en: It is well known that interfaces in nanomaterials can act as ultra-fast short-circuit diffusion paths, as originating from local structural, chemical and/or electronic modifications at the interface. For example, the interface diffusivity of Cu in Cu/AlN nanomultilayers can be up to two orders of magnitude higher as compared to the bulk, which may promote interfacial premelting of Cu. Extensive ab initio calculations of vacancy formation and migration energies in Cu/AlN nanomultilayers were performed to arrive at the fundamental understanding of such anomalously fast interface diffusion phenomena. It was found that both the metallic Al-terminated interface and the mixed-bonded N-terminated interface promote high atomic interface mobilities by lowering the vacancy formation and vacancy migration energies in the interfacial Cu planes. Moreover, the out-of-plane vacancy migration energies highlights a strong tendency of vacancy segregation toward both interfaces.

en: Anomalously low vacancy formation energies and migration barriers at Cu/AlN interfaces from ab initio calculations

ab-initio

display_name: ab-initio

metal-ceramic-interfaces

display_name: metal-ceramic-interfaces

nanomultilayers

display_name: nanomultilayers

vacancy-driven-diffusion

display_name: vacancy-driven-diffusion


$oid: OBSOLETE

en: Polyelectrolyte complexes (PECs), formed via the self-assembly of oppositely charged polysaccharides, are highly valued for their biocompatibility, biodegradability, and hydrophilicity, offering significant potential for biotechnological applications. However, the complex nature and lack of insight at a molecular level into polyelectrolytes conformation and aggregation often hinders the possibility of achieving an optimal control of PEC systems, limiting their practical applications. To address this problem, an in-depth investigation of PECs microscopic structural organization is required. In this work, for the first time, a hybrid approach that combines experimental techniques with atomistic molecular dynamics simulations is used to elucidate, at a molecular level, the mechanisms underlying the aggregation and structural organization of complexes formed by gellan and chitosan, i.e. PECs commonly used in food technology. This combined analysis reveals a two-step complexation process: gellan initially self-assembles into a double-helix structure, subsequently surrounded and stabilized by chitosan via electrostatic interactions. Furthermore, these results show that complexation preserves the individual conformation and intrinsic functionality of both polyelectrolytes, thereby ensuring the efficacy of the PECs in biotechnological applications.

en: Unveiling the self-assembly process of gellan-chitosan complexes through a combination of atomistic simulations and experiments

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

chitosan

display_name: chitosan

gellan

display_name: gellan

gels

display_name: gels

polyelectrolyte-complexes

display_name: polyelectrolyte-complexes

polysaccharides

display_name: polysaccharides


en: Raman spectra play an important role in characterizing two-dimensional materials, as they provide a direct link between the atomic structure and the spectral features. In this work, we present an  automatic computational workflow for Raman spectra using all-electron density functional perturbation theory. Utilizing this workflow, we have successfully completed the Raman spectra calculation for 3504 different two-dimensional materials, with the resultant data saved in a data repository.

en: High-throughput computation of ab initio Raman spectra for two-dimensional materials

fhi-aims

display_name: fhi-aims

raman-spectra

display_name: raman-spectra

two-dimensional-material

display_name: two-dimensional-material


en: In industrial metal forming processes, the generation of datasets for inline and optical quality assessment is expensive and time-consuming. Within the research project SimKI, conventional metal forming plants were digitalized under use of perception-based sensors in combination with a completely redesigned forming tool. The integration of optical quality observation methods connected with a retrofitting approach of the press tool provides the opportunity to generate an information-feedback loop that predicts part defects prior to their occurrence. The SimKI-method additionally combines conventional statistical measurement methods with AI-based defect detection algorithms that are trained by a) generic datasets of a finite-element simulation, b) real component images of a 3D imaging device, and c) a combination of both. The generated datasets are used to accelerate the training of a DNN-based algorithm in order to identify the position and deviation from the agreed quality. The high degree of innovation is based on obtaining real-time component quality information under use of AI-based optical quality assessment, which in turn provides information to the control algorithm of the smart forming tool.

en: Recursive quality optimization of a smart forming tool under use of perception based hybrid datasets for training of a deep neural network

artificial-intelligence

display_name: artificial-intelligence

defect-detection

display_name: defect-detection

gocator

display_name: gocator


en:
We show that, contrary to popular assumptions, predictions from machine learning potentials built upon high-dimensional atom-density representations almost exclusively occur in regions of the representation space which lie outside the convex hull defined by the training set points. We then propose a perspective to rationalise the domain of robust extrapolation and accurate prediction of atomistic machine learning potentials in terms of the probability density induced by training points in the representation space.
The data here contained can be used to reproduce all results and graphs shown in the article. We also include the trajectory files for the Au13 dataset we generate by running molecular dynamics simulations of an Au nanoparticle containing 13 atoms at temperatures of 50K, 100K, 200K, 300K, and 400K. Details regarding the generation of such dataset can be found in the supplementary information file for the article.

en: On the robust extrapolation of high-dimensional machine learning potentials

density-functional-theory

display_name: density-functional-theory

machine-learning

display_name: machine-learning

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Using density functional theory calculations with spin-orbit coupling (SOC), we report on the temperature-dependent thermodynamical properties of Pb: electrical resistivity, thermal expansion (TE), heat capacity, bulk modulus and its pressure derivative. For the former, we employed the state-of-the-art ab initio Boltzmann Transport Equation formalism, and we calculated the effect of TE. In accordance with previous work, we show that SOC improves the description of the phonon dispersion and the resistivity. We argue that this is caused by a joint mutual effect of an increase in the electronic nesting and an increase in the electron-phonon coupling. Interestingly, including TE incorporates non-linearity into the resistivity at high temperatures, whose magnitude depends on whether SOC is included or not. We suggest that mechanisms beyond the quasi-harmonic approximation should be considered to get a better description of Pb with SOC at high temperatures.

en: Effects of spin-orbit coupling and thermal expansion on the phonon-limited resistivity of Pb from first principles

ab-initio

display_name: ab-initio

electron-phonon-coupling

display_name: electron-phonon-coupling

electronic-structure

display_name: electronic-structure

first-principles

display_name: first-principles

phonons

display_name: phonons

quantum-espresso

display_name: quantum-espresso

transport

display_name: transport


en: The understanding of dynamic process of epitaxial microstructure forming in laser additive manufacturing is of vital importance for achieving products with single crystalline texture. Here, we perform in-situ, real-time synchrotron Laue diffraction experiments to capture the microstructural evolution of nickel-based single-crystal superalloys during rapid laser remelting process. In-situ synchrotron radiation Laue diffraction characterizes the crystal rotation behavior and stray grains formation process. With complementary thermo-mechanical coupled finite element simulation and molecular dynamics simulation, we identify that the crystal rotation is governed by the localized heating/cooling heterogeneity induced deformation gradient, and that the subgrains rotation caused by rapid dislocation movement and complex stress field could be the major mechanism in the generation of granular stray grains at the bottom of the melt pool.

en: Dynamic crystal rocking of nickel-based single crystal superalloy during the epitaxial growth of the additive manufacturing process

in-situ-laue-diffraction

display_name: in-situ-laue-diffraction

laser-remelting

display_name: laser-remelting

microstructural-evolution

display_name: microstructural-evolution

nickel-based-superalloy

display_name: nickel-based-superalloy


en:
We present an orbital-resolved extension of the Hubbard U correction to density-functional theory (DFT). Compared to the conventional shell-averaged approach, the prediction of energetic, electronic and structural properties is strongly improved, particularly for compounds characterized by both localized and hybridized states in the Hubbard manifold. The numerical values of all Hubbard parameters are readily obtained from linear-response calculations. The relevance of this more refined approach is showcased by its application to bulk solids pyrite (FeS₂) and pyrolusite (β-MnO₂), as well as to six Fe(II) molecular complexes. Our findings indicate that a careful definition of Hubbard manifolds is indispensable for extending the applicability of DFT+U beyond its current boundaries. The present orbital-resolved scheme aims to provide a computationally undemanding yet accurate tool for electronic structure calculations of charge-transfer insulators, transition-metal (TM) complexes and other compounds displaying significant orbital hybridization.
This dataset contains all Quantum ESPRESSO input and output files as well as all pseudopotentials that were used to generate the results of this study. Moreover, an ``EXAMPLES'' folder provides guidance on how to apply the LR-cDFT approach to evaluate orbital-resolved DFT+U parameters in practise.

en: Orbital-resolved DFT+U for molecules and solids

cdft

display_name: cdft

constrained-dft

display_name: constrained-dft

dft

display_name: dft

dftu

display_name: dftu

dftuv

display_name: dftuv

hubbard

display_name: hubbard

linear-response

display_name: linear-response

lr-cdft

display_name: lr-cdft

marvel

display_name: marvel

orbital-resolved

display_name: orbital-resolved


en: A theory for strengthening for multicomponent non-dilute alloys possessing short-range order (SRO) has recently been developed. The theory predicts that, in addition to a well-known athermal strengthening, there is a notable effect of SRO on the solute–dislocation interactions that can decrease or increase the strength relative to a random alloy. Here, carefully designed atomistic simulations in a model binary NbW alloy are used to demonstrate that alloy strength due to solute–dislocation interactions can be increased or decreased, depending on the SRO and consistent with theoretical predictions. Specifically, SRO is introduced using fictitious solute– solute interactions in an alloy system with very small true solute–solute interactions, and the Nudged Elastic Band (NEB) method is then used to compute the energy barriers for edge dislocation motion for various levels of SRO. Energy barriers, and hence alloy strengths, can be decreased when the Warren-Cowley SRO parameters are negative (attraction of unlike solutes). The theoretical predictions for the same system are in reasonable quantitative agreement with the simulation results. These findings demonstrate the unexpected possibility of reduced strength due to SRO and also further validate the analytical theory as a tool to guide alloy design.

en: Atomistic simulations reveal strength reductions due to short-range order in alloys

alloys

display_name: alloys

short-range-order

display_name: short-range-order

simulation

display_name: simulation

theory

display_name: theory

yield-strength

display_name: yield-strength


en: Koopmans spectral functionals are a class of orbital-density-dependent functionals designed to accurately predict spectroscopic properties. They do so markedly better than their Kohn-Sham density-functional theory counterparts, as demonstrated in earlier works on benchmarks of molecules and bulk systems. This work is a complementary study where --- instead of comparing against real, many-electron systems --- we test Koopmans spectral functionals on Hooke's atom, a toy two-electron system that has analytical solutions for particular strengths of its harmonic confining potential. As these calculations clearly illustrate, Koopmans spectral functionals do an excellent job of describing Hooke's atom across a range of confining potential strengths. This work also provides broader insight into the features and capabilities of Koopmans spectral functionals more generally.

en: Testing Koopmans spectral functionals on the analytically-solvable Hooke's atom

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).

electronic-structure

display_name: electronic-structure

hookes-atom

display_name: hookes-atom

koopmans-spectral-functionals

display_name: koopmans-spectral-functionals

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals


en:
With increasing interest in Majorana physics for possible quantum bit applications, a large interest has been developed to understand the properties of the interface between a s-type superconductor and a topological insulator. Up to this point the interface analysis was mainly focused on in-situ prepared Josephson junctions, which consist of two coupled single interfaces or to ex-situ fabricated single interface devices. In our work we utilize a novel fabrication process, combining selective area growth and shadow evaporation which allows the characterization of a single in-situ fabricated Nb/(Bi0.15Sb0.85)2Te3 nano interface. The resulting high interface transparency, is apparent by a zero bias conductance increase by a factor of 1.7. Furthermore, we present a comprehensive differential conductance analysis of our single in-situ interface for various magnetic fields, temperatures and gate voltages. Additionally, density functional theory calculations of the superconductor/topological insulator interface are performed in order to explain the peak-like shape of our differential conductance spectra and the origin of the observed smearing of conductance features.

This dataset contains the DFT and experimental raw data discussed in the associated publication.

en: Characterization of single in situ prepared interfaces composed of niobium and a selectively-grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

materialscloud

en: Materials Cloud

envi

en: Environment

density-functional-theory

display_name: density-functional-theory

experiment

display_name: experiment

majorana

display_name: majorana

superconductivity

display_name: superconductivity

topological-materials

display_name: topological-materials

topological-superconductor

display_name: topological-superconductor

transport

display_name: transport


en: Co-based catalysts are promising candidates to replace the Ir/Ru-based oxides for the oxygen evolution reaction (OER) in an acidic environment. However, both the reaction mechanism and the active species in an acidic environment remain unclear. In this study, by combining surface-sensitive soft X-ray adsorption spectroscopy (sXAS) characterization with electrochemical analysis, we unveil the truly active Co species for acidic OER. Surfaces composed of only high-spin CoII are found to be not active due to their unfavorable deprotonation to form CoIII-OH species. In contrast, we show that the presence of low-spin CoIII is essential to promote surface reconstruction and catalysis of OER. The correlation between OER activity and Co oxidation/spin state represents a breakthrough in the structure-activity relationship of Co-based catalysts for acidic OER, which interestingly does not hold in the alkaline and neutral environments. These findings not only help to design efficient acidic OER catalysts, but also deepen the understanding of the reaction mechanism.

en: Unveiling the pH-dependent structure-activity relationship of Co-based catalysts toward oxygen evolution reaction

acidic-oxygen-evolution

display_name: acidic-oxygen-evolution

co-oxidation-state

display_name: co-oxidation-state

cobalt-based-catalyst

display_name: cobalt-based-catalyst

spin-state

display_name: spin-state

structure-activity-relationship

display_name: structure-activity-relationship


en: The AV₃Sb₅ kagome superconductors series are of intense interest due to their diverse and intricate properties. The breaking of time-reversal symmetry (TRS) in the normal state of these superconductors stands as a significant feature, yet the extent to which this effect can be tuned remains uncertain. Here, we employ a unique low-energy muon spin rotation technique combined with local field numerical analysis to study the TRS breaking response as a function of depth from the surface in single crystals of RbV₃Sb₅ with charge order and Cs(V0.86Ta0.14)₃Sb₅ without charge order. In the bulk (specifically above 30 nm from the sur face) of RbV₃Sb₅, we have detected a notable increase in the internal field width experienced by the muon ensemble. This increase occurs within the charge ordered state. Intriguingly, the muon spin relaxation rate is significantly enhanced near the surface of RbV₃Sb₅ (specifically within a depth range of 30-40 nm from the surface), and this effect commences at temperatures significantly higher than the onset of charge order. Conversely, in Cs(V0.86Ta0.14)₃Sb₅, which lacks charge order, we do not observe a similar enhancement in the internal field width, neither in the bulk nor at the surface. These observations indicate a strong connection between charge order and TRS breaking on one hand, and on the other hand, suggest that TRS breaking can be manipulated to occur prior to long-range charge order. This research offers compelling evidence for depth-dependent magnetism in AV₃Sb₅ superconductors in the presence of charge order. Such findings are likely to illuminate the intricate microscopic mechanisms that underpin the TRS breaking phenomena in these materials.

en: Depth-dependent time reversal symmetry breaking response in the charge-ordered kagome material RbV₃Sb₅

dft

display_name: dft

kagome-metal

display_name: kagome-metal

muon-spin-spectroscopy

display_name: muon-spin-spectroscopy


en: We perform extensive molecular dynamics simulations of an ensemble of realistic microgel particles in swollen conditions in a wide range of packing fractions ζ. We compare neutral and charged microgels, where we consider charge distribution adherent to experimental conditions. Through a detailed analysis of singleparticle behavior, we are able to identify the different regimes occurring upon increasing concentration: from shrinking to deformation and interpenetration, always connecting our findings with available experimental observations. We then link these single-particle features with the collective behavior of the suspension, finding evidence of a structural reentrance that has no counterpart in the dynamics. Hence, while the maximum of the radial distribution function displays a nonmonotonic behavior with increasing ζ, the dynamics, quantified by the microgels' mean-squared displacement, always slows down. This behavior, at odds with the simple Hertzian model, can be described by a phenomenological multi-Hertzian model, which takes into account the enhanced internal stiffness of the core. However, also this model fails when deformation enters into play, whereby more realistic many-body models are required. Thanks to our analysis, we are able to unveil the key physical mechanisms, shrinking and deformation, giving rise to the structural reentrance that holds up to very large packing fractions. We further identify key similarities and differences between neutral and charged microgels, for which we detect at high enough ζ the fusion of charged shells, previously invoked to explain key experimental findings, and responsible for the structural reentrance. Overall, our study establishes a powerful framework to uncover the physics of microgel suspensions, paving the way to tackle different regimes, e.g., high temperature, and internal architectures, such as for hollow and ultralow-cross-linked microgels, where experimental evidence is still limited.

en: Numerical study of neutral and charged microgel suspensions: from single-particle to collective behavior

collective-behavior

display_name: collective-behavior

elasticity

display_name: elasticity

microgels

display_name: microgels


en: Simulations of condensed matter systems at the hybrid density functional theory (DFT) level  pose significant computational challenges. The elevated costs arise from the non-local nature of the Hartree-Fock exchange (HFX) in conjunction with the necessity to approach the thermodynamic limit (TDL). In this work, we address these issues with the development of a new efficient method for the calculation of HFX in periodic systems, employing k-point sampling. We rely on a local atom-specific resolution-of-the-identity scheme, the use of atom-centered Gaussian type orbitals (GTOs), and the truncation of the Coulomb interaction to limit computational complexity. Our real-space approach exhibits a scaling that is  at worst linear with the number of k-points.  Issues related to basis set diffuseness are effectively addressed through the auxiliary density matrix method (ADMM). We report the implementation in the CP2K software package, as well as accuracy and performance benchmarks. The method demonstrates excellent agreement with equivalent Gamma-point supercell calculations in terms of relative energies and nuclear gradients. Good strong and weak scaling performances, as well as GPU acceleration, make this implementation a promising candidate for high-performance computing.

en: Efficient periodic resolution-of-the-identity Hartree-Fock exchange method with k-point sampling and Gaussian basis sets

auxiliary-density-matrix-method

display_name: auxiliary-density-matrix-method

high-performance-computing

display_name: high-performance-computing

hybrid-dft

display_name: hybrid-dft

k-point-sampling

display_name: k-point-sampling

method-development

display_name: method-development

periodic-hartree-fock

display_name: periodic-hartree-fock


en: Prismatic slip of the screw  dislocation in magnesium at temperatures ≳ 150 K is understood to be governed by double-cross-slip of the stable basal screw through the unstable prism screw and back to the basal screw, with the activation energy controlled by the formation energy of two basal-basal kinks. However, atomistic studies of the double-kink process predict activation energies roughly twice those derived experimentally. Here, a new mechanism of prism glide is proposed, analyzed theoretically, and demonstrated qualitatively and quantitatively via direct molecular dynamics (MD) simulations. The new mechanism is intrinsically 3d, and involves the nucleation of a single kink at the junction where a 3d prismatic dislocation loop transitions from the basal screw segment to non-screw prismatic character. The relevant kink energies are calculated using recently-developed Neural-Network Potentials (NNPs) for Mg that show good agreement versus DFT for basal and prism  dislocations, enabling a parameter-free analytic model for the activation barrier. Direct MD simulations show both operation of the precise proposed mechanism and a stress-dependent activation barrier that agrees reasonably with the analytic model. Predictions of dislocation velocity compare very well with in-situ TEM data, and macroscopic strength versus temperature can also be understood. Overall, the new intrinsically 3d mechanism for dislocation glide due to single kink nucleation rather than double-kink nucleation explains key features of the prismatic slip in Mg and may have broader applicability in other metals where kink nucleation processes control thermally-activated flow.

en: Mechanism of thermally-activated prismatic slip in Mg

magnesium

display_name: magnesium

marvel

display_name: marvel

neural-network-potential

display_name: neural-network-potential

prismatic-slip

display_name: prismatic-slip


en: The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation of experimentally observable material properties such as optical absorption and electrical conductivity. We discuss the challenges inherent in the construction of a machine-learning (ML) framework aimed at predicting the DOS as a combination of local contributions that depend in turn on the geometric configuration of neighbors around each atom, using quasiparticle energy levels from density functional theory as training data. We present a challenging case study that includes configurations of silicon spanning a broad set of thermodynamic conditions, ranging from bulk structures to clusters and from semiconducting to metallic behavior. We compare different approaches to represent the DOS, and the accuracy of predicting quantities such as the Fermi level, the electron density at the Fermi level, or the band energy, either directly or as a side product of the evaluation of the DOS. We find that the performance of the model depends crucially on the resolution chosen to smooth the DOS and that there is a tradeoff to be made between the systematic error associated with the smoothing and the error in the ML model for a specific structure. We find however that the errors are not strongly correlated among similar structures, and so the average DOS over an ensemble of configurations is in very good agreement with the reference electronic structure calculations, despite the large nominal error on individual configurations. We demonstrate the usefulness of this approach by computing the density of states of a large amorphous silicon sample, for which it would be prohibitively expensive to compute the DOS by direct electronic structure calculations and show how the atom-centered decomposition of the DOS that is obtained through our model can be used to extract physical insights into the connections between structural and electronic features.

en: Learning the electronic density of states in condensed matter

cosmo-epfl

display_name: cosmo-epfl

snsf

display_name: snsf


en: Prismatic slip in magnesium at temperatures T ≲ 150 K occurs at ∼ 100 MPa independent of temperature, and jerky flow due to large prismatic dislocation glide distances is observed; this athermal regime is not understood. In contrast, the behavior at T ≳ 150 K is understood to be governed by a thermally-activated double-cross-slip of the stable basal screw dislocation through an unstable or weakly metastable prism screw configuration and back to the basal screw. Here, a range of neural network potentials (NNPs) that are very similar for many properties of Mg including the basal-prism-basal cross-slip path and pro- cess, are shown to have an instability in prism slip at a potential-dependent critical stress. One NNP, NNP-77, has a critical instability stress in good agreement with experiments and also has basal-prism-basal transition path energies in very good agreement with DFT results, making it an excellent potential for understanding Mg prism slip. Full 3d simulations of the expansion of a prismatic loop using NNP-77 then also show a transition from cross-slip onto the basal plane at low stresses to prismatic loop expansion with no cross- slip at higher stresses, consistent with in-situ TEM observations. These results reveal (i) the origin and prediction of the observed unstable low-T prismatic slip in Mg and (ii) the critical use of machine-learning potentials to guide discovery and understanding of new important metallurgical behavior.

en: A low-temperature prismatic slip instability in Mg understood using machine learning potentials

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).

minimum-energy-path

display_name: minimum-energy-path


en: We present an approach for the calculation of the Z2 topological invariant in non-crystalline two-dimensional quantum spin Hall insulators. While topological invariants were originally mathematically introduced for crystalline periodic systems, and crucially hinge on tracking the evolution of occupied states through the Brillouin zone, the introduction of disorder or dynamical effects can break the translational symmetry and imply the use of larger simulation cells, where the k-point sampling is typically reduced to the single Γ-point. Here, we introduce a single-point formula for the spin Chern number that enables to adopt the supercell framework, where a single Hamiltonian diagonalisation is performed. Our single-point approach allows to calculate the spin Chern number even when the spin operator does not commute with the Hamiltonian, as in the presence of Rashba spin-orbit coupling. This archive entry contains the results of the single-point calculations of the topological invariant on the tight-binding Kane-Mele model for large supercells (up to 7200 sites). Convergence tests as function of the supercell size are reported, both in the pristine case and in presence of Anderson disorder. Single-point calculations of the spin Chern number are carried out over the entire phase diagram of the Kane-Mele model. The study of topological phase transitions due to disorder is performed in terms of single-point spin Chern number by averaging over several realisations of the Anderson disorder in the supercell.

en: Single-point spin Chern number in a supercell framework

materialscloud

en: Materials Cloud

anderson-disorder

display_name: anderson-disorder

kane-mele-model

display_name: kane-mele-model

spin-chern-number

display_name: spin-chern-number

supercell-framework

display_name: supercell-framework

topological-insulators

display_name: topological-insulators


en: Cobalt-based oxides are active electrocatalysts for the oxygen evolution reaction (OER) in alkaline electrolytes. However, their OER activity at near-neutral pHs is generally low and more active OER catalysts at neutral pHs are desired for practical applications. Herein, La0.2Sr0.8CoO3–δ, La0.2Sr0.8Co0.8Fe0.2O3–δ, La0.5Sr1.5CoO4–δ and CoOx catalysts were prepared by the flame spray synthesis method and their surface was functionalized by a dry phosphate incorporation process. Small amount of P was incorporated on the surface of the catalyst (in the range of ppm). All the samples were characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and soft and hard X-ray absorption spectroscopy (XAS) before and after the functionalization process. The electrocatalytic activity towards OER of the different nanoparticle catalysts was investigated in electrolytes with different pH values (pH = 7, 12.5, 13, and 13.5).

en: The role of phosphate functionalization on the oxygen evolution reaction activity of cobalt-based oxides at different pH values

envi

en: Environment

alkaline-water-electrolysis

display_name: alkaline-water-electrolysis

experimental

display_name: experimental

neutral-ph

display_name: neutral-ph

phosphate-ion-functionalization

display_name: phosphate-ion-functionalization


en: We present a potential explanation for the strain-induced metal-insulator transition that has recently been observed in thin films of SrCrO₃ using density-functional theory (DFT) and its extension to DFT+U. Our calculations show that the unstrained system exhibits a C-type antiferromagnetically ordered ground state, which is near to a Jahn-Teller instability, given realistic values of the Hubbard U parameter. However, the significant energy overlap between the higher-lying dxy band and the dxz/dyz band works against the JT distortion's. When epitaxially strained, this overlap is reduced by the lowering of the dxyband relative to dxz/dyz as the system gets closer to the nominal integer filling. The degeneracy between the dxz and dyz orbitals is subsequently lifted by the JT distortion, opening a gap in the electronic band structure.

en: Evidence for Jahn-Teller-driven metal-insulator transition in strained SrCrO₃ from first principles calculations

dftu

display_name: dftu

jahn-teller-effect

display_name: jahn-teller-effect

orbital-order

display_name: orbital-order


en: The crystal structure of a material is essentially determined by the nature of its chemical bonding. Consequently, the atomic coordination intimately correlates with the degree of ionicity or covalency of the material. Based on this principle, materials with similar chemical compositions can be successfully categorized into different coordination groups. However, counterexamples recently emerged in complex ternary compounds. For instance, strongly covalent IB-IIIA-VIA₂ compounds, such as AgInS₂, prefer tetrahedrally coordinated structure (TCS), while strongly ionic IA-VA-VIA₂ compounds, such as NaBiS₂, would favor octahedrally coordinated structure (OCS). One naturally expects that IB-VA-VIA₂ compounds with intermediate ionicity or covalency, such as AgBiS₂, should then have a mix-coordinated structure (MCS) consisting of covalent AgS₄ tetrahedra and ionic BiS₆ octahedra. Surprisingly, only OCS was observed experimentally for AgBiS₂. To resolve this puzzle, we perform first-principles studies of the phase stabilities of ternary compounds at finite temperatures. We find that AgBiS₂ indeed prefers MCS at the ground state, in agreement with the typical expectation, but under experimental synthesis conditions disordered OCS becomes energetically more favorable because of its low mixing energy and high configurational entropy. This dataset includes structural information for the MCS and OCS configurations of ABX₂ compounds, along with the principal input data used for each calculation.

en: Dataset of disorder-stabilized unfavorable coordination in complex ABX₂ compounds

first-principles

display_name: first-principles

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

vasp

display_name: vasp


en: Since the preliminary work of Anisimov and co-workers, the Hubbard corrected DFT+U functional has been used for predicting properties of correlated materials by applying on-site effective Coulomb interactions to specific orbitals. However, the determination of the Hubbard U parameter has remained under intense discussion despite the multitude of approaches proposed. Here, we define a selection criterion based on the use of polaronic defect states for the enforcement of the piecewise linearity of the total energy upon electron occupation. A good agreement with results from piecewise-linear hybrid functionals is found for the electronic and structural properties of polarons, including the formation energies. The values of U determined in this way are found to give a robust description of the polaron energetics upon variation of the considered state. In particular, we also address a polaron hopping pathway, finding that the determined value of U leads to accurate energetics without requiring a configurational-dependent U. It is emphasized that the selection of U should be based on physical properties directly associated with the orbitals to which U is applied, rather than on more global properties such as band gaps and band widths.  For comparison, we also determine U through a well-established linear-response scheme finding noticeably different values of U and consequently different formation energies. Possible origins of these discrepancies are discussed. As case studies, we consider the self-trapped electron in BiVO₄, the self-trapped hole in MgO, the Li-trapped hole in MgO, and the Al-trapped hole in 𝛼-SiO₂.

en: Hubbard U through polaronic defect states

density-functional-theory

display_name: density-functional-theory

hybrid-functionals

display_name: hybrid-functionals

polarons

display_name: polarons

self-interaction

display_name: self-interaction


en: We establish the sign of the linear magnetoelectric (ME) coefficient, α, in chromia, Cr₂O₃. Cr₂O₃ is the prototypical linear ME material, in which an electric (magnetic) field induces a linearly proportional magnetization (polarization), and a single magnetic domain can be selected by annealing in combined magnetic (H) and electric (E) fields. Opposite antiferromagnetic domains have opposite ME responses, and which antiferromagnetic domain corresponds to which sign of response has previously been unclear. We use density functional theory (DFT) to calculate the magnetic response of a single antiferromagnetic domain of Cr₂O₃ to an applied in-plane electric field at 0 K. We find that the domain with nearest neighbor magnetic moments oriented away from (towards) each other has a negative (positive) in-plane ME coefficient, α⊥, at 0 K. We show that this sign is consistent with all other DFT calculations in the literature that specified the domain orientation, independent of the choice of DFT code or functional, the method used to apply the field, and whether the direct (magnetic field) or inverse (electric field) ME response was calculated. Next, we reanalyze our previously published spherical neutron polarimetry data to determine the antiferromagnetic domain produced by annealing in combined E and H fields oriented along the crystallographic symmetry axis at room temperature. We find that the antiferromagnetic domain with nearest-neighbor magnetic moments oriented away from (towards) each other is produced by annealing in (anti-)parallel E and H fields, corresponding to a positive (negative) axial ME coefficient, α∥, at room temperature. Since α⊥ at 0 K and α∥ at room temperature are known to be of opposite sign, our computational and experimental results are consistent. This dataset contains the input data to reproduce the calculation of the magnetoelectric effect as plotted in Fig. 3 of the manuscript, for Elk, Vasp, and Quantum Espresso.

en: On the sign of the linear magnetoelectric coefficient in Cr₂O₃

dft

display_name: dft

horizon-europe

display_name: horizon-europe

magnetoelectric

display_name: magnetoelectric


en: Low-crosslinked polymer networks have recently been found to behave auxetically when subjected to small tensions, that is, their Poisson's ratio ν becomes negative. In addition, for specific state points, numerical simulations revealed that diamond-like networks reach the limit of mechanical stability, exhibiting values of ν = −1, a condition that we define as hyper-auxeticity. This behavior is interesting per se for its consequences in materials science but is also appealing for fundamental physics because the mechanical instability is accompanied by evidence of criticality. In this work, we deepen our understanding of this phenomenon by performing a large set of equilibrium and stress–strain simulations in combination with phenomenological elasticity theory. The two approaches are found to be in good agreement, confirming the above results. We also extend our investigations to disordered polymer networks and find that the hyper-auxetic behavior also holds in this case, still manifesting a similar critical-like behavior as in the diamond one. Finally, we highlight the role of the number density, which is found to be a relevant control parameter determining the elastic properties of the system. The validity of the results under disordered conditions paves the way for an experimental investigation of this phenomenon in real systems, such as hydrogels.

en: Auxetic polymer networks: The role of crosslinking, density, and disorder

auxetic-materials

display_name: auxetic-materials

elasticity

display_name: elasticity

hydrogels

display_name: hydrogels


en: Phenalenyl (C₁₃H₉) is an open-shell spin-1/2 nanographene. Using scanning tunneling microscopy (STM) inelastic electron tunneling spectroscopy (IETS), covalently-bonded phenalenyl dimers have been shown to feature conductance steps associated with singlet-triplet excitations of a spin-1/2 dimer with antiferromagnetic exchange. In a recent work, we address the possibility of tuning the magnitude of the exchange interactions by varying the dihedral angle between the two molecules within a dimer. Theoretical methods, ranging from density functional theory calculations to many-body model Hamiltonians solved within different levels of approximation, are used to explain STM-IETS measurements of twisted phenalenyl dimers on a h-BN/Rh(111) surface. By means of first-principles calculations, we also propose strategies to induce sizable twist angles in surface-adsorbed phenalenyl dimers via functional groups, including a photoswitchable scheme. This record contains data that support the results discussed in the manuscript.

en: Conformational tuning of magnetic interactions in coupled nanographenes

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).

dmrg

display_name: dmrg

magnetic-nanographenes

display_name: magnetic-nanographenes

snsf

display_name: snsf

stmsts

display_name: stmsts


en: Magnetostriction drives a rhombohedral distortion in the cubic rock salt antiferromagnet MnO at the Nèel temperature TN=118 K.  As an unexpected consequence we show that this distortion acts to localize the site of an implanted muon due to the accompanying redistribution of electron density. This lifts the degeneracy between equivalent sites, resulting in a single observed muon precession frequency.  Above TN, the muon instead becomes delocalized around a network of equivalent sites.  Our first-principles simulations based on Hubbard-corrected density-functional theory and molecular dynamics are consistent with our experimental data and help to resolve a long-standing puzzle regarding muon data on MnO, as well as having wider applicability to other magnetic oxides.

en: Magnetostriction-driven muon localisation in an antiferromagnetic oxide

materialscloud

en: Materials Cloud

dftuv

display_name: dftuv

experimental

display_name: experimental

marvel

display_name: marvel

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: Comprehending the structure and dynamics of water is crucial in various fields such as water desalination, ion separation, electrocatalysis, and biochemical processes. While reported works show that the ab-initio molecular dynamics (AIMD) can accu- rately portray water's structure, the artificial high temperature (AHT) from 120K to 30K is needed to mimic the quantum nature of hydrogen-bond network from GGA, metaGGA to hybrid functionals. The AHT proves to be an inadequate approach for systems involving aqueous multiphase mixtures, such as water-solid interfaces and aque- ous solutions. This is due to the activation of additional phonons in other phases, which can lead to an overestimation of the dynamics for nearby water molecules. In this work, we find the regularized SCAN (rSCAN) functional can well capture both the structure and dynamics of liquid water at ambient conditions without AHT. Moreover, rSCAN can well match the experimental results of hydration structures for alkali, alkali earth and halide ions. We anticipate that the versatile and accurate rSCAN functional will emerge as a key tool based on ab-initio simulation for investigating chemical processes in aqueous environments.

en: Ab-initio simulation of liquid water without artificial high temperature

envi

en: Environment

aimd

display_name: aimd

density-functional-theory

display_name: density-functional-theory

machine-learning-potential

display_name: machine-learning-potential

metagga

display_name: metagga

water

display_name: water


en:
Understanding the thermodynamics of adsorbates on surfaces is central to many (electro)catalysis applications. In first-principles calculations, additional challenges arise when considering charged adsorbates owing to long-range electrostatic interactions in the in-plane and normal directions. Here, we derive an analytical correction to obtain the energy profiles of individual charged adsorbates on metallic surfaces from finite-cell calculations in periodic boundary conditions. The method is illustrated by calculating the adsorption energy profiles of Li+, Na+, and K+ on graphite from first-principles, highlighting the very slow convergence with system size of the periodic calculations and the need to correctly recover the infinite limit.
In this record, we provide the generic input file used to generate the calculated energies of Fig. 4.

en: Charged adsorbates on metallic surfaces from periodic to open boundary conditions

charged-defects

display_name: charged-defects

dft

display_name: dft

electrochemistry

display_name: electrochemistry

surface--interface

display_name: surface--interface


en: Isostructural metal-organic frameworks (MOFs), namely MFU-4 and MFU-4-Br, in which the pore apertures are defined by anionic side ligands (Cl− and Br−, respectively), were synthesized and loaded with noble gases. By selecting the type of side ligand, one can fine-tune the pore aperture size, allowing for precise regulation of the entry and release of gas guests. In this study, we conducted experiments to examine gas loading and release using krypton and xenon as model gases, and we complemented our findings with computational modeling. Remarkably, the loaded gas guests remained trapped inside the pores even after being exposed to air under ambient conditions for extended periods, in some cases for up to several weeks. Therefore, we focused on determining the energy barrier preventing gas release using both theoretical and experimental methods. The results were compared in relation to the types of hosts and guests, providing valuable insights into the gas trapping process in MOFs, as well as programmed gas release in air under ambient conditions. Furthermore, the crystal structure of MFU-4-Br was elucidated using the three-dimensional electron diffraction (3DED) technique, and the bulk purity of the sample was subsequently verified through Rietveld refinement. The data in this record are supplementary data to the manuscript with DOI 10.26434/chemrxiv-2024-vb8pj.

en: Experimental and Theoretical Insights on Gas Trapping in MOFs: A Case Study with Noble Gases and MFU-4 Type MOFs

computational-modeling

display_name: computational-modeling

crystal-engineering

display_name: crystal-engineering

electron-diffraction

display_name: electron-diffraction

gas-storage

display_name: gas-storage

metal-organic-framework

display_name: metal-organic-framework


en: In this paper, we proposed a model coupling the lattice Boltzmann and the phase field methods with anisotropic effects is proposed, which is used to numerically describe the growth and movement of dendrites in rapid solidification of alloys. The model was applied to investigate the effects of dendrite movement and interfacial non-equilibrium on evolution of dendritic patterns for Si-9.0at%As and the CET for Al-3.0wt%Cu alloys. Both the growth and remelt processes of isolated dendrites are studied, and the result reveals the remelting influences on dendrite growth and solute micro-segregation in the condition of directional solidification. This dataset contains the underlying data for the above. This work demonstrates that the proposed model has a wide range of applicability and great potential to simulate the microstructure evolution with various solidification conditions.

en: An anisotropic lattice Boltzmann - phase field model for dendrite growth and movement in rapid solidification of binary alloys

dendrite-growth

display_name: dendrite-growth

lattice-boltzmann

display_name: lattice-boltzmann

phase-field

display_name: phase-field

rapid-solidification

display_name: rapid-solidification

solid-sedimentation

display_name: solid-sedimentation


en: Nitrate is a significant contaminant in Polar snow. Its photolysis in environmental sunlight generates reactive nitrogen, which impacts the oxidative capacity of the atmosphere, influencing the fate and lifetimes of pollutants. The photolysis of nitrate can produce either NO2 or NO2- , with recent experiments suggesting that the process is accelerated at the air-ice interface compared to the bulk solution. In this study, we employed multiscale modeling approaches to investigate the enhanced photoreactivity of nitrate at the ice surface in the presence of two different cations. We characterized the solvation shell of NO3- and explored its pairing with cations in water and ice using ab initio molecular dynamics and enhanced sampling. Molecular trajectories were used to calculate light absorption spectra at different solvation conditions and finite temperature. Our analysis revealed that the pairing of nitrate with cations may alter the molar absorption coefficient of nitrate at the air-ice interface affecting the rate of photolysis observed in experiments of ammonium nitrate deposited on snow.

en: Solvation Structure and UV-Visible Absorption Spectra of the Nitrate Anion at the Air-Ice Interface by First Principles Molecular Simulations

ice-surface

display_name: ice-surface

molecular-dynamics

display_name: molecular-dynamics

nitrate

display_name: nitrate

solvation

display_name: solvation

tddft

display_name: tddft

uv-vis-absorption

display_name: uv-vis-absorption


en: Twisted van der Waals heterostructures have recently emerged as a versatile platform for engineering interaction-driven, topological phenomena with a high degree of control and tunability. Since the initial discovery of correlated phases in twisted bilayer graphene, a wide range of moiré materials have emerged with fascinating electronic properties. While the field of twistronics has rapidly evolved and now includes a range of multi-layered systems, moiré systems comprised of double trilayer graphene remain elusive. Here, we report electrical transport measurements combined with tight-binding calculations in twisted double trilayer graphene (TDTLG). We demonstrate that small-angle TDTLG (~1.7−2.0ᵒ) exhibits an intrinsic bandgap at the charge neutrality point. Moreover, by tuning the displacement field, we observe a continuous insulator-semimetal-insulator transition at the CNP, which is also captured by tight-binding calculations. These results establish TDTLG systems as a highly tunable platform for further exploration of magneto-transport and optoelectronic properties.

en: Electric field tunable bandgap in twisted double trilayer graphene

experimental

display_name: experimental

marvel

display_name: marvel

tight-binding

display_name: tight-binding

twisted-multilayer-graphene

display_name: twisted-multilayer-graphene

wanniertools

display_name: wanniertools


en: The dataset uploaded here records atomic positions, lattices vectors and Python scripts for tight-binding calculations related to the paper entitled "Modulated Dirac bands and integer hopping ratios in a honeycomb lattice of phenalenyl-tessellation molecules." In a family of nanographene called phenalenyl-tessellation molecules (PTMs), two types of zero modes appear: one is uniformly extended over the entire molecule and the other is localized around vacancies. Therefore, it is expected that energy bands reflecting the properties of these two types of zero modes will appear in a honeycomb PTM (H-PTM). In this study, we show that modulated energy gap and the Fermi velocity of Dirac bands appear in H-PTMs and that the effective two-site model has positive integer hopping ratios based on the uniformly extended zero mode and  the number of connections between PTMs. Furthermore, we find that the localized zero modes around vacancies can coexist with the modulated Dirac bands. The tight-binding calculations confirm that modulated Dirac bands with integer hopping ratios and coexisting localized zero modes that are consistent with analytical solutions for H-PTMs.

en: Tight-binding calculation files of modulated Dirac bands and integer hopping ratios in a honeycomb lattice of phenalenyl-tessellation molecules

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).

band-gap

display_name: band-gap

flat-bands

display_name: flat-bands

graphene

display_name: graphene

honeycomb-lattice

display_name: honeycomb-lattice

tight-binding-model

display_name: tight-binding-model


en:
Quantifying the uncertainty of regression models is essential to ensure their reliability, particularly since their application often extends beyond their training domain. Based on the solution of a constrained optimization problem, this work proposes 'prediction rigidities' as a formalism to obtain uncertainties of arbitrary pre-trained regressors. A clear connection between the suggested framework and Bayesian inference is established, and a last-layer approximation is developed and rigorously justified to enable the application of the method to neural networks. This extension affords cheap uncertainties without any modification to the neural network itself or its training procedure. The effectiveness of this approach is shown for a wide range of regression tasks, ranging from simple toy models to applications in chemistry and meteorology.
This record includes computational experiments supporting the MLST paper titled "A prediction rigidity formalism for low-cost uncertainties in trained neural networks".

materialscloud

en: Materials Cloud

confidence-interval

display_name: confidence-interval

laplace-approximation

display_name: laplace-approximation

machine-learning

display_name: machine-learning

neural-networks

display_name: neural-networks

neural-tangent-kernel

display_name: neural-tangent-kernel

prediction-rigidity

display_name: prediction-rigidity

regressors

display_name: regressors

uncertainty-quantification

display_name: uncertainty-quantification


en: An atomic-level understanding of radiation-induced damage in simple polymers like polyethylene is essential for determining how these chemical changes can alter the physical and mechanical properties of important technological materials such as plastics. We performed ensembles of quantum simulations of radiation damage in a polyethylene analog using the Density Functional Tight Binding method to help bind its radiolysis and subsequent degradation as a function of radiation dose. Chemical degradation products are categorized with a graph theory approach, and we compute occurrence rates of unsaturated carbon bond formation, crosslinking, cycle formation, chain scission reactions, and out-gassing products. Statistical correlations between product pairs show significant correlations between chain scission reactions, unsaturated carbon bond formation, and out-gassing products, though these correlations decrease with increasing atom recoil energy. Our results present relatively simple chemical descriptors as possible indications of network rearrangements in the middle range of excitation energies. The data set contains how DFTB+ simulations were setup and running isomorphic analysis and graphs to obtain chemical structures.

en: Quantum simulations of radiation damage in a molecular polyethylene analog

dftb

display_name: dftb

graph-theory

display_name: graph-theory

isomorphic-analysis

display_name: isomorphic-analysis

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation


en: The dataset contains records of Charpy V-notch impact tests of nuclear structural materials. The focus is on studying the influence of specimen dimensions and geometry on Charpy impact test properties. The dataset was created through an extensive literature review of scientific articles. The extracted data points from the literature review are organized into a tabular format database containing 4,961 test records with 55 parameters, including material type and composition, manufacturing information, irradiation conditions, specimen size and dimensions, and Charpy properties. Materials science experts conducted systematic validation checks to ensure the accuracy of the information related to material type, manufacturing processes, treatment methods, chemical composition, testing conditions, as well as other pertinent information.

en: Dataset of Charpy V-notch impact test records of nuclear structural materials

envi

en: Environment

charpy-v-notch-impact-test

display_name: charpy-v-notch-impact-test

miniature-specimens

display_name: miniature-specimens

nuclear-structural-materials

display_name: nuclear-structural-materials

reactor-pressure-vessel-steels

display_name: reactor-pressure-vessel-steels

specimen-size-effect

display_name: specimen-size-effect

sub-sized-specimens

display_name: sub-sized-specimens


en: We employ ab-initio electronic-structure calculations to investigate the charge-density waves and periodic lattice distortions in bilayer 2H-NbSe₂. We demonstrate that the vertical stacking can give rise to a variety of patterns that may lower the symmetry of the charge-density waves exhibited separately by the two composing 1H-NbSe₂ monolayers. The general tendency to a spontaneous symmetry breaking observed in the ground state and the first excited states is shown to originate from a non-negligible interlayer coupling. Simulated images for scanning tunneling microscopy as well as geometric structure factors show signatures of the different stacking orders. This may not only be useful to reinterpret past experiments on surfaces and thin films, but it may also be exploited to devise ad hoc experiments for the investigation of the stacking order in 2H-NbSe₂. We anticipate that our analysis not only applies to the 2H-NbSe₂, but is also relevant for thin films and bulk, whose smallest centrosymmetric component is indeed the bilayer. Finally, our results illustrate clearly that the vertical stacking is not only important for 1T structures, as exemplified by the metal-to-insulator transition observed in 1T-TaS₂, but seems to be a general feature of metallic layered transition metal dichalcogenides as well. The dataset includes the fully relaxed atomic positions of the most favorable charge-density waves, as well as the main output files of the electronic structure calculations. Selected files for the charge densities are also included.

en: Stacking of charge-density waves in 2H-NbSe₂ bilayers

charge-density-waves

display_name: charge-density-waves

dft

display_name: dft

marie-curie-fellowship

display_name: marie-curie-fellowship

stacking-order

display_name: stacking-order

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides


en:
Passivation oxide formation is the key for corrosion control of metal alloys.  The kinetics of competing oxide formation and dissolution determines alloy corrosion behaviors in aqueous solution. Despite the important role of the multi-component oxide evolution, little has been known on the kinetics from the atomistic level.  We have built a computational framework that enables simulations of competing kinetic processes in multi-component oxides from first principles. The effects of applied voltage, pH and temperature on oxide growth, dissolution and reprecipitation can all be captured in this model. Combining with our experimental measurements on Alloy 22 and a Ni80%-Cr20% model alloy, we identified three voltage regimes with distinct oxide thicknesses and compositions.
The oxide energetics of various stoichiometries are calculated by the density functional theory (DFT). Then the obtained data are used to train a surrogate lattice Hamiltonian with the cluster expansion (CE) method. Finally, kinetic Monte Carlo (KMC) simulations are run with the cation hopping barriers calculated on-the-fly based on the local environments from the combination of the above Hamiltonian and the linear Brønsted−Evans−Polanyi (BEP) relation.

en: Atomic-scale understanding of oxide growth and dissolution kinetics of Ni-Cr alloys

cluster-expansion

display_name: cluster-expansion

kinetics

display_name: kinetics

ni-cr-oxide

display_name: ni-cr-oxide

vasp

display_name: vasp


en: Cluster expansions are commonly employed as surrogate models to link the electronic structure of an alloy to its finite-temperature properties. Using cluster expansions to model materials with several alloying elements is challenging due to a rapid increase in the number of fitting parameters and training set size. We introduce the embedded cluster expansion (eCE) formalism that enables the parameterization of accurate on-lattice surrogate models for alloys containing several chemical species. The eCE model simultaneously learns a low dimensional embedding of site basis functions along with the weights of an energy model. A prototypical senary alloy comprised of elements in groups 5 and 6 of the periodic table is used to demonstrate that eCE models can accurately reproduce ordering energetics of complex alloys without a significant increase in model complexity. Further, eCE models can leverage similarities between chemical elements to efficiently extrapolate into compositional spaces that are not explicitly included in the training dataset. The eCE formalism presented in this study unlocks the possibility of employing cluster expansion models to study multicomponent alloys containing several alloying elements.

en: Constructing multicomponent cluster expansions with machine-learning and chemical embedding

ab-initio

display_name: ab-initio

machine-learning

display_name: machine-learning


en: Hydrogen boride (HB) sheet is a newly developed two-dimensional boron-based nanosheet. To explore its potential in electronic and catalytic applications, it's crucial to assess its chemical stability with common substances. In this study, we examine its stability in water, a substance frequently encountered in ambient conditions and various applications. Focusing on the HB sheet's edge, we utilized a nanoribbon model to observe water-edge interactions. This record includes the crystal structures optimized through first-principles calculations, which were used to analyze the properties and interactions between water and the HB sheet. Additionally, input files for system calculations are provided to facilitate reproducibility of the study's results.

en: Interplay of hydrogen boride sheets with water: An insight into edge stability

boron

display_name: boron

density-functional-theory

display_name: density-functional-theory

hydrogen-boride-sheet

display_name: hydrogen-boride-sheet

water

display_name: water


en: Within many-body perturbation theory, we calculate band offsets for a set of epitaxial interfaces, including AlP/GaP, AlAs/GaAs, Ge/AlAs, Ge/GaAs, Ge/ZnSe, Si/GaP, ZnSe/GaAs, and CaF2/Si. We consider various quasiparticle self-consistent 𝐺𝑊 schemes with or without including vertex functions. In particular, we consider two types of effective vertex functions complying with the Ward identity in the long range, one of which additionally carries a short-range part, which has been found to improve ionization potentials. The obtained band offsets correspond to model interface structures that match the experimental lattice parameters of the bulk components. Strain, zero-phonon renormalization, and spin-orbit coupling effects are properly accounted for. For the band offsets of the semiconductor-semiconductor interfaces, all the self-consistent 𝐺𝑊 schemes yield similar mean absolute errors on the order of 0.2 eV. In the case of the CaF2/Si interface, the calculated band offsets show large indetermination spanning an interval up to 1 eV, the discrepancy with respect to experiment being correlated with the error by which the band gap of the insulator is described. Through 𝐺𝑊 calculations for selected interface models, we further assess the effect of self-consistently updating the charge density. Our result support the practice of relying on semilocal or hybrid-functional schemes for determining the line-up potential.

en: Band alignments through quasiparticle self-consistent 𝐺𝑊 with efficient vertex corrections

band-alignments

display_name: band-alignments

epitaxial-interfaces

display_name: epitaxial-interfaces

gw-calculations

display_name: gw-calculations


en:
The adsorption energies of perfluorobutanesulfonic acid, perfluorobutanoic acid, and trifluoroacetic acid on functionalized activated carbon are calculated from first principles. We introduce a novel approach based on a thermochemical cycle and a continuum solvation model to address neutral and charged adsorption complexes and account for concentration, pH, and pore-size effects. The results highlight the benefit of N-based functional groups for enhancing the removal of challenging, short-chain perfluoroalkyl substances from water by activated carbon.

This record includes the output files of Quantum ESPRESSO relaxation calculations of PFAS adsorption on functionalized activated carbon.

en: Adsorption of Short-Chain Perfluoroalkyl Substances (PFAS) on Functionalized Activated Carbon from First Principles

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).

activated-carbon

display_name: activated-carbon

dft

display_name: dft

pfas

display_name: pfas


en:
In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based models to methods based on the three-dimensional structure of reactants and products. In tandem, many representations have been developed to predict experimental targets, which may hold promise for barrier prediction as well. Here, we bring together all of these efforts and benchmark various methods (Morgan fingerprints, the DRFP, the CGR representation-based Chemprop, SLATMd, B²Rl², EquiReact and language model BERT + RXNFP) for the prediction of computed activation barriers on three diverse datasets.
This record includes data to support the article "Benchmarking machine-readable vectors of chemical reactions on computed activation barriers". This supports the github repository https://github.com/lcmd-epfl/benchmark-barrier-learning which contains the codes and duplicates the data.

materialscloud

en: Materials Cloud

benchmark

display_name: benchmark

chemical-reactions

display_name: chemical-reactions

epfl

display_name: epfl

erc

display_name: erc

snsf

display_name: snsf


en: The dataset contains records of Charpy V-notch impact tests of nuclear structural materials. The focus is on studying the influence of specimen dimensions and geometry on Charpy impact test properties. The dataset was created through an extensive literature review of scientific articles. The extracted data points from the literature review are organized into a tabular format database containing 4,775 test records with 55 parameters, including material type and composition, manufacturing information, irradiation conditions, specimen size and dimensions, and Charpy properties. Materials science experts conducted systematic validation checks to ensure the accuracy of the information related to material type, manufacturing processes, treatment methods, chemical composition, testing conditions, as well as other pertinent information.

en: Dataset of Charpy V-notch impact test records of nuclear structural materials

charpy-v-notch-impact-test

display_name: charpy-v-notch-impact-test

miniature-specimens

display_name: miniature-specimens

nuclear-structural-materials

display_name: nuclear-structural-materials

reactor-pressure-vessel-steels

display_name: reactor-pressure-vessel-steels

specimen-size-effect

display_name: specimen-size-effect

sub-sized-specimens

display_name: sub-sized-specimens


en: This study discloses the effect of hydrogen impurities on the local chemical bonding states and structure of amorphous alumina films by predicting measured Auger parameter shifts using a combination of atomistic and electrostatic modeling. Different amorphous alumina polymorphs with variable H-content and density, as grown by atomic layer deposition, were successfully modeled using a universal machine learning interatomic potential. The annealing of highly defective crystalline hydroxide structures with experimental H-contents at the corresponding atomic layer deposition temperatures led to excellent agreement between theory and experiment in the density and structure of the resulting amorphous alumina polymorphs. The measured Auger parameter shifts of Al cations in such polymorphs were accurately predicted with respect to the H content by assuming that all H atoms are present in the form of hydroxyl ligands in the randomly interconnected 4-fold, 5-fold, and 6-fold nearest-coordination spheres of Al. As revealed by a combination of atomistic and electrostatic modeling, the measured Auger shifts with an increase in the H content and an accompanying decrease in the oxide density depend on the complex correlations between local coordination, bond lengths, bond angles, and ligand type(s) around the core-ionized atoms. Moreover, cryogenic X-ray photoelectron spectroscopy is suggested to offer new insights into the local chemical and structural building blocks of crystalline and amorphous oxides by reducing thermal noise. These findings and fundamental knowledge contribute to advancing the design of e.g. hydrogen oxide barrier films, oxide membranes for H separation, H storage materials, and fuel cells for a hydrogen-based economy.

en: Effect of hydrogen on the local chemical bonding states and structure of amorphous alumina by atomistic and electrostatic modeling and first principles calculations of auger parameter shifts

envi

en: Environment

amorphous-oxide

display_name: amorphous-oxide

atomic-layer-deposition-ald

display_name: atomic-layer-deposition-ald

auger-parameter

display_name: auger-parameter

density-functional-theory-dft

display_name: density-functional-theory-dft

electrostatic-modeling

display_name: electrostatic-modeling

hydrogen

display_name: hydrogen

molecular-dynamics-md

display_name: molecular-dynamics-md

x-ray-photoelectron-spectroscopy-xps

display_name: x-ray-photoelectron-spectroscopy-xps


en: Chalcogenide perovskites have emerged as a promising class of materials for the next generation of optoelectronic applications, with BaZrS3 attracting significant attention due to its wide bandgap, earth-abundant composition, and thermal and chemical stability. However, previous studies have consistently reported weak and ambiguous photoluminescence (PL), regardless of synthesis method, raising questions about the intrinsic optoelectronic quality of this compound. In this work, strong, band-to-band-dominated PL is demonstrated at room temperature in high-quality BaZrS3 single crystals, with a PL quantum yield of ∼0.005%. Despite the narrow, single-component PL emission band, time-resolved PL measurements reveal a carrier lifetime of 1.0 ± 0.2 ns. To understand the origin of the strong PL and short carrier lifetime, multiwavelength excitation and polarization-dependent Raman measurements are performed, supported by first-principles lattice dynamics calculations. All 23 theoretically predicted Raman-active modes and their symmetries are identified, providing a comprehensive reference for future studies. These results indicate that phonon-assisted carrier decay and nontrivial electron-phonon interactions contribute to the short carrier lifetimes, as evidenced by Raman spectroscopy and DFT calculations. Further studies on compositional variations or partial cation/anion substitutions can mitigate electron-phonon coupling and enhance carrier lifetimes. By establishing a detailed reference for the intrinsic vibrational and optoelectronic properties of BaZrS3, this work paves the way for further advancements in chalcogenide perovskites for energy and optoelectronic technologies.

en: BaZrS3 lights up: the interplay of electrons, photons, and phonons in strongly luminescent single crystals

chalcogenide-perovskite

display_name: chalcogenide-perovskite

electron-phonon-coupling

display_name: electron-phonon-coupling

optoelectronic

display_name: optoelectronic

raman-spectroscopy

display_name: raman-spectroscopy


en: Skutterudites are promising materials for thermoelectric and spintronics applications. Here we explore spin fluctuations in the FeSb3 skutterudite and their effect on its electronic structure using Hubbard-corrected density-functional theory calculations. We identify multiple magnetic and charge-disproportionated configurations, with an antiferromagnetic metallic ground state. Paramagnetic fluctuations modeled through a special quasirandom spin structure open a 61 meV gap, consistent with experiments. This state features non-degenerate spin channels and band-avoided crossings, hinting at a potential altermagnetic transition with topological features. Mapping the electronic structure to a Heisenberg Hamiltonian fails to explain the low Néel temperature (10 K), highlighting the role of magnetic exchange frustration and the need for more in-depth experimental investigations.This dataset contains first-principles calculations supporting the study “Spin fluctuations steer the electronic behavior in the FeSb₃ skutterudite”. It includes linear-response Hubbard parameters, phonon dispersions, electronic band structures, special quasirandom structures modeling of paramagnetism, and magnetic exchange interactions for FeSb₃. The data document how spin fluctuations stabilize the structure, open a small electronic gap, and strongly affect magnetic energetics.

en: Spin fluctuations steer the electronic behavior in the FeSb3 skutterudite

condensed-matter-physics

display_name: condensed-matter-physics

first-principles-simulations

display_name: first-principles-simulations

heisenberg-model

display_name: heisenberg-model

magnetism

display_name: magnetism

paramagnetism

display_name: paramagnetism

special-quasi-random-structures

display_name: special-quasi-random-structures

spin-fluctuations

display_name: spin-fluctuations


en: Electron-phonon coupling is a key interaction that governs diverse physical processes such as carrier transport, superconductivity, and optical absorption. Calculating such interactions from first-principles with methods beyond density-functional theory  remains a challenge. We introduce here a finite-difference framework for computing electron-phonon couplings for any electronic structure method that provides eigenvalues and eigenvectors, and showcase applications for hybrid and Koopmans functionals, and $GW$ many-body perturbation theory. Our approach introduces a novel projectability scheme based on eigenvalue differences and bypasses many of the limitations of the direct finite difference methods. It also leverages symmetries to reduce the number of independent atomic displacements, thereby keeping computational costs manageable. This approach enables seamless integration with established first-principles codes for generating displaced supercells, performing Wannier interpolations, and evaluating transport properties. Applications to silicon and gallium arsenide show that advanced electronic-structure functionals predict different electron-phonon couplings and modify band curvatures, resulting in much more accurate estimates of intrinsic carrier drift mobilities and effective masses. In general, our method provides a robust and accessible framework for exploring electron-phonon interactions in complex materials with state-of-the-art electronic structure methods.

en: Carrier mobilities and electron-phonon interactions beyond DFT

beyond-dft-methods

display_name: beyond-dft-methods

boltzmann-transport-equation

display_name: boltzmann-transport-equation

koopmans-functional

display_name: koopmans-functional

snsf

display_name: snsf


en:
Experiments involving resonant optical excitation of infrared-active phonons in crystals have emerged as a powerful new way to tune materials properties. A puzzling and so far unexplained aspect of some so-called nonlinear phononics experiments is that the observed lifetimes of the optically created metastable phases are sometimes orders of magnitude longer than expected based on the nonlinear phononics mechanism assumed in most works. We use a combination of phenomenological theory and first-principles calculations to demonstrate that strong coupling between different lattice degrees of freedom (strains and Raman-active phonons) can give rise to a long-lived metastable phase recently observed in experiments on perovskite LaAlO3 [Hortensius et al. npj Quantum Mater. 5 95 (2020)]. We show that the long-timescale oscillatory response in the experimental optical reflectivity data is not due solely to shear strains, as originally suggested, but arises from a “hybrid” mode involving displacements of Raman-active phonons of the same symmetry. Our work suggests that strong coupling between different order parameters can provide a mechanism for long-lived optically created metastable phases and points towards strategies, such as strain engineering, for modifying or increasing the lifetime of light-induced phases in ultrafast optical experiments.

This archive contains the data files used to produce Figures 2-4 of the described paper.

en: Understanding long-lived metastable phases in ultrafast optical experiments

complex-oxides

display_name: complex-oxides

first-principles

display_name: first-principles


en: Ultrathin nanowires could play a central role in next-generation downscaled electronics. Here, we explore some of the most promising candidates identified from previous high-throughput screening: CuC2, TaSe3, and AuSe2, to gain insight into the thermodynamic and anharmonic behaviors of nanowires that could be exfoliated from weakly-bonded three-dimensional materials. We analyze thermal stability, linear thermal expansion, and anharmonic heat capacity using the stochastic self-consistent harmonic approximation. Notably, our work unveils exotic features common among all the 1D wires: a colossal record negative thermal expansion and very large deviations from the Dulong-Petit law due to strong anharmonicity.

en: Extreme anharmonicity and thermal contraction of 1D wires

anharmonicity

display_name: anharmonicity

density-functional-theory

display_name: density-functional-theory

heat-capacity

display_name: heat-capacity

negative-thermal-expansion

display_name: negative-thermal-expansion

one-dimensional-materials

display_name: one-dimensional-materials

sscha

display_name: sscha


en: The confining walls made by 2D materials are often considered as solid boundary conditions in studies of fluid transport through nanochannels, while the atomically thin walls inherently exhibit thermal fluctuations at finite temperature. In this work, we investigate the solid-liquid interfacial friction properties of water confined within flexible nanochannels using machine-learning-potential molecular dynamics. Surprisingly, we find that the friction coefficient (λ) increases with lateral size L in the flexible nanochannels, following a linear relationship with 1/L, which is absent in rigid channels. For thicker nanochannel walls with large bending stiffness (D), this size dependence weakens. This 1/L scaling resembles the size-dependent thermal fluctuation amplitude of 2D sheets, suggesting that λ can be well controlled by applying the mechanical strain to the channel walls via controlling the phonon modes associated with surface fluctuations. Further analysis reveals that the λ can be decomposed into the contribution from lattice roughness and the thermal-fluctuation-induced ripple of 2D surface, where the second term scales with D−1/2. These findings offer insights into the manipulation of nanoscale flow through precise control of local curvature and fluid-solid coupling.

en: Machine-learning potential molecular dynamics reveals the critical role of flexibility in solid-liquid nanofluidic friction

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).

flexibility

display_name: flexibility

liquidsolid-friction

display_name: liquidsolid-friction

machine-learning-potential

display_name: machine-learning-potential


en:
In this paper, we show many-body calculations of magnon-phonon (mag-ph) coupling based on the ab initio Bethe-Salpeter equation. We derive expressions for mag-ph coupling matrices and compute them in 2D ferromagnets, focusing on hydrogenated graphene and monolayer CrI3. Our analysis shows that electron-phonon (e-ph) and mag-ph interactions differ significantly, where modes with weak e-ph coupling can exhibit strong mag-ph coupling (and vice versa), and reveals which phonon modes couple more strongly with magnons. In both materials studied here, the inelastic magnon relaxation times decrease abruptly above the threshold for emission of strongly coupled phonons, revealing a low-energy window where magnons are long-lived. Averaging over this window, we compute the temperature-dependent magnon mean-free path, a key figure of merit for spintronics, entirely from first principles. The theory and computational tools shown in this work enable studies of magnon interactions, scattering, and dynamics in generic materials, advancing the design of magnetic systems and magnon- and spin-based devices.

This archive include the necessary inputs for DFT, DFPT in Quantum Espresso, and GW-BSE in Yambo code. Since the routine for magnon-phonon coupling is not published, we provided the raw data files used for the figures in our paper as the reference.

en: Magnon-phonon interactions from first principles

materialscloud

en: Materials Cloud

bethe-salpeter-equation

display_name: bethe-salpeter-equation

magnon-phonon-coupling

display_name: magnon-phonon-coupling


en: Rare-earth superhydrides have attracted considerable attention because of their high critical superconducting temperature under extreme pressures. They are known to have localized valence electrons, implying strong electronic correlations. However, such many-body effects are rarely included in first-principles studies of rare-earth superhydrides because of the complexity of their high-pressure phases. In this work, we use a combined density functional theory and dynamical mean-field theory approach to study both electrons and phonons in the prototypical rare-earth superhydride CeH9, shedding light on the impact of electronic correlations on its critical temperature for phonon-mediated superconductivity. Our findings indicate that electronic correlations result in a larger electronic density at the Fermi level, a bigger superconducting gap, and softer vibrational modes associated with hydrogen atoms. Together, the inclusion of these correlation signatures increases the Migdal-Eliashberg superconducting critical temperature from 47 K to 96 K, close to the measured 95 K. Our results reconcile experimental observations and theoretical predictions for CeH9 and herald a path towards the quantitative modeling of phonon-mediated superconductivity for interacting electron systems.

en: Impact of electronic correlations on the superconductivity of high-pressure CeH9

envi

en: Environment

electronic-correlations

display_name: electronic-correlations

high-pressure

display_name: high-pressure

superconductivity

display_name: superconductivity


en: Strongly correlated physics arises from electron-electron scattering within partially filled orbitals. Organic molecules in open-shell configurations are therefore good candidates to exhibit many-body effects. We focus on electron transport in a two-terminal single-molecule junction setup, where the molecular bridge consists of an organic radical with a molecular orbital that hosts a single unpaired electron (SOMO). We perform beyond state-of-the-art numerical simulations combining an ab-initiodescription of the chemical environment, with quantum field-theoretical techniques that account for many-body effects. The key observation is that the SOMO resonance is prone to splitting and we identify a giant electronic scattering rate as the driving many-body mechanism, akin to that of the Mott metal-to-insulator transition. By comparing linear and cyclic radicals, we show that the spatial distribution of the SOMO and its projection on the molecular backbone have dramatic consequences for the transport properties of the junction. We argue that the phenomenon and the underlying microscopic mechanism apply to a broad family of open-shell molecular systems, and can explain puzzling experimental observations such as suppressed conductance in radical junctions.

en: Strongly correlated physics in organic open-shell quantum systems

dft

display_name: dft

dmft

display_name: dmft

exact-diagonalization

display_name: exact-diagonalization

transport

display_name: transport


en: Spin-wave excitations are fundamental to understanding the behavior of magnetic materials and hold promise for future information and communication technologies. Yet, modeling these accurately in transition-metal compounds remains challenging, starting from the self-interaction errors affecting localized and partially filled $d$-orbitals in density-functional theory (DFT) with (semi-)local functionals. In this work, we compare three advanced first-principles approaches for computing magnetic exchange parameters and magnon dispersions in NiO and MnO, all based on a common DFT+$U$ ground state with ab initio Hubbard $U$ values obtained from density-functional perturbation theory. Two methods extract exchange parameters directly: one via total-energy differences using the four-state mapping ($\Delta E$), and the other via the magnetic force theorem (MFT) using infinitesimal spin rotations. Magnon dispersions are then obtained from a Heisenberg Hamiltonian through linear spin-wave theory (LSWT). The third approach, time-dependent density-functional perturbation theory with $U$ (TDDFPT+$U$), yields magnon dispersions directly from the dynamical spin susceptibility, with exchange parameters fitted a posteriori, for comparison, via LSWT. Our results show that TDDFPT+$U$ and the Heisenberg model based on $\Delta E$-derived parameters align well with experimental neutron scattering data, whereas the MFT-based approach shows larger discrepancies, possibly due to some inherent approximations and limitations of the particular implementation used. This study benchmarks the accuracy of state-of-the-art first-principles techniques for spin-wave modeling and contributes to advancing reliable computational tools for the study and design of magnetic materials.

en: Comparative study of magnetic exchange parameters and magnon dispersions in NiO and MnO from first principles

dftu

display_name: dftu

four-state-mapping-analysis

display_name: four-state-mapping-analysis

heisenberg-j

display_name: heisenberg-j

linear-spin-wave-theory

display_name: linear-spin-wave-theory

magnetic-force-theorem

display_name: magnetic-force-theorem

magnon-dispersion

display_name: magnon-dispersion

magnons

display_name: magnons

mno

display_name: mno

nio

display_name: nio

quantum-espresso

display_name: quantum-espresso

spin-waves

display_name: spin-waves


en: This dataset contains the optimized structures of hole polarons in anatase and rutile TiO₂, calculated using the DFT+U and PBE0(α) functionals, with parameters tuned to satisfy the piecewise linearity condition. It also includes hole polaron migration paths in anatase and rutile, optimized using the nudged elastic band method at the DFT+U level. Additionally, pristine TiO₂ structures and an example input file for Quantum ESPRESSO are provided.

en: Migration of hole polarons in anatase and rutile TiO₂ through piecewise-linear functionals

anatase

display_name: anatase

hopping

display_name: hopping

polaron

display_name: polaron

rutile

display_name: rutile

semiconductor

display_name: semiconductor


en:
This record contains the complete optimization trajectories, potential model, and analysis data for the Nudged Elastic Band (NEB) calculation of the ethylene + N$_2$O cycloaddition, a Grignard rearrangement, and a bicyclobutane  reaction. This dataset supports the accompanying manuscript "Two-dimensional RMSD projections for reaction path visualization and validation" and enables the full reproduction of the reported 2D RMSD landscapes and 1D energy profiles.

Transition state or minimum energy path finding methods constitute a routine component of the computational chemistry toolkit. Standard analysis involvestrajectories conventionally plotted in terms of the relative energy to the initial state against a cumulative displacement variable, or the image number.These dimensional reductions obscure structural rearrangements in high dimensions and are often history dependent. This precludes the ability tocompare optimization histories of different methods beyond the number of calculations, time taken, and final saddle geometry. We present a method mappingtrajectories onto a two-dimensional projection defined by a permutation corrected root mean square deviation from the reactant and product configurations. Energyis represented as an interpolated color-mapped surface constructed from all optimization steps using a gradient-enhanced Gaussian Process with the inversemultiquadric kernel, whose posterior variance contours delineate data-supported regions from extrapolated ones. A rotated coordinate frame decomposes the RMSDplane into reaction progress and orthogonal distance. We show the utility of the framework on a cycloaddition reaction, where a machine-learned potentialsaddle and density functional theory reference lie on comparable energy contours despite geometric displacements, along with the ratification of thevisualization for more complex reactions, a Grignard rearrangement, and a conrotatory bicyclobutane ring opening.

The provided data encompasses the entire computational workflow: from the pre-trained PET-OMAT machine-learned potential and initial endpoint geometries to the intermediate NEB optimization steps and the final converged reaction path.

nudged-elastic-band

display_name: nudged-elastic-band

saddle-search-methods

display_name: saddle-search-methods

transition-states

display_name: transition-states

visualization

display_name: visualization


en: The choice of structural resolution is a fundamental aspect of protein modelling, determining the balance between descriptive power and interpretability. Although atomistic simulations provide maximal detail, much of this information is redundant to understand the relevant large-scale motions and conformational states. Here, we introduce an unsupervised, information-theoretic framework that determines the minimal number of atoms required to retain a maximally informative description of the configurational space sampled by a protein. This framework quantifies the informativeness of coarse-grained representations obtained by systematically decimating atomic degrees of freedom and evaluating the resulting clustering of sampled conformations. Application to molecular dynamics trajectories of dynamically  diverse proteins shows that the optimal number of retained atoms scales linearly with system size, averaging about four heavy atoms per residue--remarkably consistent with the resolution of well-established coarse-grained models, such as MARTINI and SIRAH. Furthermore, the analysis shows that the optimal retained atoms number depends not only on molecular size but also on the extent of conformational exploration, decreasing for systems dominated by collective motions. The proposed method establishes a general criterion to identify the minimal structural detail that preserves the essential configurational information, thereby offering a new viewpoint on the structure-dynamics-function relationship in proteins and guiding the construction of parsimonious yet informative multiscale models.

en: Determining the optimal structural resolution of proteins through an information-theoretic analysis of their conformational ensemble

coarse-graining

display_name: coarse-graining

model-resolution

display_name: model-resolution

molecular-dynamics

display_name: molecular-dynamics