en: The recently discovered vanadium-based Kagome metals AV₃Sb₅ (A = K, Rb, Cs) undergo a unique phase transition into charge-density wave (CDW) order which precedes both unconventional superconductivity and time-reversal symmetry breaking. Therefore the essential first step in building a full understanding of the role of CDW in establishing these unconventional phases is to unveil the symmetries and the microscopic nature of the charge-ordered phase. Here, we determine the exact structure of the 2×2×2 superlattice that develops below the charge-density wave ordering temperature (TCDW) in RbV₃Sb₅. We present a comprehensive set of ⁵¹V, ⁸⁷Rb, and ¹²¹Sb nuclear magnetic resonance (NMR) measurements and density functional theory simulations of NMR observables to provide a unique site-selective view into the local nature of the charge-ordered phase. The combination of these experimental results with simulations provides compelling evidence that the CDW structure prevailing below 103 K in RbV₃Sb₅ is the so-called inverse Star of David pattern, π-shifted along the c axis. These findings put severe constraints on the topology of these Kagome compounds and thus provide essential guidance for the development of an appropriate theoretical framework for predicting properties of exotic electronic orders arising within the CDW phase.

en: Microscopic nature of the charge-density wave in the kagome superconductor RbV₃Sb₅

dft

display_name: dft

nuclear-magnetic-resonance

display_name: nuclear-magnetic-resonance

nuclear-quadrupole-resonance

display_name: nuclear-quadrupole-resonance


$oid: OBSOLETE

materialscloud

approval_status: approved

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

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

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente


en: This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases of d-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupied d states near the Fermi level, we determine that the large, sharp d density of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.

en: Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

density-functional-theory

display_name: density-functional-theory

equivariant-neural-networks

display_name: equivariant-neural-networks

gaussian-processes

display_name: gaussian-processes

machine-learned-force-fields

display_name: machine-learned-force-fields

transition-metals

display_name: transition-metals


en: The process of catalytically oxidizing carbon monoxide (CO) remains a critical issue across various industrial sectors. However, it continues to be a challenge to achieve effective CO oxidation at low temperatures using non-noble metal catalysts. This study addresses these gaps by investigating the effects of dilute gallium (Ga) doping on the catalytic performance of flower-like ceria (CeO₂) microspheres. By using a modified hydrothermal synthesis method, we prepared the Ga-doped CeO₂ microspheres and characterized their morphology, surface area, and evidence of oxygen vacancy through various experimental techniques as well as computational simulation method. Our findings disclosed that the incorporation of Ga significantly enhances the catalytic performance of CeO₂, with the optimal doping level (2 mol% Ga) achieving a 90% CO conversion temperature (T90) of 388.9 °C, obviously lower than that of pristine CeO₂ (488.5 °C). This work demonstrates that dilute Ga doping effectively improves the catalytic properties of CeO₂-based materials, offering a potential strategy for developing effective CO oxidation catalysts.

en: Enhanced catalytic performance towards CO oxidation of broccoli-like Ceria microsphere by dilute Ga doping

catalytic-enhancement

display_name: catalytic-enhancement

ceria-microspheres

display_name: ceria-microspheres

co-oxidation

display_name: co-oxidation

gallium-doping

display_name: gallium-doping

hydrothermal-synthesis

display_name: hydrothermal-synthesis

oxygen-vacancy

display_name: oxygen-vacancy


en: Muon spin rotation and relaxation spectroscopy is a powerful tool for studying magnetic materials, offering a local probe that complements scattering techniques and provides advantages in cases of strong incoherent scattering or neutron absorption. By integrating computational methods (DFT+μ), the microscopic interactions driving the observed signals can be precisely quantified, enhancing the technique's predictive power. We present a set of efficient algorithms and workflows - implemented in the AiiDA framework - that automate the DFT+μ procedure, where the muon is treated as a hydrogen impurity within the density functional theory framework. Our approach automates the identification of muon stopping sites, dipolar interactions, and hyperfine interactions. In this record we share the result of our calculations on well-known compounds, to demonstrate the accuracy and ease of use of our protocol.

en: Automated computational workflows for muon spin spectroscopy

aiida

display_name: aiida

aiida-impuritysupercellconv

display_name: aiida-impuritysupercellconv

aiida-muon

display_name: aiida-muon

automated-workflows

display_name: automated-workflows

dftmu

display_name: dftmu

first-principles

display_name: first-principles

marvel

display_name: marvel

muon-spin-spectroscopy

display_name: muon-spin-spectroscopy


density-functional-theory

display_name: density-functional-theory


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

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

gaas

display_name: gaas

gallium-arsenide

display_name: gallium-arsenide

machine-learning-potential

display_name: machine-learning-potential

molecular-dynamics-simulations

display_name: molecular-dynamics-simulations

nanowire

display_name: nanowire

neural-network-potential

display_name: neural-network-potential

ordering-at-the-interface

display_name: ordering-at-the-interface

snsf

display_name: snsf


en: Materials for high-temperature environments are actively being investigated for deployment in aerospace and nuclear applications. This study uses computational approaches to unravel the crystallography, and thermodynamics of a promising class of refractory alloys containing aluminum. Accurate first-principles calculations, cluster expansion models, and statistical mechanics techniques are employed to rigorously analyze precipitation in a prototypical senary Al-Nb-Ta-Ti-V-Zr alloy. Finite-temperature calculations reveal a strong tendency for aluminum to segregate to a single sublattice at elevated temperatures. Precipitate and matrix compositions computed with our ab-initio model are in excellent agreement with previous experimental measurements (Soni et al., 2020). Surprisingly, conventional B2-like orderings are found to be both thermodynamically and mechanically unstable in this alloy system. Complex anti-site defects are essential to forming a stable ordered precipitate. Our calculations reveal that the instability of B2 compounds can be related to a simple electron counting rule across all binary alloys formed by elements in groups 4,5, and 6. The results of this study provide viable routes toward designing high-temperature materials for deployment in extreme environments.

en: First-principles thermodynamics of precipitation in aluminum-containing refractory alloys

ab-initio

display_name: ab-initio

alloy-theory

display_name: alloy-theory

cluster-expansion

display_name: cluster-expansion

phase-stability

display_name: phase-stability

precipitation

display_name: precipitation


en: Homogenous enantioselective catalysis is nowadays the cornerstone in the manufacturing of enantiopure substances, but its technological implementation suffers from well-known impediments like the lack of endurable catalysts exhibiting long-term stability. The catalytically active intermetallic compound Palladium-Gallium (PdGa), conserving innate bulk chirality on its surfaces, represent a promising system to study asymmetric chemical reactions by heterogeneous catalysis, with prospective relevance for industrial processes. In a recent publication we investigate the adsorption of 10,10′-dibromo-9,9′-bianthracene (DBBA) on the PdGa:A(-1-1-1) Pd3-terminated surface by means of scanning tunneling microscopy (STM) and spectroscopy (STS). A highly enantioselective adsorption of the molecule evolving into a near 100% enantiomeric excess below room temperature is observed. This exceptionally high enantiomeric excess is attributed to temperature activated conversion of the S to the R chiral conformer. Tip-induced bond cleavage of the R conformer shows a very high regioselectivity of the DBBA debromination. The experimental results are interpreted by density functional theory atomistic simulations. This work extends the knowledge of chirality transfer onto the enantioselective adsorption of non-planar molecules and manifests the ensemble effect of PdGa surfaces resulting in robust regioselective debromination. This record contains data that support the results discussed in the manuscript.

en: Asymmetric molecular adsorption and regioselective bond cleavage on chiral PdGa crystals

cscs

display_name: cscs

enantioselectivity

display_name: enantioselectivity

marvelasm

display_name: marvelasm

surface-chemistry

display_name: surface-chemistry


density-functional-theory

display_name: density-functional-theory


en: Advanced quantum transport approach from first-principle to shed light on the influence of orientation misalignments on the performance of BP-based field-effect transistors, for which the input files are reported. Both n-and p-type configurations are investigated for six alignment angles, in the ballistic limit of transport and in the presence of electron-phonon and charged impurity scattering.

en: Impact of orientation misalignments on black phosphorus ultrascaled field-effect transistors

computational-materials

display_name: computational-materials

field-effect-transistors

display_name: field-effect-transistors

quantum-transport

display_name: quantum-transport


materialscloud

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

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


en: In this paper we use density functional theory combined with dynamical mean-field theory (DFT+DMFT) to study interface effects between the correlated metal CaVO3 and the two typical substrate materials SrTiO3 and LaAlO3. We find that the CaVO3/SrTiO3 interface has only a marginal influence on the CaVO3 thin film, with the dominant effect being the (bulklike) epitaxial strain imposed by the large lattice mismatch, rendering the CaVO3 film insulating due to the enhanced orbital polarization related to the strong level splitting between the t2g orbitals. In contrast, at the polar CaVO3/LaAlO3 interface, the presence of the interface can have a huge effect on the physical properties, depending both on the specific interface termination and on the specific boundary conditions imposed by the multilayer geometry. We compare three approaches to modeling the CaVO3/LaAlO3 interface, all of which impose a different set of (electrostatic) boundary conditions. Our results demonstrate that different substrates, interface terminations, and electrostatic boundary conditions can drastically affect the properties of thin-film heterostructures, indicating the potential tunability of the interfacial properties via multilayer engineering.

en: Materials Cloud

en: Tailoring interfacial properties in CaVO3 thin films and heterostructures with SrTiO3 and LaAlO3: A DFT+DMFT study

correlated-metal

display_name: correlated-metal

dynamical-mean-field-theory

display_name: dynamical-mean-field-theory

first-principles-calculations

display_name: first-principles-calculations

metal-insulator-transition

display_name: metal-insulator-transition

multilayer-thin-films

display_name: multilayer-thin-films

superlattices

display_name: superlattices


envi

en: Environment


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

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

calcium-batteries

display_name: calcium-batteries

marokite

display_name: marokite

perovskite

display_name: perovskite

post-spinel

display_name: post-spinel


en:
Pyrene is one of the most widely investigated aromatic hydrocarbons due to its unique optical and electronic properties. Hence, pyrene-based ligands have been investigated for the synthesis of metal-organic frameworks (MOFs) in the last few years. This dataset collects the atomic structures of the pyrene-based MOFs discussed in Table 1 of Ref. 1.

The crystal structures have been manually curated to resolve partial occupancies and remove solvent molecules. Charge-neutral structures were optimized using DFT following the CURATED protocol described in 10.1021/acscentsci.9b00619.

en: Pyrene-based metal organic frameworks

erc

display_name: erc

metal-organic-framework

display_name: metal-organic-framework

mof

display_name: mof

pyrene

display_name: pyrene

snsf

display_name: snsf


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

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

computational-screening

display_name: computational-screening

marvel

display_name: marvel

photoelectrochemical-water-splitting

display_name: photoelectrochemical-water-splitting

surface-passivation

display_name: surface-passivation


en: The use of machine learning to accelerate computer simulations is on the rise. In atomistic simulations, the use of machine learning interatomic potentials (ML-IAPs) can significantly reduce computational costs while maintaining accuracy close to that of ab initio methods. To achieve this, ML-IAPs are trained on large datasets of images, meaning atomistic configurations labeled with data from ab initio calculations. Focusing on carbon, we have created a dataset, CA-9, consisting of 48000 images labeled with energies, forces and stress tensors obtained via ab initio molecular dynamics (AIMD). We use deep learning to train state-of-the-art neural network potentials (NNPs), a form of ML-IAP, on the CA-9 dataset and investigate how training and validation data can affect the performance of the NNPs. Our results show that image generation with AIMD causes a high degree of similarity between the generated images, which has a detrimental effect on the NNPs. However, by carefully choosing which images from the dataset are included in the training and validation data, this effect can be mitigated. We end by benchmarking our trained NNPs in real-world applications and show we can reproduce results from ab initio calculations with an accuracy higher than previously published ML- or classic IAPs.

en: CA-9, a dataset of carbon allotropes for training and testing of neural network potentials

carbon

display_name: carbon

dataset

display_name: dataset

interatomic-potential

display_name: interatomic-potential

machine-learning

display_name: machine-learning

neural-network-potential

display_name: neural-network-potential


pyrene-based-metal-organic-frameworks

title_for_slug: pyrene-based-metal-organic-frameworks


en: Machine learning (ML) algorithms have undergone an explosive development impacting every aspect of computational chemistry. To obtain reliable predictions, one needs to maintain the proper balance between the black-box nature of ML frameworks and the physics of the target properties. One of the most appealing quantum-chemical properties for regression models is the electron density, and some of us recently proposed a transferable and scalable model based on the decomposition of the density onto an atom-centered basis set. The decomposition, as well as the training of the model, is at its core a minimization of some loss function, which can be arbitrarily chosen and may lead to results of different quality. Well-studied in the context of density fitting (DF), the impact of the metric on the performance of ML models has not been analyzed yet. In this work, we compare predictions obtained using the overlap and the Coulomb repulsion metrics for both the decomposition and training. As expected, the Coulomb metric used as both the DF and ML loss functions leads to the best results for the electrostatic potential and dipole moments. The origin of this difference lies in the fact that the model is not constrained to predict densities that integrate to the exact number of electrons N. Since an a posteriori correction for the number of electrons decreases the errors, we proposed a modification of the model where N is included directly into the kernel function, which allowed to lower the errors on the test and out-of-sample sets.

en: Impact of quantum-chemical metrics on the machine learning prediction of electron density

correction-number-of-electrons

display_name: correction-number-of-electrons

epfl

display_name: epfl

quantum-chemical-metrics

display_name: quantum-chemical-metrics


erc

display_name: erc


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

en: Correlated states in twisted double bilayer graphene

correlated-states

display_name: correlated-states

cscs

display_name: cscs

tdbg

display_name: tdbg

twisted-double-bilayer-graphene

display_name: twisted-double-bilayer-graphene


materialscloud

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

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


en:
We have studied electrochemical *CO-*CO coupling in explicit electrolyte with density functional theory, molecular dynamics, and metadynamics. We considered both the *CO-*CO coupling reaction and the charging process required to keep the potential constant. The charging process consists of transferring explicit cations from the electrolyte and electrons from the potentiostat to the interface. Under constant charge conditions (non-constant electrostatic potential), the *CO-*CO coupling reaction energies are relative insensitive to the charge state at the interface and the electrolyte composition and the reaction occurs with co-adsorption of water. Under constant potential conditions, the *CO-*CO coupling reaction is stabilized at lower potentials because of charging and the reaction is influenced by the electrolyte composition.
Here we have collected the data from the eight AIMD metadynamics simulations conducted in the study. Each AIMD data tar.gz file contains the VASP input files (INCAR, KPOINTS, POTCAR, ICONST), the VASP output files for the full AIMD run (OUTCAR*, PENALTYPOT), python scripts that have been used to analyze the AIMD run, data files made by those scripts (*dat), a folder (0/) used to set up single point calculations of workfunction and Bader chages at 0.125 ps intervals along the AIMD trajectory, and one folder (*.000ps) containing an example of a workfunction and Bader charge calculation.

en: Towards constant potential modeling of CO-CO coupling at liquid water-Cu(100) interfaces

ab-initio-molecular-dynamics

display_name: ab-initio-molecular-dynamics

electrocatalysis

display_name: electrocatalysis

water-metal-interfaces

display_name: water-metal-interfaces


materialscloud

en: Materials Cloud


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

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

envi

en: Environment

electron-dynamics

display_name: electron-dynamics

electronic-bands

display_name: electronic-bands

experimental

display_name: experimental

marvel

display_name: marvel

snsf

display_name: snsf

topological-phase-transition

display_name: topological-phase-transition

type-ii-weyl-semimetal

display_name: type-ii-weyl-semimetal


en:
Energy efficiency is motivating the search for new high-temperature metals. Some new body-centered-cubic random multicomponent "high entropy alloys (HEAs)" based on refractory elements (Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr) possess exceptional strengths at high temperatures but the physical origins of this outstanding behavior are not known.
Here, by using a recent mechanistic theory, we have computed the high-temperature (T=1300K) yield strength based on solute strengthening of over 10 million alloys within the whole Al-Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr alloy family. Also the yield strength/density has been computed.
This database enables the efficient search of new alloys with exceptional high-temperature strength.

en: Prediction of yield strength in refractory body-centered-cubic High Entropy Alloys

epfl

display_name: epfl

high-entropy-alloys

display_name: high-entropy-alloys

high-temperature-strength

display_name: high-temperature-strength

solute-strengthening

display_name: solute-strengthening


erc

display_name: erc


en: We investigate optical absorption spectra obtained through time-dependent density functional theory (TD-DFT) based on nonempirical hybrid functionals that are designed to correctly reproduce the dielectric function. The comparison with state-of-the-art GW calculations followed by the solution of the Bethe-Salpeter equation (BSE-GW) shows close agreement for both the transition energies and the main features of the spectra. We confront TD-DFT with BSE-GW by focusing on the model dielectric function and the local exchange-correlation kernel. The present TD-DFT approach achieves the accuracy of BSE-GW at a fraction of the computational cost.

en: Accurate optical spectra through time-dependent density functional theory based on screening-dependent hybrid functionals

bethe-salpeter-equation

display_name: bethe-salpeter-equation

gw

display_name: gw

hybrid-functionals

display_name: hybrid-functionals

many-body-techniques

display_name: many-body-techniques

optical-absorption-spectroscopy

display_name: optical-absorption-spectroscopy


en:
Folding of villin miniprotein was studied by parallel tempering metadynamics driven by machine learning. To obtain a training set for machine learning, we generated a large series of structures of the protein by the de novo protein structure prediction package Rosetta. A neural network was trained to approximate the Rosetta score. Parallel tempering metadynamics driven by this approximated Rosetta score successfully predicted the native structure and the free energy surface of the studied system.
These files make it possible to rerun all simulations. The directory METAD contains input files for metadynamics (no folding events observed). The directory PT-METAD contains input files for parallel tempering metadynamics. All simulations were done using Gromacs 2016.4, Anncolvar 0.8, Plumed 2.4 and OpenMPI 4.0.0.

en: Sampling enhancement by metadynamics driven by machine learning and de novo protein modelling

collective-variable

display_name: collective-variable

machine-learning

display_name: machine-learning

metadynamics

display_name: metadynamics

protein-folding

display_name: protein-folding

scoring-function

display_name: scoring-function


en: Temperature-induced Lifshitz transitions have been identified in several materials. Their chemical potential shows a substantial shift with changing temperature. The common feature of these materials is the coexistence of electron and hole pockets in the vicinity of the chemical potential. Here, we report the observation of temperature-induced chemical potential shift and Lifshitz transition in a layered type-II Weyl semimetal, TaIrTe4. The reversal of the polarity of the Hall resistivity and thermoelectric power (TEP) as the temperature increases clearly signal an appreciable shift of the chemical potential and change of the Fermi surface. It is corroborated by the improving agreement between the experimental TEP and the one calculated with temperature-dependent chemical potential. The complete disappearance of an electron pocket, consistent with the change of the Fermi surface when the chemical potential moves downwards, provides an evident signature of a temperature-induced Lifshitz transition in TaIrTe4.

en: Transport signatures of temperature-induced chemical potential shift and Lifshitz transition in layered type-II Weyl semimetal TaIrTe4

chemical-potential-shift

display_name: chemical-potential-shift

cscs

display_name: cscs

lifshitz-transition

display_name: lifshitz-transition

marvel

display_name: marvel

thermoelectric-power

display_name: thermoelectric-power

two-channel-model

display_name: two-channel-model

weyl-semimetal

display_name: weyl-semimetal


epfl

display_name: epfl


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

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

afosr

display_name: afosr

dftu

display_name: dftu

doe

display_name: doe

electron-phonon-coupling

display_name: electron-phonon-coupling

epsrc

display_name: epsrc

first-principles-calculations

display_name: first-principles-calculations

jcap

display_name: jcap

kfas

display_name: kfas

lattice-dynamics

display_name: lattice-dynamics

nersc

display_name: nersc

nffa

display_name: nffa

nsf

display_name: nsf

phonons

display_name: phonons

polarons

display_name: polarons

snsf

display_name: snsf

transition-metal-oxides

display_name: transition-metal-oxides

wannier-function-methods

display_name: wannier-function-methods


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).

afosr

display_name: afosr

marvel

display_name: marvel


collective-variable

display_name: collective-variable

machine-learning

display_name: machine-learning

metadynamics

display_name: metadynamics

protein-folding

display_name: protein-folding

scoring-function

display_name: scoring-function


en: This record contain data to support the result we published in the work "Collective All‐Carbon Magnetism in Triangulene Dimers". Triangular zigzag nanographenes, such as triangulene and its π‐extended homologues, have received widespread attention as organic nanomagnets for molecular spintronics, and may serve as building blocks for high‐spin networks with long‐range magnetic order, which are of immense fundamental and technological relevance. In the publication we present the on‐surface synthesis and a proof‐of‐principle experimental study of magnetism in covalently bonded triangulene dimers. On‐surface reactions of rationally designed precursor molecules on Au(111) lead to the selective formation of triangulene dimers in which the triangulene units are either directly connected through their minority sublattice atoms, or are separated via a 1,4‐phenylene spacer.

en: Collective all‐carbon magnetism in triangulene dimers

erc

display_name: erc

magnetic-carbon

display_name: magnetic-carbon

nanographenes

display_name: nanographenes

spin-chains

display_name: spin-chains


materialscloud

en: Materials Cloud


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

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

dft

display_name: dft

eels

display_name: eels

eu-max

display_name: eu-max

genci

display_name: genci

gold

display_name: gold

interband-transitions

display_name: interband-transitions

intraband-transitions

display_name: intraband-transitions

liouville-lanczos-method

display_name: liouville-lanczos-method

loss-function

display_name: loss-function

marvelosp

display_name: marvelosp

mixed-excitations

display_name: mixed-excitations

plasmons

display_name: plasmons

quantum-espresso

display_name: quantum-espresso

sternheimer-equations

display_name: sternheimer-equations

tddft

display_name: tddft


envi

en: Environment


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

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

enhanced-sampling

display_name: enhanced-sampling

epfl

display_name: epfl

erc

display_name: erc

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics

snsf

display_name: snsf


en: We develop a scheme for finite-size corrections of vertical transition energies and single-particle energy levels involving defect states with built-in ionic polarization in supercell calculations.The method accounts on an equal footing for the screening of the electrons and of the ionic polarization charge arising from the lattice distortions. We demonstrate the accuracy of our corrections for various defects in MgO and in water by comparing with the dilute limit achieved through the scaling of the system size. The general validity of our formulation is also confirmed through a sum rule that connects vertical transition energies with formation energies of structurally relaxed defects.

en: Finite-size corrections of defect energy levels involving ionic polarization

defects

display_name: defects

density-functional-calculations

display_name: density-functional-calculations

dielectric-properties

display_name: dielectric-properties

electric-polarization

display_name: electric-polarization

first-principles-calculations

display_name: first-principles-calculations

optical-absorption-spectroscopy

display_name: optical-absorption-spectroscopy

polarons

display_name: polarons

vacancies

display_name: vacancies


en: The functional properties of transition metal perovskite oxides are known to result from a complex interplay of magnetism, polarization, strain, and stoichiometry. Here, we show that for materials with a cooperative Jahn-Teller distortion, such as LaMnO3 (LMO), the orbital order can also couple to the defect chemistry and induce novel material properties. At low temperatures, LMO exhibits a strong Jahn-Teller distortion that splits the eg orbitals of the high-spin Mn3+ ions and leads to alternating long, short, and intermediate Mn-O bonds. Our DFT+U calculations show that, as a result of this orbital order, the charge localization in LMO upon oxygen vacancy formation differs from other manganites, like SrMnO3, where the two extra electrons reduce the two Mn sites adjacent to the vacancy. In LMO, relaxations around the defect depend on which type of Mn-O bond is broken, affecting the d-orbital energies and leading to asymmetric and hence polar excess electron localization with respect to the vacancy. Moreover, we show that the Mn-O bond lengths, the orbital order and consequently the charge localization and polarity are tunable via strain.

en: Local polarization in oxygen-deficient LaMnO3 induced by charge localization in the Jahn-Teller distorted structure

jahn-teller-distortion

display_name: jahn-teller-distortion

oxygen-vacancies

display_name: oxygen-vacancies

polarization

display_name: polarization

prace

display_name: prace


en: A central goal of condensed matter physics is to understand the rich and diverse electronic and optical properties that emerge as wavelike electrons move through the periodically-arranged atoms in crystalline materials. However, more than 90 years after Bloch derived the functional forms of electronic waves in crystals (now known as Bloch wavefunctions) rapid scattering processes have so far prevented their direct experimental reconstruction. In high-order sideband generation (HSG), electrons and holes generated in semiconductors by a near-infrared (NIR) laser are accelerated to high kinetic energy by a strong terahertz field, and recollide to emit NIR sidebands before they are scattered. Here we reconstruct the Bloch wavefunctions of two types of holes in gallium arsenide wavelengths much longer than the spacing between atoms by experimentally measuring sideband polarizations and introducing an elegant theory that ties those polarizations to quantum interference between different recollision pathways. These Bloch wavefunctions are compactly visualized on the surface of a sphere. Because HSG can, in principle, be observed from any direct-gap semiconductor or insulator, we expect the method introduced in this Article can be used to reconstruct low-energy Bloch wavefunctions in a large class of bulk and nanostructured crystalline materials, and thus enable important new insights into the origin and engineering of electronic and optical properties of condensed matter. This record contains the data and analysis scripts used for these experiments.

en: Reconstruction of Bloch wavefunctions of holes in a semiconductor

bloch-wavefunctions

display_name: bloch-wavefunctions

condensed-matter-physics

display_name: condensed-matter-physics

experimental

display_name: experimental

gallium-arsenide

display_name: gallium-arsenide

luttinger-hamiltonian

display_name: luttinger-hamiltonian

non-equilibrium-physics

display_name: non-equilibrium-physics

nonlinear-optics

display_name: nonlinear-optics

terahertz

display_name: terahertz


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

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

batteries

display_name: batteries

electrode-materials

display_name: electrode-materials

geochemistry

display_name: geochemistry

minerals

display_name: minerals


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).


snsf

display_name: snsf


jahn-teller-distortion

display_name: jahn-teller-distortion


en: We proposed an efficient high-throughput scheme for the discovery of new stable crystalline phases. Our approach was based on the transmutation of known compounds, through the substitution of atoms in the crystal structure with chemically similar ones. The concept of similarity is defined quantitatively using a measure of chemical replaceability, extracted by data mining experimental databases. In this way we build more than 250k possible crystal phases, with almost 20k that are on the convex hull of stability. This dataset contains the optimized structure and the energy of these 250k materials calculated with the PBE approximation, in a format that is convenient for data-mining or for machine-learning applications.

en: Finding new crystalline compounds using chemical similarity

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

machine-learning

display_name: machine-learning


materialscloud

en: Materials Cloud


en:
Set of inputs to perform the calculations reported in the paper.
The i-pi input enables to perform molecular dynamics / metadynamics / REMD / PIMD simulations, with adequate thermostats.
The DFTB and LAMMPS input respectively enable to calculate force and energies within the DFTB and Neural Network Forcefield frameworks.
The CP2K input files enable to calculate force and energies at PBE and PBE0 level. The latter is used as the reference to train the neural network correction on top of DFTB.

Brief description of the work: We present a generally-applicable computational framework for the efficient and accurate characterization of molecular structural patterns and acid properties in explicit solvent using H₂O₂ and CH₃SO₃H in phenol as an example. In order to address the challenges posed by the complexity of the problem, we resort to a set of data-driven methods and enhanced sampling algorithms. The synergistic application of these techniques makes the first-principle estimation of the chemical properties feasible without renouncing to the use of explicit solvation, involving extensive statistical sampling. Ensembles of neural network potentials are trained on a set of configurations carefully selected out of preliminary simulations performed at a low-cost density-functional tight-binding (DFTB) level. Energy and forces of these configurations are then recomputed at the hybrid density functional theory (DFT) level and used to train the neural networks. The stability of the NN model is enhanced by using DFTB energetics as a baseline, but the efficiency of the direct NN (i.e., baseline-free) is exploited via a multiple-time step integrator. The neural network potentials are combined with enhanced sampling techniques, such as replica exchange and metadynamics, and used to characterize the relevant protonated species and dominant non-covalent interactions in the mixture, also considering nuclear quantum effects.

en: Simulating solvation and acidity in complex mixtures with first-principles accuracy: the case of CH₃SO₃H and H₂O₂ in phenol

acid

display_name: acid

acid-homogeneous-catalysis

display_name: acid-homogeneous-catalysis

artificial-intelligence

display_name: artificial-intelligence

catalysis

display_name: catalysis

reaction

display_name: reaction

solution-chemistry

display_name: solution-chemistry


en: We extend the quasiparticle self-consistent approach beyond the GW approximation by using a range-separated vertex function. The developed approach yields band gaps, dielectric constants, and band positions with an accuracy similar to highest-level electronic-structure calculations without exceeding the cost of regular quasiparticle self-consistent GW. We introduce an exchange-correlation kernel that accounts for the vertex over the full spatial range. In the long range it complies with the Ward identity, while it is approximated through the adiabatic local density functional in the short range. In this approach, the renormalization factor is balanced and the higher-order diagrams are effectively taken into account.

en: Vertex function compliant with the Ward identity for quasiparticle self-consistent calculations beyond GW

envi

en: Environment

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

gw

display_name: gw

ionization-potential

display_name: ionization-potential

many-body-perturbation-theory

display_name: many-body-perturbation-theory

vertex

display_name: vertex


marvel

display_name: marvel


en: The magnetic and electronic nature of the γ-Al2O3/SrTiO3 spinel/perovskite interface is explored by means of x-ray absorption spectroscopy. Polarized x-ray techniques combined with atomic multiplet calculations reveal localized magnetic moments assigned to Ti3+ at the interface with equivalent size for in- and out-of-plane magnetic field directions. Although magnetic fingerprints are revealed, the Ti3+ magnetism can be explained by a paramagnetic response at low temperature under applied magnetic fields. Modeling the x-ray linear dichroism results in a Delta0 ∼ 1.9 eV splitting between the t2g and eg states for the Ti4+ 3d0 orbitals. In addition these results indicate that the lowest energy states have the out-of-plane dxz/dyz symmetry. The isotropic magnetic moment behavior and the lowest energy dxz/dyz states are in contrast to the observations for the two-dimensional electron gas at the perovskite/perovskite interface of LaAlO3/SrTiO3 that exhibits an anisotropic magnetic dxy ground state.

en: Magnetic and electronic properties at the γ-Al2O3/SrTiO3 interface

experimental

display_name: experimental

magnetism

display_name: magnetism

two-dimensional-electron-gas

display_name: two-dimensional-electron-gas

x-ray-absorption-spectroscopy

display_name: x-ray-absorption-spectroscopy


acid

display_name: acid

machine-learning

display_name: machine-learning


acid-homogeneous-catalysis

display_name: acid-homogeneous-catalysis

artificial-intelligence

display_name: artificial-intelligence


en: Two-dimensional (2D) layered materials offer a materials platform with potential applications from energy to information processing devices. Although some single- and few-layer forms of materials such as graphene and transition metal dichalcogenides have been realized and thoroughly studied, the space of arbitrarily layered assemblies is still mostly unexplored. The main goal of this work is to demonstrate precise control of layered materials' electronic properties through careful choice of the constituent layers, their stacking, and relative orientation. Physics-based and AI-driven approaches for the automated planning, execution, and analysis of electronic structure calculations are applied to layered assemblies based on prototype one-dimensional (1D) materials and realistic 2D materials. We find it is possible to routinely generate moiré band structures in 1D with desired electronic characteristics such as a band gap of any value within a large range, even with few layers and materials (here, four and six, respectively). We argue that this tunability extends to 2D materials by showing the essential physical ingredients are already evident in calculations of two-layer MoS2 and multi-layer graphene moiré assemblies.

en: Computational design of moiré assemblies aided by artificial intelligence

artificial-neural-networks

display_name: artificial-neural-networks

high-throughput-calculations

display_name: high-throughput-calculations

two-dimensional-materials

display_name: two-dimensional-materials


electronic-structure

display_name: electronic-structure


en:
The production of enantiopure materials and molecules is of uttermost relevance in research and industry in numerous contexts, ranging from non-linear optics to asymmetric synthesis. In the context of the latter, we have investigated dehalogenation, which is an essential reaction step for a broad class of chemical reactions. Specifically, dehalogenation of prochiral 5-bromo-7-methylbenz(a)anthracene (BMA) on prototypical, chiral, intermetallic PdGa{111} surfaces under ultrahigh vacuum conditions. Enantioselective halogen elimination is demonstrated by combining temperature-programmed x-ray photoelectron spectroscopy, scanning probe microscopy, and density functional theory. On the PdGa{111} surfaces, the difference in debromination temperatures for the two BMA surface enantiomers amounts up to unprecedented 46 K. The significant dependence of the dehalogenation temperature of the BMA surface enantiomers on the atomic termination of the PdGa{111} surfaces, implies that the ensemble effect is pronounced in this reaction step. These findings evidence enantiospecific control and hence promote intrinsically chiral crystals for asymmetric on-surface synthesis.
The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.

en: Asymmetric elimination reaction on chiral metal surfaces

ab-initio

display_name: ab-initio

enantioselectivity

display_name: enantioselectivity

scanning-probe-microscopy

display_name: scanning-probe-microscopy

snsf

display_name: snsf


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

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

atomic-coordinates

display_name: atomic-coordinates

copper

display_name: copper

surface-structure

display_name: surface-structure


materialscloud

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

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


en: The record contains data that support our recent findings in the fabrication of cumulene containing polymers. Cumulene compounds are notoriously difficult to prepare and study because their reactivity increases dramatically with the increasing number of consecutive double bonds. In this respect, the emerging field of on‐surface synthesis provides exceptional opportunities because it relies on reactions on clean metal substrates under well‐controlled ultrahigh‐vacuum conditions. In the work we report the on‐surface synthesis of a polymer linked by cumulene‐like bonds on a Au(111) surface via sequential thermally activated dehalogenative C−C coupling of a tribenzoazulene precursor equipped with two dibromomethylene groups. The structure and electronic properties of the resulting polymer with cumulene‐like pentagon–pentagon and heptagon–heptagon connections have been investigated by means of scanning probe microscopy and spectroscopy methods and X‐ray photoelectron spectroscopy, complemented by density functional theory calculations.

en: On‐surface synthesis of cumulene‐containing polymers via two‐step dehalogenative homocoupling of dibromomethylene-functionalized tribenzoazulene

cscs

display_name: cscs

cumulene

display_name: cumulene

dfg

display_name: dfg

erc

display_name: erc

on-surface-synthesis

display_name: on-surface-synthesis

polymers

display_name: polymers


materialscloud

en: Materials Cloud


en: We study the nature of excess electrons in CsPbBr3 and identify several single and double polaronic states. We emphasize the importance of proper inclusion of the self-interaction corrections for the stability of small electron polarons in this material. We demonstrate that spin–orbit coupling (SOC) has a significant impact on the energetics of the polaronic states. In particular, we find that SOC disfavors electron localization and leads to different polaronic geometries. Additionally, by carrying out thermodynamic integration, we show that small electron polarons are thermally stabilized in CsPbBr3. The small energy differences between the localized and delocalized electronic states could possibly reconcile the apparently conflicting properties of high charge-carrier mobilities and low recombinations rates.

en: Small electron polarons in CsPbBr3

halide-perovskites

display_name: halide-perovskites

polarons

display_name: polarons


en: In this record we provide data to support our recent findings on the synthesis of porphyrin-capped graphene nanoribbons. On-surface synthesis has emerged as a powerful tool for the construction of large, planar, π-conjugated structures that are not accessible through standard solution chemistry. Among such solid-supported architectures, graphene nanoribbons (GNRs) hold a prime position for their implementation in nanoelectronics due to their manifold outstanding properties. Moreover, using appropriately designed molecular precursors, this approach allows the synthesis of functionalized GNRs, leading to nanostructured hybrids with superior physicochemical properties. Among the potential "partners" for GNRs, porphyrins (Pors) outstand due to their rich chemistry, robustness, and electronic richness, among others. However, the use of such π-conjugated macrocycles for the construction of GNR hybrids is challenging and examples are scarce. In a recent publication we report singly and doubly Por-capped GNR segments presenting a commensurate and triply-fused GNR–Por heterojunction. The study of the electronic properties of such hybrid structures by high-resolution scanning tunneling microscopy, scanning tunneling spectroscopy, and DFT calculations reveals a weak hybridization of the electronic states of the GNR segment and the Por moieties despite their high degree of conjugation.

en: On-surface synthesis of singly and doubly porphyrin-capped graphene nanoribbon segments

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

porphyrin

display_name: porphyrin

snf

display_name: snf


envi

en: Environment


en: In this record we provide data supporting our recent results discussed in the fabrication of non-benzenoid nanographenes. Nanographenes (NGs) have gained increasing attention due to their immense potential as tailor-made organic materials for nanoelectronics and spintronics. They exhibit a rich spectrum of physicochemical properties that can be tuned by controlling the size or the edge structure or by introducing structural defects in the honeycomb lattice. In the published manuscript we report the design and on-surface synthesis of NGs containing several odd-membered polycycles induced by a thermal procedure on Au(111). Our scanning tunneling microscopy, noncontact atomic force microscopy, and scanning tunneling spectroscopy measurements, complemented by computational investigations, describe the formation of two nonbenzenoid NGs (2A,B) containing four embedded azulene units in the polycyclic framework, via on-surface oxidative ring-closure reactions. Interestingly, we observe surface-catalyzed skeletal ring rearrangement reactions in the NGs, which lead to the formation of additional heptagonal rings as well as pentalene and as-indacene units in 2A,B, respectively. 2A,B on Au(111) both exhibit narrow experimental frontier electronic gaps of 0.96 and 0.85 eV, respectively, and Fermi level pinning of their HOMOs together with considerable electron transfer to the substrate. Ab initio calculations estimate moderate open-shell biradical characters for the NGs in the gas phase.

en: On-surface synthesis of non-benzenoid nanographenes by oxidative ring-closure and ring-rearrangement reactions

ab-initio-simulations

display_name: ab-initio-simulations

dfg-nsfc

display_name: dfg-nsfc

nanographenes

display_name: nanographenes

open-shell

display_name: open-shell


snsf

display_name: snsf


en:
We present the JuCLS (Jülich core-level shifts) database which collects first principles calculations of core-level binding energies and core-level shifts (also known as chemical shifts). The calculations for this database were performed with the FLEUR program [1], a feature-full, freely available, open source FLAPW (full-potential linearized augmented planewave) code, based on density-functional theory. The FLAPW-method is a very accurate all-electron method which within density functional theory is universally applicable to all atoms of the periodic table. All calculations are run with AiiDA through workflows within the AiiDA-FLEUR package (version 0.12.3) [2]. Our database collects predicted core-level shifts, binding energies for X-ray photoelectron spectroscopy (XPS) and as a side product formation energies. Core-level shifts are calculated within the initial state approximation and binding energies are extracted from core-hole simulations. The JuCLS v1.0 contains initial state core-level shifts and formation energies on 4435 of the 5058 stable binary metals from the Materials project database (MP) and calculations on 1271 elemental crystals from the Inorganic Crystal Structure Database (ICSD). This corresponds currently to over 130 000 unique core-level shifts and over 15 000 unique main line core-level shifts. The JuCLS database allows for the construction of theoretical X-ray photoelectron spectra containing a possible mixture of these materials. Furthermore, it allows for a direct chemical characterization of materials.

[1] https://flapw.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-fleur

en: JuCLS database of core-level shifts from all-electron density functional theory simulations for chemical analysis of X-ray photoelectron spectra

ab-initio

display_name: ab-initio

aiida-fleur

display_name: aiida-fleur

binding-energies

display_name: binding-energies

chemical-shifts

display_name: chemical-shifts

core-level

display_name: core-level

core-level-shifts

display_name: core-level-shifts

density-functional-theory

display_name: density-functional-theory

esca

display_name: esca

flapw

display_name: flapw

fleur

display_name: fleur

jucls

display_name: jucls

max

display_name: max

x-ray-photoelectron-spectroscopy

display_name: x-ray-photoelectron-spectroscopy

xps

display_name: xps


en: The article presents a series of methods that boost the speed of Wannier interpolation by several orders of magnitude, as well as their implementation in the WannierBerri code. The present dataset contains input files, scripts, and the resulting data, which allow to reproduce the examples and figures published in the article. The current version of the code is also included.

en: High performance Wannier interpolation of Berry curvature and related quantities with WannierBerri code

anomalous-hall-effect

display_name: anomalous-hall-effect

berry-curvature

display_name: berry-curvature

erc

display_name: erc

wannier-functions

display_name: wannier-functions


snsf

display_name: snsf


en: Superconductivity with a remarkably high Tc has recently been observed in hole-doped NdNiO2, a material that shares similarities with the high-Tc cuprates. This discovery promises new insights into the mechanism of unconventional superconductivity, but at the modeling level, there are fundamental issues that need to be resolved. While it is generally agreed that the low-energy properties of cuprates can, to a large extent, be captured by a single-band model, there has been a controversy in the recent literature about the importance of a multiband description of the nickelates. Here, we use a multisite extension of the recently developed GW+EDMFT method, which is free of adjustable parameters, to self-consistently compute the interaction parameters and electronic structure of hole-doped NdNiO2. This full ab initio simulation demonstrates the importance of a multiorbital description, even for the undoped compound, and it produces results for the resistivity and Hall conductance in qualitative agreement with experiment.

en: Normal State of Nd_(1-x)Sr_xNiO2 from Self-Consistent GW+EDMFT

correlated-oxides

display_name: correlated-oxides

dynamical-mean-field-theory

display_name: dynamical-mean-field-theory

gwedmft

display_name: gwedmft


materialscloud

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

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


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

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

crystal-structures

display_name: crystal-structures

donor-acceptor-copolymers

display_name: donor-acceptor-copolymers

optical-properties

display_name: optical-properties

organic-molecules

display_name: organic-molecules

photophysical-properties

display_name: photophysical-properties


en: Researchers continue to explore and develop aluminum alloys with new compositions and improved performance characteristics. An understanding of the current design space can help accelerate the discovery of new alloys. We present two datasets: 1) chemical composition, and 2) mechanical properties for predominantly wrought aluminum alloys. The first dataset contains 14,884 entries on aluminum alloy compositions extracted from academic literature and US patents using text processing techniques, including 550 wrought aluminum alloys which are already registered with the Aluminum Association. The second dataset contains 1,278 entries on mechanical properties for aluminum alloys, where each entry is associated with a particular wrought series designation, extracted from tables in academic literature.

materialscloud

en: Materials Cloud

en: Aluminum alloy compositions and properties extracted from a corpus of scientific manuscripts and US patents

aluminum

display_name: aluminum

chemical-composition

display_name: chemical-composition

experimental

display_name: experimental

materials-discovery

display_name: materials-discovery

mechanical-properties

display_name: mechanical-properties

metals-and-alloys

display_name: metals-and-alloys


en: In the present record we provide the data obtained in ARPES experiments and input/output files of Quantum ESPRESSO calculations used in the publication entitled as this record. The experimental data consist of the Fermi surface at kz=π/c, the experimental band dispersion along the MΓM, XΓX and XMX, spin-resolved ARPES spectra, and spin-resolved ARPES spectra of surface states. The theoretical data consist in the bulk and slab calculations to support the experimental data.

en: Hidden bulk and surface effects in the spin polarization of the nodal-line semimetal ZrSiTe

arpes

display_name: arpes

epfl

display_name: epfl

hidden-polarization

display_name: hidden-polarization

marvel

display_name: marvel

spin-texture

display_name: spin-texture


envi

en: Environment

snsf

display_name: snsf


en: Quantitative evaluation of the thermodynamic properties of materials—most notably their stability, as measured by the free energy—must take into account the role of thermal and zero-point energy fluctuations. While these effects can easily be estimated within a harmonic approximation, corrections arising from the anharmonic nature of the interatomic potential are often crucial and require computationally costly path integral simulations to obtain results that are essentially exact for a given potential. Consequently, different approximate frameworks for computing affordable estimates of the anharmonic free energies have been developed over the years. Understanding which of the approximations involved are justified for a given system, and therefore choosing the most suitable method, is complicated by the lack of comparative benchmarks. To facilitate this choice we assess the accuracy and efficiency of some of the most commonly used approximate methods: the independent mode framework, the vibrational self-consistent field, and self-consistent phonons. We compare the anharmonic correction to the Helmholtz free energy against reference path integral calculations. These benchmarks are performed for a diverse set of systems, ranging from simple weakly anharmonic solids to flexible molecular crystals with freely rotating units. The results suggest that, for simple solids such as allotropes of carbon, these methods yield results that are in excellent agreement with the reference calculations, at a considerably lower computational cost. For more complex molecular systems such as polymorphs of ice and paracetamol the methods do not consistently provide a reliable approximation of the anharmonic correction. Despite substantial cancellation of errors when comparing the stability of different phases, we do not observe a systematic improvement over the harmonic approximation even for relative free energies. We conclude that, at least for the classes of materials considered here, efforts toward obtaining computationally feasible anharmonic free energies should therefore be directed toward reducing the expense of path integral methods.

en: Assessment of approximate methods for anharmonic free energies

crystal-structure-prediction

display_name: crystal-structure-prediction

erc

display_name: erc

nuclear-quantum-effects

display_name: nuclear-quantum-effects

quantum-statistics

display_name: quantum-statistics


en: Fast, empirical potentials are gaining increased popularity in the computational fields of materials science, physics and chemistry. With it, there is a rising demand for high-quality reference data for the training and validation of such models. In contrast to research that is mainly focused on small organic molecules, this work presents a data set of geometry-optimized bulk phase zeolite structures. Covering a majority of framework types from the Database of Zeolite Structures, this set includes over thirty thousand geometries. Calculated properties include system energies, nuclear gradients and stress tensors at each point, making the data suitable for model development, validation or referencing applications focused on periodic silica systems.

en: Zeo-1: A computational data set of zeolite structures

bulk-phase

display_name: bulk-phase

density-functional-theory

display_name: density-functional-theory

dft

display_name: dft

horizon-europe

display_name: horizon-europe

machine-learning

display_name: machine-learning

marie-curie-fellowship

display_name: marie-curie-fellowship

silica

display_name: silica

zeolite

display_name: zeolite


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

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

machine-learning-potentials

display_name: machine-learning-potentials

on-the-fly-probability-sampling

display_name: on-the-fly-probability-sampling

opes

display_name: opes

proton-couple-electron-transfer

display_name: proton-couple-electron-transfer

reweighting

display_name: reweighting


en: Methane steam reforming (MSR) plays a key role in the production of syngas and hydrogen from natural gas. The increasing interest in the use of hydrogen for fuel cell applications demands the development of catalysts with high activity at reduced operating temperatures. Ni-based catalysts are promising systems because of their high activity and low cost, but coke formation generally poses a severe problem. Studies of ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) indicate that CH4/H2O gas mixtures react with Ni/CeO2(111) surfaces to form OH, CHx and CHxO at 300 K. All these species are easy to form and desorb at temperatures below 700 K when the rate of the MSR process accelerates. Density functional theory (DFT) modeling of the reaction over ceria-supported small Ni nanoparticles predicts relatively low activation barriers between 0.3–0.7 eV for the complete dehydrogenation of methane to carbon and the barrierless activation of water at interfacial Ni sites. Hydroxyls resulting from water activation allow CO formation via a COH intermediate with a barrier of about 0.9 eV, which is much lower than that through a pathway involving lattice oxygen from ceria. Neither methane nor water activation are rate-determining steps, and the OH-assisted CO formation through the COH intermediate constitutes a low-barrier pathway that prevents carbon accumulation. The interaction between Ni and the ceria support and the low metal loading are crucial for the reaction to proceed in a coke-free and efficient way. These results could pave the way for further advances in the design of stable and highly active Ni-based catalysts for hydrogen production.

en: Reaction pathway for coke-free methane steam reforming on a Ni/CeO2 catalyst: Active sites and role of metal-support interactions

ceria

display_name: ceria

hydrogen

display_name: hydrogen

methane

display_name: methane

nickel

display_name: nickel

steam-reforming

display_name: steam-reforming


en: This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble (PT-MetaD-WTE) simulations in PLUMED using GROMACS 2018.3.

materialscloud

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

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

en: Impact of glutamate carboxylation in the adsorption of the alpha-1 domain of osteocalcin to hydroxyapatite and titania

biomimetics

display_name: biomimetics

biomineralization

display_name: biomineralization

metadynamics

display_name: metadynamics

molecular-dynamics

display_name: molecular-dynamics


en: The systematic tuning of the lattice parameters to achieve improved kinematic compatibility between phases is a broadly effective strategy for improving the reversibility, and lowering the hysteresis, of solid-solid phase transformations. Here, "kinematic compatibility" refers to the fitting together of the phases. We present an apparently paradoxical example in which tuning to near perfect compatibility in (Zr/Hf)O2-(YNb)O4 results in a high degree of irreversibility, as manifested in explosive or "weeping" behavior on cooling through the tetragonal-to-monoclinic phase transformation. In the case of weeping the polycrystal slowly and steadily falls apart at the grain boundaries. These effects occur without chemical change. Finally, tuning to satisfy a condition we term the equidistance condition results in reversible behavior with the lowest hysteresis in this system. We give evidence that all these observations are explained by a more careful analysis of compatibility of the polycrystal, accounting for sample shape. These results show that an extreme diversity of behaviors, from reversible to explosive, is possible in a chemically homogeneous system by manipulating conditions of compatibility in unexpected ways. They provide critical concepts underlying the current search for a shape memory oxide ceramic.

en: Exploding and weeping ceramics

ceramics

display_name: ceramics

cystallographic-compatibility

display_name: cystallographic-compatibility

shape-memory

display_name: shape-memory


exploding-and-weeping-ceramics

materialscloud

en: Materials Cloud

title_for_slug: exploding-and-weeping-ceramics


en:
Spintronics applications for high-density non-volatile memories require simultaneous optimization of the perpendicular magnetic anisotropy (PMA) and current-induced magnetization switching. These properties determine, respectively, the thermal stability of a ferromagnetic memory cell and a low operation power consumption, which are mutually incompatible with the spin transfer torque as the driving force for the switching. Here, we demonstrate a strategy of alloy engineering to overcome this obstacle by using electrically induced orbital currents instead of spin currents. A non-equilibrium orbital density generated in paramagnetic γ-FeMn flows into CoPt coupled to the magnetization through spin-orbit interaction, ultimately creating an orbital torque. Controlling the atomic arrangement of Pt and Co by structural phase transition, we show that the propagation length of the transferred angular momentum can be modified concurrently with the PMA strength. We find a strong correlation to the phase transition-induced changes of d orbitals with mₗ = ±1 and mₗ = ±2 character. The close link of orbital hybridization to the dynamic orbital response and magnetic properties offers new possibilities to realize optimally designed orbitronics memory and logic applications.
This dataset contains the DFT calculations for the electronic structure of CoPt in L1₁ and A1 structures that are discussed the corresponding publication.

en: DFT calculations of the electronic structure of CoPt in L1₁ and A1 structures

density-functional-theory

display_name: density-functional-theory

orbital-torque

display_name: orbital-torque

orbitronics

display_name: orbitronics


envi

en: Environment


en: The chemical versatility of carbon imparts manifold properties to organic compounds, where magnetism remains one of the most desirable but elusive. Polycyclic aromatic hydrocarbons, also referred to as nanographenes, show a critical dependence of electronic structure on the topologies of the edges and the π-electron network, which makes them model systems with which to engineer unconventional properties including magnetism. In 1972, Erich Clar envisioned a bow-tie-shaped nanographene, C38H18, where topological frustration in the π-electron network renders it impossible to assign a classical Kekulé structure without leaving unpaired electrons, driving the system into a magnetically non-trivial ground state. In this record we include data needed to support our recent work where we demonstrate the experimental realization and in-depth characterization of this emblematic nanographene, known as Clar's goblet. Scanning tunnelling microscopy and spin excitation spectroscopy of individual molecules on a gold surface reveal a robust antiferromagnetic order with an exchange-coupling strength of 23 meV, exceeding the Landauer limit of minimum energy dissipation at room temperature. Through atomic manipulation, we realize switching of magnetic ground states in molecules with quenched spins. Our results provide direct evidence of carbon magnetism in a hitherto unrealized class of nanographenes, and prove a long-predicted paradigm where topological frustration entails unconventional magnetism, with implications for room-temperature carbon-based spintronics.

en: Topological frustration induces unconventional magnetism in a nanographene

ab-initio

display_name: ab-initio

clar-goblet

display_name: clar-goblet

erc

display_name: erc

kondo

display_name: kondo

nanographene

display_name: nanographene

snsf

display_name: snsf


en: The vast chemical space of metal and ligand combinations in Transition Metal Complexes (TMCs) gives rise to a rich variety of electronic excited states with local and non-local character such as intra-ligand (IL), metal-centered (MC), metal-to-ligand (MLCT) or ligand-to-metal charge-transfer (LMCT) states. Those features are equally found in Metal Organic Frameworks (MOFs), defined as modular materials built from metal-nodes connected through organic-ligands. Because of the electronic and structural complexity of MOFs, the computational description of their excited states is a formidable challenge for which two different approaches have been usually followed: the solid state and the molecular perspective. The first consists in analysing the frontier electronic bands and crystal orbitals of the electronic ground state (GS) in periodic boundary conditions, while the latter points to an accurate computation of the excited states in representative clusters at the molecular level. Herein, we apply both approaches to evaluate the optical absorption properties of three experimentally reported Ti(IV) mononuclear MOFs with in silico metal substitutions with Zn(II), Cd(II), Fe(II), Ru(II) and Zr(IV) ions, thus covering d10, d6 and d0 electronic configurations of 1st and 2nd row TMCs in MOFs. Our analysis captures the main electronic features attributed to these systems while we discuss the main advantages and drawbacks of both approximations.

en: Optical absorption properties of metal-organic frameworks: solid state versus molecular perspective

epfl

display_name: epfl

mof

display_name: mof

optical-absorption

display_name: optical-absorption


en:
One proposed mechanism of implant fouling is attributed to the nonspecific adsorption of non-collagenous bone matrix proteins (NCPs) onto a newly implanted interface. With the goal of capturing the fundamental mechanistic and thermodynamic forces that govern changes in these NCP recognition domains as a function of γ-carboxyglutamic acid (Gla) post-translational modification and surface chemistry, we probe the adsorption process of the most commonly occurring NCP, osteocalcin, onto a mineral and metal oxide surface. Here, we apply two enhanced sampling methods to independently probe the effects of post-translational modification and peptide structure on adsorption. First, well-tempered metadynamics was used to capture the binding of acetyl and N-methylamide capped glutamic acid and Gla single amino acids onto crystalline hydroxyapatite and titania model surfaces at physiological pH. Following this, parallel tempering metadynamics in the well-tempered ensemble (PTMetaD-WTE) was used to study adsorption of the α-1 domain of osteocalcin onto hydroxyapatite and titania. Simulations were performed for the α-1 domain of osteocalcin in both its fully decarboxylated (dOC) and fully carboxylated (OC) form. Our simulations find that increased charge density due to carboxylation results in increased interactions at the interface, and stronger adsorption of the single amino acids to both surfaces. Interestingly, the role of Gla in promoting compact and helical structure in the α-1 domain resulted in disparate binding modes at the two surfaces, which is attributed to differences in interfacial water behavior. Overall, this work provides a benchmark for understanding the mechanisms that drive adsorption of Gla-containing mineralizing proteins onto different surface chemistries.

This record contains files necessary to reproduce enhanced sampling well-tempered metadynamics (wtMTD) and parallel tempering metadynamics in the well-tempered ensemble (PT-MetaD-WTE) simulations in PLUMED using GROMACS 2018.3.

biomimetics

display_name: biomimetics

biomineralization

display_name: biomineralization

metadynamics

display_name: metadynamics


molecular-dynamics

display_name: molecular-dynamics


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

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

bayesian-calibration

display_name: bayesian-calibration

dftu

display_name: dftu

markov-chain-monte-carlo

display_name: markov-chain-monte-carlo

mcmc

display_name: mcmc


en: High-strength metal alloys achieve their performance via careful control of the nucleation, growth, and kinetics of precipitation. Alloy mechanical properties are then controlled by atomic scale phenomena such as shearing of the precipitates by dislocations. Atomistic modeling to understand the operative mechanisms requires length and time scales far larger than those accessible by first-principles methods. Here, a family of Behler-Parinello neural-network potentials (NNPs) for the Al-Mg-Si system is developed to enable quantitative studies of Al-6xxx alloys. The NNP is trained on metallurgically-important quantities computed by first principles density functional theory (DFT) leading to high fidelity predictions of intermetallic compounds, elastic constants, dilute solid-solution energetics, precipitate/matrix interfaces, Al stacking fault energies, antisite defect energies, and other quantities. A preliminary examination of early-stage clustering kinetics and energetics in Al-6xxx is then made, showing the formation of low-energy Mg-Si structures and the trapping of vacancies in these clusters. The Generalized Stacking Fault Energy surfaces (GSFE) for the three prevalent β" precipitate compositions in peak-aged Al-6xxx are then computed with the NNP, and are validated by DFT computations at key points. The NNP thus shows significant transferability across structures, making it a powerful approach for chemically-accurate simulations of metallurgical phenomena in Al-Mg-Si alloys.

en: Machine learning for metallurgy: a neural network potential for Al-Mg-Si

aluminum

display_name: aluminum

machine-learning

display_name: machine-learning

metallurgy

display_name: metallurgy


materialscloud

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

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


en: In this record, we provide the data supporting our recent results on the synthesis of nitrogen-substituted undecacene analogs. Heteroatom substitution in acenes allows to tailor their remarkable electronic properties, expected to include spin-polarization and magnetism for larger members of the acene family. Here, we present a strategy for the on-surface synthesis of three undecacene analogs substituted with four nitrogen atoms on an Au(111) substrate, by employing specifically designed diethano-bridged precursors. A similarly designed precursor is used to synthesize the pristine undecacene molecule. In the publication where the results are discussed, the experimental features of scanning probe microscopy are compared with ab initio simulations, to demonstrate that the ground state of the synthesized tetraazaundecacene has considerable open-shell character on Au(111). Additionally, we demonstrate that electronegative nitrogen atoms induce a considerable shift in energy level alignment compared to the pristine undecacene, and that the introduction of hydro-aza groups causes local anti-aromaticity in the synthesized compounds. Our work provides access to the precise fabrication of nitrogen-substituted acene and its analogs, potential building-blocks of organic electronics and spintronics, and a rich playground to explore pi-electron correlation.

en: On-surface synthesis and characterization of nitrogen-substituted undecacenes

aromaticity

display_name: aromaticity

cscs

display_name: cscs

experimental

display_name: experimental

heteroacenes

display_name: heteroacenes

on-surface-synthesis

display_name: on-surface-synthesis

open-shell

display_name: open-shell


snsf

display_name: snsf


en: By combining metal nodes and organic linkers one can make millions of different metal-organic frameworks (MOFs). At present over 90,000 MOFs have been synthesized and there are databases with over 500,000 predicted structures. This raises the question of whether a new experimental or predicted structure adds new information. For MOF-chemists the chemical design space is a combination of pore geometry, metal nodes, organic linkers, and functional groups, but at present we do not have a formalism to quantify optimal coverage of chemical design space. In this work, we show how machine learning can be used to quantify similarities of MOFs. This quantification allows us to use techniques from ecology to analyse the chemical diversity of these materials in terms of diversity metrics. In particular, we show that this diversity analysis can identify biases in the databases, and how such bias can lead to incorrect conclusions. This formalism provides us with a simple and powerful practical guideline to see whether a set of new structures will have the potential for new insights, or constitute a relatively small variation of existing structures.

en: Understanding the diversity of the metal-organic framework ecosystem

chemical-space

display_name: chemical-space

diversity

display_name: diversity

metal-organic-frameworks

display_name: metal-organic-frameworks


materialscloud

en: Materials Cloud


en: In this record we provide data to support our recent findings for the fabrication of Unsaturated Carbon Nanostructures with Regularly Fused Pentagon–Heptagon Pairs. Multiple fused pentagon–heptagon pairs are frequently found as defects at the grain boundaries of the hexagonal graphene lattice and are suggested to have a fundamental influence on graphene-related materials. However, the construction of sp2-carbon skeletons with multiple regularly fused pentagon–heptagon pairs is challenging. In this work, we found that the pentagon–heptagon skeleton of azulene was rearranged during the thermal reaction of an azulene-incorporated organometallic polymer on Au(111). The resulting sp2-carbon frameworks were characterized by high-resolution scanning probe microscopy techniques and feature novel polycyclic architectures composed of multiple regularly fused pentagon–heptagon pairs. Moreover, the calculated analysis of its aromaticity revealed a peculiar polar electronic structure.

en: On-surface synthesis of unsaturated carbon nanostructures with regularly fused pentagon-heptagon pairs

carbon-nanostructures

display_name: carbon-nanostructures

open-shell-systems

display_name: open-shell-systems

polymers

display_name: polymers


envi

en: Environment