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

materialscloud

en: Materials Cloud

catalysis

display_name: catalysis

cu

display_name: cu

gaussian-process

display_name: gaussian-process


$oid: OBSOLETE

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

materialscloud

approval_status: approved

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

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

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

machine-learning

display_name: machine-learning

nmr

display_name: nmr

resolution

display_name: resolution


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


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


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

materialscloud

en: Materials Cloud

ferroelectricity

display_name: ferroelectricity

polar-discontinuity

display_name: polar-discontinuity


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

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).

magnetophononic

display_name: magnetophononic

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: 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

envi

en: Environment

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

marvel

display_name: marvel

max

display_name: max

yambo-code

display_name: yambo-code


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


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

dual-site-langmuir-dsl

display_name: dual-site-langmuir-dsl

ideal-adsorbed-solution-theory-iast

display_name: ideal-adsorbed-solution-theory-iast

metal-organic-frameworks-mofs

display_name: metal-organic-frameworks-mofs

temperature-swing-adsorption-tsa

display_name: temperature-swing-adsorption-tsa


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

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

crystal-graph-attention-networks

display_name: crystal-graph-attention-networks

density-functional-theory

display_name: density-functional-theory


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: 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

materialscloud

en: Materials Cloud

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

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).

alloy

display_name: alloy

magnesium

display_name: magnesium

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


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

envi

en: Environment

graphene

display_name: graphene

van-der-waals-density-functional

display_name: van-der-waals-density-functional

water

display_name: water


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


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

snsf

display_name: snsf

solid-solutions

display_name: solid-solutions

statistical-mechanics

display_name: statistical-mechanics


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


infrared-spectra-in-amorphous-alumina

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

title_for_slug: infrared-spectra-in-amorphous-alumina

dft

display_name: dft

infrared

display_name: infrared

vdos

display_name: vdos


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

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

arpes-dft

display_name: arpes-dft

nccr-marvel

display_name: nccr-marvel

vhss

display_name: vhss


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

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

materialscloud

en: Materials Cloud

alloy-discovery

display_name: alloy-discovery

bcc

display_name: bcc

high-entropy-alloys

display_name: high-entropy-alloys

solute-strengthening

display_name: solute-strengthening


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

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).

energy-density

display_name: energy-density

equilibrium-molecular-dynamics

display_name: equilibrium-molecular-dynamics

heat-conductivity

display_name: heat-conductivity

thermal-transport

display_name: thermal-transport


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

envi

en: Environment

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


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


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


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

materialscloud

en: Materials Cloud

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

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).

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

envi

en: Environment

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


bound-by-three-body-interactions

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.

en: Bound by three-body interactions

title_for_slug: 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


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


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


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

electronic-structure

display_name: electronic-structure

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

materialscloud

en: Materials Cloud

atomistic-models

display_name: atomistic-models

high-entropy-alloys

display_name: high-entropy-alloys

snsf

display_name: snsf

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

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).

in-situ-tem

display_name: in-situ-tem

shuffle-twinning

display_name: shuffle-twinning

superelasticity

display_name: superelasticity


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

envi

en: Environment

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


en: Atomistic simulations provide insights into structure-property relations on an atomic size and length scale that are complementary to the macroscopic observables that can be obtained from experiments.  Quantitative predictions, however, are usually hindered by the need to strike a balance between the accuracy of the calculation of the interatomic potential and the modelling of realistic thermodynamic conditions.  Machine-learning techniques make it possible to efficiently approximate the outcome of accurate electronic-structure calculations that can, therefore, be combined with extensive thermodynamic sampling.  We take elemental nickel as a prototypical material, whose alloys have applications from cryogenic temperatures up to close to their melting point and use it to demonstrate how a combination of machine-learning models of electronic properties and statistical sampling methods makes it possible to compute accurate finite-temperature properties at an affordable cost.  We demonstrate the calculation of a broad array of bulk, interfacial, and defect properties over a temperature range from 100 to 2500 K, modelling also, when needed, the impact of nuclear quantum fluctuations and electronic entropy.  The framework we demonstrate here can be easily generalized to more complex alloys and different classes of materials.

en: Finite-temperature materials modeling from the quantum nuclei to the hot electrons regime

cosmo

display_name: cosmo

electronic-density-of-states

display_name: electronic-density-of-states

epfl

display_name: epfl

machine-learning

display_name: machine-learning

materials-science

display_name: materials-science

metal-alloys

display_name: metal-alloys

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potentials

display_name: neural-network-potentials


en:
Modeling ferroelectric materials from first principles is one of the successes of density-functional theory, and the driver of much development effort, requiring an accurate description of the electronic processes and the thermodynamic equilibrium that drive the spontaneous symmetry breaking and the emergence of macroscopic polarization. We demonstrate the development and application of an integrated machine learning (ML) model that describes on the same footing structural, energetic and functional properties of barium titanate (BaTiO₃), a prototypical ferroelectric. The model uses ab initio calculations as reference and achieves accurate yet inexpensive predictions of energy and polarization on time and length scales that are not accessible to direct ab initio modeling. The ML model allows us to thoroughly probe the static and dynamical behavior of BaTiO₃ across its phase diagram, without the need to introduce a coarse-grained description of the ferroelectric transition. Furthermore, we apply the polarization model to calculate dielectric response properties of the material in a fully ab-initio manner.
This archive provides all the relevant data and input files that were used to fit the ML interatomic potential and the polarization model used in this work, along with the relevant Density-Functional Theory calculations that were used for the training set construction and the validation of the ML model. Furthermore, it provides input files and first few snapshots of all the molecular dynamics trajectories needed to investigate the thermodynamics and dielectric properties of BaTiO₃.

en: Thermodynamics and dielectric response of BaTiO₃ by data-driven modeling

dielectric-response

display_name: dielectric-response

ferroelectricity

display_name: ferroelectricity

marvel

display_name: marvel

max

display_name: max

samsung-institute-of-technology-sait

display_name: samsung-institute-of-technology-sait

snsf

display_name: snsf

swissuniversities

display_name: swissuniversities

thermodynamics

display_name: thermodynamics


en: Metal halide perovskites (MHPs) demonstrate an exceptional combination of properties. Rapid progress has extended their application beyond solar cells, light-emitting diodes, photodetectors, and lasers to include memristors, artificial synapse devices, and pressure induced emission. In particular, the vacancy-ordered double perovskite Cs₂TiBr₆ has been identified as a promising material. The effective characterization of MHPs requires accurate and efficient methods for the calculation of electronic structure. Koopmans compliant (KC) functionals are an accurate and computationally efficient alternative to many-body perturbation theory using the GW approximation but have yet only been validated on a small number of simple materials. In this work, KC functionals were applied to the more complex case of Cs₂TiBr₆ and gave a zero-temperature fundamental gap of 4.28 eV, in close agreement with the value of 4.44 eV obtained using the accurate, but more computationally expensive, evGW₀ approach. The temperature-dependent renormalization of the bandgap has also been investigated and found to be significant. Agreement with the experimental optical bandgaps of 1.76–2.0 eV would also require the inclusion of exciton binding energy.

en: Accurate and efficient computation of the fundamental bandgap of the vacancy-ordered double perovskite Cs₂TiBr₆

koopmans-functionals

display_name: koopmans-functionals

metal-halide-perovskites

display_name: metal-halide-perovskites

quasi-particle-self-consistent-gw

display_name: quasi-particle-self-consistent-gw


en: The Fe(CoB)/MgO interface is vital to spintronics as it exhibits the tunneling magnetoresistance (TMR) effect and interfacial perpendicular magnetic anisotropy (PMA) simultaneously. To further enhance TMR and PMA for the development of high-density magnetoresistive random access memory, it is essential to clarify the behavior of Fe atoms interfaced with MgO. This study reveals that the spin and orbital magnetic moments of Fe are enhanced at the Fe/MgO interface. The enhancement in the orbital magnetic moment is much more significant than that predicted by the standard density functional theory. Theoretical calculations based on the orbital polarization correction reproduce this enhancement, the origin of which is attributed to the electron-electron correlation resulting from electron localization at the Fe/MgO interface. The present findings highlight the importance of electro--electron correlation at ferromagnet/oxide interfaces, which has often been disregarded in spintronics, and provide a new perspective in materials design.

en: Electron correlation enhances orbital polarization at a ferromagnetic metal/insulator interface

experimental

display_name: experimental

femgo

display_name: femgo

interface

display_name: interface

magnetic-anisotropy

display_name: magnetic-anisotropy

spintronics

display_name: spintronics


en: The precise introduction of nonplanar pores in the backbone of graphene nanoribbon represents a great challenge. In a recent work, we explore a synthetic strategy toward the preparation of nonplanar porous graphene nanoribbon from a predesigned dibromohexabenzotetracene monomer bearing four cove-edges. Successive thermal annealing steps of the monomers indicate that the dehalogenative aryl-aryl homocoupling yields a twisted polymer precursor on a gold surface and the subsequent cyclodehydrogenation leads to a defective porous graphene nanoribbon containing nonplanar [14]annulene pores and five-membered rings as characterized by scanning tunneling microscopy and noncontact atomic force microscopy. Although the C–C bonds producing [14]annulene pores are not achieved with high yield, our results provide new synthetic perspectives for the on-surface growth of nonplanar porous graphene nanoribbons. The record contains data to support the results of our work

en: On-surface synthesis of porous graphene nanoribbons containing nonplanar [14]annulene pores

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

on-surface-synthesis

display_name: on-surface-synthesis

stm

display_name: stm


en: On-surface synthesis has recently emerged as an effective route towards the atomically precise fabrication of graphene nanoribbons (GNRs) of controlled topologies and widths. However, whether and to what degree structural disorder occurs in the resulting samples is a crucial issue for prospective applications that remains to be explored. Here, we experimentally visualize ubiquitous missing benzene rings at the edges of 9-atom wide armchair nanoribbons that form upon cleavage of phenyl groups in the precursor molecules. These defects are referred to as 'bite' defects. First, we address their density and spatial distribution on the basis of scanning tunnelling microscopy and find that they exhibit a strong tendency to aggregate. Next, we explore their effect on the quantum charge transport from first-principles calculations, revealing that such imperfections substantially disrupt the conduction properties at the band edges. Finally, we generalize our theoretical findings to wider nanoribbons in a systematic manner, hence establishing practical guidelines to minimize the detrimental role of such defects on the charge transport. Overall, our work portrays a detailed picture of 'bite' defects in bottom-up armchair GNRs and assesses their effect on the performance of carbon-based nanoelectronic devices.

en: Quantum electronic transport across 'bite' defects in graphene nanoribbons

materialscloud

en: Materials Cloud

cscs

display_name: cscs

defects

display_name: defects

electronic-transport

display_name: electronic-transport

gnr

display_name: gnr

marvel

display_name: marvel

onr

display_name: onr


en: Electrochemical reduction of CO(2) to value-added chemicals and fuels is a promising strategy to sustain pressing renewable energy demands and address climate change issues. Direct observation of reaction intermediates during the CO(2) reduction reaction will contribute to mechanistic understandings and thus promote the design of catalysts with the desired activity, selectivity, and stability. Herein, we combined in situ electrochemical shell-isolated nanoparticle-enhanced Raman spectroscopy and ab initio molecular dynamics calculations to investigate the CORR process on Cu single-crystal surfaces in various electrolytes. Competing redox pathways and coexistent intermediates of CO adsorption dimerization, oxidation, and hydrogenation, as well as Cu-Oad/Cu-OHad species at Cu-electrolyte interfaces, were simultaneously identified using in situ spectroscopy and further confirmed with isotope-labeling experiments. With AIMD simulations, we report accurate vibrational frequency assignments of these intermediates based on the calculated vibrational density of states and reveal the corresponding species in the electrochemical CO redox landscape on Cu surfaces. Our findings provide direct insights into key intermediates during the reduction of CO(2) and offer a full-spectroscopic tool (40–4,000 cm⁻¹) for future mechanistic studies.

en: In situ spectroelectrochemical probing of CO redox landscape on copper single-crystal surfaces

materialscloud

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

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

aimd

display_name: aimd

electrocatalysis

display_name: electrocatalysis

in-situ-raman

display_name: in-situ-raman


en: The prediction of material properties through electronic-structure simulations based on density-functional theory has become routinely common, thanks, in part, to the steady increase in the number and robustness of available simulation packages. This plurality of codes and methods aiming to solve similar problems is both a boon and a burden. While providing great opportunities for cross-verification, these packages adopt different methods, algorithms, and paradigms, making it challenging to choose, master, and efficiently use any one for a given task. Leveraging recent advances in managing reproducible scientific workflows, we demonstrate how developing common interfaces for workflows that automatically compute material properties can tackle the challenge mentioned above, greatly simplifying interoperability and cross-verification. We introduce design rules for reproducible and reusable code-agnostic workflow interfaces to compute well-defined material properties, which we implement for eleven different quantum engines and use to compute three different material properties. Each implementation encodes carefully selected simulation parameters and workflow logic, making the implementer's expertise of the quantum engine directly available to non-experts. Full provenance and reproducibility of the workflows is guaranteed through the use of the AiiDA infrastructure. All workflows are made available as open-source and come pre-installed with the Quantum Mobile virtual machine, making their use straightforward. This entry contains all data and scripts to reproduce the figures of the corresponding scientific paper.

en: Common workflows for computing material properties using different quantum engines

envi

en: Environment

aiida

display_name: aiida

automated

display_name: automated

common-interfaces

display_name: common-interfaces

intersect

display_name: intersect

marvelosp

display_name: marvelosp

max

display_name: max

snsf

display_name: snsf

verification

display_name: verification

workflows

display_name: workflows


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

en: Unidirectional Kondo scattering in layered NbS2

first-principles-calculation

display_name: first-principles-calculation

vasp

display_name: vasp


en: Charge neutrality and their expected itinerant nature makes excitons potential transmitters of information. However, exciton mobility remains inaccessible to traditional optical experiments that only create and detect excitons with negligible momentum. Here, using angle-resolved photoemission spectroscopy, we detect dispersing excitons in quasi-one-dimensional metallic trichalcogenide, TaSe₃. The low density of conduction electrons and low dimensionality in TaSe₃ combined with a polaronic renormalization of the conduction band and the poorly screened interaction between these polarons and photo-induced valence holes leads to various excitonic bound states that we interpret as intrachain and interchain excitons, and possibly trions. The thresholds for the formation of a photo-hole together with an exciton appear as side valence bands with dispersions nearly parallel to the main valence band, but shifted to lower excitation energies. The energy separation between side and main valence bands can be controlled by surface doping, enabling the tuning of certain exciton properties. This document contains the raw data of this project.

en: Multiple mobile excitons manifested as sidebands in quasi-one-dimensional metallic TaSe₃

arpes

display_name: arpes

dispersive-bands-from-excitons

display_name: dispersive-bands-from-excitons

interchain-excitons-and-trions

display_name: interchain-excitons-and-trions

mobile-excitons-in-metal

display_name: mobile-excitons-in-metal


en: The design of open-shell carbon-based nanomaterials is at the vanguard of materials science, steered by their beneficial magnetic properties like weaker spin–orbit coupling than that of transition metal atoms and larger spin delocalization, which are of potential relevance for future spintronics and quantum technologies. A key parameter in magnetic materials is the magnetic exchange coupling (MEC) between unpaired spins, which should be large enough to allow device operation at practical temperatures. In a recent work, we theoretically and experimentally explore three distinct families of nanographenes (NGs) (A, B, and C) featuring majority zigzag peripheries. Through many-body calculations, we identify a transition from a closed-shell ground state to an open-shell ground state upon an increase of the molecular size. Our predictions indicate that the largest MEC for open-shell NGs occurs in proximity to the transition between closed-shell and open-shell states. Such predictions are corroborated by the on-surface syntheses and structural, electronic, and magnetic characterizations of three NGs (A[3,5], B[4,5], and C[4,3]), which are the smallest open-shell systems in their respective chemical families and are thus located the closest to the transition boundary. Notably, two of the NGs (B[4,5] and C[4,3]) feature record values of MEC (close to 200 meV) measured on the Au(111) surface. Our strategy for maximizing the MEC provides perspectives for designing carbon nanomaterials with robust magnetic ground states. This record contains the data for the simulations discussed in our manuscript.

en: Steering large magnetic exchange coupling in nanographenes near the closed-shell to open-shell transition

dft

display_name: dft

nanographenes

display_name: nanographenes

open-shell

display_name: open-shell

spectroscopy

display_name: spectroscopy


en: Landau-Lifshitz-Gilbert (LLG) spin-dynamics calculations based on the extended Heisenberg Hamiltonian is an important tool in computational materials science involving magnetic materials. LLG simulations allow to bridge the gap from expensive quantum mechanical calculations with small unit cells to large supercells where the collective behavior of millions of spins can be studied. In this work we present the AiiDA-Spirit plugin that connects the spin-dynamics code Spirit to the AiiDA framework. AiiDA provides a Python interface that facilitates performing high-throughput calculations while automatically augmenting the calculations with metadata describing the data provenance between calculations in a directed acyclic graph. The AiiDA-Spirit interface thus provides an easy way for high-throughput spin-dynamics calculations. The interface to the AiiDA infrastructure furthermore has the advantage that input parameters for the extended Heisenberg model can be extracted from high-throughput first-principles calculations including a proper treatment of the data provenance that ensures reproducibility of the calculation results in accordance to the FAIR principles. We describe the layout of the AiiDA-Spirit plugin and demonstrate its capabilities using selected examples for LLG spin-dynamics and Monte Carlo calculations. Furthermore, the integration with first-principles calculations through AiiDA is demonstrated at the example of gamma-Fe, where the complex spin-spiral ground state is investigated.

en: The AiiDA-Spirit plugin for automated spin-dynamics simulations and multi-scale modelling based on first-principles calculations

density-functional-theory

display_name: density-functional-theory

landau-lifshitz-gilbert-equation

display_name: landau-lifshitz-gilbert-equation

llg

display_name: llg

monte-carlo

display_name: monte-carlo

skyrmion

display_name: skyrmion

spin-dynamics

display_name: spin-dynamics


en:
A semi-automated protocol largely based on AiiDA has been developed and exploited to explore the yet-unsolved crystal structure of the recently-discovered AsTe₃ material with potential thermoelectric applications due to its ultralow thermal conductivity. The workflow involves different steps of increasing precision and computational cost, in a sequential approach to generate, refine and evaluate model AsTe₃ structures based on supercells of elemental-Te from the stand point of As/Te chemical disorder. Our studies shed light on the structural complexity that has prevented, to this day, a direct structure determination of the recently-discovered crystalline AsTe₃ material, despite the new synthesis protocol that has led to its obtention in a pure and fully crystalline phase, by congruent crystallization from the parent AsTe₃ glass. Structural models of crystalline AsTe₃ reveal a composition based on an intergrowth of subnanometric As₂Te₃ and Te domains with potentially defected interfaces that intimately interfere with the electronic properties of this material.
This repository contains data generated in the course of the structure-construction-and-evaluation protocol for subsets of AsTe₃ structural models obtained at different steps of the workflow, with the full provenance included, in the form of an AiiDA archive. Scripts and workchains developped specifically for this study are also privided, along with the atomic structures of the most relevant AsTe₃ models identified, in common file formats for researchers not familiar with AiiDA databases.

en: Insights into the structural complexity and local disorder of crystalline AsTe₃ from semi-automated first-principles modelling

automation

display_name: automation

chemical-disorder

display_name: chemical-disorder

structural-complexity

display_name: structural-complexity

structural-models

display_name: structural-models

thermoelectrics

display_name: thermoelectrics


en: Due to their high accuracy, Double-Hybrid Density functionals emerged to important methods for molecular electronic-structure calculations. The high computational costs of double-hybrid calculations in condensed phase and the lack of efficient gradient implementations thereof inhibit a wide applicability for periodic systems. We present an implementation of gradients for Double-Hybrid functional theory into CP2K. The Auxiliary Density Matrix Method (ADMM) reduces the overhead from the Hartree-Fock calculations providing an efficient and accurate methodology to tackle condensed phase systems. First applications to water containing systems of different densities and molecular crystals pave the way for advanced studies. We present large benchmark systems to discuss the efficiency of our methodology on modern super computing hardware.

en: Double-Hybrid Density functionals for the condensed phase: gradients, stress tensor, and Auxiliary-Density Matrix Method acceleration

materialscloud

en: Materials Cloud

analytical-gradients

display_name: analytical-gradients

auxiliary-density-matrix-method

display_name: auxiliary-density-matrix-method

benchmark

display_name: benchmark

condensed-matters

display_name: condensed-matters

cscs

display_name: cscs

double-hybrid-functional

display_name: double-hybrid-functional

electronic-structure-method

display_name: electronic-structure-method

molecular-crystals

display_name: molecular-crystals

snsf

display_name: snsf


en: Singlet fission (SF) is a promising multiexciton-generating process. Its demanding energy splitting criterion - that the S1 energy must be at least twice that of T1 - has limited the range of materials capable of SF. We propose heteroatom oxidation as a robust strategy to achieve sufficient S1/T1 splitting, and demonstrate the potential of this approach for intramolecular SF.

en: Heteroatom oxidation controls singlet-triplet energy splitting in singlet fission building blocks

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).

conjugated-polymers

display_name: conjugated-polymers

donor-acceptor-systems

display_name: donor-acceptor-systems

epfl

display_name: epfl

excited-states

display_name: excited-states

singlet-fission

display_name: singlet-fission


en: The efficient activation of methane and simultaneous water dissociation are crucial in many catalytic reactions on oxide-supported transition metal catalysts. On very low-loaded Ni/CeO₂ surfaces, methane easily fully decomposes, CH₄ -> C + 4H,  and water dissociates, H₂O -> OH + H. However, in important reactions such as the direct oxidation of methane to methanol (MTM), where complex interplay exists between reactants (CH₄, O₂), it is desirable to avoid the complete dehydrogenation of methane to carbon.  Remarkably, the barrier for the activation of C-H bonds in CHx (x= 1-3) species on Ni/CeO₂ surfaces can be manipulated by adding Cu, forming bimetallic NiCu clusters, whereas the ease for cleavage of O-H bonds in water, is not affected by ensemble effects, as obtained from density functional theory-based calculations. CH4 activation occurs only on Ni sites and H₂O activation on both Ni and Cu sites. The MTM reaction pathway for the example of the Ni₃Cu₁/CeO₂ model catalyst predict higher selectivity and a lower activation barrier for methanol production, compared with that for Ni₄-CeO₂. These findings point toward a possible strategy to design active and stable catalysts which can be employed for methane activation and conversions.

en: Tuning selectivity in the direct conversion of methane to methanol: bimetallic synergistic effects on the cleavage of C-H and O-H bonds over NiCu/CeO₂ catalysts

envi

en: Environment

bimetallic

display_name: bimetallic

ceria

display_name: ceria

methane-activation

display_name: methane-activation

water-activation

display_name: water-activation


en: The properties of molecules and materials containing light nuclei are affected by their quantum mechanical nature. Accurate modeling of these quantum nuclear effects requires computationally demanding path integral techniques. Considerable success has been achieved in reducing the cost of such simulations by using generalized Langevin dynamics to induce frequency-dependent fluctuations. Path integral generalized Langevin equation methods, however, have this far been limited to the study of static, thermodynamic properties due to the large perturbation to the system's dynamics induced by the aggressive thermostatting. Here, we introduce a post-processing scheme, based on analytical estimates of the dynamical perturbation induced by the generalized Langevin dynamics, which makes it possible to recover meaningful time correlation properties from a thermostatted trajectory. We show that this approach yields spectroscopic observables for model and realistic systems that have an accuracy comparable to much more demanding approximate quantum dynamics techniques based on full path integral simulations.

en: Inexpensive modeling of quantum dynamics using path integral generalized Langevin equation thermostats

erc

display_name: erc

marvel

display_name: marvel

molecular-dynamics

display_name: molecular-dynamics

nuclear-quantum-effects

display_name: nuclear-quantum-effects

vibrational-spectra

display_name: vibrational-spectra