en: Skutterudites are crystals with a cagelike structure that can be augmented with filler atoms ("rattlers"), usually leading to a reduction in thermal conductivity that can be exploited for thermoelectric applications. Here, we leverage the recently introduced Wigner formulation of thermal transport to elucidate the microscopic physics underlying heat conduction in skutterudites, showing that filler atoms can drive a crossover from the Boltzmann to the Wigner regimes of thermal transport, i.e., from particlelike conduction to wavelike tunneling. At temperatures where the thermoelectric efficiency of skutterudites is largest, wavelike tunneling can become comparable to particlelike propagation. We define a Boltzmann deviation descriptor able to differentiate the two regimes and relate the competition between the two mechanisms to the materials' chemistry, providing a design strategy to select rattlers and identify optimal compositions for thermoelectric applications.

en: Crossover from Boltzmann to Wigner thermal transport in thermoelectric skutterudites

marvel

display_name: marvel

phonons

display_name: phonons

thermal-conductivity

display_name: thermal-conductivity

thermoelectrics

display_name: thermoelectrics


$oid: OBSOLETE

en:
The potential profile and the energy level offset of core/shell heterostructured nanocrystals (h-NCs) determine the photophysical properties and the charge transport characteristics of h-NC solids. However, limited material choices for heavy metal-free III-V/II-VI h-NCs pose challenges in comprehensive control of the potential profile. Herein, we present an approach to such control by steering dipole densities at the interface of III-V/II-VI h-NCs. The controllable heterovalency at the interface is responsible for interfacial dipole densities that result in the vacuum-level shift, providing an additional knob for the control of optical and electrical characteristics of h-NCs. The synthesis of h-NCs with atomic precision allows us to correlate interfacial dipole moments with the nanocrystals' photochemical stability and optoelectronic performance.

The description was referred to the abstract of the original paper. All numerical data of the main figures in the articles are included in this data repository.
In particular, each tab of the data file indicates each panel in the main figures.
Please refer to the main research article.

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

en: Interface polarization in heterovalent core/shell nanocrystals

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

experimental

display_name: experimental

heterostructured-nanocrystal

display_name: heterostructured-nanocrystal

interface-polarization

display_name: interface-polarization


en: The mapped gaussian process (MGP) force-field used to elucidate the surface alloying of Cu-Zn. The force-field is made based on first-principles data by using machine-learning technique called Gaussian Process as implemented in FLARE package (https://github.com/mir-group/flare). Active and on-the-fly learning were employed to build the database efficiently. The simulation reveals atomistic details of the alloying process, i.e., the incorporation of deposited Zn adatoms to the Cu substrate. The surface alloying is found to start at upper and lower terraces near the step edge, which emphasize the role of steps and kinks in the alloying. The incorporation of Zn at the middle terrace was found at the later stage of the simulation.

en: The mapped gaussian process (MGP) force-field of Cu-Zn surface alloy

cu-zn-surface

display_name: cu-zn-surface

first-principles

display_name: first-principles

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en:
**Data for Properties of α-Brass Nanoparticles. 1. Neural Network Potential Energy Surface**
Jan Weinreich, Anton Römer, Martín Leandro Paleico, and Jörg Behler

53 841 reference structures of alpha brass (less 40 % Zn) with following split
 - 4009 brass clusters
 - 8492 molten brass bulk structures
 - 8964 copper slabs, and 16 878 brass slabs
 - 5377 copper bulk structures
 - 10 121 brass bulk structures have been included.

53 841 total energies and 8 903 340 force components. The ranges of values for the energies and force components to be fitted have a width of about 2 eV/atom and 15 eV/Å, respectively. However, some structures may have slightly higher Zn content as discussed in Fig 3 (https://arxiv.org/abs/2001.10906)

The archive contains an easily usable npz file as well as the original input.data file used to fit the potential energy surface. Additionally a Jupyter notebook describes in great detail how the data was converted to the npz format and how to read the data e.g. for subsequent use with python. In addition an example VASP calculation was added to provide detailed information about how the reference data was calculated with DFT.

DETAILS:
- DFT PB VASP-5.3 target accuracy of the total energy few meV/atom
- Convergence tests with respect to the number of k-points showed that in order to fulfill this criterion a k-point grid of 12 × 12 × 12 is needed for a conventional four-atom copper fcc unit cell with a lattice constant of about 3.63 Å along with a plane wave cutoff energy of 500 eV and projector augmented wave potentials.(61,63)
- Larger systems have been calculated using an adapted k-point grid corresponding to the same k-point density. The Γ-point centered k-point grids have been constructed employing the Monkhorst–Pack scheme. For surface calculations, 4–14 layer slabs with a total vacuum thickness of at least 8 Å have been used.
- In the case of cluster calculations, which have also been treated in a periodic setup, the periodic images of the clusters have been separated by at least 8 Å in all three spatial directions. The convergence of very large clusters with diameters of d ≈ 22 Å, which have been used to include specific atomic environments in the data set, has been extensively tested and we found that using the Γ-point only is sufficient to reach the required convergence level.

en: Properties of α-brass nanoparticles. 1. Neural network potential energy surface

alloys

display_name: alloys

brass

display_name: brass

database

display_name: database

dft

display_name: dft

neural-networks

display_name: neural-networks

potential-energy-surfaces

display_name: potential-energy-surfaces


en: Using vertex-corrected quasiparticle self-consistent GW schemes, we address the electronic structure of two manganese dioxide polymorphs, α-MnO₂ and β-MnO₂. In particular, we determine the fundamental band gaps, the macroscopic dielectric constants, the magnetic moments of the Mn atoms, the band structures and the associated densities of states. Additionally, we obtain the imaginary component of the dielectric function ε₂(𝜔) from the solution of the  Bethe–Salpeter equation. For β-MnO₂, we record overall good agreement when comparing the density of states with XPS/BIS spectra and the dielectric function ε₂(𝜔) with optical response spectra. Applied to α-MnO₂, whose pristine bulk structure is poorly characterized, our work provides a prediction at the same level of theory. The quality of the achieved description is further supported by comparisons with experimental spectra of nanostructured and doped variants. This study demonstrates that state-of the-art GW methods successfully account for key electronic-structure features of MnO₂ polymorphs.

en: Electronic structure of α-MnO₂ and β-MnO₂ through GW with vertex corrections

electronic-structure

display_name: electronic-structure

gw

display_name: gw

manganese-oxide

display_name: manganese-oxide

many-body-perturbation-theory

display_name: many-body-perturbation-theory

vertex-corrections

display_name: vertex-corrections


en:
We propose a variational algorithm to study the real time dynamics of quantum systems as a ground-state problem on quantum devices. The method is based on the original proposal of Feynman and Kitaev to encode time into a register of auxiliary qubits.
We prepare the Feynman-Kitaev Hamiltonian acting on the composed system as a qubit operator and find an approximate ground state using the Variational Quantum Eigensolver. We apply the algorithm to the study of the dynamics of a transverse field Ising chain with an increasing number of spins and time steps, proving a favorable scaling in terms of the number of two qubit gates.
Through numerical experiments, we investigate its robustness against hardware noise, showing that the method can be use to evaluate dynamical properties of quantum systems and detect the presence of dynamical quantum phase transitions by measuring Loschmidt echoes.
The scripts provided implement the algorithm both in Python, using the Qiskit library, and in Julia, using the Yao.jl package.
Moreover, we included the data to reproduce the figures of the manuscript without running the simulations.

en: Variational dynamics as a ground-state problem on a quantum computer

marvel

display_name: marvel

quantum-computing

display_name: quantum-computing

quantum-simulation

display_name: quantum-simulation

real-time-evolution

display_name: real-time-evolution


en: The piecewise linearity condition on the total energy with respect to the total magnetization of finite quantum systems is derived using the infinite-separation-limit technique. This generalizes the well-known constancy condition, related to static correlation error, in approximate density functional theory. The magnetic analog of Koopmans' theorem in density functional theory is also derived. Moving to fractional electron count, the tilted-plane condition is derived, lifting certain assumptions in previous works. This generalization of the flat-plane condition characterizes the total energy surface of a finite system for all values of electron count N and magnetization M. This result is used in combination with tabulated spectroscopic data to show the flat-plane structure of the oxygen atom, among others. We find that derivative discontinuities with respect to electron count sometimes occur at noninteger values. A diverse set of tilted-plane structures is shown to occur in d-orbital subspaces, depending on chemical coordination. General occupancy-based total-energy expressions are demonstrated thereby to be necessarily dependent on the symmetry-imposed degeneracies.

en: Tilted-plane structure of the energy of finite quantum systems

density-functional-theory

display_name: density-functional-theory

static-correlation-error

display_name: static-correlation-error


en: Computational searches for new materials are naturally turning from binary systems, to ternary and other multicomponent systems, and beyond. Here, we select the industrially-relevant metals Ti and Al and report the results of an extensive structure prediction study on the ternary titanium-carbon-oxygen (Ti-C-O) and aluminium-carbon-oxygen (Al-C-O) systems. We map out for the first time the full phase stability of Ti-C-O and Al-C-O compounds using first-principles calculations, through simple, effcient and highly parallel random structure searching in conjunction with techniques based on complex network theory. This record contains the crystal structures used to generate our ternary convex hulls for these systems. We provide input files for the CASTEP density-functional theory code, crystallographic '.res' files of the relaxed structures, and CASTEP output files showing atomic positions and forces calculated during relaxation.

en: Navigating the Ti-C-O and Al-C-O ternary systems through theory-driven discovery

carbonate-minerals

display_name: carbonate-minerals

structure-prediction

display_name: structure-prediction

ternary-systems

display_name: ternary-systems


en: Using first-principles techniques, we study the structural, magnetic, and electronic properties of (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices of varying thickness (n=2,4,6). We find that the properties of the thinnest superlattice (n=2) are similar to the celebrated half-metallic ferromagnetic alloy La2/3Sr1/3MnO₃, with quenched Jahn-Teller distortions. At intermediate thickness (n=4), the a⁻a⁻a⁻ tilting pattern transitions to the a⁻a⁻c⁺ tilting pattern, driven by the lattice degrees of freedom in the LaMnO₃ region. The emergence of the Jahn-Teller modes and the spatial extent needed for their development play a key role in this structural transition. For the largest thickness considered (n=6), we unveil an emergent separation of Jahn-Teller and volume-breathing orders in the ground-state structure with the a⁻a⁻c⁺ tilting pattern, whereas it vanishes in the antiferromagnetic configurations. The ground state of all superlattices is half-metallic ferromagnetic, not affected by the underlying series of structural transitions. Overall, these results outline a thickness-induced crossover between the physical properties of bulk La2/3Sr1/3MnO₃ and bulk LaMnO₃. The dataset includes the fully relaxed atomic positions of the most favorable tilting patterns, as well as the main output files of the electronic structure calculations. Selected files for the density of states are also included.

en: Emergent half-metal with mixed structural order in (111)-oriented (LaMnO₃)₂ₙ|(SrMnO₃)ₙ superlattices

dft

display_name: dft

dftu

display_name: dftu

electronic-properties

display_name: electronic-properties

magnetic-properties

display_name: magnetic-properties

oxide-heterostructures

display_name: oxide-heterostructures


en:
The electronic structure, interatomic bonding, and mechanical properties of two supercell models of Ni-based super alloys are calculated by using ab initio density functional theory methods. The alloys are in the face centered cubic lattice having 864 atoms and eleven elements: Haynes282 (Ni₄₄₄Cr₂₀₂Co₇₉Al₅₆Ti₂₅Mo₂₅Fe₁₂Mn₃Si₅C₁₂B) and Inconel740 (Ni₃₇₃Cr₂₄₆Co₁₅₃Al₃₃Ti₂₁Nb₆MoFe₆
Mn₃Si₁₇C₅). These multi-component alloys have very complex electronic structure, bonding and partial charge distributions depending on the composition and strength of local bonding environment. We employ the novel concept of total bond order density (TBOD) and its partial components (PBOD) to ascertain the internal cohesion that controls the intricate balance between the propensity of metallic bonding between Ni, Cr and Co, and the strong bonds with C and Al. We find Inconel740 has slightly stronger mechanical properties than Haynes282. Comparison with more conventional high entropy alloys with equal components are discussed.

materialscloud

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

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

en: Materials Cloud

en: Ab initio simulation of structure and properties in Ni-based superalloys Haynes282 and Inconel740

effective-charge

display_name: effective-charge


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

envi

en: Environment

artificial-intelligence

display_name: artificial-intelligence

defect-detection

display_name: defect-detection

gocator

display_name: gocator


en: We present evidence of a strong circular photon drag effect (PDE) in topological insulators (TIs) through the observation of threefold rotationally symmetric helicity-dependent topological photocurrents using THz spectroscopy in epitaxially-grown Bi₂Se₃ with reduced crystallographic twinning. We establish how twinned domains introduce competing nonlinear optical (NLO) responses inherent to the crystal structure that obscure geometry-sensitive optical processes through the introduction of a spurious mirror symmetry. Minimizing the twinning defect reveals strong NLO response currents whose magnitude and direction depend on the alignment of the excitation to the crystal axes and follow the threefold rotational symmetry of the crystal. Notably, photocurrents arising from helical light reverse direction for left/right circular polarizations and maintain a strong azimuthal dependence—a result uniquely attributable to the circular PDE, where the photon momentum acts as an applied in-plane field stationary in the laboratory frame. Our results demonstrate new levels of control over the magnitude and direction of photocurrents in TIs and that the study of single-domain films is crucial to reveal hidden phenomena that couple topological order and crystal symmetries.

en: Emergence of threefold symmetric helical photocurrents in epitaxial low twinned Bi₂Se₃

electronic-structure

display_name: electronic-structure

experimental

display_name: experimental

photon-drag-effect

display_name: photon-drag-effect

spectroscopy

display_name: spectroscopy

terahertz

display_name: terahertz

topological-materials

display_name: topological-materials


en: A catalyst possessing a broad substrate scope, in terms of both turnover and enantioselectivity, is sometimes called "general". Despite their great utility in asymmetric synthesis, truly general catalysts are difficult or expensive to discover via traditional high-throughput screening and are, therefore, rare. Existing computational tools accelerate the evaluation of reaction conditions from a pre-defined set of experiments to identify the most general ones, but cannot generate entirely new catalysts with enhanced substrate breadth. For these reasons, we report an inverse design strategy based on the open-source genetic algorithm NaviCatGA and on the OSCAR database of organocatalysts to simultaneously probe the catalyst and substrate scope and optimize generality as primary target. We apply this strategy to the Pictet–Spengler condensation, for which we curate a database of 820 reactions, used to train statistical models of selectivity and activity. Starting from OSCAR, we define a combinatorial space of millions of catalyst possibilities, and perform evolutionary experiments on a diverse substrate scope that is representative of the whole chemical space of tetrahydro-β-carboline products. While privileged catalysts emerge, we show how genetic optimization can address the broader question of generality in asymmetric synthesis, extracting structure–performance relationships from the challenging areas of chemical space.

en: A genetic optimization strategy with generality in asymmetric organocatalysis as primary target

catalysis

display_name: catalysis

enantioselectivity

display_name: enantioselectivity

generality

display_name: generality

genetic-optimization

display_name: genetic-optimization

machine-learning

display_name: machine-learning

nccr-catalysis

display_name: nccr-catalysis

organic-molecules

display_name: organic-molecules

organocatalysis

display_name: organocatalysis


en: Raman spectroscopy is a widely-used non-destructive material characterization method, which provides information about the vibrational modes of the material and therefore of its atomic structure and chemical composition. Raman spectra can be simulated using atomistic first-principles methods but these are computationally demanding and thus the existing databases of computational Raman spectra are fairly small. We developed an optimized workflow to efficiently calculate the Raman tensors, from which the Raman spectra can be straightforwardly simulated. The workflow was benchmarked and validated by comparison to experiments and previous computational methods for select technologically relevant material systems. Using the workflow, we performed high-throughput calculations for a large set of materials (5099) belonging to many different material classes, and collected the results to a database.

en: High-throughput computation of Raman spectra from first principles

density-functional-theory

display_name: density-functional-theory

high-throughput

display_name: high-throughput

raman-tensors

display_name: raman-tensors


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: Hydroxyapatite (HA, Ca10PO4(OH)2) is a widely explored material in the experimental domain of biomaterials science, because of its resemblance with natural bone minerals. Specifically, in the bioceramic community, HA doped with multivalent cations (e.g., Mg+2, Fe+2, Sr+2, etc.) has been extensively investigated in the last few decades. Experimental research largely established the critical role of dopant content on the changes in mechanical and biocompatibility properties. The plethora of experimental measurements of mechanical response on doped HA is based on compression or indentation testing of polycrystalline materials. Such measurements, as well as computational predictions of me,  on single crystalline (doped) HA are scarce. On that premise, the present study aims to build atomistic models of Fe2+-doped HA, a model system, with varying Fe content (10, 20, 30, and 40 mol%) and to explore their uniaxial tensile response by means of molecular dynamics (MD) simulation, together with the calculation of IR spectrum. In the equilibrated unit cell structures, Ca(1) sites were found to be energetically favourable for Fe2+ substitution. The local distribution of Fe2+ ions significantly affect the atomic partial charge distribution and chemical symmetry surrounding the functional groups. These signatures are reflected in the significant decrease in the intensity of IR peaks and are found in the Fe-doped HA, together with peak splitting because of the symmetry change in the crystal structure. Another important objective of this work is to computationally predict the mechanical response of doped HA in their single crystal format. An interesting observation is that the elastic anisotropy of undoped HA was not compromised with Fe-doping. Tensile strength (TS) is systematically reduced in doped HA with Fe+2 dopant content and a decrease in TS with temperature can be attributed to the increased thermal agitation of atoms at elevated temperatures. The physics of the tensile response was rationalized in terms of the strain dependent changes in covalent/ionic framework (Ca-P distance, P-O bond strain, O-P-O angular strain, O-H bond distance). Further, the dynamic changes in covalent bond network were energetically analyzed by calculating the changes in O-H and P-O bond vibrational energy. Summarizing, the current work develops our foundational understanding of the atomistic phenomena involved in the phase stability and tensile response of Fe-doped HA single crystals.

en: In silico study on probing atomistic insight into structural stability and tensile properties of Fe-doped hydroxyapatite single crystals

hydroxyapatite

display_name: hydroxyapatite

iron-doping

display_name: iron-doping

md-simulation

display_name: md-simulation

mechanical-response

display_name: mechanical-response


en: We present a first-principles method to calculate electron-phonon coupling elements in atomic systems, and showcase its application to the evaluation of the phonon-limited mobility of n-type single-layer MoS₂. The method combines a density functional theory (DFT) plane-wave supercell approach with a real-space maximally localized Wannier basis. It enables the calculation of electronic structure, phonon displacements with their corresponding frequencies, and real-space electron-phonon coupling elements on the same footing, without the need for density functional perturbation theory (DFPT) or Wannier interpolation. We report a low-field, intrinsic mobility of 274 cm²/Vs at room temperature for MoS₂, and highlight its dependence on carrier density and temperature. In addition, we compare our findings to the latest available modeling data and put them in perspective with the experimentally measured values. Based on these observations, the mobilities presented in this work appear to be compatible with experimental results, when taking into account other scattering sources. Hence, the proposed approach provides a reliable framework for mobility calculations that can be extended towards large-scale device simulations.

en: Electron-phonon calculations using a wannier-based supercell approach: applications to the monolayer MoS₂ mobility

ab-initio

display_name: ab-initio

carrier-transport

display_name: carrier-transport

dft

display_name: dft

electron-mobility

display_name: electron-mobility

electron-phonon-coupling

display_name: electron-phonon-coupling

snsf

display_name: snsf


en: Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics. However, low carrier mobility in 2DM transistors driven by phonon scattering remains a critical challenge. To address this issue, we propose the controlled introduction of localized tensile strain as an effective mean to inhibit electron-phonon scattering in 2DM. Strain is achieved by conformally adhering the 2DM via van-der-Waals forces to a dielectric layer previously nanoengineered with a gray-tone topography. Our results show that monolayer MoS₂ FETs under tensile strain achieve an 8-fold increase in on-state current, reaching mobilities of 185 cm²/Vs at room temperature, in good agreement with theoretical calculations. The present work on nanotopographic grayscale surface engineering and the use of high-quality dielectric materials has the potential to find application in the nanofabrication of photonic and nanoelectronic devices. Here we report the main data and codes needed to reproduce the theoretical findings of this work.

materialscloud

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

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

en: Materials Cloud

en: Deterministic grayscale nanotopography to engineer mobilities in strained MoS₂ FETs

density-functional-theory

display_name: density-functional-theory

first-principles

display_name: first-principles

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

envi

en: Environment

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:
We use a combination of symmetry analysis, phenomenological modeling, and first-principles density functional theory to explore the interplay between the magnetic ground state and the detailed atomic structure in the hexagonal rare-earth manganites. We find that the magnetic ordering is sensitive to a breathing mode distortion of the Mn and O ions in the ab plane, which is described by the K1 mode of the high-symmetry structure. Our density functional calculations of the magnetic interactions indicate that this mode particularly affects the single-ion anisotropy and the interplanar symmetric exchanges. By extracting the parameters of a magnetic model Hamiltonian from our first-principles results, we develop a phase diagram to describe the magnetic structure as a function of the anisotropy and exchange interactions. This in turn allows us to explain the dependence of the magnetic ground state on the identity of the rare-earth ion and on the K1 mode.
The attached files contain VASP input files and bash scripts for running all the DFT calculations in the manuscript.

en: Influence of the triangular Mn-O breathing mode on magnetic ordering in multiferroic hexagonal manganites

dftu

display_name: dftu

erc

display_name: erc

marvel

display_name: marvel


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

kagome-metal

display_name: kagome-metal

muon-spin-spectroscopy

display_name: muon-spin-spectroscopy


en: Magnetic materials can display many solutions to the electronic-structure problem, corresponding to different local or global minima of the energy functional. In Hartree-Fock or density-functional theory different single-determinant solutions lead to different magnetizations, ionic oxidation states, hybridizations, and inter-site magnetic couplings. The vast majority of these states can be fingerprinted through their projection on the atomic orbitals of the magnetic ions. We have devised an approach that provides an effective control over these occupation matrices, allowing us to systematically explore the landscape of the potential energy surface. We showcase the emergence of a complex zoology of self-consistent states; even more so when semi-local density-functional theory is augmented - and typically made more accurate - by Hubbard corrections. Such extensive explorations allow to robustly identify the ground state of magnetic systems, and to assess the accuracy (or not) of current functionals and approximations

en: The energy landscape of magnetic materials

high-throughput

display_name: high-throughput

openmodel

display_name: openmodel


en: In contrast to inorganic quantum wells, hybrid quantum wells (HQWs) based on metal-organic semiconductors are characterized by relatively soft lattices, in which excitonic states can strongly couple to lattice phonons. Therefore, understanding the lattice's impact on exciton dynamics is essential for harnessing the optoelectronic potential of HQWs. Beyond 2D metal halide perovskites, layered metal-organic chalcogenides (MOCs) are an air-stable, underexplored material class hosting room-temperature excitons that could be exploited as photodetectors, light emitting devices, and ultrafast photoswitches. Here, we elucidate the role of phonons in the optical transitions of the prototypical MOC [AgSePh]∞. Impulsive stimulated Raman scattering (ISRS) allows us to detect coherent exciton oscillations driven by Fröhlich interaction with low-energy optical phonons. Steady state absorption and Raman spectroscopies reveal a strong exciton-phonon coupling (Huang-Rhys parameter ~1.7) and its anharmonicity, manifested as non-trivial temperature-dependent Stokes shift. Our ab initio calculations support these observations, hinting at an anharmonic behavior of the low-energy phonons < 200 cm⁻¹. Our results untangle complex exciton-phonon interactions in MOCs, establishing an ideal testbed for room-temperature many-body phenomena.

en: Anharmonic exciton-phonon coupling in metal-organic chalcogenides hybrid quantum wells

exciton-phonon-coupling

display_name: exciton-phonon-coupling

metal-organic-chalcogenides

display_name: metal-organic-chalcogenides

raman-spectroscopy

display_name: raman-spectroscopy


en: The α/β interface is central to the microstructure and mechanical properties of titanium alloys. We investigate the structure, thermodynamics and migration of the coherent and semicoherent Ti α/β interfaces as a function of temperature and misfit strain via molecular dynamics (MD) simulations, thermodynamic integration and an accurate, DFT-trained Deep Potential. The structure of an equilibrium semicoherent interface consists of an array of steps, an array of misfit dislocations, and coherent terraces. Analysis determines the dislocation and step (disconnection) array structure and habit plane. The MD simulations show the detailed interface morphology dictated by intersecting disconnection arrays. The steps are shown to facilitate α/β interface migration, while the misfit dislocations lead to interface drag; the drag mechanism is different depending on the direction of interface migration. These results are used to predict the nature of α phase nucleation on cooling through the α-β phase transition.

en: Coherent and semicoherent interfaces in titanium: structure, thermodynamics, migration

free-energy

display_name: free-energy

molecular-dynamics-simulation

display_name: molecular-dynamics-simulation

titanium-interfaces

display_name: titanium-interfaces


en: Topological data analysis based on persistent homology has been applied to the molecular dynamics simulation for the fast ion-conducting phase (α-phase) of AgI, to show its effectiveness on the ion-migration mechanism analysis. Time-averaged persistence diagrams of α-AgI, which quantitatively records the shape and size of the ring structures in the given atomic configurations, clearly showed the emergence of the four-membered rings formed by two Ag and two I ions at high temperatures. They were identified as common structures during the Ag ion migration. The averaged potential energy change due to the deformation of four-membered ring agrees well with the activation energy calculated from the conductivity Arrhenius plot. The concerted motion of two Ag ions via the four-membered ring was also successfully extracted from molecular dynamics simulations by our approach, providing the new insight into the specific mechanism of the concerted motion.

en: Topological data analysis of superionic conductor silver iodide

ion-migration

display_name: ion-migration

persistence-diagram

display_name: persistence-diagram


en:
Super-resolution microscopy has become a powerful tool to investigate the internal structure of complex colloidal and polymeric systems, such as microgels, at the nanometer scale. An interesting feature of this method is the possibility of monitoring microgel response to temperature changes in situ. However, when performing advanced microscopy experiments, interactions between the particle and the environment can be important. Often microgels are deposited on a substrate, since they have to remain still for several minutes during the experiment. In the publication associated with this data, we use direct stochastic optical reconstruction microscopy (dSTORM) and advanced coarse-grained molecular dynamics simulations to investigate how individual microgels anchored on hydrophilic and hydrophobic surfaces undergo their volume phase transition with temperature. We find that, in the presence of a hydrophilic substrate, the structure of the microgel is unperturbed and the resulting density profiles quantitatively agree with simulations performed under bulk conditions. Instead, when a hydrophobic surface is used, the microgel spreads at the interface and an interesting competition between the two hydrophobic strengths, monomer–monomer vs monomer–surface, comes into play at high temperatures.
The data deposited on the Materials Cloud Archive contains the initial microgel configuration in LAMMPS read format, the calculated radii and the density profiles under the different temperatures and surfaces.

materialscloud

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

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

en: Materials Cloud

en: Probing temperature responsivity of microgels and its interplay with a solid surface by super-resolution microscopy and numerical simulations

cineca-iscra

display_name: cineca-iscra

experimental

display_name: experimental

microgels

display_name: microgels

molecular-dynamics

display_name: molecular-dynamics

volume-phase-transition

display_name: volume-phase-transition


en: Fracture dictates the service limits of metallic structures. Damage tolerance of materials may be characterized by fracture toughness rigorously developed from fracture mechanics, or less rigorous yet more easily obtained impact toughness (or impact energy as a variant). Given the promise of high-entropy alloys (HEAs) in structural and damage-tolerance applications, we compiled a dataset of fracture toughness and impact toughness/energy from the literature till mid-2022. The dataset is subdivided into three categories, i.e., fracture toughness, impact toughness, and impact energy, which contain 148, 14, and 78 distinct data records, respectively. On top of the alloy chemistry and measured fracture quantities, each data record also records the factors influential to fracture. Examples are material processing history, phase structure, grain size, uniaxial tensile properties such as yield strength and elongation, and testing conditions.

en: Dataset for fracture and impact toughness of high-entropy alloys

envi

en: Environment

fracture-toughness

display_name: fracture-toughness

high-entropy-alloys

display_name: high-entropy-alloys

impact-energy

display_name: impact-energy

impact-toughness

display_name: impact-toughness


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

en: Mechanism of charge transport in lithium thiophosphate

electrical-conductivity

display_name: electrical-conductivity

green-kubo-time-correlation-functions

display_name: green-kubo-time-correlation-functions

lithium-ion-diffusion

display_name: lithium-ion-diffusion

lithium-thiophosphate

display_name: lithium-thiophosphate

machine-learning

display_name: machine-learning

marvel

display_name: marvel

phase-transitions

display_name: phase-transitions

post-gga-density-functional-theory

display_name: post-gga-density-functional-theory

snsf-sinergia

display_name: snsf-sinergia


en: Kagome metals have emerged as pivotal materials in condensed matter physics due to their unique geometric arrangement and intriguing electronic properties. Understanding the origin of magnetism in these materials, particularly in iron rich Fe-Sn binary compounds like Fe₃Sn, holds a significant importance, as they represent potential candidates for permanent magnets with a high Curie temperature and a strong magnetic anisotropy. In the present study, we employ density-functional theory and dynamical mean-field theory to analyze the electronic structure and magnetic properties of Fe₃Sn. Our investigation reveals the presence of several nearly-flat bands and Weyl nodes at low excitation energies. The inclusion of local correlation effects is shown to push these features even closer to the Fermi energy, which may be important for their manipulation via external stimuli. Regarding magnetism, the Hubbard-like interaction leads to an increase of orbital polarization at the expenses of a minor reduction of the spin moment. The magnetic anisotropy energy exhibits a strong dependence on the particular choice of the Coulomb interaction parameters. Additionally, our detailed analysis of the interatomic exchange interactions indicates a significant contribution from the antisymmetric exchange, i.e. the Dzyaloshinskii-Moriya interaction, which showcases the existence of magnetic chirality in the system. Overall, our investigation highlights a strong interplay between the flat bands near the Fermi level, the local Coulomb interaction and the triangular geometry of the lattice, which plays a crucial role in driving the magnetic properties of this material.

en: Exploring strong electronic correlations in the breathing kagome metal Fe₃Sn

dftdmft

display_name: dftdmft

dzyaloshinskii-moriya-interaction-dmi

display_name: dzyaloshinskii-moriya-interaction-dmi

electronic-structure

display_name: electronic-structure

flat-band

display_name: flat-band

kagome-metal

display_name: kagome-metal

magnetism

display_name: magnetism


en: The dataset provides records of tensile properties of nuclear structural materials. The focus is on studying the influence of specimen dimensions and geometry on mechanical properties such as yield strength, ultimate tensile strength, uniform elongation, and total elongation. The dataset was created through an extensive literature review of scientific articles and databases. The search inclusion criteria targeted peer-reviewed studies on tensile testing of sub-sized specimens, providing quantitative data on tensile properties relative to specimen size. The extracted data points from the literature review were organized into a tabular format database containing 1,070 tensile testing records with 54 parameters, including material type and composition, manufacturing information, irradiation conditions, specimen size and dimensions, and tensile properties. Materials science experts conducted systematic checks to validate the collected data, ensuring accuracy in the material type, manufacturing processes and treatment methods, and testing conditions, as well as verifying the chemical composition and other pertinent information. Our team performed statistical analyses to identify and address data outliers, ensuring the reliability of the dataset.

en: Dataset of tensile properties for sub-sized specimens of nuclear structural materials

nuclear-structural-materials

display_name: nuclear-structural-materials

specimen-size-effect

display_name: specimen-size-effect

sub-sized-specimens

display_name: sub-sized-specimens

tensile-properties

display_name: tensile-properties


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

activated-carbon

display_name: activated-carbon

dft

display_name: dft

pfas

display_name: pfas


en: The thermoresponsiveness of polymer-based soft materials opens perspectives in many applicative fields. This property in hydrated systems has the simple origin of a reversible de-mixing across a lower critical solution temperature, and has been explored for several chemically different amphiphilic polymers, each of them with specific critical conditions and phase behaviours. This work investigates for the first time by extensive atomistic molecular dynamics simulations the temperature dependence of the infinitely diluted aqueous solution of two such thermoresponsive macromolecules, poly(N-isopropyl-methacrylamide), PNIPMAM, and poly(2-isopropyl-2-oxazoline), PIPOX, in comparison to poly(N-isopropylacrylamide), PNIPAM, the much-more studied prototype system for polymers exhibiting a lower consolute boundary in water. The evolution of conformation and hydration water of the macromolecules is detected in a temperature range from well-below to well-above the transition temperature, with a favourable comparison to available experimental data. The resulting molecular description provides an explanation for deviations in solution properties of these macromolecules, including the effect of chaotropic anions and of solvent isotopic composition on the value of the lower critical solution temperature and the transition enthalpy. Overall, simulation findings show how the trade-off between gain in translational entropy of water molecules, associated with the reduction in solvent-excluded volume during the transition, and polymer-specific conformational features, determines the temperature response of these macromolecules in aqueous solution. In light of this molecular characterisation, a correlation between the single chain behaviour across the transition and the type I or type II phase diagram of the polymer aqueous solution can be postulated.

en: Understanding the lower critical solution temperature of amphiphilic synthetic polymers in water: the role of conformation and hydration

coil-to-globule-transition

display_name: coil-to-globule-transition

hydration-water

display_name: hydration-water

lcst

display_name: lcst

thermoresponsive-polymers

display_name: thermoresponsive-polymers


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

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: 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.

materialscloud

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

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

en: Materials Cloud

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: Defect engineering in two-dimensional semiconductors has been exploited to tune the optoelectronic properties and introduce new quantum states in the band gap. Chalcogen vacancies in transition metal dichalcogenides in particular have been found to strongly impact charge carrier concentration and mobility in 2D transistors as well as feature subgap emission and single-photon response. In this Letter, we investigate the layer-dependent charge-state lifetime of Se vacancies in WSe2. In one monolayer WSe2,we observe ultrafast charge transfer from the lowest unoccupied orbital of the top Se vacancy to the graphene substrate within 1 ± 0.2 ps measured via the current saturation in scanning tunneling approach curves. For Se vacancies decoupled by transition metal dichalcogenide (TMD) multilayers, we find a subexponential increase of the charge lifetime from 62 ±14 ps in bilayer to a few nanoseconds in four-layer WSe2, alongside a reduction of the defect state binding energy. Additionally, we attribute the continuous suppression and energy shift of the dI=dV in-gap defect state resonances at very close tip-sample distances to a current saturation effect. Our results provide a key measure of the layer-dependent charge transfer rate of chalcogen vacancies in TMDs.

en: Layer-dependent charge-state lifetime of single Se vacancies in WSe2

envi

en: Environment

defect-engineering

display_name: defect-engineering

scanning-tunneling-microscopy-stm

display_name: scanning-tunneling-microscopy-stm

transition-metal-dichalcogenide-tmd

display_name: transition-metal-dichalcogenide-tmd


en:
Phonon interactions from lattice anharmonicity govern thermal properties and heat transport in materials.These interactions are described by n-th order interatomic force constants (n-IFCs), which can be viewed as high-dimensional tensors correlating the motion of n atoms, or equivalently encoding n-phonon scattering processes in momentum space. Here, we introduce a tensor decomposition to efficiently compress n-IFCs for arbitrary order n. Using tensor learning, we find optimal low-rank approximations of n-IFCs by solving the resulting optimization problem. Our approach reveals the inherent low dimensionality of phonon-phonon interactions and allows compression of the 3 and 4-IFC tensors by factors of up to 10^3-10^4 while retaining high accuracy in calculations of phonon scattering rates and thermal conductivity. Calculations of thermal conductivity using the compressed n-IFCs achieve a speed-up by nearly three orders of magnitude with >98% accuracy relative to the reference uncompressed solution. These calculations include both 3- and 4-phonon scattering and are shown for a diverse range of materials (Si, HgTe, MgO, TiNiSn and monoclinic ZrO2).  In addition to accelerating state-of-the-art thermal transport calculations, the method shown here paves the way for modeling strongly anharmonic materials and higher-order phonon interactions.

This data contains the phonon scattering rates data with full and compressed phonon-phonon interactions. The data corresponds to Figure 3 in the paper and includes information on the phonon scattering rates for two materials: silicon and HgTe.

en: Phonon scattering rates data for silicon and HgTe

phonon-phonon-interactions

display_name: phonon-phonon-interactions

phonon-scattering-rate

display_name: phonon-scattering-rate

thermal-transport

display_name: thermal-transport


en:
GapExtractor v2.0© is a free software designed to determine the band gap energy of non-translucent samples by analyzing their diffuse reflectance spectra. The analysis is based on the Tauc-method and the Kubelka and Munk formalism. The algorithm is coded in the Python 3.11.5 programming language. By coping, running or distributing this software, you indicate your acceptance of the license terms.

Steps to reproduce: Unzip GapExtractor v2.0 file; run gapextractor_v2.0.py; check the required phyton libraries; install if necessary.

en: GapExtractor v2.0

band-gap-energy

display_name: band-gap-energy

diffuse-reflectance-spectroscopy

display_name: diffuse-reflectance-spectroscopy

polyphasic-samples

display_name: polyphasic-samples

tauc-method

display_name: tauc-method


en: Gallium nitride (GaN) is a wide-bandgap semiconductor of significant interest for applications in solid-state lighting, power electronics, and radio-frequency amplifiers. An important limitation of this semiconductor is its low intrinsic hole mobility, which hinders the development of p-channel devices and the large-scale integration of GaN CMOS in next-generation electronics. Prior research has explored the use of strain to improve the hole mobility of GaN, but a systematic analysis of all possible strain conditions and their impact on the mobility is lacking. In this study, we introduce a piezomobility tensor notation to characterize the relationship between applied strain and hole mobility in GaN. To map the strain-dependence of the hole mobility, we solve the ab initio Boltzmann transport equation, accounting for electron-phonon scattering and GW quasiparticle energy corrections.

en: Design of high-mobility p-type GaN via the piezomobility tensor

electron-phonon-coupling

display_name: electron-phonon-coupling

hole-mobility

display_name: hole-mobility

nitrides

display_name: nitrides


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

flexibility

display_name: flexibility

liquidsolid-friction

display_name: liquidsolid-friction

machine-learning-potential

display_name: machine-learning-potential


en: ZnO nanoparticle powders are an important and common starting material for functional devices that require the highest purity for electronic and optical applications. In this combined ab initio and experimental study, we use electron paramagnetic resonance (EPR) spectroscopy to detect shallow donor states in the ZnO lattice via their characteristic EPR resonance at g = 1.96. Using DFT calculations that account for the chemical environment and the high temperatures during the gas-phase synthesis in conjunction with control experiments with atomic hydrogen, we show that these paramagnetic defects correspond to neutral hydrogenated oxygen sites (OHO0). As a key implication of these findings, ZnO particle powders, although produced under pure gas-phase synthesis conditions and subsequently annealed in vacuum to 873 K, were found to be doped with hydrogen at a base concentration of 10-5 at% and higher. This, in turn, highlights the often-overlooked role of unwanted hydrogen in nanoscale ZnO as components for applications in optics, electronics, and sensing.

en: Ubiquitous shallow trap states and lattice hydrogenation of ZnO particles

defect

display_name: defect

hydrogen

display_name: hydrogen

zno

display_name: zno


en:
A mathematical parameter is proposed to describe the p-p-s electronic coupling strength in transition metal dichalcogenides (TMDCs). Two key descriptors, Iband(p−s)Iband(p−s) and Cband(p−p′)Cband(p−p′), are defined as follows:

Iband(p−s)=ϵp−ϵsϵp,Cband(p−p′)=ϵp′−ϵpϵp′Iband(p−s)=ϵpϵp−ϵs,Cband(p−p′)=ϵp′ϵp′−ϵp

where ϵϵ represents the p-band or s-band center positions of the atoms. Here, pp, p′p′, and ss refer to the p-band of the doped anion atom, the p-band of the first neighboring six S/Se atoms around the doped anion atom, and the s-band of Li atoms, respectively. Iband(p−s)Iband(p−s) characterizes the energy gap between the doped TMDCs and lithium polysulfides (LiPS), where a smaller value indicates a reduced band center energy gap, leading to enhanced interfacial electron transfer dynamics and a stronger interaction between the doped TMDCs and LiPS. On the other hand, Cband(p−p′)Cband(p−p′) quantifies the coupling strength between the p-band of the doped anion atoms and the neighboring S/Se atoms, where a smaller value indicates stronger coupling.

The relationship between the Gibbs energy barrier (ΔGΔG) and the coupling descriptors Iband(p−s)Iband(p−s) and Cband(p−p′)Cband(p−p′) is established through a machine learning approach, represented as:

ΔGi=f(Iband(i)(p−s),Cband(i)(p−p′))ΔGi=f(Iband(i)(p−s),Cband(i)(p−p′))

The model demonstrates that Iband(p−s)Iband(p−s) and Cband(p−p′)Cband(p−p′) effectively capture the relationship between the p-p-s coupling strength and the Gibbs free energy barrier, with a fitting result achieving an average Root Mean Square Error (RMSE) of approximately 0.07 eV.

en: A machine-learning (ML) assisted approach revealing p-p-s electronic coupling descriptor

catalytic-activity

display_name: catalytic-activity

electronic-coupling

display_name: electronic-coupling

li-s-batteries

display_name: li-s-batteries

machine-learning-prediction

display_name: machine-learning-prediction


en:
A molecular level understanding of surface chemistry involved in the focused electron beam induced deposition (FEBID) with metalorganic molecules is crucial for enhancing metal content in the nanostructures. Here we investigate the FEBID process of trimethyl(methylcyclopentadienyl)platinum(IV) [MeCpPtMe₃] using focused electron beam induced mass spectrometry (FEBiMS), a recently developed in situ analytical technique. A comparison with gas-phase electron impact fragmentation, along with density-functional-theoretical calculations and molecular dynamics simulations are presented. The results indicate that charged fragments generated via dissociative ionization exhibit strong adsorption to the substrate and lack sufficient kinetic energy to desorb, suggesting that the most observed charged species during FEBID originate from gasphase fragmentation above the surface. Furthermore, we propose processes like charge neutralization and dissociative recombination, mechanisms not previously considered in FEBID, could be significant contributors for increasing metal content in the resulting nanostructures.

The data is discussed in the study "C. S. Jureddy, J. Jurczyk, K. Mackosz, H. Lyschuk, J. Kocisek, P. Weber, M. Ernst, A. Verkhovtsev, A. V. Solov'yov, J. Fedor and I. Utke, Phys. Chem. Chem. Phys., 2025"

materialscloud

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

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

en: Materials Cloud

en: Desorption of fragments upon electron impact on adsorbates: implications for electron beam induced deposition

dft

display_name: dft

experimental

display_name: experimental

febid

display_name: febid

molecular-dynamics

display_name: molecular-dynamics

surface-and-gas-phase-processes

display_name: surface-and-gas-phase-processes


en: The inner structure of polymeric microgels critically influences their responsiveness and potential applications, yet remaining challenging to resolve at molecular resolution. In this work, a structural characterization of thermoresponsive copolymer microgels is provided by integrating small-angle neutron scattering (SANS), dynamic light scattering (DLS), and nuclear magnetic resonance (NMR) measurements with multi-scale simulations. Specifically, Poly(N-isopropylacrylamide-co-N-isopropylmethacrylamide), P(NIPAM-co-NIPMAM), copolymer microgels, in which a random monomer distribution is conventionally assumed, are considered. By synthesizing different samples, including isotopically labeled microgels via selective deuteration, the microgels swelling behavior is probed and distinct polymer-specific signatures are revealed. To elucidate their internal distribution, monomer-resolved microgel simulations are performed across different copolymer models. A direct comparison between experimental and numerical form factors provides evidence of preferential organization into block structures, challenging the prevailing view of random distribution. 13C-NMR experiments confirm NIPAM-rich blocks and atomistic simulations link this unexpected block-like architecture to distinct local hydrogen-bonding patterns. This integrated approach provides the first direct evidence of preferential block formation in P(NIPAM-co-NIPMAM) microgels. Beyond this system, these results establish a generalizable strategy for unveiling hidden structural order in copolymer microgels, offering new strategies to tailor their design and to enhance control of material responsivity.

en: Thermoresponsive copolymer microgels synthesized via single-step precipitation polymerization: random or block structure?

envi

en: Environment

copolymerization

display_name: copolymerization

microgels

display_name: microgels

molecular-modeling

display_name: molecular-modeling

nmr-spectroscopy

display_name: nmr-spectroscopy

selective-neutron-scattering

display_name: selective-neutron-scattering


en:
Traditional atomistic machine learning (ML) models serve as surrogates for quantum mechanical (QM) properties, predicting quantities such as dipole moments and polarizabilities, directly from compositions and geometries of atomic configurations. With the emergence of ML approaches to predict the "ingredients" of a QM calculation, such as the ground state charge density or the effective single-particle Hamiltonian, it has become possible to obtain multiple properties through analytical physics-based operations on these intermediate ML predictions. We present a framework to seamlessly integrate the prediction of an effective electronic Hamiltonian, for both molecular and condensed-phase systems, with PySCFAD, a differentiable QM workflow. This integration facilitates training models indirectly against functions of the Hamiltonian such as electronic energy levels, dipole moments, polarizability, etc. We then use this framework to explore various possible choices within the design space of hybrid ML/QM models, examining the influence of incorporating multiple targets on model performance and learning a reduced-basis ML Hamiltonian that can
reproduce targets computed from a much larger basis. Our benchmarks evaluate the accuracy and transferability of these hybrid models, compare them against predictions of atomic properties from their surrogate models, and provide indications to guide the design of the interface between the ML and QM components of the model. For our benchmarks we have used a subset of the QM7 and QM9 datasets as well as two extrapolative datasets for long chain polyalkenes/acenes and polyenoic acid series, along with a small graphene dataset.

en: Exploring the design space of machine-learning models for quantum chemistry with a fully differentiable framework

automatic-differentiation

display_name: automatic-differentiation

hamiltonian

display_name: hamiltonian

machine-learning

display_name: machine-learning


en: Cobalt-based oxides have been investigated as potential alternatives to Ir/Ru-based oxides for catalyzing the oxygen evolution reaction (OER) in acidic media. Past research, however, is mainly focused on the spinel oxide structure so far. Exploring alternative crystal structures is essential for expanding the material library and developing highly efficient OER catalysts for acidic environments. As a proof of concept, we demonstrate that Co-based perovskite oxides can drive acidic OER effectively. Appling hard/soft X-ray absorption spectroscopy (hXAS/sXAS) characterizations, we show that the La and Ce doped SrCoO3 (denoted as LSC and CSC, respectively) have a bulk-average Co oxidation state close to 3+ and surface-dominant low-spin CoIII species. Electrochemical analysis reveals that they only show one Co redox pair, similar to CoOOH in acidic environments. The recorded Tafel slopes are around ~65 mV dec-1, comparable to the benchmarking Ir/Ru-based catalysts. The combination of the spectroscopic and electrochemical findings presented here highlights the important role of low-spin CoIII species in catalyzing OER in acidic environments and contributes to the rational design of non-noble metal OER catalysts.

en: Cobalt-based perovskite oxides as catalysts for acidic oxygen evolution reaction

acidic-oxygen-evolution-reaction

display_name: acidic-oxygen-evolution-reaction

cobalt-based-catalysts

display_name: cobalt-based-catalysts

cobalt-oxidation-state

display_name: cobalt-oxidation-state

perovskite-oxides

display_name: perovskite-oxides

x-ray-adsorption-spectroscopy

display_name: x-ray-adsorption-spectroscopy


en: The intrinsic stress in nanomultilayers (NMLs) is typically dominated by interface stress, which is particularly high in immiscible Cu/W NMLs. Here, atomistic simulations with a chemically-accurate neural network potential reveal the role of interfacial intermixing and metastable phase formation on the interface stress levels.  These results rationalize an experimentally-reported compressive-to-tensile transition as a function of NML deposition conditions and the extremely high interface stresses under some conditions.

en: Uncovering the origin of interface stress enhancement and compressive-to-tensile stress transition in immiscible nanomultilayers

cuw-nanomultilayers

display_name: cuw-nanomultilayers

interface-stress

display_name: interface-stress

intermixing

display_name: intermixing

metastable-phases

display_name: metastable-phases

molecular-statics

display_name: molecular-statics


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:
Dual function materials (DFMs) enable reactive carbon capture (RCC), an intensified approach to carbon dioxide capture and utilization for cost and energy input reductions. Yet, there is a fundamental lack of understanding of mechanisms around CO2 adsorption and subsequent conversion on these materials, hindering further development. Herein, we investigated several supported alkaline metal oxides for their CO2 adsorption characteristics to find that Na/Al2O3 had the highest CO2 adsorption capacity, accompanied by a variety of CO2 adsorption geometries as identified by in situ DRIFTS and computational modeling. The addition of catalytic metals (Ru, Pd) increased the adsorption capacity of Na/Al2O3 without altering binding modes. In the subsequent reactive desorption step, acetate and formate intermediates were observed. Notably, this mechanistic investigation identified that the formation of acetate species was unique to RCC on a DFM, as these species were not observed in co-fed hydrogenation over the DFM or RCC over a Na-free catalyst.

Herein, we share the structural CONTCARs obtained using periodic PBE calculations in VASP for hydrated (110) and (100) surfaces of gamma-alumina, Na2O-modified surface models for Na/Al2O3, subsequent structures of various surface carbonate (CO3*) and bicarbonate (HCO3*) configurations formed on each of these surfaces upon CO2 adsorption and adsorbed acetate and formate radicals on the surfaces.

en: Identifying mechanistic differences between co-fed CO2 hydrogenation and reactive CO2 capture using Ru and Pd dual function materials

alumina

display_name: alumina

density-functional-theory

display_name: density-functional-theory

dfm

display_name: dfm

dft

display_name: dft

dual-function-material

display_name: dual-function-material

rcc

display_name: rcc

reactive-carbon-capture

display_name: reactive-carbon-capture


en: The total energy is a fundamental characteristic of solids, molecules, and nanostructures. In most first-principles calculations of the total energy, the nuclear kinetic operator is decoupled from the many-body electronic Hamiltonian and the dynamics of the nuclei is reintroduced afterwards. This two-step procedure introduced by Born and Oppenheimer (BO) is approximate. Energies beyond the electronic and vibrational (or phononic) main contributions might be relevant when small energy differences are important, such as when predicting stable polymorphs or describing magnetic energy landscape. We clarify the different flavors of BO decoupling and give an exact formulation for the total energy in the basis of BO electronic wavefunctions. Then, we list contributions, beyond the main ones, that appear in a perturbative expansion in powers of M0-1/4, where M0 is a typical nuclear mass, up to sixth order. Some of these might be grouped and denoted the electron-phonon contribution to total energy,  Eelph, that first appears at fourth order. The electronic inertial mass contributes at sixth order. We clarify that the sum of the Allen-Heine-Cardona zero-point renormalization of eigenvalues over occupied states is not the electron-phonon contribution to the total energy but a part of the phononic contribution. The computation of the lowest-order Eelph is implemented and shown to be small but non-negligible (3.8 meV per atom) in the case of diamond and its hexagonal polymorph. We also estimate the electronic inertial mass contribution and confirm the size-consistency of all computed terms.

materialscloud

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

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

en: Materials Cloud

en: In search of the electron-phonon contribution to total energy

ab-initio

display_name: ab-initio

diamond

display_name: diamond

electron-phonon-coupling

display_name: electron-phonon-coupling

total-energy

display_name: total-energy


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.

envi

en: Environment

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: This study employed density functional theory in combination with the Materials Project database to systematically screen the unexplored phase space of Ag–In–I double salts. High-throughput screening of the Ag–In–I ternary phase space reveals several stable and metastable compounds belonging to two distinct structural families: tetrahedrally and octahedrally coordinated phases, with characteristic band gaps of approximately 3.0 eV and 2.0 eV, respectively. Although these materials are unlikely to function as efficient photovoltaic absorbers, their tunable band gaps and favorable stability make them promising candidates for charge transport and other optoelectronic applications. This dataset contains the input and output files for all DFT and hybrid functional calculations, the theoretically predicted potential of each material as absorber layer under different lighting conditions, as computed by spectroscopic limited maximum efficiency metric, as well as the structures of the uniquely identified polymorphs. All data are organized such that files are grouped according to the figures in the main text, along with selected files from the supplementary material.

en: Computational screening and discovery of Silver–Indium Halide double salts.

computational-materials-desing

display_name: computational-materials-desing

high-throughput

display_name: high-throughput

indoor-photovoltaics

display_name: indoor-photovoltaics

perovskite-inspired-materials

display_name: perovskite-inspired-materials

solar-cells

display_name: solar-cells


en: The 𝛽-pyrochlore is a charge ice – each tetrahedron of the pyrochlore lattice is occupied by two Ni2+ and two Cr3+ according to an ice rule, resulting in fully packed same-species loops with power-law length distribution. Using inelastic neutron scattering and numerical simulations, we show that the spin dynamics can be well described by a model with three antiferromagnetic interaction strengths, one for Ni-Ni, Cr-Ni, and Cr-Cr interactions. Because the strengths of the two intra-loop interactions are quite different, the fluctuations of each type of loop can be identified in the spectrum. therefore forms an algebraic loop liquid in which power-law cation correlations control the spin dynamics. Our parameters predict a transition to spin nematic order with associated arrest of dynamics at 𝑇𝑛≈0.55 K, while we observe a freezing transition at 𝑇𝑓=2.3K. Measurements of magnetisation, ac and non-linear susceptibility show that this is not a canonical spin glass transition so we associate it with the development of slow dynamics due to inter-loop nematic correlations.

en: Supporting data for the paper "Algebraic loop liquid in the pyrochlore CsNiCrF6"

correlated-disorder

display_name: correlated-disorder

frustrated-magnetism

display_name: frustrated-magnetism

inelastic-neutron-scattering

display_name: inelastic-neutron-scattering


en: Photocatalytic water splitting has attracted considerable attention for renewable energy production. Since the first reported photocatalytic water splitting by titanium dioxide, this material remains one of the most promising photocatalysts, due to its suitable band gap and band-edge positions. However, predicting both of these properties is a challenging task for existing computational methods. Here we show how Koopmans spectral functionals can accurately predict the band structure and level alignment of rutile, anatase, and brookite TiO₂ using a computationally efficient workflow that only requires (a) a DFT calculation of the photocatalyst/vacuum interface and (b) a Koopmans spectral functional calculation of the bulk photocatalyst. The success of this approach for TiO₂ suggests that this strategy could be deployed for assessing the suitability of novel photocatalyst candidates. This record contains for each polymorph: (a) a calculation of a slab; (b) KI and pKIPZ band structure calculation of the bulk system.

en: Predicting the suitability of photocatalysts for water splitting using Koopmans spectral functionals: the case of TiO₂ polymorphs

electronic-structure

display_name: electronic-structure

koopmans-spectral--functionals

display_name: koopmans-spectral--functionals

orbital-density-dependent-functionals

display_name: orbital-density-dependent-functionals

photocatalysis

display_name: photocatalysis

water-splitting

display_name: water-splitting


en: We study the electronic structure and dynamical correlations in antiferromagnetic BiFeO3, a prototypical room-temperature multiferroic, using a variety of static and dynamical first-principles methods. Conventional static Hubbard corrections (DFT+U, DFT+U+V) incorrectly predict a deep-valence Fe 3d peak (around -7 eV) in antiferromagnetic BiFeO3, in contradiction with hard-X-ray photoemission. We resolve this failure by using a recent generalization of DFT+U to include a frequency-dependent screening – DFT+U(ω) – or using a dynamical Hubbard functional (dynH). The screened Coulomb interaction U(ω), computed with spin-polarized RPA and projected onto maximally localized Fe 3d Wannier orbitals, is expressed as a sum-over-poles, yielding a self-energy that augments the Kohn–Sham Hamiltonian. This DFT+U(ω) approach predicts a fundamental band gap of 1.53 eV, consistent with experiments, and completely eliminates the unphysical deep-valence peak. The resulting simulated HAXPES spectrum reproduces the experimental lineshape with an accuracy comparable to state-of-the-art approaches. Our work highlights the critical nature of dynamical screening in complex oxides and of DFT+U(ω) as a predictive and computationally efficient approach to address the electronic structure of correlated materials.

en: Electronic structure and dynamical correlations in antiferromagnetic BiFeO3

density-functional-theory

display_name: density-functional-theory

dynamical-correlations

display_name: dynamical-correlations


en:
This archive provides the AiiDA workflows, metadata, and computational datasets associated with the study of vibrational frequencies and Stark tuning rates at electrochemical interfaces within the framework of grand-canonical density functional theory (GC-DFT) combined with continuum electrochemical models.

In this work, the electrochemical potential is treated as a degree of freedom by adjusting the number of electrons in the Kohn-Sham equations, enabling simulations at fixed potential. Based on the relationship between free energy and grand potential, physical properties such as atomic forces, vibrational frequencies, and Stark tuning rates are consistently evaluated. While atomic forces are found to be equivalent to Hellmann-Feynman forces in the canonical ensemble, vibrational frequencies and Stark tuning rates exhibit distinct behavior under grand-canonical conditions.

The archive contains input parameters, workflows, and computed results obtained using finite-displacement methods for the evaluation of vibrational properties and Stark tuning rates. These data enable the reproduction of the results reported in the associated publication and provide a reference for future studies of electrochemical interfaces under constant potential conditions.

en: Vibrational frequencies and stark tuning rate with continuum electro-chemical models and grand canonical density functional theory

grand-canonical-dft

display_name: grand-canonical-dft

stark-tuning-rate

display_name: stark-tuning-rate

vibrational-frequencies

display_name: vibrational-frequencies


en: Niobium diselenide (NbSe2) has garnered significant attention due to the coexistence of superconductivity and charge density waves (CDWs) down to the monolayer limit. However, realistic modeling of CDWs—capturing effects such as layer number, twist angle, and strain—remains challenging due to the high computational cost of first-principles methods. Here, we develop a physically informed workflow for training machine-learning interatomic potentials (MLIPs) based on the E(3)-equivariant Allegro architecture, tailored to capture the subtle structural and dynamical signatures of CDWs in mono- and bilayer NbSe2. We find that while CDW lattice distortions are relatively easy to learn, modeling vibrational properties remains more challenging. It requires targeted dataset design and careful hyperparameter tuning, pushing the boundaries and testing the extensibility of current MLIP frameworks. Our MLIPs enable reliable simulations of commensurate and incommensurate CDW phases, including their sensitivity to dimensionality and stacking, as well as CDW dynamics, phonons, and transition temperatures estimated via the stochastic self-consistent harmonic approximation. This work opens new possibilities for studying and tuning CDWs in NbSe2 and other two-dimensional systems, with implications for electron-phonon coupling, superconductivity, and advanced materials design.

en: Exploring charge density waves in two-dimensional NbSe2 with machine learning

charge-density-waves

display_name: charge-density-waves

machine-learned-interatomic-potentials

display_name: machine-learned-interatomic-potentials