AndreaBozzo/ceres-open-data-index huggingface dataset:
Self-consistent Hubbard parameters from density-functional perturbation theory in the ultrasoft and projector-augmented wave formulations

The self-consistent evaluation of Hubbard parameters using linear-response theory is crucial for quantitatively predictive calculations based on Hubbard-corrected density-functional theory. Here, we extend a recently-introduced approach based on density-functional perturbation theory (DFPT) for the calculation of the on-site Hubbard U to also compute the inter-site Hubbard V. DFPT allows to reduce significantly computational costs, improve numerical accuracy, and fully automate the calculation of the Hubbard parameters by recasting the linear response of a localized perturbation into an array of monochromatic perturbations that can be calculated in the primitive cell. In addition, here we generalize the entire formalism from norm-conserving to ultrasoft and projector-augmented wave formulations, and to metallic ground states. After benchmarking DFPT against the conventional real-space Hubbard linear response in a supercell, we demonstrate the effectiveness of the present extended Hubbard formulation in determining the equilibrium crystal structure of LiₓMnPO₄ (x=0,1) and the subtle energetics of Li intercalation.

Tags: cscs, density-functional-perturbation-theory, extended-hubbard-functionals, hubbard-corrected-density-functional-theory, hubbard-on-site-u-and-inter-site-v-parameters, li-ion-batteries, limnpo4, linear-response-theory, marvel, mnpo4, monochromatic-perturbations, projector-augmented-wave-method, self-interaction-corrections, ultrasoft-pseudopotentials, voltages
Atomic structures of 100nm x 100nm large oxide-, nitride-, sulfide-, and phosphide-derived copper surfaces

Cif files of relaxed "derived" copper surfaces from Cu2O, Cu2S, Cu3N, and Cu3P using EMT and published in J Gauthier, JH Stenlid, F Abild-Pedersen, M Head-Gordon, AT Bell, ACS Energy Letters, "The role of roughening to enhance selectivity to C2+ products during CO2 electroreduction on copper" (2021). These structures were used to evaluate the effect of roughening on catalytic selectivity of copper in electrochemcial CO2 reduction into valuable products such as fuels and commodity chemicals.

Tags: atomic-coordinates, copper, surface-structure
Towards predictive many-body calculations of phonon-limited carrier mobilities in semiconductors

We probe the accuracy limit of ab initio calculations of carrier mobilities in semiconductors, within the framework of the Boltzmann transport equation. By focusing on the paradigmatic case of silicon, we show
that fully predictive calculations of electron and hole mobilities require many-body quasiparticle corrections to band structures and electron-phonon matrix elements, the inclusion of spin-orbit coupling, and an extremely fine sampling of inelastic scattering processes in momentum space. By considering all these factors we obtain excellent agreement with experiment, and we identify the band effective masses as the most critical parameters to achieve predictive accuracy. Our findings set a blueprint for future calculations of carrier mobilities, and pave the way to engineering transport properties in semiconductors by design.

Tags: ab-initio-calculations, electrical-conductivity, electron-phonon-coupling, lattice-dynamics, many-body-techniques, prace, transport-phenomena, wannier-function-methods
Ab initio modeling of thermal transport through van der Waals materials

An advanced modeling approach is presented to shed light on the thermal transport properties of van der Waals materials (vdWMs) composed of single-layer transition metal dichalcogenides (TMDs) stacked on top of each other with a total or partial overlap only in the middle region. It relies on the calculation of dynamical matrices from first principles and on their usage in a phonon quantum transport simulator. We observe that vibrations are transferred microscopically from one layer to the other along the overlap region which acts as a filter selecting out the states that can pass through it. Our work emphasizes the possibility of engineering heat flows at the nanoscale by carefully selecting the TMD monolayers that compose vdWMs.

Tags: cscs, marveldd3, snsf, thermal-properties, transition-metal-dichalcogenides, van-der-waals-materials
On‐surface synthesis and characterization of triply fused porphyrin–graphene nanoribbon hybrids

On‐surface synthesis offers a versatile approach to prepare novel carbon‐based nanostructures that cannot be obtained by conventional solution chemistry. Graphene nanoribbons (GNRs) have potential for a variety of applications. A key issue for their application in molecular electronics is in the fine‐tuning of their electronic properties through structural modifications, such as heteroatom doping or the incorporation of non‐benzenoid rings.
In this record we provide data to support our recent publication that reports the covalent fusion of grapnene nanoribbons (GNRs) and porphyrins (Pors). We demonstrated selective on‐surface synthesis of a Por–GNR hybrid, which consists of two Pors connected by a short GNR segment. The atomically precise structure of the Por–GNR hybrid has been characterized by bond‐resolved scanning tunneling microscopy and noncontact atomic force microscopy. The electronic properties have been investigated by scanning tunneling spectroscopy, in combination with DFT calculations, which reveals a low electronic gap of 0.4 eV

Tags: ab-initio, graphene-nanoribbons, marveldd3, on-surface-synthesis, porphyrin, snsf
Full daytime sub-ambient radiative cooling in commercial-like paints with high figure of merit

Radiative cooling is a passive cooling technology by reflecting sunlight and emitting radiation in the sky window. Although highly desired, full daytime sub-ambient radiative cooling in commercial-like single-layer particle-matrix paints is yet to be achieved. Here we demonstrate full daytime sub-ambient radiative cooling in CaCO3-acrylic paint by utilizing the large bandgap CaCO3 fillers, a high particle concentration of 60% and a broad size distribution. Our paint shows high solar reflectance of 95.5% and high normal emissivity of 0.94 in the sky window. Field tests show cooling power exceeding 37W/m2 and surface temperature more than 1.7˚C below ambient at noon. A figure of merit RC is proposed to compare the cooling performance independent of weather conditions. The standard RC of our paint is 0.49, among the best radiative cooling performance while offering unprecedented benefits of the convenient paint form, low cost, and the compatibility with commercial paint fabrication process.

Tags: atmospheric-sky-window, daytime-radiative-cooling, figure-of-merit, lorentz-mie-theory, monte-carlo-simulation, particle-matrix-paint
Correlated states in twisted double bilayer graphene

Electron–electron interactions play an important role in graphene and related systems and can induce exotic quantum states, especially in a stacked bilayer with a small twist angle. For bilayer graphene where the two layers are twisted by the 'magic angle', flat band and strong many-body effects lead to correlated insulating states and superconductivity. In contrast to monolayer graphene, the band structure of untwisted bilayer graphene can be further tuned by a displacement field, providing an extra degree of freedom to control the flat band that should appear when two bilayers are stacked on top of each other. Here, we report the discovery and characterization of displacement field-tunable electronic phases in twisted double bilayer graphene. We observe insulating states at a half-filled conduction band in an intermediate range of displacement fields. Furthermore, the resistance gap in the correlated insulator increases with respect to the in-plane magnetic fields and we find that the g factor, according to the spin Zeeman effect, is ~2, indicating spin polarization at half-filling. These results establish twisted double bilayer graphene as an easily tunable platform for exploring quantum many-body states.

Tags: correlated-states, cscs, epfl, marvel, tdbg, twisted-double-bilayer-graphene
First principles correction scheme for linear-response time-dependent density functional theory calculations of core electronic states

Linear-response time-dependent density functional theory (LR-TDDFT) for core level spectroscopy using standard local functionals suffers from self-interaction error and a lack of orbital relaxation upon creation of the core hole. As a result, LR-TDDFT calculated X-ray absorption near edge structure (XANES) spectra need to be shifted along the energy axis to match experimental data. We propose a correction scheme based on many body perturbation theory to calculate the shift from first principles. The ionization potential of the core donor state is first computed and then substituted for the corresponding Kohn--Sham orbital energy, thus emulating Koopmans' condition. Both self-interaction error and orbital relaxation are taken into account. The method exploits the localized nature of core states for efficiency and integrates seamlessly in our previous implementation of core level LR-TDDFT, yielding corrected spectra in a single calculation. We benchmark the correction scheme on molecules at the K- and L-edges as well as for core binding energies and report accuracies comparable to higher order methods. We also demonstrate applicability in large and extended systems and discuss efficient approximations.

Tags: first-principles, marveldd4, tddft, xas
Asymmetric elimination reaction on chiral metal surfaces

The production of enantiopure materials and molecules is of uttermost relevance in research and industry in numerous contexts, ranging from non-linear optics to asymmetric synthesis. In the context of the latter, we have investigated dehalogenation, which is an essential reaction step for a broad class of chemical reactions. Specifically, dehalogenation of prochiral 5-bromo-7-methylbenz(a)anthracene (BMA) on prototypical, chiral, intermetallic PdGa{111} surfaces under ultrahigh vacuum conditions. Enantioselective halogen elimination is demonstrated by combining temperature-programmed x-ray photoelectron spectroscopy, scanning probe microscopy, and density functional theory. On the PdGa{111} surfaces, the difference in debromination temperatures for the two BMA surface enantiomers amounts up to unprecedented 46 K. The significant dependence of the dehalogenation temperature of the BMA surface enantiomers on the atomic termination of the PdGa{111} surfaces, implies that the ensemble effect is pronounced in this reaction step. These findings evidence enantiospecific control and hence promote intrinsically chiral crystals for asymmetric on-surface synthesis. 
The record contains input files to reproduce the calculations discussed in the manuscript and the raw data of the experimental images discussed.

Tags: ab-initio, enantioselectivity, marveldd3, scanning-probe-microscopy, snsf
Sampling enhancement by metadynamics driven by machine learning and de novo protein modelling

Folding of villin miniprotein was studied by parallel tempering metadynamics driven by machine learning. To obtain a training set for machine learning, we generated a large series of structures of the protein by the de novo protein structure prediction package Rosetta. A neural network was trained to approximate the Rosetta score. Parallel tempering metadynamics driven by this approximated Rosetta score successfully predicted the native structure and the free energy surface of the studied system.
These files make it possible to rerun all simulations. The directory METAD contains input files for metadynamics (no folding events observed). The directory PT-METAD contains input files for parallel tempering metadynamics. All simulations were done using Gromacs 2016.4, Anncolvar 0.8, Plumed 2.4 and OpenMPI 4.0.0.

Tags: collective-variable, machine-learning, metadynamics, protein-folding, scoring-function
Reinvestigating the surface and bulk electronic properties of Cd3As2

This record contains the experimental results of our reinvestigation of the bulk and surface electronic properties of Cd3As2, a well-known material proposed to realize the 3D Dirac semimetal phase. By using polarization-based matrix element effects in photoemission, we reveal multiple bands crossing the Fermi level, characterized by different orbital character. Those states exhibit also largely different effective masses, and by combining alkali metal deposition and photon energy dependent ARPES, we report that the linearly dispersing band, which was previously interpreted as a bulk Dirac particle, is indeed a 2D surface Dirac state.

Tags: 3d-dirac-semimetal, electronic-bands, erc, experimental, marvel, polarization-and-energy-dependent-arpes, snsf
Porous functionalized polymers enable generating and transporting hyperpolarized mixtures of metabolites

Hyperpolarization by dissolution dynamic nuclear polarization (dDNP) has enabled promising applications in spectroscopy and imaging, but remains poorly widespread due to experimental complexity. Broad democratization of dDNP would require remote preparation and distribution of hyperpolarized samples from dedicated facilities. We describe here new hyperpolarizing polymers (HYPOPs) that can generate radical- and contaminant-free hyperpolarized samples within minutes with lifetimes exceeding hours in the solid state. HYPOPs feature tunable macroporous porosity, with porous volumes up to 80% and concentration of nitroxide radicals grafted in the bulk matrix up to 285 μmol g-1. Analytes can be efficiently impregnated as aqueous/alcoholic solutions and hyperpolarized up to P(13C) =25% within 8 min, through the combination of 1H spin diffusion and 1H →13C cross polarization. Solutions of 13C-analytes of biological interest hyperpolarized in HYPOPs display a very long solid-state 13C relaxation times of 5.7 h at 3.8 K, thus prefiguring transportation over long distances.

Tags: dnp, experimental, hyperpolarization, porous-polymers
Designing crystallization to tune the performance of phase-change memory: rules of hierarchical melt and coordinate bond

While alloy design has practically shown an efficient strategy to mediate two seemingly conflicted performances of writing speed and data retention in phase-change memory, the detailed kinetic pathway of alloy-tuned crystallization is still unclear. Here, we propose hierarchical melt and coordinate bond strategies to solve them, where the former stabilizes a medium-range crystal-like region and the latter provides a rule to stabilize amorphous. The Er0.52Sb2Te3 compound we designed achieves writing speed of 3.2 ns and ten-year data retention of 161 °C. We provide a direct atomic-level evidence that two neighbor Er atoms stabilize a medium-range crystal-like region, acting as a precursor to accelerate crystallization; meanwhile, the essential reason of stabilization originates from the formation of coordinate bonds by sharing lone-pair electrons of chalcogenide atoms with the empty 5d orbitals of Er atoms. The two rules pave the way for the development of storage-class memory with excellent comprehensive performance to achieve next revolutionary technology node.

Tags: coordinate-bond, er-sb-te, experimental, hierarchical-melt, phase-change-memory
Molecular mechanism of gas solubility in liquid: constant chemical potential molecular dynamics simulations

Accurate prediction of gas solubility in a liquid is crucial in many areas of chemistry, and a detailed understanding of the molecular mechanism of the gas solvation continues to be an active area of research. Here, we extend the idea of the constant chemical potential molecular dynamics (CμMD) approach to the calculation of the gas solubility in the liquid under constant gas chemical potential conditions. As a representative example, we utilize this method to calculate the isothermal solubility of carbon dioxide in water. Additionally, we provide microscopic insight into the mechanism of solvation that preferentially occurs in areas of the surface where the hydrogen network is broken.

Tags: constant-chemical-potential-simulations, erc, marveldd1, solution
Fast Bayesian force fields from active learning: study of inter-dimensional transformation of stanene

Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor the quality of model predictions. A current limitation of existing GP force fields is that the prediction cost grows linearly with the size of the training data set, making accurate GP predictions slow. 
In this work, we exploit the special structure of the kernel function to construct a mapping of the trained Gaussian process model, including both forces and their uncertainty predictions, onto spline functions of low-dimensional structural features. This method is incorporated in the Bayesian active learning workflow for training of Bayesian force fields. 
To demonstrate the capabilities of this method, we construct a force field for stanene and perform large scale dynamics simulation of its structural evolution. 
We provide a fully open-source implementation of our method, as well as the training and testing examples with the stanene dataset.

Tags: bayesian-inference, machine-learning, molecular-dynamics, phase-transition, stanene
Fast Bayesian force fields from active learning and mapped Gaussian processes: application to structural phase transition of stanene

Gaussian process (GP) regression is one promising technique of constructing machine learning force fields with built-in uncertainty quantification, which can be used to monitor the quality of model predictions. A current limitation of existing GP force fields is that the prediction cost grows linearly with the size of the training data set, making accurate GP predictions slow. 
In this work, we exploit the special structure of the kernel function to construct a mapping of the trained Gaussian process model, including both forces and their uncertainty predictions, onto spline functions of low-dimensional structural features. This method is incorporated in the Bayesian active learning workflow for training of Bayesian force fields. 
To demonstrate the capabilities of this method, we construct a force field for stanene and perform large scale dynamics simulation of its structural evolution. 
We provide a fully open-source implementation of our method, as well as the training and testing examples with the stanene dataset.

Tags: bayesian-inference, machine-learning, molecular-dynamics, phase-transition, stanene
Enlisting potential cathode materials for rechargeable Ca batteries.

The development of rechargeable batteries based on a Ca metal anode demands the identification of suitable cathode materials. This work investigates the potential application of a variety of compounds, which are selected from the In-organic Crystal Structural Database (ICSD) considering 3d-transition metal oxysulphides, pyrophosphates, silicates, nitrides, and phosphates with a maximum of four different chemical elements in their composition. Cathode perfor-mance of CaFeSO, CaCoSO, CaNiN, Ca3MnN3, Ca2Fe(Si2O7), CaM(P2O7) (M = V, Cr, Mn, Fe, Co), CaV2(P2O7)2, Ca(VO)2(PO4)2 and α-VOPO4 is evaluated throughout the calculation of operation voltages, volume changes associated to the redox reaction and mobility of Ca2+ ions. Some materials exhibit attractive specific capacities and intercalation voltages combined with energy barriers for Ca migration around 1 eV (CaFeSO, Ca2FeSi2O7 and CaV2(P2O7)2). Based on the DFT results, αI-VOPO4 is identified as a potential Ca-cathode with a maximum theoretical specific capacity of 312 mAh/g, an average intercalation voltage of 2.8 V and calculated energy barriers for Ca migration below 0.65 eV (GGA functional).

Tags: ca-batteries, cathode-materials, h2020, neb, vasp
Computational design of moiré assemblies aided by artificial intelligence

Two-dimensional (2D) layered materials offer a materials platform with potential applications from energy to information processing devices. Although some single- and few-layer forms of materials such as graphene and transition metal dichalcogenides have been realized and thoroughly studied, the space of arbitrarily layered assemblies is still mostly unexplored. The main goal of this work is to demonstrate precise control of layered materials' electronic properties through careful choice of the constituent layers, their stacking, and relative orientation. Physics-based and AI-driven approaches for the automated planning, execution, and analysis of electronic structure calculations are applied to layered assemblies based on prototype one-dimensional (1D) materials and realistic 2D materials. We find it is possible to routinely generate moiré band structures in 1D with desired electronic characteristics such as a band gap of any value within a large range, even with few layers and materials (here, four and six, respectively). We argue that this tunability extends to 2D materials by showing the essential physical ingredients are already evident in calculations of two-layer MoS2 and multi-layer graphene moiré assemblies.

Tags: artificial-neural-networks, electronic-structure, high-throughput-calculations, two-dimensional-materials
Radial spin texture of the Weyl fermions in chiral tellurium

Trigonal tellurium, a small-gap semiconductor with pronounced magneto-electric and magneto-optical responses, is among the simplest realizations of a chiral crystal. We have studied by spin- and angle-resolved photoelectron spectroscopy its unconventional electronic structure and unique spin texture. We identify Kramers–Weyl, composite, and accordionlike Weyl fermions, so far only predicted by theory, and show that the spin polarization is parallel to the wave vector along the lines in k space connecting high-symmetry points. Our results clarify the symmetries that enforce such spin texture in a chiral crystal, thus bringing new insight in the formation of a spin vectorial field more complex than the previously proposed hedgehog configuration. Our findings thus pave the way to a classification scheme for these exotic spin textures and their search in chiral crystals.

This records refers to the experimental data shown in the referenced article, saved as txt files along with a metadata descriptor file.

Tags: chirality, erc, experimental, h2020, snsf, spinarpes, topological-materials
On-surface synthesis of polyazulene with 2,6-connectivity

Azulene, the smallest neutral nonalternant aromatic hydrocarbon, serves not only as a prototype for fundamental studies but also as a versatile building block for functional materials because of its unique opto(electronic) properties. The record contains data to support our recent work where we report the on-surface synthesis and characterization of the homopolymer of azulene connected exclusively at the 2,6-positions using 2,6-diiodoazulene as the monomer precursor. Properties of carbon-based aromatic systems are sensitively determined by their bond topologies. So far, much attention has been paid to the design and synthesis of aromatic materials like conjugated polymers and nanographenes constituted by alternant hydrocarbons, which do not possess odd-membered rings. In contrast, incorporation of non-alternant hydrocarbons has only rarely been explored.

Tags: ab-initio, azulene, marveldd3, on-surface-synthesis, snsf