en: In this record we provide data to support our recent findings for the magnetic properties of rhombus-shaped nanographenes. Nanographenes with zigzag edges are predicted to manifest non-trivial π-magnetism resulting from the interplay of concurrent electronic effects, such as hybridization of localized frontier states and Coulomb repulsion between valence electrons. This provides a chemically tunable platform to explore quantum magnetism at the nanoscale and opens avenues towards organic spintronics. The magnetic stability in nanographenes is thus far greatly limited by the weak magnetic exchange coupling, which remains below the room-temperature thermal energy. In our work, we report the synthesis of large rhombus-shaped nanographenes with zigzag peripheries on gold and copper surfaces. Single-molecule scanning probe measurements show an emergent magnetic spin singlet ground state with increasing nanographene size. The magnetic exchange coupling in the largest nanographene (C70H22, containing five benzenoid rings along each edge), determined by inelastic electron tunnelling spectroscopy, exceeds 100 meV or 1,160 K, which outclasses most inorganic nanomaterials and survives on a metal electrode.

en: Large magnetic exchange coupling in rhombus-shaped nanographenes with zigzag periphery

ab-initio

display_name: ab-initio

cscs

display_name: cscs

graphene-flagship

display_name: graphene-flagship

magnetic-carbon

display_name: magnetic-carbon

nanographenes

display_name: nanographenes

snsf

display_name: snsf


$oid: OBSOLETE

en: This entry includes the MD trajectories of several semiconductor-water interfaces generated with ab initio molecular dynamics using the rVV10 density functional at the temperature of 350 K. Eight semiconductor surfaces are considered, namely GaAs(110), GaP(110), GaN(10-10), CdS(10-10), ZnO(10-10), SnO2(110), rutile TiO2(110) and anatase TiO2(101). For GaAs, GaP and anatase TiO2, the trajectories for the interfaces with both the molecular and the dissociative adsorption mode of water are provided. In addition, the relaxed atomic structures of the semiconductor surfaces used to calculate the ionization potential (IP) reported in [Chem. Mater. 2018, 30, 94−111] are added.

en: MD trajectories of semiconductor-water interfaces and relaxed atomic structures of semiconductor surfaces

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

md-trajectory

display_name: md-trajectory

semiconductor-water-interface

display_name: semiconductor-water-interface


en: The ab initio determination of the character and properties of electronic excited states (ES) is the cornerstone of modern theoretical photochemistry. Yet, traditional ES methods become readily impractical when applied to fairly large molecules, or when used on thousands of different systems. In contrast, Machine Learning (ML) techniques have demonstrated their accuracy at retrieving ES properties of large molecular databases at a reduced computational cost. Especially for excited states applications, non-linear algorithms tend to be specialized and to target only individual properties. Learning fundamental quantum chemical objects potentially represents a more efficient, yet complex, alternative as a large number of molecular properties could be then extracted through post-processing. Herein, we report the general framework able to learn three fundamental objects of an ES: the hole and particle densities, as well as the transition density. We demonstrate the advantages of targeting those outputs of an ES computation, and address the additional complexity of learning 3-dimensional scalar fields. We apply our predictions to obtain a list of derived properties, including the state character and the topological descriptors of the exciton, for the two bands (nπ* and ππ*) of a collection of 3432 azoheteroarene photoswitches. In doing so, we prove that the proposed approach offers a way to access ES information of different kinds, bypassing the need of traditional electronic structure computations, while retaining ab initio accuracy.

en: Learning the exciton properties of azo-dyes

azo-dyes

display_name: azo-dyes

epfl

display_name: epfl

erc

display_name: erc

hole-and-particle-densities

display_name: hole-and-particle-densities

machine-learning

display_name: machine-learning

photoswitches

display_name: photoswitches


en: Group 15 elements in zero oxidation state (P, As, Sb and Bi), also called pnictogens, are rarely used in catalysis due to the difficulties associated in preparing well–structured and stable materials. Here, we report on the synthesis of highly exfoliated, few layer 2D phosphorene and antimonene in zero oxidation state, suspended in an ionic liquid, with the native atoms ready to interact with external reagents while avoiding aerobic or aqueous decomposition pathways, and on their use as efficient catalysts for the alkylation of nucleophiles with esters. The few layer pnictogen material circumvents the extremely harsh reaction conditions associated to previous superacid–catalyzed alkylations, by enabling an alternative mechanism on surface, protected from the water and air by the ionic liquid. These 2D catalysts allow the alkylation of a variety of acid–sensitive organic molecules and giving synthetic relevancy to the use of simple esters as alkylating agents.

en: Few layer 2D pnictogens catalyze the alkylation of soft nucleophiles with esters.

alkylation

display_name: alkylation

antimonene

display_name: antimonene

black-phosphorous

display_name: black-phosphorous

esters

display_name: esters

ionic-liquids

display_name: ionic-liquids


en: We investigate twisted double bilayer graphene (TDBG), a four-layer system composed of two AB-stacked graphene bilayers rotated with respect to each other by a small angle. Our ab-initio band structure calculations reveal a considerable energy gap at the charge point neutrality that we assign to the intrinsic symmetric polarization (ISP). We then introduce the ISP effect into the tight-binding parameterization and perform calculations on TDBG models that include lattice relaxation effects down to very small twist angles. We identify a narrow region around the magic angle θ*= 1.3° characterized by a manifold of remarkably flat bands gapped out from other states even without external electric fields. To understand the fundamental origin of the magic angle in TDBG, we construct a continuum model that points to a hidden mathematical link to the twisted bilayer graphene (TBG) model, thus indicating that the band flattening is a fundamental feature of TDBG, and is not a result of external fields.

en: Moiré Flat Bands in Twisted Double Bilayer Graphene

continuum-model

display_name: continuum-model

flat-bands

display_name: flat-bands

magic-angle

display_name: magic-angle

moire-superlattice

display_name: moire-superlattice

tight-binding-model

display_name: tight-binding-model

twisted-double-bilayer-graphene

display_name: twisted-double-bilayer-graphene

wanniertools

display_name: wanniertools


en: We present a database of energy and NMR chemical shifts DFT calculations of 4150 crystal organic solids. The structures contain only H/C/N/O/S atoms and were subject to all-atoms geometry optimisation. Calculations were carried out using Quantum Espresso and GIPAW.

en: Chemical Shifts in Molecular Solids by Machine Learning Datasets

chemical-shifts

display_name: chemical-shifts

energy-calculations

display_name: energy-calculations

gipaw

display_name: gipaw

nmr

display_name: nmr

organic-solids

display_name: organic-solids

quantum-espresso

display_name: quantum-espresso

snsf

display_name: snsf


en:
This record refers to a study on the electroluminescence of individual GNRs suspended between the tip of a scanning tunneling microscope (STM) and a Au(111) substrate. Emission spectra of such GNR junctions reveal a bright and narrow band emission of red light, whose energy can be tuned with the bias voltage applied to the junction, but always lying below the gap of infinite GNRs. Comparison with ab initio calculations indicates that the emission involves electronic states localized at the GNR termini. The results shed light on unpredicted optical transitions in GNRs.

The record includes the computational data that allows to reproduce the published results.

en: Bright Electroluminescence from Single Graphene Nanoribbon Junctions

density-functional-theory

display_name: density-functional-theory

electroluminescence

display_name: electroluminescence

graphene-nanoribbons

display_name: graphene-nanoribbons

gw

display_name: gw

induced-light-emission

display_name: induced-light-emission

max

display_name: max

prace

display_name: prace

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy

single-molecule-junction

display_name: single-molecule-junction


en: Vertically aligned nanocomposites (VANs) films have self-assembled pillar-matrix nanostructures. Owing to their large area-to-volume ratios,  interfaces in VAN films are expected to play key roles in inducing functional properties, but our understanding is hindered by limited knowledge about their structures. Motivated by the lack of definitive explanation for the experimentally-found enhanced ionic conductivity in Sm-doped-CeO2/SrTiO3 VAN films, we determine the structure at vertical interfaces using random structure searching and explore how it can affect ionic conduction. This record contains the candidate structures and provenance of the DFT validation calculations. Previously unknown interface structures are found, with lower energy than that of an optimized hand-built model. We find a strongly distorted oxygen sub-lattice which gives a complex landscape of vacancy energies. The cation lattice remains similar to the bulk phase but has a localized strain field. The excess energy of the interface is similar to that of high angle grain boundaries in SrTiO3.

en: Determining interface structures in vertically aligned nanocomposite films

solid-solid-interface

display_name: solid-solid-interface

structure-prediction

display_name: structure-prediction


en: Molecular simulations with periodic boundary conditions require to define a certain cutoff distance   beyond which pairwise dispersion interactions are neglected. For the simulation of homogeneous phases it is well-established to use tail-corrections, that can remedy this truncation of the potential. These corrections are built under the assumption that beyond  the cutoff the radial distribution function is equal to one. In this work we shed some light on the discussion whether or not tail corrections should be used in the  modelling of heterogeneous systems. We show that for the adsorption of gasses in a diverse set  nanoporous crystalline materials (zeolites, Covalent Organic Frameworks (COFs), and Metal Organic Frameworks (MOFs)), tail-corrections are an appropriate choice with which the results are much less sensitive to the details of the truncation.

en: Applicability of tail-corrections in the molecular simulations of porous materials

covalent-organic-frameworks

display_name: covalent-organic-frameworks

gcmc

display_name: gcmc

marvel

display_name: marvel

metal-organic-frameworks

display_name: metal-organic-frameworks

tail-corrections

display_name: tail-corrections

zeolites

display_name: zeolites


en: The electronic properties of the oxygen vacancy and interstitial in amorphous Al2O3 are studied via ab initio molecular dynamics simulations and hybrid functional calculations. Our results indicate that these defects do not occur in amorphous Al2O3, due to structural rearrangements which assimilate the defect structure and cause a delocalization of the associated defect levels. The imbalance of oxygen leads to a nonstoichiometric compound in which the oxygen occurs in the form of O2– ions. Intrinsic oxygen defects are found to be unable to trap excess electrons. For low Fermi energies, the formation of peroxy linkages is found to be favored leading to the capture of holes. The relative +2/0 defect levels occur at 2.5 eV from the valence band.

en: Oxygen defects in amorphous Al2O3

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).

holes

display_name: holes

oxygen-interstitial

display_name: oxygen-interstitial

oxygen-vacancy

display_name: oxygen-vacancy

peroxy-linkage

display_name: peroxy-linkage


en:
Regioselective derivatization of oligosaccharides is a challenging issue in carbohydrate chemistry. A commonly required series of (de)protection steps substantially lowers synthetic yields and increases time demands. We present here a regioselective one-step introduction of benzylic substituents at 3-hydroxy moieties of beta-D-galactopyranosyl-(1<->1)-thio-beta-D-galactopyranoside (TDG) employing tin butyl oxide in fair isolated yields. These glycomimetics act as inhibitors of galectins - human lectins, which are biomedically attractive targets for therapeutic inhibition. The affinity of prepared glycomimetics to recombinant galectin-1 and galectin-3 was studied in ELISA-type assay and their inhibitory potential was also demonstrated on the surface of a model HEK293 cell line. The results of biological experiments were correlated with data from molecular modelling with both galectins. The present work reveals a facile and elegant synthetic route for the preparation of glycomimetics that exhibit differing selectivity and affinity to various galectins depending on the choice of 3-O-substitution.
In order to rationalize structure-activity relationships of tested ligands we carried out a series of molecular dynamics simulations and quantum chemical calculations. We present input and output files for quantum chemical geometry optimizations and calculations of interactions energies. These calculations were carried out in Gaussian 09 package. These results can be visualized using Molden, Molekel or other programs.
Molecular dynamics simulations were carried out using Gromacs 5.1.3 package. Initial structures of production simulations and trajectories (without water) are presented. The results can be visualized by VMD or other structure visualization packages with a support for trajectory input.

en: Regioselective 3-O-Substitution of Unprotected Thiodigalactosides: Direct Route to Galectin Inhibitors

materialscloud

en: Materials Cloud

envi

en: Environment

galectin

display_name: galectin

glycobiology

display_name: glycobiology

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: This entry provides MD trajectories for bulk water and the water-vacuum interface generated with ab initio molecular dynamics using rVV10 density functional at the temperature of 350 K. In the rVV10 functional, the parameter b is set to 9.3.

en: MD trajectories of bulk water and of the water-vacuum interface

md-trajectory

display_name: md-trajectory

water-vacuum-interface

display_name: water-vacuum-interface


en:
The ever-growing availability of computing power and sustained development of advanced computational methods have contributed much to recent scientific progress.
These developments present new challenges driven by the sheer amount of calculations and data to manage. Next-generation exascale supercomputers will harden these challenges, such that automated and scalable solutions become crucial. In recent years, we have been developing AiiDA (http://www.aiida.net), a robust open-source high-throughput infrastructure addressing the challenges arising from the needs of automated workflow management and data provenance recording. Here, we introduce developments and capabilities required to reach sustained performance, with AiiDA supporting throughputs of tens of thousands processes/hour, while automatically preserving and storing the full data provenance in a relational database making it queryable and traversable, thus enabling high-performance data analytics. AiiDA's workflow language provides advanced automation, error handling features and a flexible plugin model to allow interfacing with any simulation software. The associated plugin registry enables seamless sharing of extensions, empowering a vibrant user community dedicated to making simulations more robust, user-friendly and reproducible.

This archive record contains the data to reproduce the figures on engine performance in the section "Event versus polling-based engine" of the paper entitled "AiiDA 1.0, a scalable computational infrastructure for automated reproducible workflows and data provenance". It also includes instructions to reproduce the actual data from scratch using AiiDA v1.1.1 and AiiDA v0.12.5.

automation

display_name: automation

emmc

display_name: emmc

erc

display_name: erc

high-throughput

display_name: high-throughput

intersect

display_name: intersect

marketplace

display_name: marketplace

max

display_name: max

nffa

display_name: nffa

pasc

display_name: pasc

prace

display_name: prace

reproducibility

display_name: reproducibility

snsf

display_name: snsf

swissuniversities

display_name: swissuniversities

workflows

display_name: workflows


en: Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model. This severely limits the practical application of these models in systems with dynamics governed by important rare events, such as chemical reactions and diffusion. We present an adaptive Bayesian inference method for automating the training of interpretable, low-dimensional, and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations. Within an active learning framework, the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model. The method is applied to a range of single- and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency, while requiring a minimal amount of ab initio training data. We provide a fully open-source implementation of our method, as well as a procedure to map trained models to computationally efficient tabulated force fields.

en: On-the-Fly Active Learning of Interpretable Bayesian Force Fields for Atomistic Rare Events

bayesian-inference

display_name: bayesian-inference

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en: This entry provides the most stable defect configurations of hydrogen, carbon, and nitrogen impurities in alumina, which are identified through ab initio molecular dynamics in various charge states and structural relaxations with the PBE functional. The structural configurations related to carbon and nitrogen impurities are found to depend on the total charge set in the simulation cell.

en: Extrinsic Defects in Amorphous Oxides: Hydrogen, Carbon, and Nitrogen Impurities in Alumina

alumina

display_name: alumina

carbon

display_name: carbon

extrinsic-defects

display_name: extrinsic-defects

hydrogen

display_name: hydrogen

nitrogen

display_name: nitrogen

total-charge

display_name: total-charge


en: Distributed photovoltaics in living environment harvest the sunlight in different incident angles throughout the day. The development of planer solar cells with large light-receiving angle can reduce the requirements in installation form factor and is therefore urgently required. Here, thin film organic photovoltaics with nano-sized phase separation integrated in micro-sized surface topology is demonstrated as an ideal solution to proposed applications. All-polymer solar cells, by means of a newly developed sequential processing, show large magnitude hierarchical morphology with facilitated exciton-to-carrier conversion. The nano fibrilar donor-acceptor network and micron-scale optical field trapping structure in combination contributes to an efficiency of 19.06% (certified 18.59%), which is the highest value to date for all-polymer solar cells. Furthermore, the micron-sized surface topology also contributes to a large light-receiving angle. A 30% improvement of power gain is achieved for the hierarchical morphology comparing to the flat-morphology devices. These inspiring results show that all-polymer solar cell with hierarchical features are particularly suitable for the commercial applications of distributed photovoltaics due to its low installation requirement.

en: All-polymer organic solar cells with nano-to-micron hierarchical morphology and large light receiving angle

all-polymer-solar-cell

display_name: all-polymer-solar-cell

organic-solar-cells

display_name: organic-solar-cells

surface-topology

display_name: surface-topology


en: We study the dynamics of photoinduced charge carriers in semirealistic models of LaVO3 and YTiO3 polar heterostructures. It is shown that two types of impact ionization processes contribute to the carrier multiplication in these strongly correlated multiorbital systems: The first mechanism involves local spin state transitions, while the second mechanism involves the scattering of high-kinetic-energy carriers. Both processes act on the 10-fs timescale and play an important role in the harvesting of high-energy photons in solar cell applications. As a consequence, the optimal gap size for Mott solar cells is substantially smaller than for semiconductor devices.

en: Hund excitations and the efficiency of Mott solar cells

dft

display_name: dft

erc

display_name: erc

out-of-equilibrium-physics

display_name: out-of-equilibrium-physics

solar-cells

display_name: solar-cells


en: Weyl semimetals in three-dimensional crystals provide the paradigm example of topologically protected band nodes. It is usually taken for granted that a pair of colliding Weyl points annihilate whenever they carry opposite chiral charges. In stark contrast, here we report that Weyl points in systems symmetric under the composition of time-reversal with a π-rotation are characterized by a non-Abelian topological invariant. The topological charges of the Weyl points are transformed via braid phase factors which arise upon exchange inside symmetric planes of the reciprocal momentum space. We elucidate this process with an elementary two-dimensional tight-binding model implementable in cold-atoms setups and in photonic systems. In three dimensions, interplay of the non-Abelian topology with point-group symmetry is shown to enable topological phase transitions in which pairs of Weyl points may scatter or convert into nodal-line rings. By combining our theoretical arguments with first-principles calculations, we predict that Weyl points occurring near the Fermi level of zirconium telluride (ZrTe) carry non-trivial values of the non-Abelian charge, and that uniaxial compression strain drives a non-trivial conversion of the Weyl points into nodal lines.

en: Non-Abelian reciprocal braiding of Weyl points and its manifestation in ZrTe

epfl

display_name: epfl

non-abelian-braiding

display_name: non-abelian-braiding

snsf

display_name: snsf

taas

display_name: taas

weyl-semimetal

display_name: weyl-semimetal

zrte

display_name: zrte


en: Machine-learned potentials (MLPs) trained on ab initio data combine the computational efficiency of classical interatomic potentials with the accuracy and generality of the first-principles method used in the creation of the respective training set. In this work, we implement and train a MLP to obtain an accurate description of the potential energy surface and property predictions for organic compounds, as both single molecules and in the condensed phase. We devise a dual descriptor, based on the atomic cluster expansion (ACE), that couples an information-rich short-range description with a coarser long-range description that captures weak intermolecular interactions. We employ uncertainty-guided active learning for the training set generation, creating a dataset that is comparatively small for the breadth of application and consists of alcohols, alkanes, and an adipate. Utilizing that MLP, we calculate densities of those systems of varying chain lengths as a function of temperature, obtaining a discrepancy of less than 4% compared with experiment. Vibrational frequencies calculated with the MLP have a root mean square error of less than 1 THz compared to DFT. The heat capacities of condensed systems are within 11% of experimental findings, which is strong evidence that the dual descriptor provides an accurate framework for the prediction of both short-range intramolecular and long-range intermolecular interactions.

en: A dual-cutoff machine-learned potential for condensed organic systems obtained via uncertainty-guided active learning

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).

diffusion

display_name: diffusion

heat-capacity

display_name: heat-capacity

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics

radial-distribution-functions

display_name: radial-distribution-functions

training-data

display_name: training-data

vasp

display_name: vasp


en: Transition metal dichalcogenides (TMDs) in the 1T polymorph are subject to a rich variety of periodic lattice distortions, often referred to as charge-density waves (CDWs) when not too strong. We study from first principles the fermiology and phonon dispersion of three representative single-layer transition metal disulfides with different occupation of the t2g subshell: TaS2 (t1 2g), WS2 (t2 2g), and ReS2 (t3 2g) across a broad range of doping levels. While strong electron-phonon interactions are at the heart of these instabilities, we argue that away from half-filling of the t2g subshell, the doping dependence of the calculated CDW wave vector can be explained from simple fermiology arguments, so that a weak-coupling nesting picture is a useful starting point for understanding. On the other hand, when the t2g subshell is closer to half-filling, we show that nesting is irrelevant, while a real-space strong-coupling picture of bonding Wannier functions is more appropriate and simple bond-counting arguments apply. Our study thus provides a unifying picture of lattice distortions in 1T TMDs that bridges the two regimes, while the crossover between these regimes can be attained by tuning the filling of the t2g orbitals.

en: Unified picture of lattice instabilities in metallic transition metal dichalcogenides

materialscloud

en: Materials Cloud

envi

en: Environment

charge-density-wave

display_name: charge-density-wave

chemical-bonding

display_name: chemical-bonding

fermi-surface-nesting

display_name: fermi-surface-nesting

lattice-distortion

display_name: lattice-distortion

phonons

display_name: phonons

susceptibility

display_name: susceptibility

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides

wannier-functions

display_name: wannier-functions


en: In this work, surface reconstructions on the (100) surface of CaF2 are comprehensively investigated. The configurations were explored by employing the Minima Hopping Method (MHM) coupled to a machine-learning interatomic potential, that is based on a charge equilibration scheme steered by a neural network (CENT). The combination of these powerful methods revealed about 80 different morphologies for the (100) surface with very similar surface formation energies differing by not more than 0.3 J m−2. To take into account the effect of temperature on the dynamics of this surface as well as to study the solid–liquid transformation, molecular dynamics simulations were carried out in the canonical (NVT) ensemble. By analyzing the atomic mean-square displacements (MSD) of the surface layer in the temperature range of 300–1200 K, it was found that in the surface region the F sublattice is less stable and more diffusive than the Ca sublattice. Based on these results we demonstrate that not only a bulk system, but also a surface can exhibit a sublattice premelting that leads to superionicity. Both the surface sublattice premelting and surface premelting occur at temperatures considerably lower than the bulk values. The complex behaviour of the (100) surface is contrasted with the simpler behavior of other low index crystallographic surfaces.

en: Surface reconstructions and premelting of the (100) CaF2 surface

charge-equilibration-scheme

display_name: charge-equilibration-scheme

marvel

display_name: marvel

minima-hopping

display_name: minima-hopping

snsf

display_name: snsf

surface-reconstructions

display_name: surface-reconstructions


en: Designing an appropriate set of collective variables is crucial to the success of several enhanced sampling methods. Here we focus on how to obtain such variables from information limited to the metastable states. We characterize these states by a large set of descriptors and employ neural networks to compress this information in a lower-dimensional space, using Fisher's linear discriminant as an objective function to maximize the discriminative power of the network. We test this method on alanine dipeptide, using the non-linearly separable dataset composed by atomic distances. We then study an intermolecular aldol reaction characterized by a concerted mechanism. The resulting variables are able to promote sampling by drawing non-linear paths in the physical space connecting the fluctuations between metastable basins. Lastly, we interpret the behavior of the neural network by studying its relation to the physical variables. Through the identification of its most relevant features, we are able to gain chemical insight into the process.

en: Data-Driven Collective Variables for Enhanced Sampling

collective-variables

display_name: collective-variables

enhanced-sampling

display_name: enhanced-sampling

erc

display_name: erc

metadynamics

display_name: metadynamics

neural-networks

display_name: neural-networks

opes

display_name: opes

plumed

display_name: plumed


en: Two-dimensional (2D) transition metal dichalcogenides (TMDs) exist in two polymorphs, referred to as 1T and 1H, depending on the coordination sphere of the transition metal atom. The broken octahedral and trigonal prismatic symmetries lead to different crystal and ligand field splittings of the d electron states, resulting in distinct electronic properties. In this work, we quantify the crystal and ligand field parameters of 2D TMDs using a Wannier-function approach. We adopt the methodology proposed by Scaramucci et al (2015 J. Phys.: Condens. Matter 27 175503) that allows to separate various contributions to the ligand field by choosing different manifolds in the construction of the Wannier functions. We discuss the relevance of the crystal and ligand fields in determining the relative stability of the two polymorphs as a function of the filling of the d-shell. Based on the calculated parameters, we conclude that the ligand field, while leading to a small stabilizing factor for the 1H polymorph in the d1 and d2 TMDs, plays mostly an indirect role and that hybridization between different d orbitals is the dominant feature. We investigate trends across the periodic table and interpret the variations of the calculated crystal and ligand fields in terms of the change of charge-transfer energy, which allows developing simple chemical intuition

en: Crystal field, ligand field, and interorbital effects in two-dimensional transition metal dichalcogenides across the periodic table

crystal-field

display_name: crystal-field

epfl

display_name: epfl

hybridization

display_name: hybridization

ligand-field

display_name: ligand-field


en: Titania (TiO2) is used extensively in biomedical applications; efforts to boost the biocompatibility of TiO2 include coating it with the titania binding hexamer, RKLPDA. To understand the binding mechanism of this peptide, we employ molecular dynamics simulations enhanced by metadynamics to study three amino acids present in the peptide – arginine (R), lysine (K), and aspartate (D), on four TiO2 variants that have different degrees of surface hydroxyl groups. We find that binding is a function of both sidechain charge and structure, with R binding to all four surfaces, whereas the affinity of K and D is dependent on the distribution of hydroxyl groups. Informed by this, we study the binding of the titania binding hexamer and 12mer (RKLPDAPGMHTW) on two of the four surfaces, and we see strong correlations between the binding free energy and the primary binding residues, in agreement with prior experiments and simulations. We propose that the discrepancies observed in prior work stem from distribution of surface hydroxyl groups that may be difficult to precisely control on the TiO2 interface.

en: Molecular Recognition and Specificity of Biomolecules to Titanium Dioxide from MD Simulations

biomaterials

display_name: biomaterials

metal-oxide

display_name: metal-oxide

surface-hydroxylation

display_name: surface-hydroxylation


en: Anatomically realistic organ replicas or phantoms allow for accurate studies and reproducible research. To recreate a human kidney, mimicry of the viscoelastic properties of the human kidney is crucial. However, none of the related work addressed the design and development of a kidney phantom using only silicone as material. In contrast to paraffin and hydrogel, silicone is an ideal variant for its extended shelf life, soft-tissue-like feeling, and viscoelastic modularity. To this end, we conducted uniaxial compression testing and Cauchy stress modeling. Results indicate that none of the available manufacturer silicone brands are suitable for the task of creating a realistic kidney phantom. Indeed, the tested silicone mixtures in low and high strain do not fall within the required approximate target compressive moduli of 20 kPa and 500 kPa, respectively. This work provides a frame of reference for future work by avoiding the pitfalls of the selected ready-made silicones and reusing the reported theoretical and experimental setup to design a realistic replica of the kidney organ.

en: Data from Uniaxial Compression testing and validation scripts for Cauchy stress modeling to design anatomical silicone replicas

blatz-model

display_name: blatz-model

cauchy-stress

display_name: cauchy-stress

kidney

display_name: kidney

replica

display_name: replica

silicone

display_name: silicone

strain

display_name: strain

stress

display_name: stress

uniaxial-compression

display_name: uniaxial-compression

youngs-modulus

display_name: youngs-modulus


en:
We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical topological insulator Sb2Te3. The density functional calculations of this work were performed with the JuKKR package [1], which allows to embed translational invariance breaking impurities into a crystalline host system based on the Korringa-Kohn-Rostoker Green function method, and were performed with the AiiDA-KKR package [2]. Our database collects, among others, predicted impurity properties like charge doping introduced by the defects, magnetic moments of the impurities and impurity density of states calculations. We include calculations for the intrinsic Fermi level in the middle of the bulk band gap as well as for shifted Fermi level into valence and conduction band which models different experimental conditions. The impurities were embedded into different layers throughout a 6 quintuple layer thick film which allows to investigate the effect of the topological surface state (localized at the surface) on impurity properties. The JuDiT database allows to uncover chemical trends in impurity properties and can help optimizing the next generation of topological materials.

[1] https://jukkr.fz-juelich.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-kkr

en: The JuDiT database of impurities embedded into a topological insulator

aiida-kkr

display_name: aiida-kkr

density-functional-theory

display_name: density-functional-theory

impurities

display_name: impurities

impurity

display_name: impurity

impurity-density-of-states

display_name: impurity-density-of-states

impurity-properties

display_name: impurity-properties

judit

display_name: judit

kkr

display_name: kkr

max

display_name: max

quantum-anomalous-hall-insulator

display_name: quantum-anomalous-hall-insulator

topological-insulator

display_name: topological-insulator

viti

display_name: viti


en: The record contains the theoretical data supporting a recent publication where we discuss the band gap of finite  armchair graphene nanoribbons with a width of seven rows of carbon atoms (7‐AGNRs) on Au(111) through scanning tunneling microscopy/spectroscopy combined with density functional theory calculations.

en: Band gap of atomically precise graphene nanoribbons as a function of ribbon length and termination

materialscloud

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

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

ab-initio

display_name: ab-initio

dft

display_name: dft

graphene-nanoribbons

display_name: graphene-nanoribbons

stm

display_name: stm


en: We use density-functional theory plus dynamical mean-field theory to demonstrate the emergence of a metallic layer at the interface between the two Mott insulators LaTiO3 and LaVO3. The metallic layer is due to charge transfer across the interface, which alters the valence state of the transition-metal cations close to the interface. Somewhat counterintuitively, the charge is transferred from the Ti cations with formal d1 electron configuration to the the V cations with formal d2 configuration, thereby increasing the occupation difference of the t2g states. This can be understood as a result of a gradual transition of the charge-transfer energy, or electronegativity, across the interface. The spatial extension of the metallic layer, in particular toward the LaTiO3 side, can be controlled by epitaxial strain, with tensile strain leading to a localization within a thickness of only two unit cells. Our results open up a route for creating a tunable quasi-two-dimensional electron gas in materials with strong electronic correlations.

en: Charge transfer in LaVO3/LaTiO3 multilayers: Strain-controlled dimensionality of interface metallicity between two Mott insulators

materialscloud

en: Materials Cloud

dynamical-mean-field-theory

display_name: dynamical-mean-field-theory

first-principles-calculations

display_name: first-principles-calculations

mott-insulators

display_name: mott-insulators

multilayer-thin-films

display_name: multilayer-thin-films

superlattices

display_name: superlattices

two-dimensional-electron-gas

display_name: two-dimensional-electron-gas


en: In a recent publication we inspected the mechanism of the  azide–alkyne Huisgen cycloaddition. We studied the dynamical aspects of the process using metadynamics computer simulations. We focused on the conformational aspects that determine the course of the reaction and characterize its free energy landscape. This record contains data related to the calculations discussed in the publication.

en: The reaction mechanism of the azide–alkyne Huisgen cycloaddition

envi

en: Environment

huisgen-cycloaddition

display_name: huisgen-cycloaddition

marvel

display_name: marvel

metadynamics

display_name: metadynamics


en: The element Vanadium (V) appears unique among alloying elements for providing high strengthening in both the fcc Co-Cr-Fe-Mn-Ni-V and bcc Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr high-entropy alloy families. The origin of Vanadium's special role is its atomic volume: large in the fcc alloys and small in the bcc alloys, and thus having a large misfit volume in both crystalline structures. A parameter-free theory applicable to both fcc and bcc HEAs rationalizes this finding, with predictions of strength across a range of fcc and bcc alloys in quantitative and qualitative agreement with experiments. In the fcc class, the analysis demonstrates why the newly-discovered NiCoV and Ni0.632V0.368 alloys have far higher strength than any other fcc alloy and are predicted to be the highest attainable. In the bcc class, the analysis demonstrates that the addition of V always increases the strength relative to the same alloys without V. The optimization of complex alloys for high strength should thus center around the inclusion of V as a primary element at concentration levels of around 25 at.%.

en: Vanadium is an optimal element for strengthening in both fcc and bcc high-entropy alloys

epfl

display_name: epfl

high-entropy-alloys

display_name: high-entropy-alloys

solute-strengthening-theory

display_name: solute-strengthening-theory

vanadium

display_name: vanadium

yield-strength

display_name: yield-strength


en: Full-band atomistic quantum transport simulations based on first principles are employed to assess the potential of band-to-band tunneling field-effect-transistors (TFETs) with a 2-D channel material as future electronic circuit components. We demonstrate that single layer transition metal dichalcogenides (TMDs) are not well-suited for TFET applications. There might, however, exist a great variety of 2-D semiconductors that have not even been exfoliated yet: this work pinpoints some of the most promising candidates among them to realize highly efficient TFETs. Single-layer SnTe, As, TiNBr, and Bi are all found to ideally deliver ON-currents larger than 100 μA/μm at 0.5 V supply voltage and 0.1 nA/μm OFF current value. We show that going from single to multiple layers can boost the TFET performance as long as the gain from a narrowing band gap exceeds the loss from the deteriorating gate control. Finally, a 2-D van der Waals heterojunction TFET is revealed to perform almost as well as the best single-layer homojunction, paving the way for research in optimal 2-D material combinations.

en: Ab initio simulation of band-to-band tunneling FETs with single- and few-layer 2-D materials as channels

ab-initio

display_name: ab-initio

device-simulation

display_name: device-simulation

quantum-transport

display_name: quantum-transport

tfets

display_name: tfets


en: High power SiC MOSFET technologies are critical for energy saving in, e.g., distribution of electrical power. They suffer, however, from low near-interface mobility, the origin of which has not yet been conclusively determined. Here, we present unique concerting evidence for the presence of interface defects in the form of carbon clusters at native thermally processed oxides of SiC. These clusters, with a diameter of 2–5 nm, are HF-etch resistant and possess a mixture of graphitic (sp2) and amorphous (sp3 mixed in sp2) carbon bonds different from the normal sp3 carbon present in 4H-SiC. The nucleation of such defects during thermal oxidation as well as their atomic structure is elucidated by state-of-the-art atomistic and electronic structure calculations. In addition, our property prediction techniques show the impact of the simulated carbon accumulates on the electronic structure at the interface.

en: Evidence for carbon clusters present near thermal gate oxides affecting the electronic band structure in SiC-MOSFET

microfabrication

display_name: microfabrication

mosfet

display_name: mosfet

snsf

display_name: snsf


en: In ultra-thin two-dimensional (2-D) materials, the formation of ohmic contacts with top metallic layers is a challenging task that involves different processes than in bulk-like structures. Besides the Schottky barrier height, the transfer length of electrons between metals and 2-D monolayers is a highly relevant parameter. For MoS2, both short (≤30 nm) and long (≥0.5 μm) values have been reported, corresponding to either an abrupt carrier injection at the contact edge or a more gradual transfer of electrons over a large contact area. Here we use ab initio quantum transport simulations to demonstrate that the presence of an oxide layer between a metallic contact and a MoS2 monolayer, for example TiO2 in case of titanium electrodes, favors an area-dependent process with a long transfer length, while a perfectly clean metal-semiconductor interface would lead to an edge process. These findings reconcile several theories that have been postulated about the physics of metal/MoS2 interfaces and provide a framework to design future devices with lower contact resistances.

en: Electron transport through metal/MoS2 interfaces: edge- or area-dependent process?

ab-initio-device-simulations

display_name: ab-initio-device-simulations

contact-physics

display_name: contact-physics

fermi-level-pinning

display_name: fermi-level-pinning

metal-semiconductor-interfaces

display_name: metal-semiconductor-interfaces

transfer-length

display_name: transfer-length


en: We present a fully ab-initio, unbiased structure search of the configurational space of decorated C60 fullerenes in the presence of an electric field. We observed that the potential energy surface (PES) is significantly perturbed by an external electric field and that the energetic ordering of low energy isomers differs with and without electric field. We identify the energetically lowest configuration for a varying number of decorating atoms (1 ≤ n ≤ 12) for Li and (1 ≤ n ≤ 6) for K on the C60 surface at different electric field strengths. Using the correct geometric ground state in the electric field for the calculation of the dipole we obtain better agreement with the experimentally measured values than previous calculations based on the ground state in absence of an electric field. Since the lowest energy structures are typically nearly degenerate in energy, a combination of different structures is expected to be found at room temperature. The experimentally measured dipole is therefore also expected to contain significant contributions from several low energy structures.

en: Influence of an external electric field on the potential energy surface of alkali decorated C60

alkali-atom

display_name: alkali-atom

electric-field

display_name: electric-field

free-energy

display_name: free-energy


en: In a recent work, we reported a combined in-solution and on-surface synthesis of π-extended triangulene, a non-Kekulé nanographene with the structural formula C33H15, consisting of ten benzene rings fused in a triangular fashion. The distinctive topology of the molecule entails the presence of three unpaired electrons that couple to form a spin quartet ground state. In this record we include experimental and computational data that support the findings of the manuscript.

en: Synthesis and Characterization of π-Extended Triangulene

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).

nanographenes

display_name: nanographenes

non-kekule

display_name: non-kekule

on-surface-synthesis

display_name: on-surface-synthesis

triangulene

display_name: triangulene


en: Rare-earth nickelates exhibit a remarkable metal-insulator transition accompanied by a symmetry-lowering structural distortion. Using model considerations and first-principles calculations, we present a theory of this phase transition which reveals the key role of the coupling between electronic and lattice instabilities. We show that the transition is driven by the proximity to an instability towards electronic disproportionation which couples to a specific structural distortion mode, cooperatively driving the system into the insulating state. This allows us to identify two key control parameters of the transition: the susceptibility to electronic disproportionation and the stiffness of the lattice mode. We show that our findings can be rationalized in terms of a Landau theory involving two coupled order parameters, with general implications for transition-metal oxides.

en: Mechanism and control parameters of the coupled structural and metal-insulator transition in nickelates

materialscloud

en: Materials Cloud

dftdmft

display_name: dftdmft

electronic-structure

display_name: electronic-structure

nickelates

display_name: nickelates


en: Chemists continuously harvest the power of non-covalent interactions to control phenomena in both the micro- and macroscopic worlds. From the quantum chemical perspective, the strategies essentially rely upon an in-depth understanding of the physical origin of these interactions, the quantification of their magnitude and their visualization in real-space. The total electron density ρ(r) represents the simplest yet most comprehensive piece of information available for fully characterizing bonding patterns and non-covalent interactions. The charge density of a molecule can be computed by solving the Schrödinger equation, but this approach becomes rapidly demanding if the electron density has to be evaluated for thousands of different molecules or very large chemical systems, such as peptides and proteins. Here we present a transferable and scalable machine-learning model capable of predicting the total electron density directly from the atomic coordinates. The regression model is used to access qualitative and quantitative insights beyond the underlying ρ(r) in a diverse ensemble of sidechain–sidechain dimers extracted from the BioFragment database (BFDb). The transferability of the model to more complex chemical systems is demonstrated by predicting and analyzing the electron density of a collection of 8 polypeptides.

en: Electron density learning of non-covalent systems

envi

en: Environment

electron-density

display_name: electron-density

machine-learning

display_name: machine-learning

non-covalent-systems

display_name: non-covalent-systems


rethinking-metadynamics

en: Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly construction of a bias potential that is a function of a selected number of collective variables. We propose here a change in perspective that shifts the focus from the bias to the probability distribution reconstruction while retaining some of the key characteristics of metadynamics, such as flexible on-the-fly adjustments to the free energy estimate. The result is an enhanced sampling method that presents a drastic improvement in convergence speed, especially when dealing with suboptimal and/or multidimensional sets of collective variables. The method is especially robust and easy to use and in fact requires only a few simple parameters to be set, and it has a straightforward reweighting scheme to recover the statistics of the unbiased ensemble. Furthermore, it gives more control of the desired exploration of the phase space since the deposited bias is not allowed to grow indefinitely and it does not push the simulation to uninteresting high free energy regions. We demonstrate the performance of the method in a number of representative examples.

en: Rethinking Metadynamics

title_for_slug: rethinking-metadynamics

enhanced-sampling

display_name: enhanced-sampling

erc

display_name: erc

umbrella-sampling

display_name: umbrella-sampling


en: In a recent publication we demonstrated the on surface synthesis of a porous nanographene and we characterized its electronic properties combining spectroscopy experiments to ab-initio simulations. In this record we provide experimental and computational data that support the results discussed in the manuscript.

en: On-Surface Synthesis of a Non-Planar Porous Nanographene

ab-initio

display_name: ab-initio

nanographene

display_name: nanographene


en: Sampling complex free-energy surfaces is one of the main challenges of modern atomistic simulation methods. The presence of kinetic bottlenecks in such surfaces often renders a direct approach useless. A popular strategy is to identify a small number of key collective variables and to introduce a bias potential that is able to favor their fluctuations in order to accelerate sampling. Here, we propose to use machine-learning techniques in conjunction with the recent variationally enhanced sampling method [O. Valsson, M. Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to determine such potential. This is achieved by expressing the bias as a neural network. The parameters are determined in a variational learning scheme aimed at minimizing an appropriate functional. This required the development of a more efficient minimization technique. The expressivity of neural networks allows representing rapidly varying free-energy surfaces, removes boundary effects artifacts, and allows several collective variables to be handled.

en: Neural networks-based variationally enhanced sampling

biomolecules

display_name: biomolecules

crystallization

display_name: crystallization

deep-learning

display_name: deep-learning

marvel

display_name: marvel

plumed

display_name: plumed

rare-events

display_name: rare-events

silicon

display_name: silicon


en: Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environment effects, which promote competing interactions and alter their static gas-phase properties. Recently, neural network potentials (NNPs) trained on Density Functional Theory (DFT) data have become increasingly popular to simulate molecular phenomena in condensed phase with an accuracy comparable to ab initio methods. To date, most applications have centered on solid-state materials or fairly simple molecules made of a limited number of elements. Herein, we focus on the persistence and strength of chalcogen bonds involving benzotelluradiazole in condensed phase. While the tellurium-containing heteroaromatic molecules are known to exhibit pronounced interactions with anions and lone pairs of different atoms, the relevance of competing intermolecular interactions, notably with the solvent, is complicated to monitor experimentally but also challenging to model at an accurate electronic structure level.  Here, we train direct and baselined NNPs to reproduce hybrid DFT energies and forces in order to identify what are the most prevalent non-covalent interactions occurring in a solute-Cl-THF mixture. The simulations in explicit solvent highlight the clear competition with chalcogen bonds formed with the solvent and the short-range directionality of the interaction with direct consequences for the molecular properties in the solution. The comparison with other potentials (e.g., AMOEBA, direct NNP, and continuum solvent model) also demonstrates that baselined NNPs offer a reliable picture of the non--covalent interaction interplay occurring in solution.

en: Assessing the persistence of chalcogen bonds in solution with neural network potentials

chalcogen-bonding-in-solution

display_name: chalcogen-bonding-in-solution

epfl

display_name: epfl

molecular-dynamics

display_name: molecular-dynamics

neural-network-potentials

display_name: neural-network-potentials

non-covalent-interactions

display_name: non-covalent-interactions

snsf

display_name: snsf


en:
The design rules for materials are clear for applications with a single objective. For most applications, however, there are often multiple, sometimes competing objectives where there is no single best material, and the design rules change to finding the set of Pareto optimal materials.
In this work, we introduce an active learning algorithm that directly uses the Pareto dominance relation to compute the set of Pareto optimal materials with desirable accuracy.
We apply our algorithm to de novo polymer design with a prohibitively large search space.
Using molecular simulations, we compute key descriptors for dispersant applications and reduce the number of materials that need to be evaluated to reconstruct the Pareto front with a desired confidence by over 98% compared to random search.
This work showcases how simulation and machine learning techniques can be coupled to discover materials within a design space that would be intractable using conventional screening approaches.

en: Bias free multiobjective active learning for materials design and discovery

active-learning

display_name: active-learning

erc

display_name: erc

machine-learning

display_name: machine-learning

multiobjective

display_name: multiobjective

polymers

display_name: polymers


en: Ultrafast electron delocalization induced by a femtosecond laser pulse is a well-known process in which electrons are ejected from the ions within the laser pulse duration. However, very little is known about the speed of electron localization out of an electron gas in correlated metals, i.e., the capture of an electron by an ion. Here, we demonstrate by means of pump-probe x-ray techniques across the Eu L3 absorption edge that an electron localization process in the EuNi2(Si0.21Ge0.79)2 intermetallic material occurs within a few hundred femtoseconds after the optical excitation. Spectroscopy and diffraction data collected simultaneously at low temperature and for various laser fluences show that the localization dynamics process is much faster than the thermal expansion of the unit cell along the c direction which occurs within picoseconds. Nevertheless, this latter process is still much slower than pure electronic effects, such as screening, and the subpicosecond timescale indicates an optical phonon drive origin. In addition, comparing the laser fluence dependence of the electronic response with that found in other intermediate 4 f valence materials, we suggest that the electron localization process observed in this Eu-based correlated metal is mainly related to changes in the 4 f hybridization. The observed ultrafast electron localization process sparks fundamental questions for our understanding of electron correlations and their coupling to the lattice.

en: Ultrafast electron localization in the EuNi2(Si0.21Ge0.79)2 correlated metal

materialscloud

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

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

experimental

display_name: experimental

pump-and-probe-x-ray-techniques

display_name: pump-and-probe-x-ray-techniques

ultrafast-electron-delocalization

display_name: ultrafast-electron-delocalization

valence-transition

display_name: valence-transition


en:
Vertically aligned nanocomposite (VAN) films, comprising nanopillars of one phase embedded in a matrix of another, have shown great promise for a range of applications due to their high interfacial areas oriented perpendicular to the substrate. In particular, oxide VANs show enhanced oxide-ion conductivity in directions that are orthogonal to those found in more conventional thin-film heterostructures, however the structure of the interfaces and its influence on conductivity remain unclear. In this work 17O NMR spectroscopy is used to study CeO2–SrTiO3 VAN thin films: selective isotopic enrichment is combined with a lift-off technique to remove the substrate, facilitating detection of the 17O NMR signal from single atomic layer interfaces. By performing the isotopic enrichment at variable temperatures, the superior oxide-ion conductivity of the VAN films compared to the bulk materials is shown to arise from enhanced oxygen mobility at this interface; oxygen motion at the interface is further identified from 17O relaxometry experiments. The structure of this interface is solved by calculating the NMR parameters using density functional theory combined with random structure searching, allowing the chemistry underpinning the enhanced oxide-ion transport to be proposed. Finally, a comparison is made with 1% Gd-doped CeO2–SrTiO3 VAN films, for which greater NMR signal can be obtained due to paramagnetic relaxation enhancement, while the relative oxide-ion conductivities of the phases remain similar. These results highlight the information that can be obtained on interfacial structure and dynamics with solid-state NMR spectroscopy, in this and other nanostructured systems, our methodology being generally applicable to overcome sensitivity limitations in thin-film studies.
The dataset contains the Experimental data, first-principles calculations and random structures searching results.

en: Revealing the structure and oxygen transport at interface in complex oxide heterostructures via 17O NMR spectroscopy

materialscloud

en: Materials Cloud

interface

display_name: interface

oxide

display_name: oxide

solid-state-nmr

display_name: solid-state-nmr

thin-films

display_name: thin-films


en: We report on the first example of quantum coherence between the spins of muons and quadrupolar nuclei. We observe this effect in vanadium intermetallic compounds which adopt the A15 crystal structure, and whose members include all technologically dominant superconductors. The entangled states are extremely sensitive to the local structural and electronic environments through the electric field gradient at the quadrupolar nuclei. This case-study demonstrates that positive muons can be used as a quantum sensing tool to probe also structural and charge related phenomena in materials, even in the absence of magnetic order. The data here contained can be used to reproduce all results and graphs shown in the article.

en: Entanglement between a muon spin and I>1/2 nuclear spins

envi

en: Environment

density-functional-theory

display_name: density-functional-theory

quantum-coherence

display_name: quantum-coherence


en: In the past decades many density-functional theory methods and codes adopting periodic boundary conditions have been developed and are now extensively used in condensed matter physics and materials science research. Only in 2016, however, their precision (i.e., to which extent properties computed with different codes agree among each other) was systematically assessed on elemental crystals: a first crucial step to evaluate the reliability of such computations. We discuss here general recommendations for verification studies aiming at further testing precision and transferability of density-functional-theory computational approaches and codes. We illustrate such recommendations using a greatly expanded protocol covering the whole periodic table from Z=1 to 96 and characterizing 10 prototypical cubic compounds for each element: 4 unaries and 6 oxides, spanning a wide range of coordination numbers and oxidation states. The primary outcome is a reference dataset of 960 equations of state cross-checked between two all-electron codes, then used to verify and improve nine pseudopotential-based approaches. Such effort is facilitated by deploying AiiDA common workflows that perform automatic input parameter selection, provide identical input/output interfaces across codes, and ensure full reproducibility. Finally, we discuss the extent to which the current results for total energies can be reused for different goals (e.g., obtaining formation energies). This data entry contains all data to reproduce the results, as well as the resulting curated all-electron dataset and the scripts to generate the figures of the paper.

en: How to verify the precision of density-functional-theory implementations via reproducible and universal workflows

automation

display_name: automation

dft

display_name: dft

equation-of-state

display_name: equation-of-state

pseudopotentials

display_name: pseudopotentials

verification

display_name: verification


en: Due to their remarkable properties, single-layer 2-D materials appear as excellent candidates to extend Moore's scaling law beyond the currently manufactured silicon FinFETs. However, the known 2-D semiconducting components, essentially transition metal dichalcogenides, are still far from delivering the expected performance. Based on a recent theoretical study that predicts the existence of more than 1800 exfoliable 2-D materials, we investigate here the 100 most promising contenders for logic applications.

en: 2‐D materials for ultrascaled field-effect transistors: one hundred candidates under the ab initio microscope

ab-initio-device-simulation

display_name: ab-initio-device-simulation

cscs

display_name: cscs

performance-comparison

display_name: performance-comparison

prace

display_name: prace

snsf

display_name: snsf


en:
The JuHemd (Jülich-Heusler-magnetic-database) is a collection of the magnetic phase transition types and transition temperatures (Tc) for experimentally documented Heusler and Heusler-like materials, as found by density functional calculations augmented by the Monte Carlo method, and as reported by experiment in the literature.
The database contains results on 400 compounds, many of them with different setups of the chemical order/disorder, totaling 776 systems. The ground state electronic structure was obtained by density functional theory calculations with the JuKKR code. Two exchange-correlation functionals were employed: the local density approximation (LDA) and the generalized gradient approximation (GGA). The chemical disorder was treated within the coherent-potential approximation. For 306 materials (627 systems) with sizable magnetization, the Heisenberg exchange parameters were evaluated using the method of infinitesimal rotations and the Tc was determined by our in-house Monte Carlo program. The simulated data for all the compounds in the database are accompanied by experimental data published in the literature: the crystal structure, the lattice constant, the Tc and the character of the magnetic phase transition. The correlation between the experimental reports and the results for LDA and GGA functionals and the statistical analysis of these results will be published elsewhere.

en: The JuHemd (Jülich-Heusler-magnetic-database) of the Monte Carlo simulated critical temperatures of the magnetic phase transition for experimentally reported Heusler and Heusler-like materials

critical-temperature

display_name: critical-temperature

erc

display_name: erc

heusler-alloy

display_name: heusler-alloy

jlvmd

display_name: jlvmd

juhemd

display_name: juhemd

kkr

display_name: kkr

magnetic-phase-transition

display_name: magnetic-phase-transition

magnetic-structure

display_name: magnetic-structure

max

display_name: max

monte-carlo

display_name: monte-carlo


en: The renormalization of electronic eigenenergies due to electron-phonon coupling (temperature dependence and zero-point motion effect) is sizable in many materials with light atoms. This effect, often neglected in ab initio calculations, can be computed using the perturbation-based Allen-Heine-Cardona theory in the adiabatic or non-adiabatic harmonic approximation. After a short description of the recent progresses in this field and a brief overview of the theory, we focus on the issue of phonon wavevector sampling convergence, until now poorly understood. Indeed, the renormalization is obtained numerically through a slowly converging q-point integration. For non-zero Born effective charges, we show that a divergence appears in the electron-phonon matrix elements at q → Γ, leading to a divergence of the adiabatic renormalization at band extrema. This problem is exacerbated by the slow convergence of Born effective charges with electronic wavevector sampling, which leaves residual Born effective charges in ab initio calculations on materials that are physically devoid of such charges. Here, we propose a solution that improves this convergence. However, for materials where Born effective charges are physically non-zero, the divergence of the renormalization indicates a breakdown of the adiabatic harmonic approximation, which we assess here by switching to the non-adiabatic harmonic approximation. Also, we study the convergence behavior of the renormalization and develop reliable extrapolation schemes to obtain the converged results. Finally, the adiabatic and non-adiabatic theories, with corrections for the slow Born effective charge convergence problem (and the associated divergence) are applied to the study of five semiconductors and insulators: α-AlN, β-AlN, BN, diamond, and silicon. For these five materials, we present the zero-point  renormalization, temperature dependence, phonon-induced lifetime broadening, and the renormalized electronic band structure.

en: Temperature dependence of the electronic structure of semiconductors and insulators

ab-initio

display_name: ab-initio

allen-heine-cardona

display_name: allen-heine-cardona

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

temperature-dependence

display_name: temperature-dependence

zero-point-renormalization

display_name: zero-point-renormalization


en:
Enormous research efforts are currently devoted to the discovery of 'perovskite-inspired materials', aiming to replicate the astonishing optoelectronic performance of lead-halide perovskites (LHPs). Recently, chalco halides of group IV/V elements have attracted attention due to the stability provided by stronger metal-chalcogen bonds, alongside compositional flexibility and ns2 cations — a performance-defining feature of LHPs. Following the experimental report of stable, solution-grown tin-antimony sulfoiodide (Sn2SbS2I3) solar cells, with power conversion efficiencies above 4%, we comprehensively characterise the structural and electronic properties of this emerging material. We find that the experimentally-reported centrosymmetric Cmcm crystal structure represents an average over multiple polar Cmc2_1 configurations. This dynamic crystal structure and ferroelectric behaviour could benefit photovoltaic performance. Using state-of-the-art ab initio methods, we assess the efficiency limits of this material, finding maximal solar-conversion efficiencies η_max > 30 % with film thicknesses t > 0.5μm, at the radiative limit.

Open-access Materials Horizons paper: https://doi.org/10.1039/D1MH00764E
Talks on this and other works at: https://www.youtube.com/channel/UCoVGnBeZeWmKzv8_-PzCKCw

en: Hidden spontaneous polarisation in the chalcohalide photovoltaic Sn2SbS2I3

chalcohalide

display_name: chalcohalide

defect-tolerance

display_name: defect-tolerance

density-functional-theory

display_name: density-functional-theory

earth-abundant

display_name: earth-abundant

epsrc

display_name: epsrc

ferroelectric

display_name: ferroelectric

lone-pair

display_name: lone-pair

perovskite-inspired

display_name: perovskite-inspired

photovoltaic

display_name: photovoltaic

polarisation

display_name: polarisation

symmetry-breaking

display_name: symmetry-breaking

thin-film-photovoltaic

display_name: thin-film-photovoltaic

vasp

display_name: vasp


en: Perovskite yttrium tantalum oxynitride is theoretically proposed as a promising semiconductor for solar water splitting because of the predicted bandgap and energy positions of band edges. In experiment, however, we show here that depending on processing parameters, yttrium tantalum oxynitrides exist in multiphases, including the desired perovskite YTaON2, defect fluorite YTa(O,N,o)4, and N-doped YTaO4. These multiphases have bandgaps ranging between 2.13 and 2.31 eV, all responsive to visible light. The N-doped YTaO4, perovskite main phase, and fluorite main phase derived from crystalline fergusonite oxide precursors exhibit interesting photoelectrochemical performances for water oxidation, while the defect fluorite derived from low crystallized scheelite-type oxide precursors show negligible activity. Preliminarily measurements show that loading IrOx cocatalyst on N-doped YTaO4 significantly improves its photoelectrochemical performance encouraging further studies to optimize this new material for solar fuel production.

en: Yttrium tantalum oxynitride multiphases as photoanodes for water oxidation

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).

computational-screening

display_name: computational-screening

marvel

display_name: marvel

oxynitride-perovskite

display_name: oxynitride-perovskite

solar-water-splitting

display_name: solar-water-splitting


en: This entry provides the atomic structures of three bulk amorphous TiO2 models generated through the melt-and-quench method with different cooling rates and of ten O-O peroxy linkages obtained by adding two holes to the bulk model constructed with the lowest cooling rate.

en: Intrinsic defects in amorphous TiO2

materialscloud

en: Materials Cloud

bulk-model

display_name: bulk-model

holes

display_name: holes

peroxy-linkage

display_name: peroxy-linkage


en: This record contains the experimental and computational data needed to support the work done on on-surface synthesis of conjugated polymers consisting of indeno[2,1-b]fluorene units, which are antiaromatic and open-shell biradicaloids. The observed reaction products have been characterized via low-temperature scanning tunneling microscopy/spectroscopy and noncontact atomic force microscopy, complemented by density-functional theory calculations. These polymers present a low band gap when adsorbed on Au(111). Moreover, their pronounced antiaromaticity and radical character, elucidated by ab initio calculations, make them promising candidates for applications in electronics and spintronics. Further, they provide a rich playground to explore magnetism in low-dimensional organic nanomaterials.

en: On-surface synthesis of antiaromatic and open-shell indeno[2,1-b]fluorene polymers and their lateral fusion into porous ribbons

envi

en: Environment

antiaromatic

display_name: antiaromatic

density-functional-theory

display_name: density-functional-theory

nics

display_name: nics

on-surface-reactions

display_name: on-surface-reactions

polymers

display_name: polymers


en: Molecular simulations are computationally expensive, especially in systems with multiple free energy minima. To address this problem many enhanced sampling techniques have been developed. Metadynamics uses a bias potential defined as a sum of Gaussian hills in space of few (one or two) collective variables. This bias potential disfavors states that have been visited since the beginning of the simulation. Multiple walker metadynamics simulates the system in multiple parallel replicas. The bias potential disfavors states that have been visited since the beginning of the simulation in any replica. Flying Gaussian method presented here also simulates the system in multiple parallel replicas. It disfavors states that are, at certain moment, similar in two or more replicas. It was demonstrated on Alanine Dipeptide in vacuum and water, cis/trans-isomerisation of Proline-containing peptides and Met-enkephalin.

en: Free-Energy Surface Prediction by Flying Gaussian Method

enhanced-sampling

display_name: enhanced-sampling

free-energy

display_name: free-energy

metadynamics

display_name: metadynamics

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: We determine the transition levels of electron and hole polarons at the BiVO4–water interface through thermodynamic integration within a hybrid functional scheme, thereby accounting for the liquid nature of the water component. The electron polaron is found to be less stable at the interface than in the bulk by 0.18 eV, while for the hole polaron the binding energy increases by 0.20 eV when the charge localizes in the surface layer of BiVO4. These results indicate that interfacial effects on the polaron binding energy and charge distribution are sizeable and cannot trivially be inferred from bulk calculations.

en: Electron and Hole Polarons at the BiVO4–Water Interface

molecular-dynamics

display_name: molecular-dynamics

polarons

display_name: polarons

water-splitting

display_name: water-splitting


en: The morphology, interfacial bonding energetics and charge transfer of Ni clusters and nanoparticles on slightly-reduced CeO2-x(111) surfaces at 100 to 300 K have been studied using single crystal adsorption calorimetry (SCAC), low-energy ion scattering spectroscopy (LEIS), X-ray photoelectron spectroscopy (XPS), low energy electron diffraction (LEED) and density functional theory (DFT).  The initial heat of adsorption of Ni vapor decreased with the extent of pre-reduction (x) of the CeO2-x(111), showing that stoichiometric ceria adsorbs Ni more strongly than oxygen vacancies.  On CeO1.95(111) at 300 K, the heat dropped quickly with coverage in the first 0.1 ML, attributed to nucleation of Ni clusters on stoichiometric steps, followed by the Ni particles spreading onto less favorable terrace sites. At 100 K, the clusters nucleate on terraces due to slower diffusion. Adsorbed Ni monomers are in the +2 oxidation state, and they bind by ~45 kJ/mol more strongly to step sites than terraces. The measured heat of adsorption versus average particle size on terraces is favorably compared to DFT calculations.  The Ce 3d XPS lineshape showed an increase in Ce3+/Ce4+ ratio with Ni coverage, providing the number of electrons donated to the ceria per Ni atom. The charge transferred per Ni is initially large but strongly decreases with increasing cluster size for both experiments and DFT, and shows large differences between clusters at steps versus terraces. This charge is localized on the interfacial Ni and Ce atoms in their atomic layers closest to the interface. This knowledge is crucial to understanding the nature of the active sites on the surface of Ni-CeO2 catalysts for which metal-oxide interactions play a very important role in the activation of O-H and C-H bonds.  The changes in these interactions with Ni particle size (metal loading) and the extent of reduction of the ceria help to explain how previously reported catalytic activity and selectivity change with these same structural details.

en: Ni Nanoparticles on CeO2(111): Energetics, Electron Transfer and Structure by Ni Adsorption Calorimetry, Spectroscopies and DFT

ni-charge-transfer

display_name: ni-charge-transfer

ni-heat-of-adsorption

display_name: ni-heat-of-adsorption


en: The bifunctional mechanism for the oxygen evolution reaction (OER) involving two distinct reaction sites is studied through the computational hydrogen electrode method for a set of catalyst materials including rutile TiO2(110), anatase TiO2(101), SnO2(110), RuO2(110), IrO2(110), Ni2P(0001), and BiVO4(001). The calculations are performed both at the semilocal level and at the hybrid functional level. Moreover, anodic conditions are modeled and their effect on the OER free energy steps is evaluated. The free energies of the reaction steps indicate that for specific combinations of catalysts, the limitations due to the linear scaling relationship can be overcome, leading to smaller overpotentials for the overall OER. At the same time, a detailed analysis of the results reveals a strong dependence on the adopted functional. For both functionals, it is shown that the energy level of the highest occupied electronic state can serve as a descriptor to guide the search for the optimal catalyst acting as a hydrogen acceptor. These results support the bifunctional mechanism as a means to break the linear scaling relationship and to further reduce the overpotential of the OER.

en: Oxygen evolution reaction: Bifunctional mechanism breaking the linear scaling relationship

bifunctional

display_name: bifunctional

epfl

display_name: epfl

interface

display_name: interface

linear-scaling

display_name: linear-scaling

oer

display_name: oer

overpotential

display_name: overpotential

oxygen-evolution-reaction

display_name: oxygen-evolution-reaction


en: A widespread method of crystal preparation is to precipitate it from a supersaturated solution. In such a process, control of solution concentration is of paramount importance. The nucleation process, polymorph selection, and crystal habits depend crucially on this thermodynamic parameter. When performing molecular dynamics simulations with a fixed number of molecules in the canonical ensemble, crystal growth is accompanied by a decrease in the solution concentration. This modification of the thermodynamic condition leads to significant artifacts. Inspired by the recent development of the constant chemical potential molecular dynamics simulation method by Perego et al. [J. Chem. Phys. 2015, 142, 144113], we develop a spherical variant of it to study nucleation from solution. Our method allows determining the crystal nucleus size and nucleation rates at constant supersaturation. As an example, we study the homogeneous nucleation of sodium chloride from its supersaturated aqueous solution.

en: Molecular Dynamics Simulations of Crystal Nucleation from Solution at Constant Chemical Potential

erc

display_name: erc

nucleation

display_name: nucleation

nucleation-kinetics

display_name: nucleation-kinetics

solution-crystallization

display_name: solution-crystallization


en: The pathway of the oxygen evolution reaction at the Pt(1 1 1)/water interface is disclosed through constant Fermi level molecular dynamics. Upon the application of a positive bias potential H2O_ads and O_ads adsorbates are found to arrange in a hexagonal lattice with an irregular alternation. Increasing further the electrode potential then induces the oxygen evolution reaction, which is found to proceed through a hydrogen peroxide intermediate. Calculation of the associated overpotential shows a reduction of 0.2 eV compared to the associative mechanism. This result highlights the forcefullness of the applied scheme in exploring catalytic reactions in an unbiased way.

en: Reaction pathway of oxygen evolution on Pt(1 1 1) revealed through constant Fermi level molecular dynamics

materialscloud

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

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

constant-fermi-level-molecular-dynamics

display_name: constant-fermi-level-molecular-dynamics

oer-mechanism

display_name: oer-mechanism


en: A good hydrogen storage material should adsorb hydrogen in high concentrations and with optimal binding energies. Exohedrally metal decorated carbon fullerene structures were proposed as a promising material in this context. We present a fully ab-initio, unbiased structure search of the configurational space of decorated C60 fullerenes and find that many of the hitherto postulated ground state structures are not ground states. We determine the energetically lowest configurations for decorations with a varying number of decorating atoms (2 ≤ n ≤ 32) for alkali metals, alkaline-earth metals as well as some other important elements and find that the dense uniform distribution of the decorating atoms over the surface of the C60 , desired for hydrogen storage, can be obtained only for a few elements. An understanding of the behavior of the decorating atoms can be obtained by analyzing their bonding characteristics via the electron localization function.

en: Stable structures of exohedrally decorated C60-fullerenes

materialscloud

en: Materials Cloud

elements

display_name: elements

exohedral

display_name: exohedral

snsf

display_name: snsf


en: This repository contains the PLUMED-2 input files required to generate the data used in the ITRE publications. ITRE is a method to reweight Molecular Dynamics trajectory biased with a history-dependent potential (such as Metadynamics), and calculate unbiased thermodynamic observables. Since it uses the trajectory itself as a proxy of a grid, its scaling does not depend on the dimensionality of the space explored. In addition, thanks to its formulation, it is less affected by out-of-equilibrium points that characterize the early stages of a biased calculation and are usually discarded. Thanks to this feature, it can be used to increase the statistics when evaluating a thermodynamic observable from biased calculation.

en: Iterative unbiasing of quasi-equilibrium sampling

envi

en: Environment

enhanced-sampling

display_name: enhanced-sampling

molecular-dynamics

display_name: molecular-dynamics

statistical-mechanics

display_name: statistical-mechanics


en:
Molecular mechanics potentials for small molecules suffer inaccuracies. To apply corrections we used a concept called property map to calculate corrections. It was calculated as a sum of [correction_i exp(-lambda D(x, x_i))] divided by the sum of [exp(-lambda D(x, x_i))], where correction_i is the difference between the accurate and inaccurate potential for i-th landmark structure x_i, lambda is a chosen prefactor, D is a distance (e.g. RMSD or MSD) and x are atomic coordinates. The concept was tested on alanine dipeptide (all combinations of 7 force fields, one used as a model of accurate and one as inaccurate). Next it was applied on an anticancer drug Imatinib (General AMBER Force Field corrected to DFT).
Simulations were carried out in Gromacs 2016.4. DFTB/MM simulation was carried out in CP2K 7.1. Correction was Implemented using Plumed 2.4. DFT energies were calculated by ORCA 4.0 at the BP86/def2-TZVP level of theory.

en: Property map collective variable as a useful tool for force field correction

dft

display_name: dft

free-energy

display_name: free-energy

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

molecular-mechanics

display_name: molecular-mechanics


en: In this work we demonstrate the on surface synthesis of  nonacene and heptacene and we discuss their open shell character comparing experimental evidence to theoretical predictions. The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.

en: On-surface light-induced generation of higher acenes and elucidation of their open-shell character

ab-initio

display_name: ab-initio

gw

display_name: gw

on-surface-synthesis

display_name: on-surface-synthesis

scanning-probe-microscopy

display_name: scanning-probe-microscopy


en: Recent experiments show that the CoCrFeNiPd high-entropy alloy (HEA) is significantly stronger than CoCrFeNi and with nanoscale composition fluctuations beyond those expected for random alloys. These fluctuations were suggested to be responsible for strengthening. Here, a recent parameter-free theory for initial yield strength in fcc random alloys is shown to predict the strength of CoCrFeNiPd in good agreement with experiments. The strengthening is due mainly to the large misfit volume of Pd in CoCrFeNi, indicating that the effects of the non-random composition fluctuations are secondary. Analyses of strength variations and strengthening-associated length scales help rationalize why dislocation motion is insensitive to such fluctuations. These findings point to the value of theory for understanding the mechanical behavior of HEAs.

en: Origin of high strength in the CoCrFeNiPd high-entropy alloy

epfl

display_name: epfl

high-entropy-alloys

display_name: high-entropy-alloys

palladium

display_name: palladium

solute-strengthening-theory

display_name: solute-strengthening-theory

yield-strength

display_name: yield-strength


en: We screen a database of more than 69,000 hypothetical covalent organic frameworks (COFs) for carbon capture, using parasitic energy as a metric. In order to compute CO2-framework interactions in molecular simulations, we develop a genetic algorithm to tune the charge equilibration method and derive accurate framework partial charges. Nearly 400 COFs are identified with parasitic energy lower than that of an amine scrubbing process using monoethanolamine; over 70 are better performers than the best experimental COFs; and several perform similarly to Mg-MOF-74. We analyze the effect of pore topology on carbon capture performance in order to guide development of improved carbon capture materials.

en: In silico discovery of covalent organic frameworks for carbon capture

cofs

display_name: cofs

computational-screening

display_name: computational-screening

covalent-organic-frameworks

display_name: covalent-organic-frameworks

erc

display_name: erc

gas-adsorption

display_name: gas-adsorption


en: Many low-thermal-conductivity (κL) crystals show intriguing temperature (T) dependence of κL: κL∝T-1 (crystal-like) at intermediate temperatures whereas weak T-dependence (glass-like) at high temperatures. It has been in debate whether thermal transport can still be described by phonons at the Ioffe-Regel limit. In this work, we propose that most phonons are still well defined for thermal transport, whereas they carry heat via dual channels: "normal" phonons described by the Boltzmann transport equation theory and "diffuson-like" phonons described by the diffusion theory. Three physics-based criteria are incorporated into first-principles calculations to judge mode-by-mode between the two phonon channels. Case studies on La2Zr2O7 and Tl3VSe4 show that normal phonons dominate low temperatures while diffuson-like phonons dominate high temperatures. Our present dual-phonon theory enlightens the physics of hierarchical phonon transport as approaching the Ioffe-Regel limit, and provides a numerical method that should be practically applicable to many materials with vibrational hierarchy.

en: Vibrational hierarchy leads to dual-phonon transport in low thermal conductivity crystals

dual-phonon-theory

display_name: dual-phonon-theory

theoretical-calculation

display_name: theoretical-calculation

thermal-conductivity

display_name: thermal-conductivity


en: Density functional theory calculations were used to obtain the generalized stacking fault energy curves in six BCC metals: Cr, Mo, Nb, Ta, V, and W. Among them, antiferromagnetism was considered only in Cr. Results based on non-magnetic Cr are denoted as Cr-NM.

en: Generalized stacking fault energy curves for six body-centered cubic refractory metals

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).

body-centered-cubic-refractory-metals

display_name: body-centered-cubic-refractory-metals

density-functional-theory

display_name: density-functional-theory

generalized-stacking-fault-energies

display_name: generalized-stacking-fault-energies


en: In solution crystallization, solvent has a profound effect on controlling crystal morphology. However, the role played by solvents in affecting crystal morphology remains elusive. Here, we accompany experiments with molecular dynamics simulations to investigate crystallization of an anti-tuberculosis drug, isoniazid, in different solvents. Experiments show that isoniazid grows as needle-like crystals in water, while in alcohols such as methanol, ethanol and isopropanol, it exhibits a rod-like crystal habit. The aspect ratio of isoniazid crystals decreases with the decrease in the relative solvent polarity. We modeled these experiments by performing molecular dynamics simulations of isoniazid crystallization in different solvents at constant chemical potential thus keeping the solution concentration constant. The simulation results reveal a rough growth mechanism for the fast growing (1 1 0) surface, and bulk transport of the solute from solution to the growing surface is the limiting-step. In accordance with experiments, the relative growth rate of this surface decreases from methanol, ethanol to isopropanol. On the other hand, the slow growing (0 0 2) surface appears to follow a stepwise growth mechanism, with a surface integration step chiefly controlling the growth. The relative growth rate of this surface increases from methanol to ethanol and isopropanol.

en: Solvent-mediated morphology selection of the active pharmaceutical ingredient isoniazid: Experimental and simulation studies

materialscloud

en: Materials Cloud

crystal-growth

display_name: crystal-growth

marvel

display_name: marvel

morphology

display_name: morphology

solution-crystallization

display_name: solution-crystallization

solvent-effect-on-crystal-shape

display_name: solvent-effect-on-crystal-shape