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

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

collective-behavior

display_name: collective-behavior

elasticity

display_name: elasticity

microgels

display_name: microgels


$oid: OBSOLETE

en:
Prediction of microstructure evolution during material processing is essential to control the material properties. Simulation tools for microstructure evolution prediction based on physical concepts are computationally expensive and time-consuming. Therefore, they are not practical when either there is an urgent need for microstructure morphology during the process, or there is a need to generate big microstructure datasets. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. We propose a Predictive Recurrent Neural Network (PredRNN) model for the microstructure prediction, which extends the inner-layer transition function of memory states in LSTMs to spatiotemporal memory flow. As a case study, we used a dataset from spinodal decomposition simulation of FeCrCo alloy created by the phase-field method for training and predicting future microstructures by previous observations. The results show that the trained network predicts quantitatively accurate microstructure morphologies while it is several orders of magnitude faster than the phase field method.
The trained model aims to generate future material microstructures by learning from the historical microstructures, where the visual dynamics are believed to have modular structures that can be learned with compositional subsystems. A PredRNN (https://github.com/thuml/predrnn-pytorch) model was trained to predict Fe-Cr-Co microstructures evolution during the spinodal decomposition.

en: Spatiotemporal prediction of microstructure evolution with predictive recurrent neural network

materialscloud

approval_status: approved

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

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

en: Materials Cloud

de: Materials Cloud

fr: Materials Cloud

it: Materials Cloud

political_level: other

state: active

type: organization

psi

capacity: public

type: dataset

key: guid

key: uri

value: DCAT Harvester Materials Cloud

envi

de: Umwelt

en: Environment

fr: Environnement

it: Ambiente

phase-field-spinodal-decomposition

display_name: phase-field-spinodal-decomposition


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

en: Mechanism of thermally-activated prismatic slip in Mg

magnesium

display_name: magnesium

marvel

display_name: marvel

neural-network-potential

display_name: neural-network-potential

prismatic-slip

display_name: prismatic-slip


en: 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: Augmented plane wave methods enable an efficient description of atom-centered or localized features of the electronic density, circumventing high energy cutoffs and thus prohibitive computational costs of pure plane wave formulations. To complement existing implementations for ground-state properties and excitation energies, we present the extension of the Gaussian and augmented plane wave method to excited-state nuclear gradients within the Tamm–Dancoff approximation of time-dependent density functional theory and its implementation in the CP2K program package. Benchmarks for a test set of 35 small molecules demonstrate that maximum errors in the nuclear forces for excited states of singlet and triplet spin multiplicity are smaller than 0.1 eV/Å. The method is furthermore applied to the calculation of the zero-phonon line of defective hexagonal boron nitride. This spectral feature is reproduced with an error of 0.6 eV in comparison to GW–Bethe–Salpeter reference computations and 0.4 eV in comparison to experimental measurements. Accuracy assessments and applications thus demonstrate the potential use of the outlined developments for large-scale applications on excited-state properties of extended systems. The data in this record are supplementary data to the published article with DOI 10.1021/acs.jctc.4c00614.

en: Excited-state forces with the Gaussian and augmented plane wave method for the Tamm–Dancoff approximation of time-dependent density functional theory

augmented-plane-wave-methods

display_name: augmented-plane-wave-methods

gaussian-basis-sets

display_name: gaussian-basis-sets


en:
Dynamical potentials appear in many advanced electronic-structure methods, including self-energies from many-body perturbation theory, dynamical mean-field theory, electronic-transport formulations, and many embedding approaches. Here, we propose a novel treatment for the frequency dependence, introducing an algorithmic inversion method that can be applied to dynamical potentials expanded as sum-over-poles. This approach allows for an exact solution of Dyson-like equations at all frequencies via a mapping to a matrix diagonalization, and provides simultaneously frequency-dependent (spectral) and frequency-integrated (thermodynamic) properties of the Dyson-inverted propagators.
The transformation to a sum-over-poles is performed introducing n-th order generalized Lorentzians as an improved basis set to represent the spectral function of a propagator.
Numerical results for the homogeneous electron gas at the G0W0 level are provided to argue for the accuracy and efficiency of such unified approach.
In this record, we provide the input and outputs of the AGWX suite (see article) used in the work. Also, we add the plots of the obtained Green's function for all densities, k-points, and frequencies.

en: A unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

computational-materials-science

display_name: computational-materials-science

homogeneous-electron-gas

display_name: homogeneous-electron-gas

many-body-perturbation-theory-gw

display_name: many-body-perturbation-theory-gw

max

display_name: max

snsf

display_name: snsf


en: Linear scaling relations have led to an understanding of trends in catalytic activity and selectivity of many reactions in heterogeneous and electro-catalysis. Yet, linear scaling between the chemisorption energies of any two small molecule adsorbates is not guaranteed. A prominent example is the lack of scaling between the chemisorption energies of carbon and oxygen on transition metal surfaces. In this work, we show that this lack of scaling originates from different re-normalised adsorbate valence energies of lower-lying oxygen versus higher-lying carbon. We develop a model for chemisorption of small molecule adsorbates within the d-band model by combining a modified form of the Newns-Anderson hybridisation energy with an effective orthogonalization term. We develop a general descriptor to a priori determine if two adsorbates are likely to scale with each other. This record contains the AiiDA archive required to reproduce all calculations in the manuscript.

en: Limits to scaling relations between adsorption energies?

catalysis

display_name: catalysis

d-band-model

display_name: d-band-model

scaling-relations

display_name: scaling-relations


en: Hydrogen boride (HB) sheets are metal-free two-dimensional materials comprising boron and hydrogen in a 1:1 stoichiometric ratio. In spite of the several advancements, the fundamental interactions between HB sheets and discrete molecules remain unclear. Here, we report the adsorption of CO2 and its conversion to CH4 and C2H6 using hydrogen-deficient HB sheets. Although fresh HB sheets did not adsorb CO2, hydrogen-deficient HB sheets reproducibly physisorbed CO2 at 297 K. The adsorption followed the Langmuir model with a saturation coverage of 2.4 × 10−4 mol g−1 and a heat of adsorption of approximately 20 kJ mol−1, which was supported by density functional theory calculations. When heated in a CO2 atmosphere, hydrogen-deficient HB began reacting with CO2 at 423 K. The detection of CH4 and C2H6 as CO2 reaction products in a moist atmosphere indicated that hydrogen-deficient HB promotes C–C coupling and CO2 conversion reactions. Our findings highlight the application potential of HB sheets as catalysts for CO2 conversion.

en: Carbon dioxide adsorption and conversion to methane and ethane on hydrogen boride sheets

carbon-dioxide

display_name: carbon-dioxide

density-functional-theory

display_name: density-functional-theory

ethane

display_name: ethane

hydrogen-boride

display_name: hydrogen-boride

methane

display_name: methane

two-dimensional

display_name: two-dimensional


en: We study the water dehydrogenation reaction at the BiVO₄(010)-water interface by combining nudged-elastic-band calculations and electronic structure calculations at the hybrid functional level. We investigate the pathway and the kinetic barrier for the adiabatic reaction going from the hole polaron localized in BiVO₄ to the dehydrogenation of the adsorbed water molecule at the interface. The reaction is found to involve the H2O•⁺ radical cation as intermediate, to have a kinetic barrier of 0.7 eV, and to be initiated by the electron transfer. The calculated kinetic barrier is in good agreement with experiment and is consistent with the slow hole transfer kinetics observed at the surface of BiVO₄. To characterize the structural changes occurring during this process, we analyze the O-H distances for three relevant water molecules. We also examine the Wannier functions around the O atom of the adsorbate involved in the reaction to reveal the changes in the electronic structure during the hole hopping. The projected density of states of the lowest unoccupied molecular orbitals allows us to identify the atomic orbitals that are primarily involved in the reaction. We expect that the proposed reaction mechanism generally holds when the surface coverage is dominated by molecularly adsorbed water.

en: Oxygen evolution at the BiVO₄-water interface: mechanism of the water dehydrogenation reaction

marvel

display_name: marvel

metal-oxide

display_name: metal-oxide

water-dehydrogenation-reaction

display_name: water-dehydrogenation-reaction


en: Oxides containing metals or semimetals from the p-block of the periodic table, e.g., indium oxide or antimony oxide, are of interest as transparent conductors and light absorbers for solar energy conversion due to the tunability of their electronic conductivity and optical absorption. Comparatively, these oxides have found limited applications in solar-to-hydrogen photocatalysis primarily due to their high electronegativity, which impedes electron transfer for converting protons into hydrogen. We have shown recently that inserting s-block metal cations into p-block oxides is effective at lowering electronegativities while affording further control of band gaps. Here, we explain the origins of this dual tunability by demonstrating the mediator role of s-block metal cations in modulating orbital hybridization while not contributing to frontier electronic states. From this result, we carry out a comprehensive computational study of 109 ternary oxides of s- and p-block metal elements as candidate photocatalysts for solar hydrogen generation. We downselect the most desirable materials using band gaps and band edges obtained from Hubbard-corrected density-functional theory with Hubbard parameters computed entirely from first principles, evaluate the stability of these oxides in aqueous conditions, and characterize experimentally four of the remaining materials, synthesized with high phase uniformity, to critically assess the accuracy of the computational models. We thus propose nine oxide semiconductors, including CsIn₃O₅, Sr₂In₂O₅, and KSbO₂ which, to the extent of our literature review, have not been previously considered as water-splitting photocatalysts. This record contains the data for the simulations discussed in our manuscript.

en: Ternary oxides of s- and p-block metals for photocatalytic solar-to-hydrogen conversion

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).

dftu

display_name: dftu

photocatalysis

display_name: photocatalysis


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.

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

materialscloud

en: Materials Cloud

envi

en: Environment

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

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

first-principles

display_name: first-principles

grand-canonical-monte-carlo

display_name: grand-canonical-monte-carlo

vasp

display_name: vasp


en: A detailed understanding of how molecules interact with two-dimensional materials, particularly concerning energy level alignment and charge transfer processes, is essential to incorporate functional molecular films into next-generation 2D material-organic hybrid devices. One of the major challenges in integrating molecular films in field-effect transistors is facilitating ambipolar charge transport, which is often hindered by the large electronic gap of the organic layers. In a recent work we compare the adsorption site-dependent energy level alignment of C60, C70, and C84 fullerenes induced by the spatial variation of the electrostatic surface potential of the h-BN/Rh(111) Moiré superstructure. As the size of the fullerenes increases, the HOMO-LUMO gap shrinks. In the case of C84, we find an intrinsic charge transfer from the substrate to the fullerenes adsorbed in the Moiré pore centers, rendering them negatively charged. The electric field effect-induced charging of neutral fullerenes and discharging of intrinsically negatively charged fullerenes are investigated using scanning tunneling spectroscopy, non-contact atomic force microscopy, and Kelvin probe force spectroscopy. Our findings show that on metal-supported h-BN, the LUMO level of C84 is sufficiently close to the Fermi energy that it can be neutral or 1e− negatively charged depending on slight variations of the electrostatic potential. The findings propose a path to make ambipolar charge transfer accessible and efficient by circumventing the need to overcome the fullerenes' electronic gap. This record contain data that support the results discussed in our work.

en: Ambipolar charge transfer of larger fullerenes enabled by the modulated surface potential of h-BN/Rh(111)

ab-initio

display_name: ab-initio

ambipolar-charge-transfer

display_name: ambipolar-charge-transfer

cscs

display_name: cscs

fullerenes

display_name: fullerenes

intermolecular-interactions

display_name: intermolecular-interactions

non-contact-atomic-force-microscopy

display_name: non-contact-atomic-force-microscopy

organic-hybrid-electronics

display_name: organic-hybrid-electronics

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy

snsf

display_name: snsf


en: In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We observe that all the range-separated hybrid functionals that correctly describe the long-range dielectric screening significantly improve from standard hybrid functionals such as PBE0 and HSE06. Among this group, the choice of the short-range Fock exchange fraction and the screening length can further reduce the predicted error. We then propose a universal expression for the selection of the inverse screening parameter as a function of the short-range and long-range Fock exchange fractions, which results in a mean absolute error as small as 0.15 eV for band gap prediction.

en: Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

density-functional-theory

display_name: density-functional-theory

hybrid-functional

display_name: hybrid-functional

quantum-espresso

display_name: quantum-espresso


en: This dataset includes all data presented in the figures of the main manuscript: XPS work function changes, ab-initio calculated work functions, O2p band center shifts, Densities of state for LSC and PCO, i-PLD results for LSC, LSF, STF and PCO, Densities of state for adsorbed O2 on differently decorated PCO surfaces. In this work, we investigated surface dipole changes which were induced by modification of mixed conducting surfaces with binary oxides via pulsed laser deposition.

en: Engineering surface dipoles on mixed conducting oxides with ultra-thin oxide decoration layers

oxygen-exchange

display_name: oxygen-exchange

surface-chemistry

display_name: surface-chemistry

work-function

display_name: work-function


en: Efficient O₂ reduction to H₂O₂, vital for energy conversion and environmental cleanup, relies on precise control of heterogeneous catalysts interacting with reaction species. Through high-throughput density functional theory calculations, consisting of 369 single atom catalysts, we identified the polarized descriptor (electric dipole strength) on two-dimensional carbon materials, revealing insights into the catalytic effect of support polarization. Surprisingly, this descriptor exhibits advanced scaling relationships towards H₂O₂ synthesis, incorporating factors such as active metals, coordination environments, and surface curvatures, highlighting its widespread significance. Furthermore, it demonstrates reliable predictability for O₂ adsorption in dynamic water environments, with optimal reactivity observed within the range of -1.40 to -1.00 e·Å, as confirmed by dynamic and static simulations of the 2e- pathway of O₂ reduction. In essence, these findings offer valuable insights for the rational design of electrocatalysts tailored for selective O₂ reduction.

en: Scaling relations and dynamical predictiveness of electric dipole strength on 2e- ORR catalytic property

density-functional-theory-calculations

display_name: density-functional-theory-calculations

electric-dipole-strength

display_name: electric-dipole-strength

oxygen-reduction-reaction

display_name: oxygen-reduction-reaction

support-polarization

display_name: support-polarization


en: The reactivity of silicates in aqueous solution is relevant to various chemistries ranging from silicate minerals in geology, to the C-S-H phase in cement, nanoporous zeolite catalysts, or highly porous precipitated silica. While simulations of chemical reactions can provide insight at the molecular level, balancing accuracy and scale in reactive simulations in the condensed phase is a challenge. Here, we demonstrate how a machine-learning reactive interatomic potential can accurately capture silicate-water reactivity. The model was trained on a new dataset comprising 400,000 energies and forces of molecular clusters at the 𝜔-B97XD\def2-TVZP level. To ensure the robustness of the model, we introduce a new and general active learning strategy based on the attribution of the model uncertainty, that automatically isolates uncertain regions of bulk simulations to be calculated as small-sized clusters. Our trained potential is found to reproduce static and dynamic properties of liquid water and solid crystalline silicates, despite having been trained exclusively on cluster data. Furthermore, we utilize enhanced sampling simulations to recover the self-ionization reactivity of water accurately, and the acidity of silicate oligomers, and lastly study the silicate dimerization reaction in a water solution at neutral conditions and find that the reaction occurs through a flanking mechanism.

en: Learning a reactive potential for silica-water through uncertainty attribution

active-learning

display_name: active-learning

chemical-reactions

display_name: chemical-reactions

free-energy

display_name: free-energy

neural-network-potential

display_name: neural-network-potential

silicates

display_name: silicates


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

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

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).

auxetic-materials

display_name: auxetic-materials

elasticity

display_name: elasticity

hydrogels

display_name: hydrogels


en: Materials demonstrating positive thermal expansion (PTE) or negative thermal expansion (NTE) are quite common, whereas those exhibiting zero thermal expansion (ZTE) are notably scarce. In this work, we identify the mechanical descriptors, namely in-plane tensile stiffness and out-of-plane bending stiffness, that can effectively classify PTE and NTE 2D crystals. By utilizing high throughput calculations and the state-of-the-art symbolic regression method, these descriptors aid in the discovery of ZTE or 2D Invar monolayers with the linear thermal expansion coefficient (LTEC) within ±2×10⁻⁶ K⁻¹ in the middle range of temperatures. Additionally, the descriptors assist the discovery of large PTE and NTE 2D monolayers with the LTEC larger than ±15×10⁻⁶ K⁻¹, which are so-called 2D anti-Invar monolayers. Advancing our understanding of materials with exceptionally low or high thermal expansion is of substantial scientific and technological interest, particularly in developing next-generation electronics at the nanometer even Ångstrom scale.

en: Machine learning enables the discovery of 2D Invar and anti-Invar monolayers

materialscloud

en: Materials Cloud

bending-stiffness

display_name: bending-stiffness

linear-coefficient-of-thermal-expansion

display_name: linear-coefficient-of-thermal-expansion

machine-learning

display_name: machine-learning

symbolic-regression

display_name: symbolic-regression

thermal-expansion

display_name: thermal-expansion

zero-thermal-expansion

display_name: zero-thermal-expansion


en: We present a combined density-functional theory and single-site dynamical mean-field theory (DMFT) study of vanadium dioxide (VO₂) using an unconventional set of bond-centered orbitals as the basis of the correlated subspace. VO₂ is a prototypical material undergoing a metal-insulator transition (MIT), hosting both intriguing physical phenomena and the potential for industrial applications. With our choice of correlated subspace basis, we investigate the interplay of structural dimerization and electronic correlations in VO₂ in a computationally cheaper way compared to other state-of-the-art methods, such as cluster DMFT. Our approach allows us to treat the rutile and M1 monoclinic VO₂ phases on an equal footing and to vary the dimerizing distortion continuously, exploring the energetics of the transition between the two phases. The choice of basis presented in this work hence offers a complementary view on the long-standing discussion of the MIT in VO₂ and suggests possible future extensions to other similar materials hosting molecular-orbital-like states.

en: Single-site DFT+DMFT for vanadium dioxide using bond-centered orbitals

envi

en: Environment

dft

display_name: dft

dftdmft

display_name: dftdmft


en:
Interface stress is a fundamental descriptor for interphase boundaries and is defined in strict relation to the interface energy. In nanomultilayered coatings with their intrinsically high interface density, the functional properties are generally dictated by the interface structure, which in turn is governed by the delicate interaction of residual interface and volume stresses in the coating system. In the present work, experimental estimations of the interface stress in Cu/W NMLs (with a variable residual stress state from tensile to compressive) were compared with corresponding theoretical values as calculated using DFT (adopting an incoherent bcc W{110}/fcc Cu{111} interface with variable in-plane strain). The Cu/W interface stress was experimentally tuned monotonically from positive to negative values by changing the residual stress in the W nanolayers by increasing the Ar pressure during the W deposition steps. Qualitative agreement between experiment and simulation was achieved, both confirming a decrease of the interface stress from the compressive to the tensile regime. The DFT simulations showed that Cu atoms in the vicinity of the strained Cu/W interfaces are displaced along the in-plane and out-of-plane directions in response to the acting
interface stress. Using a preliminary developed neural network potential for the immiscible Cu-W system, specific in-plane crystallographic orientation relationships for the Cu/W interfaces were also tested, which improved quantitative agreement between experiment and theory. Assumptions and limitations in experiments and theory for deriving the interface stress are critically discussed.

en: Experimental and ab initio derivation of interface stress in nanomultilayered coatings: application to immiscible Cu/W system with variable in-plane stress

ab-initio

display_name: ab-initio

copper-tungsten

display_name: copper-tungsten

interface-stress

display_name: interface-stress

xrd

display_name: xrd


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

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

hybrid-dft

display_name: hybrid-dft

oxygen-vacancy-defects

display_name: oxygen-vacancy-defects


en:
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

marvel

display_name: marvel

molecular-dynamics

display_name: molecular-dynamics

phase-transitions

display_name: phase-transitions

post-gga-density-functional-theory

display_name: post-gga-density-functional-theory

snsf-sinergia

display_name: snsf-sinergia


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

en: Local magnetoelectric effects as predictors of surface magnetic order

dft

display_name: dft

magnetism

display_name: magnetism

surface-science

display_name: surface-science

symmetry-analysis

display_name: symmetry-analysis


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

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

electronic-structure

display_name: electronic-structure

gw

display_name: gw

many-body-perturbation-theory

display_name: many-body-perturbation-theory

transition-metal-oxides

display_name: transition-metal-oxides

vertex-corrections

display_name: vertex-corrections


en: In situ interfacial rheology and numerical simulations are used to investigate microgel monolayers in a wide range of packing fractions, ζ2D. The heterogeneous particle compressibility determines two flow regimes characterized by distinct master curves. To mimic the microgel architecture and reproduce experiments, an interaction potential combining a soft shoulder with the Hertzian model is introduced. In contrast to bulk conditions, the elastic moduli vary nonmonotonically with ζ2D at the interface, confirming long-sought predictions of reentrant behavior for Hertzian-like systems.

en: Interfacial fluid rheology of soft particles

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).

elastic-properties

display_name: elastic-properties

hertzian-model

display_name: hertzian-model

liquid-liquid-interfaces

display_name: liquid-liquid-interfaces

microgels

display_name: microgels

softness-and-elasticity

display_name: softness-and-elasticity


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

en: Spectral operator representations

materialscloud

en: Materials Cloud

electronic-bands

display_name: electronic-bands

epfl

display_name: epfl

machine-learning

display_name: machine-learning

marvel

display_name: marvel


en:
The discovery of chiral helical magnetism (CHM) in Cr1/3NbS2 and the stabilization of a chiral soliton lattice (CSL) has attracted considerable interest in view of their potential technological applications. However, there is an ongoing debate regarding whether the sister compound, Mn1/3NbS2, which shares the same crystal structure, exhibits similar nontrivial properties, which rely on the stabilization of the lack of inversion symmetry at the magnetic ion. In this study, we conduct a comprehensive investigation of the magnetically ordered states of both compounds, using 53Cr, 55Mn and 93Nb nuclear magnetic resonance.  Our results, supported by density functional  calculations, detect in a high quality single crystal of Cr1/3NbS2 all the signatures of the monoaxial CHM in  a magnetic field, identifying it as a textbook NMR case. The detailed understanding of this prototypic  behavior provides a reference for Mn1/3NbS2.
Despite the much larger density of specific defects in this second single crystal, we confirm the presence of a CHM phase in the Mn compound, characterized by a very large critical field for the forced ferromagnetic phase (~ 10 T for H || c).

en: Disorder-resilient transition of Helical to Conical ground states in M1/3NbS2, M=Cr,Mn

envi

en: Environment

chiral-helical-magnetism

display_name: chiral-helical-magnetism

chiral-soliton-lattice

display_name: chiral-soliton-lattice

dft

display_name: dft

nuclear-magnetic-resonance

display_name: nuclear-magnetic-resonance


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

confidence-interval

display_name: confidence-interval

laplace-approximation

display_name: laplace-approximation

neural-networks

display_name: neural-networks

neural-tangent-kernel

display_name: neural-tangent-kernel

prediction-rigidity

display_name: prediction-rigidity

regressors

display_name: regressors

uncertainty-quantification

display_name: uncertainty-quantification


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

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

charge-density-waves

display_name: charge-density-waves

marie-curie-fellowship

display_name: marie-curie-fellowship

stacking-order

display_name: stacking-order

transition-metal-dichalcogenides

display_name: transition-metal-dichalcogenides


en: Comprehending water dynamics is crucial in various fields such as water desalination, ion separation, electrocatalysis, and biochemical processes. While ab-initio molecular dynamics (AIMD) accurately portray water's structure, computing its dynamic properties over nanosecond timescales proves cost-prohibitive. This study employs machine learning potentials (MLPs) to accurately determine the dynamical properties of liquid water with ab-initio accuracy. Our findings reveal diversity in the calculated diffusion coefficient (D) and viscosity of water (η) across different methodologies. Specifically, while the GGA, meta-GGA, and hybrid functional methods struggle to predict dynamic properties under ambient conditions, whereas methods on the higher level of Jacob's ladder of DFT approximation perform significantly better. Intriguingly, we discovered that all D and η adhere to the established Stokes-Einstein (SE) relation for all the ab-initio water. The diversity observed among different methods can be attributed to distinct structural entropy, affirming the applicability of excess entropy scaling relations across all functionals. The correlation between D and η provides valuable insights for identifying the ideal temperature to accurately replicate liquid water's dynamic properties. Furthermore, our findings can validate the rationale behind employing artificially high temperatures in the simulation of water via AIMD. These outcomes not only pave the path toward designing better functionals for water but also underscore the significance of water's many-body characteristics.

en: The dynamic diversity and invariance of ab-initio water

aimd

display_name: aimd

density-functional-theory

display_name: density-functional-theory

diffusion

display_name: diffusion

dynamical-properties

display_name: dynamical-properties

machine-learning-potential

display_name: machine-learning-potential

water

display_name: water


en: Hopf et al. first reported the high-temperature 6π-electrocyclization of cis-hexa-1,3-diene-5-yne to benzene in 1969. Subsequent studies using this cyclization have been limited by its very high reaction barrier. Here, we show that the reaction barrier for two model systems, (E)-1,3,4,6-tetraphenyl-3-hexen-1,5-diyne (1a) and (E)-3,4-bis(4-iodophenyl)-1,6-diphenyl-3-hexen-1,5-diyne 1b, is decreased by nearly half on a Au(111) surface. In recent work, we have used scanning tunneling microscopy (STM) and non-contact atomic force microscopy (nc-AFM) to monitor the Hopf cyclization of enediynes 1a,b on Au(111). Enediyne 1a undergoes two sequential, quantitative Hopf cyclizations, first to naphthalene derivative 2, and finally to chrysene 3. Density functional theory (DFT) calculations reveal that a gold atom from the Au(111) surface is involved in all steps of this reaction, and that it is crucial to lowering the reaction barrier. Our findings have important implications for the synthesis of novel graphene nanoribbons. Ullman coupling of enediyne 1b at 20 ˚C on Au(111), followed by a series of Hopf cyclizations and aromatization reactions at higher temperatures, produces nanoribbons 12, and eventually 13 upon further heating. These results show for the first time that graphene nanoribbons can be synthesized on-surface using the Hopf cyclization mechanism. This record contains all simulation data that support our scientific work.

en: Dramatic acceleration of the Hopf cyclization on gold(111): from enediynes to unusual graphene nanoribbons

cscs

display_name: cscs

dft

display_name: dft

nc-afm

display_name: nc-afm

on-surface-synthesis

display_name: on-surface-synthesis

snsf

display_name: snsf

stm

display_name: stm


en: The use of perovskite oxides as bifunctional catalysts for oxygen electrocatalysis is a promising strategy for developing high-performance unified regenerative fuel cells (URFCs), thanks to their highly tunable structure. This work explores the exsolution of well-dispersed nanoparticles containing reduced Pt species from La0.6Sr0.4Fe0.95Pt0.05O3-δ (LSFPt) as an effective approach to design bifunctional catalysts for oxygen electrocatalysis. A 10 h reduction treatment at 500 °C in 5% H2/Ar promotes the exsolution of ~1.2 nm Pt-containing nanoparticles on the surface, increasing oxygen deficiency without compromising the perovskite structure. The resulting catalyst exhibits significantly improved activity for oxygen evolution reaction (OER) and oxygen reduction reaction (ORR) in alkaline media, with over 2.5-fold performance improvement compared to the as-prepared LSFPt. Electrochemical impedance spectroscopy (EIS), combined with distribution of relaxation times (DRT) deconvolution analysis, revealed a notable decrease in medium-frequency resistance, indicating enhanced charge transfer at the electrode surface for OER and ORR. Post-mortem O K-edge spectra obtained by soft X-ray absorption spectroscopy in total electron yield mode further suggest an increased surface restructuring in the reduced LSFPt, attributed to the synergistic presence of surface defects and exsolved nanoparticles containing reduced Pt species. This one-step reduction protocol offers a promising strategy for designing efficient bifunctional electrocatalysts.

en: Harnessing bifunctional oxygen electrocatalysis: Exsolved Pt nanoparticles from La0.6Sr0.4Fe0.95Pt0.05O3-δ

bifunctional-electrocatalyst

display_name: bifunctional-electrocatalyst

distribution-of-relaxation-times-drt

display_name: distribution-of-relaxation-times-drt

oxygen-evolution-reaction-oer

display_name: oxygen-evolution-reaction-oer

oxygen-reduction-reaction-orr

display_name: oxygen-reduction-reaction-orr

perovskite

display_name: perovskite

pt-exsolution

display_name: pt-exsolution

unified-regenerative-fuel-cells

display_name: unified-regenerative-fuel-cells


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

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

materialscloud

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

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

ab-initio

display_name: ab-initio

cluster-expansion

display_name: cluster-expansion

machine-learning

display_name: machine-learning


en: Materials that efficiently promote the thermodynamically uphill water-splitting reaction under solar illumination are essential for generating carbon-free ("green") hydrogen. Mapping out the combinatorial space of potential photocatalysts for this reaction can be expedited using data-intensive materials exploration. The calculated band gaps and band alignments can serve as key indicators and metrics to computationally screen photoactive materials. Ternary main-group metal sulfides containing p- and s-block elements represent a promising, albeit underexplored, class of photocatalysts. Here, we computationally screen 86 candidate ternary main-group metal sulfides containing p- and s-block elements. By validating electronic structure predictions against experimental band gaps and band edges for synthetically accessible materials, we propose eight potential photocatalysts. Using computed Pourbaix diagrams, we further narrowed the candidate pool to four materials based on the predicted aqueous stability. We then synthesized and characterized these four materials and experimentally screened them for photoresponsiveness under photocatalytically relevant conditions. We also characterized their experimental band gaps and band edge positions and compared them with computational predictions. Based on the experimental screening protocols, we identify MgIn₂S₄ and BaSn₂S₅ as photoresponsive materials with sufficient aqueous stability to be considered in greater depth as potential photocatalysts for overall water-splitting. This record contains the computational predictions for the four candidates discussed in our manuscript.

en: Data-intensive exploration of the photoelectrochemical responses of main-group metal sulfides

materialscloud

en: Materials Cloud

photocatalysts

display_name: photocatalysts

sulfides

display_name: sulfides

water-splitting

display_name: water-splitting


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

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

envi

en: Environment

band-alignments

display_name: band-alignments

epitaxial-interfaces

display_name: epitaxial-interfaces

gw-calculations

display_name: gw-calculations


en: This study employed density functional theory with doubly screened dielectric-dependent hybrid (DSH) functional to predict the band gaps of Pb- and Sn-based inorganic and hybrid 3D halide perovskites, as well as layered hybrid perovskites. The DSH functional employs material-dependent mixing parameters derived from macroscopic electronic dielectric constant, and accurately predicts band gaps for 3D perovskites only if structural local disorder is taken into account. For layered hybrid perovskites, we propose using the calculated dielectric constant of the respective 3D perovskites to define the DSH screening. This dataset contains input and output files of all DFT and DSH calculations applied to Pb- and Sn-based layered halide perovskites with various organic spacers and multilayered structures, such as BA series with n =1, 2, 3. The computational framework introduced here provides an efficient parameter-free ab initio methodology suitable for predicting the electronic properties of 3D, layered halide perovskites and their heterostructures, towards modelling materials for advanced optoelectronic devices.

en: Three-dimensional to layered halide perovskites: a parameter-free hybrid functional method for predicting electronic band gaps

density-functional-theory

display_name: density-functional-theory

dielectric-dependent-hybrid-functional

display_name: dielectric-dependent-hybrid-functional

hybrid-perovskites

display_name: hybrid-perovskites

layered-halide-perovskite

display_name: layered-halide-perovskite


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:
A first-principles approach for calculating ion separation in solution through 2D membranes is proposed. Ionic energy profiles across the membrane are obtained first, where solvation effects are explicitly simulated by machine-learning molecular dynamics, electrostatic corrections are applied to remove finite-size capacitive effects, and a mean-field treatment of the electrochemical double layer charging is used. Entropic contributions are assessed analytically and through a thermodynamic integration scheme. Ionic separations are then inferred through a microkinetic model of the filtration process, accounting for steady-state charge separation effects across the membrane. The approach is applied to Li+, Na+, K+ sieving through a crown-ether functionalized graphene membrane, with a case study of the mechanisms for a highly selective and efficient extraction of lithium from aqueous solutions.
This record contains the MD trajectories used to generate the energy and free energy profiles of Fig. 4.

en: Ion sieving in 2D membranes from first principles

ion-sieving

display_name: ion-sieving

machine-learning

display_name: machine-learning

molecular-dynamics

display_name: molecular-dynamics


en: Precise modeling and understanding of heat transport in the superionic phase are of great interest. Although simulations combining Green-Kubo (GK) molecular dynamics with machine-learned potentials (MLPs) stand as a promising approach, substantial challenges remain due to the crucial impact of atomic diffusion. Here, we first show that the thermal conductivity (κ) of superionic materials calculated via conventional GK integral of the energy flux varies notably with the MLP model. Subsequently, we highlight that reliable, model-independent κ values can be obtained by applying Onsager’s reciprocal relations to correctly capture the coupled heat and mass transport. Remarkably, an anomalously invariant κ is observed over a wide temperature range, distinct from the characteristic trends in traditional crystals and glasses. Finally, we illustrate that conventional κ decompositions into kinetic, potential, and cross terms suffer from ambiguities in the physical interpretation, despite their mathematical rigor.

en: Heat transport in superionic materials via machine-learned molecular dynamics


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

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).

phonon-phonon-interactions

display_name: phonon-phonon-interactions

phonon-scattering-rate

display_name: phonon-scattering-rate

thermal-transport

display_name: thermal-transport


en: Charge carrier mobilities are critical parameters in halide perovskite solar cells, governing their average carrier velocity under an applied electric field and overall efficiency. Recent advances in first-principles calculations of electron-phonon interactions and carrier mobilities have enabled predictive computations for perovskite solar cells. However, the flexible octahedral frameworks and cationic displacements in these materials challenge the harmonic approximation, leading to significant difficulties in accurately calculating transport properties. To address these issues, we combine temperature-dependent effective potentials with the ab initio Boltzmann transport equations to compute carrier mobilities in a representative lead-free perovskite, CsSnBr₃. At room temperature, the electron/hole Hall mobilities in CsSnBr₃ are 106/256 cm²/Vs when neglecting anharmonic effects and 59/145 cm²/Vs when included. This overestimation of the harmonic approximation arises from the neglect of scattering coming from soft modes. We provide a workflow for performing first-principles carrier mobility calculations in anharmonic systems, advancing the predictive modeling of perovskite solar cells.

en: Impact of anharmonicity on the carrier mobility of the Pb-free CsSnBr₃ perovskite

materialscloud

en: Materials Cloud

ab-initio

display_name: ab-initio

anharmonicity

display_name: anharmonicity

electron-phonon-coupling

display_name: electron-phonon-coupling

first-principles

display_name: first-principles

mobility

display_name: mobility

perovskite

display_name: perovskite


en: The substantial consumption of lithium (Li) ions and sluggish reaction kinetics at the anode detrimentally impact the deliverable energy and fast-charging capability of lithium-ion batteries (LIBs) with silicon-based anodes. The prevailing contact prelithiation method using an electrolyte medium can replenish the active Li, but it may cause materials/electrode instability and bring barrier for Li-ion transport due to the nonuniform reaction. Here we explore a contact prelithiation methodology employing cyclic carbonate mediums that can enable spatially and temporally uniform prelithiation reaction. These mediums enable a delicate equilibrium between a Li-ion diffusion and the intrinsic prelithiation reaction rate of the material throughout the electrode depth. To gain an in-depth insight into the mechanism for producing Li-ions under the contact between Li metal and cyclic carbonate solvents, we undertook molecular dynamics simulations. Our calculation results of the self-produced Li alkyl carbonates reveal that while the long-chain Li alkyl carbonates are capable of forming an extensive polymer network in FEC and participating in the formation of a stable SEI on the Li metal surface, short-chain Li alkyl carbonates can dissolve into the solvent to produce Li-ions.

en: A salt-free medium facilitating electrode prelithiation towards fast-charging, high-energy lithium-ion batteries

envi

en: Environment

battery

display_name: battery

lithium

display_name: lithium


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

hole-mobility

display_name: hole-mobility

nitrides

display_name: nitrides


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

en: Extreme anharmonicity and thermal contraction of 1D wires

density-functional-theory

display_name: density-functional-theory

heat-capacity

display_name: heat-capacity

negative-thermal-expansion

display_name: negative-thermal-expansion

one-dimensional-materials

display_name: one-dimensional-materials

sscha

display_name: sscha


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

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

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

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).

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"

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

materialscloud

en: Materials Cloud

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: Magnetic materials are crucial for manipulating electron spin and magnetic fields, enabling applications in data storage, spintronics, charge transport, and energy conversion, while also providing insight into fundamental quantum phenomena. In numerous applications, the interaction between electrons and lattice vibrations, known as electron-phonon coupling, can be of significant importance. In that regard, we extend the EPW package to be able to interpolate the electron-phonon matrix elements combining perturbation theory and maximally localized Wannier functions. This advance allows to use dense momentum grids at a reasonable computational cost when computing electron-phonon-related quantities and physical properties. We validate our implementation considering ferromagnetic iron and nickel where we explore the absence of phonon-driven superconductivity, finding that superconductivity is intrinsically suppressed. Furthermore, we evaluate the carrier resistivity at finite temperatures for both systems, considering the role of magnetism in carrier transport. Our findings indicate that in the case of Fe, the primary contributor to resistivity is electron-phonon scattering. In contrast, for Ni, electron-phonon scattering constitutes less than one-third of the resistivity, underscoring a fundamental difference in the transport properties of the two systems.

en: Electron-phonon coupling in magnetic materials using the local spin density approximation

electron-phonon-coupling

display_name: electron-phonon-coupling

magnetism

display_name: magnetism

wannier-functions

display_name: wannier-functions


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

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

en: Magnon-phonon interactions from first principles

bethe-salpeter-equation

display_name: bethe-salpeter-equation

first-principles

display_name: first-principles

magnon-phonon-coupling

display_name: magnon-phonon-coupling


en: Polyacene analogues, consisting of short acene segments separated by nonbenzenoid rings, offer intriguing electronic properties and magnetic interactions. Pentalene-bridged polyacenes (PPs), in particular, hold promise for enhancing the electrical conductivity and potential open-shell ground states. However, PPs have remained elusive in solution chemistry due to poor solubility and limited synthetic protocols. In a recent publication,  we report the on-surface synthesis of PPs through the annulation between ortho-xylene groups. Scanning tunneling microscopy and atomic force microscopy reveal that the reconstructed Au(110) surface significantly enhances the chemoselectivity of the annulation process. Scanning tunneling spectroscopy combined with density functional theory suggests that PP exhibits a narrow direct band gap, similar to long acenes. This work demonstrates the potential for band structure engineering in polyacene analogues by incorporating nonbenzenoid rings, paving the way to advancements in organic electronics and spintronics. This record contains computational data supporting the results discussed in the manuscript.

en: Enhancing chemoselectivity of on-surface reactions on reconstructed Au(110): the case of a pentalene-bridged polyacene analogue

annulation

display_name: annulation

hydrocarbons

display_name: hydrocarbons

on-surface-synthesis

display_name: on-surface-synthesis

scanning-tunneling-microscopy

display_name: scanning-tunneling-microscopy