage and emission are small. However, basalplane cleavage remains strongly preferred, as in pure Mg. The alloys do show higher fracture toughness for all configurations due to local solute-induced deformation phenomena at the crack tip. Thus, alloying with Y is expected to improve the fracture toughness of Mg, but the persistence of basal cleavage prevents the alloy from becoming intrinsically ductile for all orientations.

en: Intrinsic fracture behavior of Mg–Y alloys

alloy

display_name: alloy

fracture

display_name: fracture

magnesium

display_name: magnesium

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

snsf

display_name: snsf


en: We have studied the interaction of water and graphene doped with nitrogen in different configurations, namely, graphitic and pyridinic nitrogen, by means of the van der Waals density functional. We found that the local nitrogen configuration plays a key role in determining the stable water configuration, while the dispersion force is responsible for the water adsorption. With the graphitic nitrogen, water prefers to orient with its oxygen toward the surface, whereas for the pyridinic nitrogen it prefers to orient with its hydrogens toward the surface, because nitrogen is positively and negatively charged for the former and the latter, respectively. Our results have great implications for the modeling of the interface between water and nitrogen-doped graphitic systems.

en: Interaction of water with nitrogen-doped graphene

graphene

display_name: graphene

van-der-waals-density-functional

display_name: van-der-waals-density-functional

water

display_name: water


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: 'Magic'-angle twisted bilayer graphene has received a lot of interest due to its flat bands with potentially non-trivial topology that lead to intricate correlated phases. A spectrum with flat bands, however, does not require a twist between multiple sheets of van der Waals materials, but rather can be realized with the application of an appropriate periodic potential. Here, we propose the imposition of a tailored periodic potential onto a single graphene layer through local perturbations that could be created via lithography or adatom manipulation, which also results in an energy spectrum featuring flat bands. Our first-principle calculations for an appropriate decoration of graphene with adatoms indeed show the presence of flat bands in the spectrum. Furthermore, we reveal the topological nature of the flat bands through a symmetry-indicator analysis. This non-trivial topology manifests itself in corner-localized states with a filling anomaly as we show using a tight-binding model. Our proposal of a single decorated graphene sheet provides a new versatile route to study correlated phases in topologically non-trivial, flat band structures.

en: Flat bands with fragile topology through superlattice engineering on single-layer graphene

marvel

display_name: marvel

topological-materials

display_name: topological-materials

vasp

display_name: vasp


materialscloud

en: Materials Cloud


en: A statistical-mechanics analysis is used to create analytic estimates for the short-range order (SRO) parameters in FCC and BCC solid solution alloys as a function of composition and temperature. As in the classic quasi-chemical method, the analysis assumes pair interactions among atoms at different distances and partitions the entire crystal into a set of identical independent clusters that are then treated like molecules in a gas.  This enables analytic development of the probabilities that govern SRO.  For binary and ternary alloys, increasingly complex clusters are considered that systematically extend the range of accuracy of the analytic model relative to reference Monte Carlo simulations.  The results enable fast assessment of likely SRO using estimated inputs for atom-atom interaction energies. In this record we provide our analytical solution as well as the simulation data supporting our theoretical prediction of the short-range order parameter in both FCC and BCC alloys.

en: Analytical models of short-range order in FCC and BCC alloys

high-entropy-alloys

display_name: high-entropy-alloys

short-range-order

display_name: short-range-order

solid-solutions

display_name: solid-solutions

statistical-mechanics

display_name: statistical-mechanics


envi

en: Environment


en: The heterogeneously catalyzed HCl oxidation reaction (Deacon reaction) over ceria leads under typical reaction conditions to a reduction and surface chlorination of CeO2. The reduced single crystalline CeO2-x(111) model surface stabilizes various ordered surface structures, e.g. (√7 × √7)R19.1°, (3 × 3), or (4 × 4), depending on the concentration of oxygen vacancies (VO). Saturating these phases with HCl at room temperature, followed by annealing to the process temperature of 700 K, leads in all cases to a uniformly covering (√3 × √3)R30° overlayer structure with identical Cl coverage and identical adsorption geometry. Low energy electron diffraction (LEED) fingerprinting, density functional theory (DFT) calculations and X-ray photoelectron spectroscopy (XPS) evidence that Cl adsorbs into the O-vacancy at the surface (Clvac) with a high adsorption energy (>2 eV). From thermal desorption spectroscopy (TDS) and XPS of Cl 2p the adsorption energy of Clvac and the water formation is found to dependent sensitively on the degree of bulk-reduction x of CeO2-x(111). Chlorine desorption in TDS shifts from 1175 K to 1320 K when the the reduction degree x is increased from CeO1.8(111) (x = 0.2) to CeO1.6(111) (x = 0.4). In order to rationalize why the formation of (√3 × √3)R30°-Clvac structure on CeO2-x(111) is independent of the original reduction degree x of CeO2 x(111), efficient diffusion of surface and bulk oxygen vacancies (VO) is required.

en: Dynamic response of oxygen vacancies on the Deacon reaction over reduced single crystalline CeO₂-x(111) surfaces

chlorine-adsorption

display_name: chlorine-adsorption

deacon-process

display_name: deacon-process

hcl-oxidation

display_name: hcl-oxidation

leed-fingerprinting

display_name: leed-fingerprinting

oxygen-vacancy-mobility

display_name: oxygen-vacancy-mobility

reduced-ceria

display_name: reduced-ceria


en: We present a combined study based on experimental measurements of infrared (IR) dielectric function and first-principles calculations of IR spectra and vibrational density of states (VDOS) of amorphous alumina (am-Al₂O₃). In particular, we show that the main features of the imaginary part of the dielectric function ε₂(ω) at ~380 and 630 cm-¹ are related to the motions of threefold coordinated oxygen atoms, which are the vast majority of oxygen atoms in am-Al₂O₃. Our analysis (involving three model structures) provides an alternative point of view with respect to an earlier suggested assignment of the vibrational modes, which relates them to the stretching and bending vibrational modes of AlOₙ (n = 4, 5, and 6) polyhedra. Our assignment is based on the additive decomposition of the VDOS and ε₂(ω) spectra, which shows that: (i) the band at ~380 cm-¹ features oxygen motions occurring in a direction normal to the plane defined by the three nearest-neighbor aluminum atoms, i.e. out-of-plane motions of oxygen atoms; (ii) Al-O stretching vibrations (i.e. in-plane motions of oxygen atoms) appear at frequencies above ~500 cm-¹, which characterize the vibrational modes underlying the band at ~630 cm-¹.

en: Infrared spectra in amorphous alumina

dft

display_name: dft

infrared

display_name: infrared

vdos

display_name: vdos


infrared-spectra-in-amorphous-alumina

title_for_slug: infrared-spectra-in-amorphous-alumina


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

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

electrochemical-barriers

display_name: electrochemical-barriers

electrochemical-kinetics

display_name: electrochemical-kinetics

proton-electron-transfer-reactions

display_name: proton-electron-transfer-reactions


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

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

epfl

display_name: epfl

lab-cosmo

display_name: lab-cosmo

machine-learning

display_name: machine-learning

marvel

display_name: marvel

max

display_name: max

snsf

display_name: snsf

solid-state-electrolytes

display_name: solid-state-electrolytes

swissuniversities

display_name: swissuniversities

thermal-transport

display_name: thermal-transport


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

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

arpes-dft

display_name: arpes-dft

nccr-marvel

display_name: nccr-marvel

vhss

display_name: vhss


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

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

alloy-discovery

display_name: alloy-discovery

bcc

display_name: bcc

high-entropy-alloys

display_name: high-entropy-alloys

solute-strengthening

display_name: solute-strengthening


materialscloud

en: Materials Cloud


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

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

quantum-computing

display_name: quantum-computing

quantum-simulation

display_name: quantum-simulation

real-time-evolution

display_name: real-time-evolution


envi

en: Environment


en: We present a method, based on the classical Green-Kubo theory of linear response, to compute the heat conductivity of extended systems, leveraging energy-density, rather than energy-current, fluctuations, thus avoiding the need to devise an analytical expression for the macroscopic energy flux. The implementation of this method requires the evaluation of the long-wavelength and low-frequency limits of a suitably defined correlation function, which we perform using a combination of recently-introduced cepstral-analysis and Bayesian extrapolation techniques. Our methodology is demonstrated against standard current-based Green-Kubo results for liquid argon and water, and solid amorphous Silica, and compared with a recently proposed similar technique, which utilizes mass-density, instead of energy-density, fluctuations.

en: Heat conductivity from energy-density fluctuations

energy-density

display_name: energy-density

equilibrium-molecular-dynamics

display_name: equilibrium-molecular-dynamics

heat-conductivity

display_name: heat-conductivity


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

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

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

marvel

display_name: marvel

on-surface-synthesis

display_name: on-surface-synthesis

stm

display_name: stm


en:
The behavior of adsorbate-induced surface transformation can be clearly understood given the mechanical aspects of such phenomenon are well described at the atomic level. In this study, we provide the atomic-level description on the formation of Cu clusters on the Cu(111) surface by performing set of molecular dynamics simulations driven by machine-learning force-field. The machine learning technique called Gaussian Process (GP), as implemented in FLARE v1.1.2 (https://github.com/mir-group/flare/tree/1.1.2) was used to construct the machine-learning force-field. The dynamics simulations were performed using LAMMPS v29Sept2021 (https://github.com/lammps/lammps/tree/stable_29Sep2021_update2). This archive contains some supplementary data including the validation structures and also the MGP potential used to drive the MD simulations in LAMMPS. Additionally, the GP potential (before mapping) containing the database of atomic environment is also made available.

The simulations at 450 K–550 K show clusters are formed within a hundred of ns when the Cu surface is exposed with CO. On the other hand, no cluster is formed within the same time interval on the clean Cu surface even at 550 K, which signifies the importance of CO exposure to the surface transformation. The effect of temperature to the formation of clusters is also investigated. The CO-decorated Cu clusters ranging from dimer to hexamer are detected within a hundred of ns at 450 K. Lowering the temperature to 350 K does not result in the formation of clusters within a hundred ns due to the scarce detachments of adatom, while raising the temperature to 550 K results in the formation of more clusters, ranging from dimer to heptamer, but with shorter lifetimes. The clusters can be formed directly through instantaneous detachment of a group of step-atoms or indirectly by aggregation of wandering Cu monomers and smaller clusters on the surface terrace. The preference to the indirect mechanism is indicated by the higher frequency of its occurrence. More details on the procedures and results of the research can be found in the paper.

en: Machine learning molecular dynamics simulation of CO-driven formation of Cu clusters on the Cu(111) surface

carbon-monoxide

display_name: carbon-monoxide

cu-surface

display_name: cu-surface

machine-learning

display_name: machine-learning

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

surface-reconstruction

display_name: surface-reconstruction


en: Superlattices made of alternating blocks of the phase change compound Sb₂Te₃ and of TiTe₂ confining layers have been recently proposed for applications in neuromorphic devices. The Sb₂Te₃/TiTe₂ heterostructure allows for a better control of multiple intermediate resistance states and for a lower drift with time of the electrical resistance of the amorphous phase. However, Sb₂Te₃ suffers from a low data retention due to a low crystallization temperature Tx. Substituting Sb₂Te₃ with a phase change compound with a higher Tx, such as GeTe, seems an interesting option in this respect. Nanoconfinement might, however, alters the crystallization kinetics with respect to the bulk. In this work, we investigated the crystallization process of GeTe nanoconfined in geometries mimicking GeTe/TiTe₂ superlattices by means of molecular dynamics simulations with a machine learning potential. The simulations reveal that nanoconfinement induces a mild reduction in the crystal growth velocities which would not hinder the application of GeTe/TiTe₂ heterostructures in neuromorphic devices with superior data retention.

en: Crystallization kinetics of nanoconfined GeTe slabs in GeTe/TiTe-like superlattices for phase change memories

crystallization

display_name: crystallization

gete

display_name: gete

nanoconfinement

display_name: nanoconfinement

neural-network-potential

display_name: neural-network-potential

neuromophic-computing

display_name: neuromophic-computing

phase-change-materials

display_name: phase-change-materials

phase-change-memories

display_name: phase-change-memories

superlattices

display_name: superlattices


en: The Random-Phase approximation (RPA) provides an appealing framework for semi-local density functional theory. In its current formulation, it is cost-effective and has a better scaling behaviour compared to other wavefunction based correlation methods. To broaden the application field for RPA, it is necessary to have first order properties available. RPA nuclear gradients allow for structure optimizations and data sampling for machine learning applications. We report on an efficient implementation of RPA nuclear gradients for massively parallel computers. We apply the implementation to two polymorphs of the benzene crystal obtaining very good cohesive and relative energies. Different correction and extrapolation schemes are investigated for further improvement of the results and in order to estimate error bars.

en: Massively parallel implementation of gradients within the Random Phase Approximation: Application to the polymorphs of benzene

benzene

display_name: benzene

density-functional-theory

display_name: density-functional-theory

high-performance-computing

display_name: high-performance-computing

nuclear-gradients

display_name: nuclear-gradients

pasc

display_name: pasc

polymorphs

display_name: polymorphs

random-phase-approximation

display_name: random-phase-approximation


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 time-honored Allen-Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that the harmonic approximation predicts that the bulk lattice thermal conductivity of harmonic solids inevitably diverges at any temperature, irrespective of configurational disorder, and that its ability to represent the heat-transport properties observed experimentally in most glasses is implicitly due to finite-size effects. Our theoretical analysis is thoroughly benchmarked against careful numerical simulations. Our findings thus reveal that a proper account of anharmonic effects is indispensable to predict a finite value for the bulk thermal conductivity in any solid material, be it crystalline or glassy. This record contains data and scripts to support the findings of the manuscript and ensure their reproducibility.

en: Unearthing the foundational role of anharmonicity in heat transport in glasses

amorphous-solids

display_name: amorphous-solids

glass

display_name: glass

max

display_name: max

thermal-transport

display_name: thermal-transport


materialscloud

en: Materials Cloud


en: The piecewise linearity condition on the total energy with respect to the total magnetization of finite quantum systems is derived using the infinite-separation-limit technique. This generalizes the well-known constancy condition, related to static correlation error, in approximate density functional theory. The magnetic analog of Koopmans' theorem in density functional theory is also derived. Moving to fractional electron count, the tilted-plane condition is derived, lifting certain assumptions in previous works. This generalization of the flat-plane condition characterizes the total energy surface of a finite system for all values of electron count N and magnetization M. This result is used in combination with tabulated spectroscopic data to show the flat-plane structure of the oxygen atom, among others. We find that derivative discontinuities with respect to electron count sometimes occur at noninteger values. A diverse set of tilted-plane structures is shown to occur in d-orbital subspaces, depending on chemical coordination. General occupancy-based total-energy expressions are demonstrated thereby to be necessarily dependent on the symmetry-imposed degeneracies.

en: Tilted-plane structure of the energy of finite quantum systems

static-correlation-error

display_name: static-correlation-error


envi

en: Environment


en: Two-dimensional superconductors attract great interest both for their fundamental physics and for their potential applications, especially in the rapidly growing field of quantum computing.  In this, we predict a remarkably high superconducting critical temperature of 21 K in the easily exfoliable, topologically nontrivial 2D semimetal W2N3. Furthermore we study how strain and doping can affect its superconducting properties.

en: Prediction of phonon-mediated superconductivity with high critical temperature in the two-dimensional topological semimetal W2N3

electron-phonon-coupling

display_name: electron-phonon-coupling

marie-curie-fellowship

display_name: marie-curie-fellowship

prace

display_name: prace

snsf

display_name: snsf

superconductivity

display_name: superconductivity


en: Atomically precise graphene nanoflakes called nanographenes have emerged as a promising platform to realize carbon magnetism. Their ground state spin configuration can be anticipated by Ovchinnikov-Lieb rules based on the mismatch of π electrons from two sublattices. While rational geometrical design achieves specific spin configurations, further direct control over the π electrons offers a desirable extension for efficient spin manipulations and potential quantum device operations. To this end,  in a recent publication, we applied a site-specific dehydrogenation using a scanning tunneling microscope tip to nanographenes deposited on a Au(111) substrate, which showed the capability of precisely tailoring the underlying π-electron system and therefore efficiently manipulating their magnetism. Through first-principles calculations and tight-binding meanfield-Hubbard modeling, we demonstrated that the dehydrogenation-induced Au—C bond formation along with the resulting hybridization between frontier π orbitals and Au substrate states effectively eliminate the unpaired π electron. Our results establish an efficient technique for controlling the magnetism of nanographenes. This record contains data that support the scientific results discussed in our manuscript.

en: Tailoring magnetism of graphene nanoflakes via tip-controlled dehydrogenation

cscs

display_name: cscs

dft

display_name: dft

magnetic-nanographene

display_name: magnetic-nanographene

on-surface-synthesis

display_name: on-surface-synthesis

stm

display_name: stm


en:
Among the family of topological superconductors derived from Bi2Se3, Cux(PbSe)5(Bi2Se3)6 is unique in its surface termination of a single quintuple layer (QL) of the topological insulator (TI) Bi2Se3 on an ordinary insulator PbSe. Here, we report a combined scanning tunneling microscopy (STM) and density functional theory (DFT) characterization of the cleaved surface of the parent compound (PbSe)5(Bi2Se3)6 (PSBS). Interestingly, the potential disorder due to the random distribution of native defects is only Γ ∼ 4 meV, among the smallest reported for TIs. Performing high-resolution quasiparticle interference imaging (QPI) near the Fermi energy (E−EF = −1 eV to 0.6 eV) we reconstruct the dispersion relation of the dominant spectral feature and our ab initio calculations show that this surface feature originates from two bands with Rashba-like splitting due to strong spin-orbit coupling and inversion symmetry breaking. Moreover, a small hexagonal distortion of the calculated Fermi surface is seen in the full momentum space distribution of the measured scattering data. Interestingly, the scattering pattern transforms into a flower-like shape with suppressed intensity along the ΓK direction, at lower energies. However, this change is not due to the forbidden backscattering in the topological surface state in Bi2Se3 but the threefold symmetry of the scattering potential itself.

This dataset contains the experimental and theoretical data of this work.

en: Quasiparticle interference on the surface of Bi2Se3 terminated (PbSe)5(Bi2Se3)6

experimental

display_name: experimental

fleur

display_name: fleur

jukkr

display_name: jukkr

qpi

display_name: qpi

quasiparticle-interference

display_name: quasiparticle-interference

topological-materials

display_name: topological-materials

topological-superconductor

display_name: topological-superconductor


en: We present Molecular Vibration Explorer, a freely accessible online database and interactive tool for exploring vibrational spectra and tensorial light-vibration coupling strength of a large collection of thiolated molecules. The `Gold' version of the database gathers the results from density functional theory calculations on 2'800 commercially available thiol compounds linked to a gold atom, with the main motivation to screen the best molecules for THz and mid-infrared to visible upconversion. Additionally, the `Thiol' version of the database contains results for 1'900 unbound thiolated compounds.They both provide access to a comprehensive set of computed spectroscopic parameters for all vibrational modes of all molecules in the database. Infrared absorption, Raman scattering and vibrational sum- and difference frequency generation cross sections can be simultaneously investigated by the user. Molecules can be screened for various parameters in custom frequency ranges, such as large Raman cross-section under specific molecular orientation, or large orientation-averaged sum-frequency generation (SFG) efficiency. The user can select polarization vectors for the electromagnetic fields, set the orientation of the molecule and customize parameters for plotting the corresponding IR, Raman and sum-frequency spectra.

en: Molecular vibration explorer: an online database and toolbox for surface-enhanced frequency conversion, infrared and Raman spectroscopy

density-functional-theory

display_name: density-functional-theory

light-vibration-couplings

display_name: light-vibration-couplings

molecular-optomechanical-conversion

display_name: molecular-optomechanical-conversion

vibrational-properties

display_name: vibrational-properties


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

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

density-of-states

display_name: density-of-states

electronic-structure

display_name: electronic-structure

epfl

display_name: epfl

erc

display_name: erc

machine-learning

display_name: machine-learning

marvel

display_name: marvel

snsf

display_name: snsf


en:
Stable bound quantum states are ubiquitous in nature. Mostly, they result from the interaction of only pairs of particles, so called two-body interactions, even when large complex many-particle structures are formed. We show that three-particle bound states occur in a generic, experimentally accessible solid state system: antiferromagnetic spin ladders, related to high-temperature superconductors. Strikingly, this binding is induced by genuine three-particle interactions; without them there is no bound state. We compute the dynamic exchange structure factor required for the experimental detection of the predicted state by resonant inelastic x-ray scattering for realistic material parameters. Our work enables us to quantify these elusive interactions and unambiguously establishes their effect on the dynamics of the quantum many-particle state.
The data provided here contains the Green function and the weights of the dynamic exchange structure factor and the corresponding Lanczos coefficients.

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: Bound by three-body interactions

bound-state

display_name: bound-state

cut

display_name: cut

rixs

display_name: rixs

spin-ladder

display_name: spin-ladder

theoretical

display_name: theoretical

triplon

display_name: triplon


bound-by-three-body-interactions

materialscloud

en: Materials Cloud

title_for_slug: bound-by-three-body-interactions


en: We investigate the structural, electronic, vibrational, power, and transport properties of the β allotrope of Ga2O3 from first principles. We find phonon frequencies and elastic constants that reproduce the correct band ordering, in agreement with experiment. We use the Boltzmann transport equation to compute the intrinsic electron and hole drift mobility and obtain room-temperature values of 258 and 1.2 cm2/Vs, respectively, as well as 6300 and 13 cm2/Vs at 100 K. Through a spectral decomposition of the scattering contribution to the inverse mobility, we find that multiple longitudinal-optical modes of Bu symmetry are responsible for the electron mobility of β-Ga2O3 but that many acoustic modes also contribute, making it essential to include all scattering processes in the calculations. Using the von Hippel low-energy criterion, we computed the breakdown field to be 5.8 MV/cm at room temperature, yielding a Baliga figure of merit of 1250 with respect to silicon, ideal for high-power electronics. This work presents a general framework to predictively investigate novel high-power electronic materials.

en: Structural, electronic, elastic, power, and transport properties of β-Ga2O3 from first principles

ab-initio

display_name: ab-initio

breakdown-field

display_name: breakdown-field

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

marie-curie-fellowship

display_name: marie-curie-fellowship

prace

display_name: prace

transport

display_name: transport


envi

en: Environment


en: Osmium complexes with osmium in different oxidation states (II, III, IV, VI) have been reported to exhibit antiproliferative activity in cancer cell lines. Herein, we demonstrate unexplored opportunities offered by 187Os nuclear forward scattering (NFS) and nuclear inelastic scattering (NIS) of synchrotron radiation for characterization of hyperfine interactions and lattice dynamics in a benchmark Os(VI) complex, K₂[OsO₂(OH)₄]. The isomer shift (𝛿 = 3.3(1) mm/s) relative to [OsIVCl₆]2– and quadrupole splitting (𝚫EQ = 12.0(2) mm/s) were determined with NFS. The Lamb-Mössbauer factor (0.80(4)) is estimated, the density of phonon states (DOS) is extracted, and a thermodynamics characterization was carried out using the NIS data combined with first principles calculations. Overall, this study provides evidence that 187Os nuclear resonance scattering is a reliable technique for the investigation of hyperfine interactions and Os specific vibrations in osmium(VI) species, and is thus applicable for such measurements in osmium complexes of other oxidation states, including those with anticancer activity such as Os(III) and Os(IV).

en: 187Os nuclear resonance scattering to explore hyperfine interactions and lattice dynamics for biological applications

hyperfine-interactions

display_name: hyperfine-interactions

lattice-dynamics

display_name: lattice-dynamics

nuclear-resonance-scattering

display_name: nuclear-resonance-scattering


en: Recently, a process has been proposed for generating negatively-curved carbon schwarzites via zeolite-templating (Braun et al., 2018). However, the proposed process leads to atomistic models which are not very symmetric and often rather defective. In the present work, an improved generation approach is developed, by imposing symmetry constraints, which systematically leads to defect-free, hence more stable, schwarzites. The stability of the newly predicted symmetric schwarzites is also compared to that of other carbon nanostructures (in particular carbon nanotubes - CNTs), which could also be accommodated within the same templates. Our results suggest that only a few of these (such as FAU, SBT and SBS) can fit schwarzites more stable than CNTs. Our predictions could help experimentalists in the crucial choice of the template for the challenging synthesis of schwarzites. Furthermore, being highly symmetric and stable phases, the models could also be synthesized by means of other experimental procedures.

en: Modeling symmetric and defect-free carbon schwarzites into various zeolite templates

carbon-nanotubes

display_name: carbon-nanotubes

random-symmetric-generation

display_name: random-symmetric-generation

schwarzites

display_name: schwarzites

zeolite-templated-nanostructures

display_name: zeolite-templated-nanostructures


density-of-states

display_name: density-of-states

electronic-structure

display_name: electronic-structure

epfl

display_name: epfl

erc

display_name: erc

machine-learning

display_name: machine-learning

marvel

display_name: marvel

snsf

display_name: snsf


en:
A recently developed bottom-up synthesis strategy enables the fabrication of graphene nanoribbons with well-defined width and non-trivial edge structures from dedicated molecular precursors. Here we discuss the synthesis and properties of zigzag nanoribbons (ZGNRs) modified with periodic cove-cape-cove units along their edges. Contrary to pristine ZGNRs, which show antiferromagnetic correlation of their edge states, the edge-modified ZGNRs exhibit a finite single particle band gap without localized edge states. We report the on-surface synthesis of such edge-modified ZGNRs and discuss tunneling conductance dI/dV spectra and dI/dV spatial maps that reveal a noticeable localization of electronic states at the cape units and the
opening of a band gap without presence of edge states of magnetic origin. A thorough ab initio investigation of the electronic structure identifies the conditions under which antiferromagnetically coupled, edge-localized states reappear in the electronic structure. Further modifications of the ribbon structure are proposed that lead to an enhancement of such features, which could find application in nanoelectronics and spintronics.
The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.

en: Graphene nanoribbons with mixed cove-cape-zigzag edge structure

density-functional-theory

display_name: density-functional-theory

graphene-nanoribbons

display_name: graphene-nanoribbons

surface-chemistry

display_name: surface-chemistry


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

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

atomistic-models

display_name: atomistic-models

high-entropy-alloys

display_name: high-entropy-alloys

solute-strengthening

display_name: solute-strengthening


en: Superelasticity, being a reversible nonlinear strain response to stress stimuli beyond the linear elastic regime, is always associated with phase transformations in its host materials, mostly metals or polymers. Theoretical rationale indicates that inorganic materials with covalent/ionic bonding normally have large energy barriers for reversible structural transitions and thus host less opportunity to achieve superelasticity. Here, we demonstrate a directional tensile superelasticity in ceramic crystal GeSe through an unconventional reversible shuffle twinning mechanism instead of martensitic phase transition. We observed, with in-situ mechanical transmission electron microscopy, an evolution in stress‒strain curve from the linear elastic behavior to a nonlinear superelastic plateau, and confirmed that such superelasticity appears simultaneously together with the generation of stripy-shaped twin domains along  orientation. Theoretical calculations revealed that the shuffle twinning process from "Z-shaped" to "anti-Z-shaped" bond-configuration leads to the release of elastic potential energy, being responsible for the emergence of tensile superelasticity therein. Note that such a highly-directional superelasticity prefers to emerge at angles near the zigzag direction owing to the anisotropic Young's modulus and Poisson's ratio in GeSe, and has never been reported in superelastic materials. Our observation provides a novel strategy to exploit tensile superelasticity and nonlinear mechanics for advanced mechanical and flexible electronics.

en: A directional tensile superelasticity in ceramic crystal via reversible shuffle twinning

in-situ-tem

display_name: in-situ-tem

shuffle-twinning

display_name: shuffle-twinning

superelasticity

display_name: superelasticity


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

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


materialscloud

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

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


en: Understanding the structure of glassy materials represents a tremendous challenge for both experiments and computations. Despite decades of scientific research, for instance, the structural origin of the density anomaly in silica glasses is still not well understood. Atomistic simulations based on molecular dynamics (MD) produce atomically resolved structure, but extracting insights about the role of disorder in the density anomaly is challenging. Here, we propose to quantify the topological differences between structural arrangements from MD trajectories using a graph-theoretical approach, such that structural differences in silica glasses that exhibit density anomaly can be captured. To balance the accuracy and speed of the MD simulations, we utilized force matching potentials to generate the silica glass structures. This approach involves casting all-atom glass configurations as networks, and subsequently applying a graph-similarity metric (D-measure). Calculated D-measure values are then taken as the topological distances between two configurations. By measuring the topological distances of configurations in silica glass simulated structures across a range of temperatures, distinct structural features could be observed at temperatures higher than the fictive temperature. In addition to quantifying structural changes in the full simulation box, we compared topological distances between local atomic environments in the glass and crystalline silica phases. Evidence from this approach suggests that more coesite-like local structures, which are less symmetric, emerge in silica glasses when density is at a minimum during the heating process.

en: Materials Cloud

en: Graph theory-based structural analysis on density anomaly of silica glass

force-matching-potential

display_name: force-matching-potential

graph-theory

display_name: graph-theory

molecular-dynamics

display_name: molecular-dynamics

silica-glass

display_name: silica-glass


envi

en: Environment