en: The phase change compound Ge₂Sb₂Te₅ (GST225) is exploited in advanced non-volatile electronic memories and in neuromorphic devices which both rely on a fast and reversible transition between the crystalline and amorphous phases induced by Joule heating. The crystallization kinetics of GST225 is a key functional feature for the operation of these devices. We report here on the development of a machine-learned interatomic potential for GST225 that allowed us to perform large scale molecular dynamics simulations (over 10000 atoms for over 100 ns) to uncover the details of the crystallization kinetics in a wide range of temperatures of interest for the programming of the devices. The potential is obtained by fitting with a deep neural network (NN) scheme a large quantum-mechanical database generated within Density Functional Theory. The availability of a highly efficient and yet highly accurate NN potential opens the possibility to simulate phase change materials at the length and time scales of the real devices.

en: Unraveling the crystallization kinetics of the Ge₂Sb₂Te₅ phase change compound with a machine-learned interatomic potential

crystallization

display_name: crystallization

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

phase-change-materials

display_name: phase-change-materials

phase-change-memories

display_name: phase-change-memories


$oid: OBSOLETE

en: Fluctuations of electric fields can change the position of a gate-defined quantum dot in a semiconductor heterostructure. In the presence of magnetic field gradient, these stochastic shifts of electron's wavefunction lead to fluctuations of electron's spin splitting. The resulting spin dephasing due to charge noise limits the coherence times of spin qubits in isotopically purified Si/SiGe quantum dots. We investigate the spin splitting noise caused by such process caused by microscopic motion of charges at the semiconductor-oxide interface. We compare effects of isotropic and planar displacement of the charges, and estimate their densities and typical displacement magnitudes that can reproduce experimentally observed spin splitting noise spectra. We predict that for defect density of 10¹⁰ cm⁻², visible correlations between noises in spin splitting and in energy of electron's ground state in the quantum dot, are expected.

en: Correlations of spin splitting and orbital fluctuations due to 1/f charge noise in the Si/SiGe Quantum Dot

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

charge-noise

display_name: charge-noise

quantum-dots

display_name: quantum-dots

simulations

display_name: simulations


en: Recently a highly ordered Moiré dislocation lattice was identified at the interface between a SrTiO₃ (STO) thin film and the (LaAlO₃)₀.₃(Sr₂TaAlO₆)₀.₇ (LSAT) substrate. A fundamental understanding of the local ionic and electronic structure around the dislocation cores is crucial to further engineer the properties of these complex multifunctional heterostructures. Here we combine experimental characterization via analytical scanning transmission electron microscopy with results of molecular dynamics and density functional theory calculations to gain insights into the structure and defect chemistry of these dislocation arrays. Our results show that these dislocations lead to undercoordinated Ta/Al cations at the dislocation core, where oxygen vacancies can easily be formed, further facilitated by the presence of cation vacancies. The reduced Ti³⁺ observed experimentally at the dislocations by electron energy-loss spectroscopy are a consequence of both the structure of the dislocation itself, as well as of the electron-doping due to oxygen vacancy formation. Finally, the experimentally observed Ti diffusion into LSAT around the dislocation core occurs only together with cation-vacancy formation in LSAT or Ta diffusion into STO.

en: Combined theoretical and experimental study of the Moiré dislocation network at the SrTiO₃-(La,Sr)(Al,Ta)O₃ interface

complex-oxide-interface

display_name: complex-oxide-interface

dislocation

display_name: dislocation

point-defects

display_name: point-defects


en: We present an ab initio method to calculate the clamped Pockels tensor of ferroelectric materials from density-functional theory (DFT), the modern theory of polarization exploiting the electric-enthalpy functional, and automated first- and second-order finite-difference derivatives of the polarizations and the Hellmann-Feynman forces. Thanks to the functional-independent capabilities of our approach, we can determine the Pockels tensor of tetragonal barium titanate (BTO) beyond the local density approximation (LDA), with arbitrary exchange-correlation (XC) functionals, for example, PBEsol. The latter, together with RRKJ ultra-soft pseudo-potentials (PP) and a supercell exhibiting local titanium off-centering, enables us to stabilize the negative optical phonon modes encountered in tetragonal BTO when LDA and norm-conserving PP are combined. As a result, the correct value range of r51, the largest experimental Pockels coefficient of BTO, is recovered. We also reveal that r51 increases with decreasing titanium off-centering for this material. The lessons learned from the structural, dielectric, and vibrational investigations of BTO will be essential to design next-generation electro-optical modulators based on the Pockels effect.

en: Ab initio functional-independent calculations of the clamped Pockels tensor of tetragonal barium titanate

ab-initio

display_name: ab-initio

aiida-vibroscopy

display_name: aiida-vibroscopy

barium-titanate

display_name: barium-titanate

density-functional-theory

display_name: density-functional-theory

electro-optics

display_name: electro-optics

imaginary-phonons

display_name: imaginary-phonons

pockels

display_name: pockels


en: Summing all Feynman diagrams with quantitative accuracy is a holy grail in theoretical physics. In condensed matter, the lattice vibration (phonon) field couples with the electrons, leading to the formation of entangled electron-phonon (e-ph) states called polarons.  In the intermediate- and strong-coupling regimes common to many conventional and quantum materials, a many-body treatment of polarons requires adding up a large number of e-ph diagrams. Diagrammatic Monte Carlo (DMC) is an efficient method for diagram summation and has been employed to study polarons within simplified e-ph models (Holstein, Frohlich, etc.).  Here we show DMC calculations based on accurate first-principles e-ph interactions, enabling numerically exact results for ground-state and dynamical properties of polarons in real materials, including the polaron formation energy, effective mass, spectral weight, phonon cloud distribution, optical conductivity, and mobility. We demonstrate such DMC calculations in systems with polarons ranging from small (localized) to large (delocalized), including LiF, SrTiO3, and TiO2 rutile and anatase. This advance is enabled by our recently developed technique for compressing first-principles e-ph interaction matrices, together with a matrix-product formalism that mitigates the DMC sign problem from multiple electronic bands. Our work enables precise modeling of e-ph interactions and polarons in coupling regimes ranging from weak to strong, opening doors to studies of transport, linear response, and superconductivity in the strong e-ph coupling regime.

en: Dataset for first-principles diagrammatic Monte Carlo for electron-phonon interactions and polaron

diagrammatic-monte-carlo

display_name: diagrammatic-monte-carlo

first-principles

display_name: first-principles

lif

display_name: lif

many-body-physics

display_name: many-body-physics

polaron

display_name: polaron

strong-e-ph-interactions

display_name: strong-e-ph-interactions


en: Calcium carbonate (CaCO₃) plays a crucial role in the global carbon cycle, and its phase diagram is of significant scientific interest. We used molecular dynamics to investigate selected structural phase transitions of calcium carbonate. Using the Raiteri potential, we explored the structural transitions occurring at the constant pressure of 1 bar, with temperatures ranging from 300 to 2500 K, and at the constant temperature of 1600 K, with pressures ranging from 0 to 13 GPa. With increasing temperature, the transitions between calcite, CaCO₃-IV, and CaCO₃-V were characterized. In the calcite structure, the carbonate ions are ordered in a planar triangular arrangement, alternating with layers of calcium ions. As the temperature increases, the transition from calcite to CaCO₃-IV occurs, leading to partial disordering of the carbonate ions. At higher temperatures, CaCO₃-IV transforms into CaCO₃-V. Through free energy analysis, we classified the latter transition as a continuous phase transition. At a temperature of 2000 K, a 'disordered CaCO₃' structure appears, characterized by low order within the calcium and carbonate sublattices and the free rotation of the carbonate ions. With increasing pressure, two calcium carbonate transformations were observed. At P = 2 GPa, the CaCO₃-V phase undergoes a phase transition into CaCO₃-IV, demonstrating that the model can describe the transition between these two phases as pressure- and temperature-driven. At P = 4.25 GPa, CaCO₃-IV undergoes a phase transition into the CaCO₃-Vb phase. This transition is classified as first-order based on free energy calculations.

en: Structural transitions of calcium carbonate by molecular dynamics simulation

calcium-carbonate

display_name: calcium-carbonate

high-pressure

display_name: high-pressure

high-temperature

display_name: high-temperature

metadynamics

display_name: metadynamics

molecular-dynamics

display_name: molecular-dynamics

phase-transitions

display_name: phase-transitions


en: The presence of defects, such as copper and oxygen vacancies, in cuprous oxide films determines their characteristic carrier conductivity and consequently their application as semiconducting systems. There are still open questions on the induced electronic re-distribution, including the formation of polarons. Indeed, to accurately reproduce the structural and electronic properties at the cuprous oxide surface, very large slab models and theoretical approaches that go beyond the standard generalized gradient corrected density functional theory are needed. In this work we investigate oxygen vacancies formed in proximity of a reconstructed Cu₂O(111) surface, where the outermost unsaturated copper atoms are removed, thus forming non-stoichiometric surface layers with copper vacancies. We address simultaneously surface and bulk properties by modelling a thick and symmetric slab, to find that hybrid exchange-correlation functionals are needed to describe the oxygen vacancy in this system. Our simulations show that the formation of oxygen vacancies is favoured in the sub-surface layer. Moreover, the oxygen vacancy leads to a splitting and left-shift of the shallow hole states in the gap, which are associated with the deficiency of copper at the surface. These findings suggest that surface electronic structure and reactivity are sensitive to the presence of oxygen vacancies, also when the latter are formed deeper within the film.

en: Understanding the role of oxygen-vacancy defects in Cu₂O(111) from first-principle calculations

hybrid-dft

display_name: hybrid-dft

oxygen-vacancy-defects

display_name: oxygen-vacancy-defects


en: High-performance n-type organic electrochemical transistors (OECTs) are essential for logic circuits and sensors. However, the performances of n-type OECTs lag far behind that of p-type ones. Conventional wisdom posits that the LUMO energy level dictates the n-type performance. Herein, we show that engineering the doped state is more critical for n-type OECT polymers. By balancing more charges to the donor moiety, we could effectively switch a p-type polymer to high-performance n-type material. Based on this concept, the polymer, P(gTDPP2FT), exhibits a record high n-type OECT performance with μC* of 54.8 F cm⁻¹ V⁻¹ s⁻¹, mobility of 0.35 cm² V⁻¹ s⁻¹, and response speed of τon/τoff = 1.75/0.15 ms. Calculations and comparison studies show that the conversion is primarily due to the more uniform charges, stabilized negative polaron, enhanced conformation, and backbone planarity at negatively charged states. Our work highlights the critical role of understanding and engineering polymers' doped states.

en: Switching p-type to high-performance n-type organic electrochemical transistors via doped state engineering

doped-state-engineering

display_name: doped-state-engineering

n-type

display_name: n-type

organic-electrochemical-transistor

display_name: organic-electrochemical-transistor


en: The electronic and vibrational properties and electron-phonon couplings of one-dimensional materials will be key to many prospective applications in nanotechnology. Dimensionality strongly affects these properties and has to be correctly accounted for in first-principles calculations. Here we develop and implement a formulation of density-functional and density-functional perturbation theory that is tailored for one-dimensional systems. A key ingredient is the inclusion of a Coulomb cutoff, a reciprocal-space technique designed to correct for the spurious interactions between periodic images in periodic-boundary conditions. This restores the proper one-dimensional open-boundary conditions, letting the true response of the isolated one-dimensional system emerge. In addition to total energies, forces and stress tensors, phonons and electron-phonon interactions are also properly accounted for. We demonstrate the relevance of the present method on a portfolio of realistic systems: BN atomic chains, BN armchair nanotubes, and GaAs nanowires. Notably, we highlight the critical role of the Coulomb cutoff by studying previously inaccessible polar-optical phonons and Fröhlich electron-phonon couplings. We also develop and apply analytical models to support the physical insights derived from the calculations and we discuss their consequences on electronic lifetimes. The present work unlocks the possibility to accurately simulate the linear response properties of one-dimensional systems, sheds light on the transition between dimensionalities and paves the way for further studies in several fields, including charge transport, optical coupling and polaritronics.

en: Density functional perturbation theory for one-dimensional systems: implementation and relevance for phonons and electron-phonon interactions

ab-initio

display_name: ab-initio

charge-transport

display_name: charge-transport

density-functional-theory

display_name: density-functional-theory

electron-phonon-coupling

display_name: electron-phonon-coupling

marvel

display_name: marvel

one-dimensional-materials

display_name: one-dimensional-materials

phonons

display_name: phonons


en: The deposited structure models of DNA adsorbed on prisitne PG/p-Si and metal (Au/W) doped PG/p-Si sheets, have been subjected to first principles calculations  based on DFT (PBE+vdW). The calculated binding affinity on PG and p-Si surface by M062X/6-31G* level of theory and adsorption energies by DFT predicts that PG has higher sensitivity towards DNA nucleic bases compared to p-Si with evident changes in their band structure properties.

en: 2D pentagonal-graphene and pentagonal-silicene sheets engineered for the detection of DNA nucleobases for genetic biomarker: A DFT study

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).

dft

display_name: dft

electronic-structure

display_name: electronic-structure


en:
Using high-throughput automation of ab-initio impurity-embedding simulations we created a database of 3d and 4d transition metal defects embedded into the prototypical topological insulators (TIs) Bi₂Te₃ and Bi₂Se₃. We simulate both single impurities as well as impurity dimers at different impurity-impurity distances inside the topological insulator matrix. We extract changes to magnetic moments, analyze the polarizability of non-magnetic impurity atoms via nearby magnetic impurity atoms and calculate the exchange coupling constants for a Heisenberg Hamiltonian.
We uncover chemical trends in the exchange coupling constants and discuss the impurities' potential with respect to magnetic order in the fields of quantum anomalous Hall insulators. In particular, we predict that co-doping of different magnetic dopants is a viable strategy to engineer the magnetic ground state in magnetic TIs.

en: High-throughput magnetic co-doping and design of exchange interactions in topological insulators

materialscloud

en: Materials Cloud

envi

en: Environment

co-doping

display_name: co-doping

jukkr

display_name: jukkr

magnetic-doping

display_name: magnetic-doping

quantum-anomalous-hall

display_name: quantum-anomalous-hall

topological-insulator

display_name: topological-insulator

topological-materials

display_name: topological-materials


en: We present a density functional theory study of the oxygen reduction reaction (ORR) on a single atom catalyst embedded in graphene, namely, TM-N₄-C (TM = Fe and Co), using the effective screening medium method combined with the reference interaction site model (ESM-RISM). It was found that Fe-N₄-C and Co-N₄-C show comparable ORR activities from the constant electrode potential simulations, in contrast to the results obtained using the constant (neutral) charge simulation, in which the superior performance of Co-N₄-C has been predicted. The constant potential method allows the variable charge and thus, resulting in a potential dependence of the reaction free energies different from that with the constant charge method in which the potential dependence is included as an ad hoc manner. We suggest the importance of the variable charge in the simulation of the electrochemical reaction, which is enabled by ESM-RISM.

en: Oxygen reduction reaction on single-atom catalysts from density functional theory calculations combined with an implicit solvation model

implicit-solvation-model

display_name: implicit-solvation-model

oxygen-reduction-reaction

display_name: oxygen-reduction-reaction

single-atom-catalyst

display_name: single-atom-catalyst


en: We present a comprehensive vibrational analysis of hydrogen boride sheet through first-principles calculations, focusing on a variety of local structural configurations including surfaces, edges, and bilayer models - some of which contains vacancy and substitutional defects. A database of vibrational modes and simulated infrared spectra was constructed, revealing distinct spectral features that serve as characteristic fingerprints for different bonding environments. By analyzing mode distributions with respect to coordination environments, we identify the distinct contributions of terminal and bridging hydrogen atoms to specific spectral regions. The results show that structural modifications, such as interlayer stacking and edge termination, have a significant influence on vibrational characteristics, particularly in the intermediate and high frequency regions. The vibrational database enables the precise interpretation of infrared spectra and offers a reliable reference for model selection and peak analysis in both experimental and theoretical studies on hydrogen boride sheet and related materials. This archive contains the database compiled from this study, comprising (i) optimized structure files, (ii) energy and force datasets used to construct the Hessian matrix and (iii) the results from the vibrational analytics, such as simulated IR spectra and mode visualizations. The database was designed for maximum accessibility; consequently, all data are supplied in multiple standard formats.

en: Dataset for vibrational recognition of local structures in hydrogen boride sheets

hydrogen-boride-sheets

display_name: hydrogen-boride-sheets

spectroscopy

display_name: spectroscopy

two-dimensional

display_name: two-dimensional


en:
Our study reveals how Gd adatoms and dimers on a superconducting Nb(110) surface induce Yu-Shiba-Rusinov (YSR) states, offering valuable insights into magnetic interactions of rare-earth atoms on superconducting surfaces. By engineering Gd dimers along the [1-10] and [001] directions, we uncover an indirect coupling between the Gd magnetic moments and the Nb substrate via their valence d electrons, leading to significant alterations in the YSR spectrum around the dimers. We further demonstrate the possibility for Néel-type spin-spiral ground states in chains of Gd atoms on Nb(110). These findings highlight the potential of 4f elements like Gd as a promising platform for controlling a spin-spiral ground state, a crucial prerequisite for realizing a topological superconductor that can host Majorana zero modes. The combination of theoretical modeling based on density functional theory, atomistic spin-dynamics simulations and experimental techniques, including scanning tunneling microscopy and spectroscopy, provides a comprehensive understanding of the coupling mechanisms and their impact on the electronic properties of these systems and establishes rare-earth magnets on Nb as a promising platform in the field.

This dataset collects the experimental and theoretical results of this work.

en: Rare-earth atoms on Nb(110) as a platform to engineer topological superconductivity

adatoms

display_name: adatoms

dftu

display_name: dftu

magnetism

display_name: magnetism

majorana-zero-mode

display_name: majorana-zero-mode

rare-earth

display_name: rare-earth

spin-dynamics

display_name: spin-dynamics

spin-spiral

display_name: spin-spiral

stm

display_name: stm

superconductivity

display_name: superconductivity

topological-superconductor

display_name: topological-superconductor


en:
Lithium ortho-thiophosphate (Li₃PS₄) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li₃PS₄ are far to be fully understood, the role of PS₄ dynamics in charge transport still being controversial. We build machine learning potentials targeting state-of-the-art DFT references (PBEsol, r²SCAN, and PBE0) to tackle this problem in all known phases of Li₃PS₄ (α, β and γ), for large system sizes and timescales. We discuss the physical origin of the observed superionic behavior of Li₃PS₄: the activation of PS₄ flipping drives a structural transition to a highly conductive phase, characterized by an increase of Li-site availability and by a drastic reduction in the activation energy of Li-ion diffusion. We also rule out any paddle-wheel effects of PS₄ tetrahedra in the superionic phases–previously claimed to enhance Li-ion diffusion–due to the orders-of-magnitude difference between the rate of PS₄ flips and Li-ion hops at all temperatures below melting.
This archive provides all the relevant data and input files that were used to fit the ML interatomic potentials used in this work, along with the relevant Density-Functional Theory calculations that were used for the training set construction, the validation of the ML models and the calculation of the electronic band structure of the β and γ structure. Furthermore, it provides input files of all the molecular dynamics trajectories needed to investigate Li-ion diffusion properties of Li₃PS₄ and the rotational dynamics of PS₄ tetrahedra. Finally, it provides the raw data to reproduce the figures of the manuscript associated with this archive.

en: Mechanism of charge transport in lithium thiophosphate

electrical-conductivity

display_name: electrical-conductivity

green-kubo-time-correlation-functions

display_name: green-kubo-time-correlation-functions

lithium-ion-diffusion

display_name: lithium-ion-diffusion

lithium-thiophosphate

display_name: lithium-thiophosphate

machine-learning

display_name: machine-learning

marvel

display_name: marvel

molecular-dynamics

display_name: molecular-dynamics

phase-transitions

display_name: phase-transitions

post-gga-density-functional-theory

display_name: post-gga-density-functional-theory

snsf-sinergia

display_name: snsf-sinergia


en:
Simulations of chemical reactivity in condensed phase systems represent an ongoing challenge in computational chemistry, where traditional quantum chemical approaches typically struggle with both the size of the system and the potential complexity of the reaction. Here, we introduce a workflow aimed at efficiently training neural network potentials (NNPs) to explore energy barriers in solution at the hybrid density functional theory level. The computational burden associated with training at the PBE0-D3(BJ) level is bypassed through the use of active and transfer learning techniques, whereas extensive sampling of the transition state region is accelerated by well-tempered metadynamics simulations using multiple time-step integration. These NNPs serve to explore a puzzling solute--solvent reactivity route involving the ring opening of N-enoxyphthalimide experimentally observed in methanol but not in 2,2,2-trifluoroethanol (TFE). This reaction represents a challenging example characterized by intricate hydrogen bonding networks and structurally ambiguous solvent-sensitive transition states. The methodology successfully delivers detailed free energy surfaces and relative energy barriers in quantitative agreement with experiment. These barriers are associated with an ensemble of transition states involving direct participation of up to five solvent molecules. While this picture contrasts with the single transition state structure assumed by current static models, no drastic qualitative difference is observed between the formed hydrogen bonding networks and the number of participating solvent molecules in methanol or TFE. The dichotomy between the two solvents thus essentially arises from an electronic effect (i.e., distinct nucleophilicity) and from the larger conformational entropy contributions in methanol. This example  underscores the critical role dynamic simulations at the ab initio levels play in capturing the full complexity of solute-solvent interactions.

The files used in our studies are listed below, ensuring reproducibility and providing resources for future studies related to this work.

en: Capturing dichotomic solvent behavior in solute–solvent reactions with neural network potentials

erc

display_name: erc

free-energy

display_name: free-energy

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Electronic band structures is a cornerstone of condensed matter physics and materials science. Conventional methods like Wannier interpolation (WI), which are commonly used to interpolate band structures onto dense k-point grids, often encounter difficulties with complex systems, such as those involving entangled bands or topological obstructions. In this work, we introduce the Hamiltonian transformation (HT) method, a novel framework that directly enhances interpolation accuracy by localizing the Hamiltonian. Using a pre-optimized transformation, HT produces a far more localized Hamiltonian than WI, achieving up to two orders of magnitude greater accuracy for entangled bands. Although HT utilizes a slightly larger, nonlocal numerical basis set, its construction is rapid and requires no optimization, resulting in significant computational speedups. These features make HT a more precise, efficient, and robust alternative to WI for band structure interpolation, as further verified by high-throughput calculations.

en: Hamiltonian transformation for accurate and efficient band structure interpolation

band-structure-interpolation

display_name: band-structure-interpolation

hamiltonian-transformation

display_name: hamiltonian-transformation

localized-hamiltonian

display_name: localized-hamiltonian


en:
Two-dimensional (2D) materials have attracted considerable attention due to their remarkable electronic, mechanical and optical properties, making them prime candidates for next-generation electronic and optoelectronic applications. Despite their widespread use in combination with substrates in practical applications, including the fabrication process and final device assembly, computational studies often neglect the effects of substrate interactions for simplicity.
In this record, we provide the results of the computational study of the stable 2D molybdenum-sulfur (Mo-S) structures on a c-cut sapphire (Al₂O₃). In particular, we provide the results of the evolutionary search in the Mo-S / Al₂O₃ (0001) system, the machine learning interatomic potential (MLIP) used for local relaxation of the systems during the evolutionary search together with its training set, post-processing data on electronic and phonon band structures of the stable 2D Mo-S structures, and the predicted stability patterns from the perspective of CVD synthesis.

en: Substrate-aware computational design of two-dimensional materials

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).

crystal-structure-prediction

display_name: crystal-structure-prediction


en: Understanding electronic interactions in high-temperature superconductors is an outstanding challenge. In the widely studied cuprate materials, experimental evidence points to strong electron-phonon (e-ph) coupling and broad photoemission spectra. Yet, the microscopic origin of this behavior is not fully understood. Here we study e-ph interactions and polarons in a prototypical parent (undoped) cuprate, La₂CuO₄ (LCO), by means of first-principles calculations. Leveraging parameter-free Hubbard-corrected density functional theory, we obtain a ground state with band gap and Cu magnetic moment in nearly exact agreement with experiments. This enables a quantitative characterization of e-ph interactions. Our calculations reveal two classes of longitudinal optical (LO) phonons with strong e-ph coupling to hole states. These modes consist of Cu-O plane bond-stretching and bond-bending as well as vibrations of apical O atoms. The hole spectral functions, obtained with a cumulant method that can capture strong e-ph coupling, exhibit broad quasiparticle peaks with a small spectral weight (Z≈0.25) and pronounced LO-phonon sidebands characteristic of polaron effects. Our calculations predict features observed in photoemission spectra, including a 40-meV peak in the e-ph coupling distribution function not explained by existing models. These results show that the universal strong e-ph coupling found experimentally in lanthanum cuprates is an intrinsic feature of the parent compound, and elucidates its microscopic origin.

en: First-principles electron-phonon interactions and polarons in the parent cuprate La₂CuO₄

materialscloud

en: Materials Cloud

dftu

display_name: dftu

electron-phonon-coupling

display_name: electron-phonon-coupling

hubbard-u

display_name: hubbard-u

parent-cuprate

display_name: parent-cuprate

phonons

display_name: phonons

polarons

display_name: polarons

spectral-function

display_name: spectral-function


en: We use symmetry analysis and density functional theory to show that changes in magnetic order at a surface with respect to magnetic order in the bulk can be generically determined by considering local magnetoelectric responses of the crystal. Specifically, analysis of the atomic-site magnetoelectric responses, or equivalently the corresponding local magnetic multipoles, can be used to predict all surface magnetic modifications arising purely from symmetry lowering via termination of the bulk magnetic order. This analysis applies even in materials with no bulk magnetoelectric response or surface magnetization. We then demonstrate our arguments for two example antiferromagnets, metallic CuMnAs and rock-salt NiO. We find that the (010) and (1-10) surfaces of CuMnAs and NiO respectively exhibit a series of antiferroically, as well as roughness-sensitive, ferroically ordered, modifications of the surface magnetic dipole moments, via canting or changes in sublattice magnitude, consistent with the bulk ordering of the magnetic multipoles. Our findings demonstrate a universal bulk-boundary correspondance allowing the general prediction of minimal possible surface and interface magnetic modifications, even in non-magnetoelectric materials. Furthermore, it paves the way for more accurate interpretations of a wide variety of surface-sensitive measurements.

en: Local magnetoelectric effects as predictors of surface magnetic order

envi

en: Environment

dft

display_name: dft

magnetism

display_name: magnetism

surface-science

display_name: surface-science

symmetry-analysis

display_name: symmetry-analysis


en:
Phase change materials are the most promising candidates for the realization of artificial synapsis for neuromorphic computing. Different resistance levels corresponding to analogic values of the
synapsis conductance can be achieved by modulating the size of an amorphous region embedded in its crystalline matrix. Recently, it has been proposed that a superlattice made of alternating layers of the phase change compound Sb₂Te₃ and of the TiTe₂ confining material allows for a better control of multiple intermediate resistance states and for a lower drift with time of the electrical resistance of the amorphous phase. In this work, we consider to substitute Sb₂Te₃ with the Ge₂Sb₂Te₅ prototypical phase change compound that should feature better data retention. By exploiting molecular dynamics simulations with a machine learning interatomic potential, we have investigated the crystallization kinetics of Ge₂Sb₂Te₅ nanoconfined in geometries mimicking Ge₂Sb₂Te₅/TiTe₂ superlattices. It turns out that nanoconfinement induces a slight reduction in the crystal growth velocities with respect to the bulk, but also an enhancement of the nucleation rate due to heterogeneous nucleation. The results support the idea of investigating Ge₂Sb₂Te₅/TiTe₂ superlattices for applications in neuromorphic devices with improved data retention. The effect on the crystallization kinetics of the addition of van der Waals interaction to the interatomic potential is also discussed.

en: Simulation of the crystallization process of Ge₂Sb₂Te₅ nanoconfined in superlattice geometries for phase change memories

crystallization

display_name: crystallization

neural-network-potential

display_name: neural-network-potential

neuromophic-computing

display_name: neuromophic-computing

phase-change-materials

display_name: phase-change-materials


en: Promoting hydrogen (H) insertion into and extraction from metal oxides plays a crucial role in tuning their properties. In our recent work, we found that the oxygen vacancy ordering in Sr(Fe,Co)Oy (SFCO) thin films can be stabilized by increasing the Co content and revealed that this stabilization is key to promoting the H insertion into SFCO oxides. This archive provides the computational inputs and crystal structures to elucidate the energies of oxygen reduction and hydrogen insertion reactions for SFCO perovskite oxides.

en: Stabilization of oxygen vacancy ordering and electrochemical-proton-insertion-and- extraction-induced large resistance modulation in strontium iron cobalt oxides Sr(Fe,Co)Oy

hydrogen

display_name: hydrogen

thermodynamics

display_name: thermodynamics


en: Through quasiparticle self-consistent GW, we investigate the electronic structure of the antiferromagnetic ground state of four transition-metal monoxides: MnO, FeO, CoO, and NiO. In addition to the random-phase approximation, we consider two different schemes incorporating effective vertex corrections. The first scheme includes in the polarizability a vertex function derived from the solution of the Bethe-Salpeter equation (BSE), whereas the second scheme includes in both the polarizability and self-energy a vertex function, which carries a long-range part satisfying the Ward identity and a short-range part derived from the adiabatic local density approximation. Our results include fundamental band gaps, macroscopic dielectric constants, and local magnetic moments, emphasizing the role of vertex corrections in the description of these key electronic properties. We provide quasiparticle band structures and projected densities of states allowing us to establish a connection with the Mott insulator picture and to highlight the overall good agreement with experimental photoemission spectra. The inclusion of the vertex in the self-energy preserves the overall shape of the band structures but generally produces larger rigid energy shifts for d bands than for sp bands. Through the solution of the Bethe-Salpeter equation, we determine excitonic effects and obtain dielectric response functions. Despite the experimental uncertainties, which appear sizable in the case of FeO, it is possible to discern a good general correspondence between the calculated and measured spectra, particularly for the absorption onsets and the peak positions. Furthermore, deep excitons are found to occur in the absorption spectra of FeO, CoO, and NiO, in qualitative agreement with the available characterization. Our work indicates that many-body perturbation theory including effective vertex corrections is able to provide a quantitatively accurate description of key electronic-structure features of transition-metal monoxides.

en: Quasiparticle self-consistent GW with effective vertex corrections in the polarizability and the self-energy applied to MnO, FeO, CoO, and NiO

electronic-structure

display_name: electronic-structure

gw

display_name: gw

many-body-perturbation-theory

display_name: many-body-perturbation-theory

transition-metal-oxides

display_name: transition-metal-oxides

vertex-corrections

display_name: vertex-corrections


en: Dislocation-grain boundary play a major role in the strength and ductility of structural materials. An understanding of governing parameters such as grain boundary local atomic structures on the outcome of this interaction can accelerate new alloy design strategies that tailors materials' microstructures. Previous studies have focused only on the subset of minimum-energy grain boundary structures. We present a comprehensive database of dislocation-grain boundary interaction for edge, screw, and 60o mixed dislocation with 587 < 110 > and < 112 > symmetric tilt grain boundary in FCC Cu consisting of 73 minimum-energy grain boundary structures and 514 metastable ones. The dataset contains the outcomes for 5234 unique interactions with a particular dislocation type, grain boundary structure, and applied shear stress.

en: Dislocation-grain boundary interaction dataset for FCC Cu

dislocation-grain-boundary-interaction

display_name: dislocation-grain-boundary-interaction

grain-boundary-structure

display_name: grain-boundary-structure

material-science

display_name: material-science


en:
This study investigates an electrolyte system composed of lithium hexafluorophosphate (LiPF6), ethylene carbonate (EC) and ethyl methyl carbonate (EMC). For the assembly of full cells, electrodes based on graphite and lithium nickel dioxide (LNO) are used. This work provides insight into the similarity of formulations of an electrolyte optimized for maximum conductivity and another one optimized for maximum cycle life are expected to be in this chemical system. The goal is to assess whether it is promising to target research efforts on finding an electrolyte formulation within this chemical space which can fulfill both requirements.
A campaign utilizing the latest version of FINALES is designed to determine conductivity values and predict end of life for various electrolyte formulations containing the aforementioned chemicals. The campaigns were able to reproducibly identify regions of high ionic conductivity of the aforementioned chemical composition. The ML methodology applied for the EOL optimisation allowed accelerated early life-time predictions.

en: FINALES - Electrolyte optimization for maximum conductivity and for maximum cycle life

battery

display_name: battery

big-map

display_name: big-map

electrolyte-formulation

display_name: electrolyte-formulation

end-of-lifetime

display_name: end-of-lifetime

experimental

display_name: experimental

ionic-conductivity

display_name: ionic-conductivity

machine-learning

display_name: machine-learning

map

display_name: map

material-acceleration-platform

display_name: material-acceleration-platform

polis

display_name: polis


en:
The combination of the high wear resistance and mechanical strength of W with the high thermal conductivity of Cu makes the Cu/W system an attractive candidate material for heat sink plasma and radiation tolerance applications. However, the resulting mechanical properties of multilayers and coatings strongly depend on the microstructure of the layers.
In this work, the mechanical properties of Cu/W nanomultilayers with different densities of internal interfaces are systematically investigated for two opposite in-plane stress states and critically discussed in comparison with literature. Atomistic simulations with the state-of-the-art neural network potential are used to explain the experimental findings. The results suggest that the microstructure, specifically the excess free volume associated with porosity and interface disorder interconnected with the stress state, has a great impact on the mechanical properties, notably Young's modulus of Cu/W nanomultilayers.

en: Effect of residual stress and microstructure on mechanical properties of sputter-grown Cu/W nanomultilayers

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).

atomistic-simulations

display_name: atomistic-simulations

cuw

display_name: cuw

hardness

display_name: hardness

nanoindentation

display_name: nanoindentation

nanomultilayers

display_name: nanomultilayers

youngs-modulus

display_name: youngs-modulus


neural-network-potential-for-zr-h

en: The introduction of Hydrogen (H) into Zirconium (Zr) influences many mechanical properties, especially due to low H solubility and easy formation of Zirconium hydride phases. Understanding the various effects of H requires studies with atomistic resolution but at scales that incorporate defects such as cracks, interfaces, and dislocations. Such studies thus demand accurate interatomic potentials. Here, a neural network potential (NNP) for the Zr-H system is developed within the  Behler-Parrinello framework. The Zr-H NNP retains the accuracy of a recent NNP for hcp Zr and exhibits excellent agreement with first-principles density functional theory (DFT) for (i) H interstitials and their diffusion in hcp Zr, (ii) formation energies, elastic constants, and surface energies of relevant Zr hydrides, and (iii) energetics of a common Zr/Zr-H interface. The Zr-H NNP shows physical behavior for many different crack orientations in the most-stable ε-hydride and structures and reasonable relative energetics for the ⟨a⟩ screw dislocation in pure Zr. This Zr-H NNP should thus be very powerful for future study of many phenomena driving H degradation in Zr that require atomistic detail at scales far above those accessible by first-principles

en: Neural network potential for Zr-H

materialscloud

en: Materials Cloud

title_for_slug: neural-network-potential-for-zr-h

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potentials

display_name: neural-network-potentials

zirconium-hydrides

display_name: zirconium-hydrides


en: Amorphous formulations are increasingly used in the pharmaceutical industry due to their increased solubility, but their structural characterization at atomic-level resolution remains extremely challenging. Here, we characterize the complete atomic-level structure of an amorphous glucagon-like peptide-1 receptor (GLP-1R) agonist using chemical shift driven NMR crystallography. The structure is determined from measured chemical shift distributions for 17 of the 32 carbon atoms and 16 of the 31 hydrogen atoms in the molecule. The chemical shifts are able to provide a detailed picture of the atomic-level conformations and interactions, and we identify the structural motifs that play a major role in stabilization of the amorphous form. In particular, hydrogen bonding of the carboxylic acid proton is strongly promoted although no carboxylic acid dimer is formed. Two orientations of the benzodioxole ring are promoted in the NMR structure, corresponding to a significant stabilization mechanism. Our observation that inclusion of water leads to stabilization of the carboxylic acid group might be used as a strategy in future formulations where hydrogen bonding between neighboring molecules may otherwise be hindered by sterics.

en: The three-dimensional atomic-level structure of an amorphous glucagon-like peptide-1 receptor agonist

envi

en: Environment

marvel

display_name: marvel

molecular-dynamics

display_name: molecular-dynamics

nmr

display_name: nmr

nmr-crystallography

display_name: nmr-crystallography


en: The potential of lead-halide perovskites for realistic applications is currently hindered by their limited long-term stability under functional activation. While the role of lattice flexibility in the thermal response of perovskites has become increasingly evident, the description of thermally-induced distortions is still unclear. In this work, we provide a unified picture of thermal activation in CsPbBr₃ across length scales, showing that lattice symmetry does not increase at high temperatures. We combine temperature-dependent XRD, Br K-edge XANES, ab initio MD simulations, and calculations of the XANES spectra by first-principles, accounting for both thermal fluctuations and core hole final state effects. We find that the octahedral tilting of the Pb-Br inorganic framework statistically adopts multiple local configurations over time - in the short-range. In turn, the stochastic nature of the local thermal fluctuations uplifts the longer-range periodic octahedral tilting characterizing the low temperature structure, with the statistical mean of the local configurations resulting in a cubic-like time-averaged lattice. These observations can be rationalized in terms of displacive thermal phase transitions through the soft mode model, in which the phonon anharmonicity of the flexible inorganic framework causes the excess free energy surface to change as a function of temperature. Our work demonstrates that the effect of thermal dynamics on the XANES spectra can be effectively described for largely anharmonic systems, provided ab initio MD simulations are performed to determine the dynamically fluctuating structures, and core hole final state effects are included in order to retrieve an accurate XANES line shape. Moreover, it shows that the soft mode model, previously invoked to describe displacive thermal phase transitions in oxide perovskites, carries a more general validity.

en: Atomic-level description of thermal fluctuations in inorganic lead halide perovskites

halide-perovskites

display_name: halide-perovskites

xas-simulation

display_name: xas-simulation


en: Materials are often represented in machine learning applications by (chemical-)geometric descriptions of their atomic structure. In this work, we propose an alternative framework for representing materials using descriptions of their electronic structure called Spectral Operator Representations (SOREPs). This record contains the code and data used to study carbon nanotubes (CNTs), barium titanate polymorphs, and the accelerated screening of transparent conducting materials with SOREPs. A data set for each application is provided: pz tight binding band structures for the three CNT configurations studied; the structures, band dispersions, and SOREP features of 127 BaTiO₃ polymorphs; and the SOREP features and ML targets for the MC3D materials considered in the accelerated screening. Additionally, code including patch files for Quantum ESPRESSO, the "sorep" python package, and the set of scripts used to prepare these data, train ML models, and plot results is provided.

en: Spectral operator representations

electronic-bands

display_name: electronic-bands

electronic-structure

display_name: electronic-structure

epfl

display_name: epfl

machine-learning

display_name: machine-learning


en: The performance of Ni-based oxygen evolution reaction (OER) electrocatalysts is enhanced upon Fe incorporation into the structure or Fe uptake from the electrolyte. In light of the promising potential of metal-organic framework (MOF) electrocatalysts for water splitting, Ni-MOF-74 is used as a model catalyst to study the effect of Fe incorporation from KOH electrolyte on the electrocatalyst's OER activity and stability. The insights obtained from X-ray diffraction and operando X-ray absorption spectroscopy characterizations of Ni-MOF-74 and an amorphous Ni metal organic compound (Ni-MOC*)  reveal that Fe uptake enhances OER by two processes: higher Ni oxidation states and enhanced flexibility of the electronic state and local structure when cycling the potential below and above the OER onset. To demonstrate the impressive OER activity and stability in Fe containing KOH, an Ni-MOC* anode was implemented in an anion exchange membrane water electrolyzer (AEM-WE) with 3 ppm Fe containing 1 M KOH electrolyte resulting in an outstanding cell voltage of 1.7 V (at an anode potential of 1.51 V) at 60 °C and 0.5 A cm-2 exceeding 130 h of stable continuous operation.

en: Revising known concepts for novel applications: Fe incorporation into Ni-MOF-74 derived oxygen evolution electrocatalysts for anion exchange membrane water electrolysis

alkalineaem-water-electrolysis

display_name: alkalineaem-water-electrolysis

electrocatalysis

display_name: electrocatalysis

fe-effect-on-ni-based-oer-catalysts

display_name: fe-effect-on-ni-based-oer-catalysts

oer

display_name: oer

operando-xasxrd

display_name: operando-xasxrd


delta-project-archive-of-old-website

en: The widespread popularity of density functional theory has given rise to an extensive range of dedicated codes for predicting molecular and crystalline properties. However, each code implements the formalism in a different way, raising questions about the reproducibility of such predictions. In K. Lejaeghere et al., Science 351 (6280), aad3000 (2016) (https://doi.org/10.1126/science.aad3000), we reported the results of a community-wide effort that compared 15 solid-state codes, using 40 different potentials or basis set types, to assess the quality of the Perdew-Burke-Ernzerhof equations of state for 71 elemental crystals. We conclude that predictions from recent codes and pseudopotentials agree very well, with pairwise differences that are comparable to those between different high-precision experiments. Older methods, however, have less precise agreement. Our benchmark provides a framework for users and developers to document the precision of new applications and methodological improvements. The underlying data of this paper were accessible during 2016-2023 at https://molmod.ugent.be/deltacodesdft. Several additions that made use of the same protocol were added later. As this website is obsolete and to ensure long-term continued access, these data are stored now under the present record of the Materials Cloud Archive.

en: Delta project — archive of old website

title_for_slug: delta-project-archive-of-old-website

delta-project

display_name: delta-project

dft-benchmarking

display_name: dft-benchmarking

precision

display_name: precision

unary-crystals

display_name: unary-crystals

verification

display_name: verification


en: A major challenge in first-principles high-throughput materials simulations is automating the selection of parameters used by simulation codes in a way that robustly ensures numerical precision and computational efficiency. Here, we propose a rigorous methodology to assess the quality of self-consistent DFT calculations with respect to smearing and k-point sampling across a wide range of crystalline materials. To achieve this, we develop criteria to reliably control average errors in total energies, forces, and other properties as a function of the desired computational efficiency, while consistently suppressing uncontrollable k-point sampling errors. Our results provide automated protocols for selecting optimized parameters based on different precision and efficiency tradeoffs. This archive contains all data related to the material structures and calculation workflows developed in this work.

en: Accurate and efficient protocols for high-throughput first-principles materials simulations

high-throughput-workflows

display_name: high-throughput-workflows

marvel

display_name: marvel

protocols

display_name: protocols

quantum-espresso

display_name: quantum-espresso


en: Antiferromagnetic Heisenberg chains exhibit two distinct types of excitation spectra: gapped for integer-spin chains and gapless for half-integer-spin chains. However, in finite-length half-integer-spin chains, quantization induces a gap, requiring precise control over sufficiently long chains to study its evolution. In a recent publication, we created length-controlled spin-1/2 Heisenberg chains by covalently linking olympicenes—Olympic ring-shaped magnetic nanographenes. With large exchange interactions, tunable lengths, and negligible magnetic anisotropy, this system is ideal for investigating length-dependent spin excitations, probed via inelastic electron tunneling spectroscopy. We observe a power-law decay of the lowest excitation energy with length L, following a 1/L dependence in the large-L regime, consistent with theory. For L=50, a V-shaped excitation continuum confirms gapless behavior in the thermodynamic limit. Additionally, low-bias current maps reveal the standing wave of a single spinon in odd-numbered chains. Our findings provide evidence for the realization of a one-dimensional analog of a gapless spin liquid within an artificial graphene lattice. This record includes all the data that support the results discussed in the publication.

en: Spin excitations in nanographene-based antiferromagnetic spin-½  Heisenberg chains

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).

cscs

display_name: cscs

dft

display_name: dft

fractional-excitation

display_name: fractional-excitation

spin-excitation

display_name: spin-excitation

spin-liquid

display_name: spin-liquid

spinon

display_name: spinon


en: Deuterium boride (DB) nanosheets were synthesized through ion exchange, and their Fourier-transform infrared absorption spectra showed isotope effects with a shift in the B-H stretching mode. Temperature-programmed desorption (TPD) experiments indicated that hydrogen release from DB and HB nanosheets primarily results from inter-layer hydrogen recombination at lower temperatures, with intra-layer recombination occurring at higher temperatures. This repository contains supplementary data related to the computational findings presented in the accompanying publication. The goal of sharing these data files is to enhance result transparency and support better reproducibility.

en: Inter-layer hydrogen recombination from hydrogen boride nanosheets elucidated by isotope labeling

materialscloud

en: Materials Cloud

density-functional-theory

display_name: density-functional-theory

deuterium-boride

display_name: deuterium-boride

hydrogen-boride

display_name: hydrogen-boride

hydrogen-carrier

display_name: hydrogen-carrier

hydrogen-release

display_name: hydrogen-release

inter-layer-hydrogen-recombination

display_name: inter-layer-hydrogen-recombination

temperature-programmed-desorption

display_name: temperature-programmed-desorption


en: Density-functional theory with extended Hubbard functionals (DFT+U+V) provides a robust framework to accurately describe complex materials containing transition-metal or rare-earth elements. It does so by mitigating self-interaction errors inherent to semi-local functionals which are particularly pronounced in systems with partially-filled d and f electronic states. However, achieving accuracy in this approach hinges upon the accurate determination of the on-site U and inter-site V Hubbard parameters. In practice, these are obtained either by semi-empirical tuning, requiring prior knowledge, or, more correctly, by using predictive but expensive first-principles calculations.  This archive entry contains Hubbard parameters, occupation matrices and other data calculated for 28 materials and covers all steps in a self-consistent procedure where, at each step new Hubbard parameters are obtained via linear-response, a process that is repeated until the parameters no longer change. The primary purpose of this dataset is to support the development and validation of machine learning models that can be used to predict Hubbard parameters, sidestepping the need for expensive ab-initio density functional perturbation theory calculations.

en: Dataset of self-consistent Hubbard parameters for Ni, Mn and Fe from linear-response

envi

en: Environment

hubbard-corrections

display_name: hubbard-corrections

machine-learning

display_name: machine-learning


en: The accurate description of redox reactions remains a challenge for first-principles calculations, but it has been shown that extended Hubbard functionals (DFT+U+V) can provide a reliable approach, mitigating self-interaction errors, in materials with strongly localized d or f electrons. Here, we first show that DFT+U+V molecular dynamics is capable to follow the adiabatic evolution of oxidation states over time, using representative Li-ion cathode materials.  In turn, this allows to develop redox-aware machine-learned potentials. We show that considering atoms with different oxidation states (as accurately predicted by DFT+U+V) as distinct species in the training leads to potentials that are able to identify the correct ground state and pattern of oxidation states for redox elements present. This is achieved, e.g., trough a combinatorial search for the lowest energy configuration. This brings the advantages of machine-learned potential to key technological applications (e.g., rechargeable batteries), which require an accurate description of the evolution of redox states.

en: Teaching oxidation states to neural networks

dftuv

display_name: dftuv

max

display_name: max

oxidation-states

display_name: oxidation-states


en: Band-to-band tunnelling field-effect transistors (TFETs) have long been considered as promising candidates for future low-power logic applications. However, fabricated TFETs rarely reach sub-60 mV/dec sub-threshold swings (SS) at room temperature. Previous theoretical studies identified Auger processes as possible mechanisms for the observed degradation of SS. Through first-principles quantum transport simulations incorporating carrier-carrier interactions within the Non-equilibrium Green's Function formalism through self-consistent GW approximation, we confirm here that Auger processes are indeed at least partly responsible for the poor performance of TFETs. Using a carbon nanotube TFET as testbed, we show that carrier-carrier scattering alone significantly increases the OFF-state current of these devices, thus worsening their sub-threshold behavior. The results are in the folder uploaded.

en: Influence of carrier-carrier interactions on the sub-threshold swing of band-to-band tunnelling transistors

electronic-structure

display_name: electronic-structure

transport

display_name: transport

wannier-functions

display_name: wannier-functions


en: Homogeneous nucleation processes are important for understanding solidification and the resulting microstructure of materials. Simulating this process requires accurately describing the interactions between atoms,  hich is further complicated by chemical order through cross-species interactions. The large scales needed to observe rare nucleation events are far beyond the capabilities of ab initio simulations. Machine-learning is used for overcoming these limitations in terms of both accuracy and speed, by building a high-dimensional neural network potential for binary Al-Ni alloys, which serve as a model system relevant to many industrial applications. The potential is validated against experimental diffusion, viscosity, and scattering data, and is applied to large-scale molecular dynamics simulations of homogeneous nucleation at equiatomic composition, as well as for pure Ni. Pure Ni nucleates in a single-step into an fcc crystal phase, in contrast to previous results obtained with a classical empirical potential. This highlights the sensitivity of nucleation pathways to the underlying atomic interactions. Our findings suggest that the nucleation pathway for AlNi proceeds in a single step toward a B2 structure, which is discussed in relation to the pure elements counterparts.

en: Homogeneous nucleation of undercooled Al-Ni melts via a machine-learned interaction potential

aluminium

display_name: aluminium

interaction-potential

display_name: interaction-potential

nickel

display_name: nickel


en: We use spin dynamics simulations to determine the origin of the unusual correlated diffuse scattering, characterised by half-moon shapes bridging the magnetic Bragg peaks, observed in the polarised elastic neutron scattering from manganese tungstate, MnWO₄. We first fit a Heisenberg Hamiltonian with twelve nearest-neighbour exchange interactions and single-ion anisotropy to the experimental ground-state magnon dispersion. We then show via spin dynamics simulations that our model Hamiltonian both reproduces the experimentally observed half-moon features and captures their persistence into the paramagnetic regime. Moreover, we identify the three-dimensional, competing antiferromagnetic interactions driving this behavior. Our work complements earlier studies of half-moon-shaped signatures in pyrochlore and triangular structures, by providing insight into their origin in a zigzag chain geometry with three-dimensional competing exchange interactions.

en: Paramagnetic half-moon shaped diffuse scattering arising from 3D magnetic frustration

diffuse-scattering

display_name: diffuse-scattering

erc

display_name: erc

horizon-europe

display_name: horizon-europe

spin-dynamics

display_name: spin-dynamics

uppasd

display_name: uppasd


en: X-ray absorption spectroscopy (XAS) is a powerful characterization technique for probing the local chemical environment of absorbing atoms. However, analyzing XAS data presents with significant challenges, often requiring extensive, computationally intensive simulations, as well as significant domain expertise. These limitations hinder the development of fast, robust XAS analysis pipelines that are essential in high-throughput studies and for autonomous experimentation. We address these challenges with a suite of transfer learning approaches for XAS prediction, each uniquely contributing to improved accuracy and efficiency, as demonstrated on simulated K-edge X-ray absorption near-edge structure (XANES) spectra database covering eight 3d transition metals (Ti-Cu). This database contains FEFF and VASP K-edge XANES spectra of 3d transition metal-containing oxide materials used to develop the above machine learning models. The materials structures are sourced from the Materials Project, corresponding to primary, secondary, ternary and quaternary oxide materials. Specifically, FEFF9 was used to compute the spectra of Ti, V, Cr, Mn, Fe, Co, Ni and Cu compounds; VASP 6.2.1 was used to compute the spectra of Ti and Cu compounds.

en: Simulated 3d transition metal oxides cation K-edge XANES dataset

materials

display_name: materials

vasp

display_name: vasp

x-ray-absorption-spectroscopy

display_name: x-ray-absorption-spectroscopy


en: Spin excitations play a fundamental role in understanding magnetic properties of materials, and have significant technological implications for magnonic devices. However, accurately modeling these in transition-metal and rare-earth compounds remains a formidable challenge. Here, we present a fully first-principles approach for calculating spin-wave spectra based on time-dependent (TD) density-functional perturbation theory (DFPT), using nonempirical Hubbard functionals. This approach is implemented in a general noncollinear formulation, enabling the study of magnons in both collinear and noncollinear magnetic systems. Unlike methods that rely on empirical Hubbard U parameters to describe the ground state, and Heisenberg Hamiltonians for describing magnetic excitations, the methodology developed here probes directly the dynamical spin susceptibility (efficiently evaluated with TDDFPT throught the Liouville-Lanczos approach), and treats the linear variation of the Hubbard augmentation (in itself calculated non-empirically) in full at a self-consistent level. Furthermore, the method satisfies the Goldstone condition without requiring empirical rescaling of the exchange-correlation kernel or explicit enforcement of sum rules, in contrast to existing state-of-the-art techniques. We benchmark the novel computational scheme on prototypical transition-metal monoxides NiO and MnO, showing remarkable agreement with experiments and highlighting the fundamental role of these newly implemented Hubbard corrections. The method holds great promise for describing collective spin excitations in complex materials containing localized electronic states.

en: Magnons from time-dependent density-functional perturbation theory and nonempirical Hubbard functionals

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).

first-principles

display_name: first-principles

hubbard-functionals

display_name: hubbard-functionals

magnetism

display_name: magnetism

marvel

display_name: marvel


en: The effect of dimensionality reduction on the crystallization kinetics of phase change materials is of relevance for the operation of ultrascaled memory devices. Therefore, the crystallization of amorphous nanoparticles (NPs) of the prototypical phase change compounds, GeTe and Ge₂Sb₂Te₅, has been addressed by several experimental works in recent years. In this work, we performed molecular dynamics simulations of the crystallization process of amorphous GeTe NPs with diameter in the range 3-6 nm (512-4096 atoms) by exploiting a machine-learned interatomic potential. We saw a few crystal nucleation events in the larger NPs but no crystallization in the smallest NP, 3 nm in diameter, in simulations lasting up to 80 ns in the temperature range 500-750 K. The analysis of the crystallization kinetics suggests that the nucleation rate per volume decreases with the NP size to an extent that prevents us from seeing crystallization in the smallest NP on our simulation time scale. This result is consistent with the large raise in crystallization temperature observed experimentally for NPs with diameters shorter than 3.5 nm.

en: Atomistic simulations of the crystallization of amorphous GeTe nanoparticles

materialscloud

en: Materials Cloud

crystallization

display_name: crystallization

gete

display_name: gete

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

neural-network-potential

display_name: neural-network-potential

neuromophic-computing

display_name: neuromophic-computing

phase-change-materials

display_name: phase-change-materials


en:
A database of 600 atomistic models of reduced graphene oxide (rGO) and hydrogenated rGO (H-rGO) was constructed, comprising 120 rGO and 480 H-rGO structures. The dataset spans a broad range of oxygen concentrations, –O–:–OH (epoxy/ether to hydroxyl) ratios, and hydrogenation levels. The database is designed for applications in computational modeling, machine learning, and structure–property analyses. The models were generated following a three-step simulation protocol:
 – Step 1 | Generation of Pseudo-GO Models: Graphene sheets were functionalized with oxygen groups (–O– or –OH), randomly distributed according to three –O–:–OH ratios (25:75, 50:50, and 75:25). Functionalization was applied symmetrically on both sides of the sheet, avoiding adjacent carbon atoms.
 – Step 2 | Thermal Reduction: Each pseudo-GO structure was subjected to annealing at four different temperatures (1000, 1500, 2000, and 2500 K). After initial relaxation at 300 K, the models were heated, equilibrated, annealed back to room temperature, and re-optimized. This step produced 120 rGO models exhibiting a range of oxygen contents, functional group distributions, and defect patterns.
 – Step 3 | Hydrogenation of rGO Models: rGO models were exposed to atomic hydrogen using a combined Grand Canonical Monte Carlo and molecular dynamics (GCMC/MD) scheme at 300 K and four hydrogen pressures (1, 2, 4, and 8 bar). Hydrogenation was performed with 50 GCMC exchange steps every 1 ps of MD, followed by relaxation and removal of unstable species. This step generated 480 H-rGO models with varying hydrogen coverage and bonding configurations.
All simulations were performed using the LAMMPS software package with the ReaxFF reactive force field.

en: Reduced graphene oxide membrane models for hydrogen storage

envi

en: Environment

functionalized-carbon-nanostructures

display_name: functionalized-carbon-nanostructures

graphene-oxide-models

display_name: graphene-oxide-models

hydrogenated-graphene-oxide

display_name: hydrogenated-graphene-oxide

reduced-graphene-oxide

display_name: reduced-graphene-oxide


en: Cement hydration is crucial for the strength development of cement-based materials; however, the mechanism that underlies this complex reaction remains poorly understood at the molecular level. An in-depth understanding of cement hydration is required for the development of environmentally friendly cement and consequently the reduction of carbon emissions in the cement industry. Here, we use molecular dynamics simulations with a reactive force field to investigate the initial hydration processes of tricalcium silicate (C₃S) and dicalcium silicate (C₂S) up to 40 ns. Our simulations provide theoretical support for the rapid initial hydration of C₃S compared to C₂S at the molecular level. The dissolution pathways of calcium ions in C₃S and C₂S are revealed, showing that, two dissolution processes are required for the complete dissolution of calcium ions in C₃S. Our findings promote the understanding of the calcium dissolution stage and serve as a valuable reference for the investigation of the initial cement hydration.

en: The initial stages of cement hydration at the molecular level

cement-hydration

display_name: cement-hydration

reaxff-reactive-force-field

display_name: reaxff-reactive-force-field


en:
We investigate popular resampling methods for estimating the uncertainty of statistical models, such as subsampling, bootstrap and the jackknife, and their performance in high-dimensional supervised regression tasks. We provide a tight asymptotic description of the biases and variances estimated by these methods in the context of generalized linear models, such as ridge and logistic regression, taking the limit where the number of samples n and dimension d of the covariates grow at a comparable fixed rate α = n/d. Our findings are three-fold: i) resampling methods are fraught with problems in high dimensions and exhibit the double-descent-like behavior typical of these situations; ii) only when α is large enough do they provide consistent and reliable error estimations (we give convergence rates); iii) in the over-parametrized regime α < 1 relevant to modern machine learning practice, their predictions are not consistent, even with optimal regularization.
This record provides the code to reproduce the numerical experiments of the related paper "Analysis of bootstrap and subsampling in high-dimensional regularized regression".

en: Analysis of bootstrap and subsampling in high-dimensional regularized regression (code)

neural-networks

display_name: neural-networks

numerical-simulation

display_name: numerical-simulation

uncertainty-quantification

display_name: uncertainty-quantification


en: Topological Weyl semimetals represent a novel class of non-trivial materials, where band crossings with linear dispersions take place at generic momenta across reciprocal space. These crossings give rise to low-energy properties akin to those of Weyl fermions, and are responsible for several exotic phenomena. Up to this day, only a handful of Weyl semimetals have been discovered, and the search for new ones remains a very active area. The main challenge on the computational side arises from the fact that many of the tools used to identify the topological class of a material do not provide a complete picture in the case of Weyl semimetals. In this work, we propose an alternative and inexpensive, criterion to screen for possible Weyl fermions, based on the analysis of the band structure along high-symmetry directions in the absence of spin-orbit coupling. We test the method by running a high-throughput screening on a set of 6000 inorganic bulk materials and identify 49 possible candidates for topological properties. A further analysis, carried out by identifying and characterizing the crossings in the Brillouin zone, shows us that 3 of these candidates are Weyl semimetals. Interestingly, while these 3 materials underwent other high-throughput screenings, none had revealed their topological behavior before.

en: High-throughput screening of Weyl semimetals

high-throughput

display_name: high-throughput

topological-materials

display_name: topological-materials

weyl-semimetal

display_name: weyl-semimetal


en: Metal-organic frameworks (MOFs) as electrocatalysts for the alkaline oxygen evolution reaction (OER) show promising catalytic activity by offering great variability and high surface areas, enabling performance optimization and mechanistic studies. However, their stability during reaction and the structure-performance relationship defining the origin of the high OER activity, are still vigorously debated. Herein, we leverage operando X-ray absorption spectroscopy and operando X-ray diffraction to unveil the structural and electronic transformations of Ni-MOF-74 during OER. We identify the irreversible destruction of the MOF-74 crystal into a highly OER active, amorphous NiOOH-metal organic compound. Based on these findings, we propose an amorphous Ni metal organic compound (Ni-MOC*) for achieving high current densities both in a three-electrode cell (14 A gNi-1 at 1.5 VRHE) and in an anion exchange membrane water electrolyzer (AEM-WE) with a stable AEM-WE performance exceeding 100 h at 500 mA cm-2.

en: From operando investigations to implementation of Ni-MOF-74 oxygen evolution electrocatalysts

alkalineaem-water-electrolysis

display_name: alkalineaem-water-electrolysis

electrocatalysis

display_name: electrocatalysis

marvel

display_name: marvel

oer

display_name: oer

operando-xasxrd

display_name: operando-xasxrd


en:
We reassess the modeling of amorphous silica bilayers as a two-dimensional classical system whose particles interact with an effective pairwise potential. We show that it is possible to reparameterize the potential developed by Roy, Heyde, and Heuer to quantitatively match the structural details of the experimental samples. We then study the glassy dynamics of the reparameterized model at low temperatures.  Using appropriate cage-relative correlation functions, which suppress the effect of Mermin-Wagner fluctuations, we highlight the presence of two well-defined Arrhenius regimes separated by a narrow crossover region, which we connect to the thermodynamic anomalies and the changes in the local structure. We find that the bond-orientational order grows steadily below the crossover temperature and is associated to transient crystalline domains of nanometric size.  These findings raise fundamental questions about the nature of glass structure in two dimensions and provide guidelines to interpret the experimental data.

This dataset is associated with "Glassy dynamics and crystalline local order in two-dimensional amorphous silica", Marco Dirindin and Daniele Coslovich (2024) [arXiv:2410.10500].
It includes scripts and data files to allow for the replication of the figures. The EPS figures in the Figures folder were generated using gnuplot version 5.4.

glass-transition

display_name: glass-transition

silica-bilayer

display_name: silica-bilayer


en: Covalent organic frameworks (COFs) are materials of growing interest for electronic applications due to their tunable structures, chemical stability, and layered architectures that support extended π-systems and directional charge transport. While their electronic properties are strongly influenced by the choice of molecular building blocks and the stacking arrangement, experimental control over these features remains limited, and the number of well-characterized COFs is still relatively small. Here, we explore two alternative strategies, hydrostatic pressure and metal intercalation, to tune the electronic structure of COFs. Using periodic density functional theory (DFT) calculations, we show that the band gap of pristine COF-1 decreases by ∼1 eV under compression up to 10 GPa. Metal intercalation induces an even greater reduction, in some cases leading to metallic behavior. We demonstrate that pressure and intercalation offer effective, continuous control over COF electronic properties, providing powerful means to complement and extend conventional design approaches.

en: Extensive band gap tunability in covalent organic frameworks via metal intercalation and high pressure

band-gap

display_name: band-gap

covalent-organic-frameworks

display_name: covalent-organic-frameworks

dft

display_name: dft

electronic-bands

display_name: electronic-bands

high-pressure

display_name: high-pressure

intercalation

display_name: intercalation


en: This dataset contains the results of density functional theory (DFT) calculations performed using Quantum ESPRESSO to study surface binding energies (SBE) and the formation energies of interstitial hydrogen (H-IFE) in various plasma-facing materials (PFMs). These calculations support the findings reported in the article Comprehensive Screening of Plasma-Facing Materials for Nuclear Fusion, where a combination of peer-reviewed data from the PAULING FILE database and first-principles calculations are used to evaluate potential PFM candidates. Key results include a detailed comparison of tungsten and alternative refractory materials, focusing on their behavior under intense neutron bombardment and plasma interactions in nuclear fusion reactors. The dataset includes input and output files from the Quantum ESPRESSO simulations, offering valuable insight into defect energetics in candidate materials.

en: DFT calculations of surface binding and interstitial hydrogen formation energies for plasma-facing materials

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).

eurofusion

display_name: eurofusion

interstitial-formation-energy

display_name: interstitial-formation-energy

nuclear-fusion

display_name: nuclear-fusion

plasma-facing-materials

display_name: plasma-facing-materials

surface-binding-energy

display_name: surface-binding-energy


en: We determine the complete atomic-level structure of the amorphous form of the drug atuliflapon, a 5-lipooxygenase activating protein (FLAP) inhibitor, via chemical-shift-driven NMR crystallography. The ensemble of preferred structures allows us to identify a number of specific conformations and interactions that stabilize the amorphous structure. These include preferred hydrogen-bonding motifs with water and with other drug molecules, as well as conformations of the cyclohexane and pyrazole rings that stabilize structure by indirectly allowing for optimization of hydrogen bonding.

en: Atomic-level structure of the amorphous drug Atuliflapon via NMR crystallography

materialscloud

en: Materials Cloud

atuliflapon

display_name: atuliflapon

nmr-crystallography

display_name: nmr-crystallography

solid-state-nmr

display_name: solid-state-nmr


en: Predicting the ground state spin of transition metal complexes is a challenging task. Previous attempts have been focused on specific regions of chemical space, whereas a more general automated approach is required to process crystallographic structures for high-throughput quantum chemistry computations. In this work, we developed a method to predict ground state spins of transition metal complexes. We started by constructing a dataset which contains 2,063 first row transition metal complexes taken from experimental crystal structures and their computed ground state spins. This dataset showed large chemical diversity in terms of metals, metal oxidation states, coordination geometries, and ligands. Then, we analyzed the trends between structural and electronic features of the complexes and their ground state spins, and put forward an empirical spin state assignment model. We also used simple descriptors to build a statistical model with >95% predictive accuracy across the board. With this, we provide a practical and automated way to determine the ground state spin of transition metal complex from structure, enabling the high-throughput exploration of crystallographic repositories.

en: Automated prediction of ground state spin for transition metal complexes

envi

en: Environment

machine-learning

display_name: machine-learning

marvel

display_name: marvel

spin-state

display_name: spin-state

transition-metal

display_name: transition-metal

transition-metal-complex

display_name: transition-metal-complex


en: Identification of the hydrogen lattice location in crystals is key to understanding and controlling hydrogen-induced properties. Combining nuclear reaction analysis with the ion channeling technique, we experimentally determined the locations of H and D in epitaxial nanofilms of titanium hydrides. It was found that 11 at.% of H are located at the octahedral site with the remaining H atoms in the tetrahedral site. Density functional theory calculations revealed that the structures with the partial octahedral site occupation are stabilized by the Fermi level shift and Jahn-Teller effect induced by hydrogen. In contrast, D was found to solely occupy the tetrahedral site owing to the mass effect on the zero-point vibrational energy. These findings suggest that site occupation of hydrogen can be controlled by changing the isotope mixture ratio, which leads to promising manifestation of novel hydrogen-related phenomena.

en: Isotope-dependent site occupation of hydrogen in epitaxial titanium hydride nanofilms

dft

display_name: dft

hydrogen

display_name: hydrogen


en: Combining the excellent thermal and electrical properties of Cu with the high abrasion resistance and thermal stability of W, Cu-W nanoparticle-reinforced metal matrix composites and nano-multilayers (NMLs) are finding applications as brazing fillers and shielding material for plasma and radiation.  Due to the large lattice mismatch between fcc Cu and bcc W, these systems have complex interfaces that are beyond the scales suitable for ab initio methods, thus motivating the development of chemically accurate interatomic potentials. Here, a neural network potential (NNP) for Cu-W is developed within the Behler-Parrinello framework using a curated training dataset that captures metallurgically-relevant local atomic environments. The Cu-W NNP accurately predicts (i) the metallurgical properties (elasticity, stacking faults, dislocations, thermodynamic behavior) in elemental Cu and W, (ii) energies and structures of Cu-W intermetallics and solid solutions, and (iii) a range of fcc Cu/bcc W  interfaces, and exhibits physically-reasonable behavior for solid W/liquid Cu systems.  As will be demonstrated in forthcoming work, this near-ab initio-accurate NNP can be applied to understand complex phenomena involving interface-driven processes and properties in Cu-W composites.

en: Machine learning potential for the Cu-W system

copper-tungsten

display_name: copper-tungsten

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

nanomultilayer

display_name: nanomultilayer

neural-network-potentials

display_name: neural-network-potentials


en: We introduce an automated, flexible framework (aiida-hubbard) to self-consistently calculate Hubbard U and V parameters from first-principles. By leveraging density-functional perturbation theory, the computation of the Hubbard parameters is efficiently parallelized using multiple concurrent and inexpensive primitive cell calculations. Furthermore, the intersite V parameters are defined on-the-fly during the iterative procedure to account for atomic relaxations and diverse coordination environments. We devise a novel, code-agnostic data structure to store Hubbard related information together with the atomistic structure, to enhance the reproducibility of Hubbard-corrected calculations. We demonstrate the scalability and reliability of the framework by computing in high-throughput fashion the self-consistent onsite U and intersite V parameters for 115 Li-containing bulk solids with up to 32 atoms in the unit cell. Our analysis of the Hubbard parameters calculated reveals a significant correlation of the onsite U values on the oxidation state and coordination environment of the atom on which the Hubbard manifold is centered, while intersite V values exhibit a general decay with increasing interatomic distance. We find, e.g., that the numerical values of U for the 3d orbitals of Fe and Mn can vary up to 3 eV and 6 eV, respectively; their distribution is characterized by typical shifts of about 0.5 eV and 1.0 eV upon change in oxidation state, or local coordination environment. For the intersite V a narrower spread is found, with values ranging between 0.2 eV and 1.6 eV when considering transition metal and oxygen interactions. This framework paves the way for the exploration of redox materials chemistry and high-throughput screening of d and f compounds across diverse research areas, including the discovery and design of novel energy storage materials, as well as other technologically-relevant applications.

en: First-principles Hubbard parameters with automated and reproducible workflows

aiida

display_name: aiida

dftu

display_name: dftu

dftuv

display_name: dftuv

hubbard

display_name: hubbard

oxidation-state

display_name: oxidation-state


en: On-surface synthesis relies on carefully designed molecular precursors that are thermally activated to afford desired, covalently coupled architectures. In a recent publication, we studied the reactions of vinyl groups on poly-para-phenylene and provided a comprehensive description of all the reaction steps taking place on the Au(111) surface under ultrahigh vacuum conditions. We find that vinyl groups successfully cyclize with the phenylene rings in the ortho positions, forming a dimethyl-dihydroindenofluorene as the repeating unit, which can be further dehydrogenated to a dimethylene-dihydroindenofluorene structure. Interestingly, the obtained polymer can be transformed cleanly into thermodynamically stable polybenzo[k]tetraphene at higher temperature, involving a previously elusive pentagon-to-hexagon transformation via ring opening and rearrangement on a metal surface. Our insights into the reaction cascade unveil fundamental chemical processes involving vinyl groups on surfaces. Because the formation of specific products is highly temperature-dependent, this innovative approach offers a valuable tool for fabricating complex, low-dimensional nanostructures with high precision and yield. This record contains the data that support the scientific results in the publication.

en: On-surface cyclization of vinyl groups on poly-para-phenylene involving an unusual pentagon to hexagon transformation

cscs

display_name: cscs

on-surface-synthesis

display_name: on-surface-synthesis

spm

display_name: spm

vinyl-cyclization

display_name: vinyl-cyclization


en:
The dynamics of (few) electrons dissolved in an ionic fluid—as when a small amount of metal is added to a solution while upholding its electronic insulation—manifests interesting properties that can be ascribed to nontrivial topological features of particle transport (e.g., Thouless' pumps). In the adiabatic regime, the charge distribution and the dynamics of these dissolved electrons are uniquely determined by the nuclear configuration. Yet, their localization into effective potential wells and their diffusivity are dictated by how the self-interaction is modeled. In this article, we investigate the role of self-interaction in the description of localization and transport properties of dissolved electrons in non-stoichiometric molten salts. Although the account for the exact (Fock) exchange strongly localizes the dissolved electrons, decreasing their tunneling probability and diffusivity, we show that the dynamics of the ions and of the dissolved electrons are largely uncorrelated, irrespective of the degree to which the electron self-interaction is treated, and in accordance with topological arguments.
This record contains input and analysis scripts to reproduce the findings of this article.

en: Self-interaction and transport of solvated electrons in molten salts

ionic-transport

display_name: ionic-transport

marie-curie-fellowship

display_name: marie-curie-fellowship

max

display_name: max

molten-salts

display_name: molten-salts

topological-materials

display_name: topological-materials

transport

display_name: transport


en: Emerging two-dimensional (2D) materials bring unprecedented opportunities for electronic applications. The design of high-performance devices requires an accurate prediction of carrier mobility in 2D materials, which can be obtained using state-of-the-art ab initio calculations. However, various factors impact the computational accuracy, leading to contradictory estimations for the mobility. In this work, targeting accurate and efficient ab initio calculations, transport properties in III-V monolayers are reported using the Boltzmann transport equation, and the influences of pseudopotential, quadrupole correction, Berry connection, and spin-orbit coupling (SOC) on mobilities are systematically investigated. Our findings are as follows: (1) The inclusion of semi-core states in pseudopotentials is important to obtain accurate calculations. (2) The variations induced by dynamical quadrupole and Berry connection when treating long range fields can be respectively 40% and 10%. (3) The impact of SOC can reach up to 100% for materials with multi-peak bands. Importantly, although SOC notably modifies the electronic wavefunctions, it negligibly impacts the dynamical matrices and scattering potential variations. As a result, the combination of fully-relativistic electron calculation and scalar-relativistic phonon calculation can strike a good balance between accuracy and cost. This work compares computational methodologies, providing guidelines for accurate and efficient calculations of mobilities in 2D semiconductors.

en: Guidelines for accurate and efficient calculations of mobilities in two-dimensional semiconductors

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).

electron-phonon-coupling

display_name: electron-phonon-coupling