AndreaBozzo/ceres-open-data-index huggingface dataset:
Vanadium is an optimal element for strengthening in both fcc and bcc high-entropy alloys

The element Vanadium (V) appears unique among alloying elements for providing high strengthening in both the fcc Co-Cr-Fe-Mn-Ni-V and bcc Cr-Mo-Nb-Ta-V-W-Hf-Ti-Zr high-entropy alloy families. The origin of Vanadium's special role is its atomic volume: large in the fcc alloys and small in the bcc alloys, and thus having a large misfit volume in both crystalline structures. A parameter-free theory applicable to both fcc and bcc HEAs rationalizes this finding, with predictions of strength across a range of fcc and bcc alloys in quantitative and qualitative agreement with experiments. In the fcc class, the analysis demonstrates why the newly-discovered NiCoV and Ni0.632V0.368 alloys have far higher strength than any other fcc alloy and are predicted to be the highest attainable. In the bcc class, the analysis demonstrates that the addition of V always increases the strength relative to the same alloys without V. The optimization of complex alloys for high strength should thus center around the inclusion of V as a primary element at concentration levels of around 25 at.%.

Tags: epfl, high-entropy-alloys, marveldd2, solute-strengthening-theory, vanadium, yield-strength
The reaction mechanism of the azide–alkyne Huisgen cycloaddition

In a recent publication we inspected the mechanism of the  azide–alkyne Huisgen cycloaddition. We studied the dynamical aspects of the process using metadynamics computer simulations. We focused on the conformational aspects that determine the course of the reaction and characterize its free energy landscape. This record contains data related to the calculations discussed in the publication.

Tags: huisgen-cycloaddition, marvel, marveldd3, metadynamics
Charge transfer in LaVO3/LaTiO3 multilayers: Strain-controlled dimensionality of interface metallicity between two Mott insulators

We use density-functional theory plus dynamical mean-field theory to demonstrate the emergence of a metallic layer at the interface between the two Mott insulators LaTiO3 and LaVO3. The metallic layer is due to charge transfer across the interface, which alters the valence state of the transition-metal cations close to the interface. Somewhat counterintuitively, the charge is transferred from the Ti cations with formal d1 electron configuration to the the V cations with formal d2 configuration, thereby increasing the occupation difference of the t2g states. This can be understood as a result of a gradual transition of the charge-transfer energy, or electronegativity, across the interface. The spatial extension of the metallic layer, in particular toward the LaTiO3 side, can be controlled by epitaxial strain, with tensile strain leading to a localization within a thickness of only two unit cells. Our results open up a route for creating a tunable quasi-two-dimensional electron gas in materials with strong electronic correlations.

Tags: dynamical-mean-field-theory, first-principles-calculations, marveldd5, mott-insulators, multilayer-thin-films, superlattices, two-dimensional-electron-gas
Band gap of atomically precise graphene nanoribbons as a function of ribbon length and termination

The record contains the theoretical data supporting a recent publication where we discuss the band gap of finite  armchair graphene nanoribbons with a width of seven rows of carbon atoms (7‐AGNRs) on Au(111) through scanning tunneling microscopy/spectroscopy combined with density functional theory calculations.

Tags: ab-initio, dft, graphene-nanoribbons, marveldd3, stm
The JuDiT database of impurities embedded into a topological insulator

We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical topological insulator Sb2Te3. The density functional calculations of this work were performed with the JuKKR package [1], which allows to embed translational invariance breaking impurities into a crystalline host system based on the Korringa-Kohn-Rostoker Green function method, and were performed with the AiiDA-KKR package [2]. Our database collects, among others, predicted impurity properties like charge doping introduced by the defects, magnetic moments of the impurities and impurity density of states calculations. We include calculations for the intrinsic Fermi level in the middle of the bulk band gap as well as for shifted Fermi level into valence and conduction band which models different experimental conditions. The impurities were embedded into different layers throughout a 6 quintuple layer thick film which allows to investigate the effect of the topological surface state (localized at the surface) on impurity properties. The JuDiT database allows to uncover chemical trends in impurity properties and can help optimizing the next generation of topological materials.

[1] https://jukkr.fz-juelich.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-kkr

Tags: aiida-kkr, density-functional-theory, impurities, impurity, impurity-density-of-states, impurity-properties, judit, kkr, max, ml4q, quantum-anomalous-hall-insulator, topological-insulator, viti
The JuDiT database of impurities embedded into a Topological Insulator

We present JuDiT (Jülich Database of impurities embedded into a Topological insulator) which collects first principles calculation of impurities embedded into the prototypical topological insulator Sb2Te3. The density functional calculations of this work were performed with the JuKKR package [1], which allows to embed translational invariance breaking impurities into crystalline host system based on the Korringa-Kohn-Rostoker Green function method, and were performed with the AiiDA-KKR package [2]. Our database collects, among others,  predicted impurity properties like charge doping introduced by the defects, magnetic moments of the impurities and impurity density of states calculations. We include calculations for the intrinsic Fermi level in the middle of the bulk band gap as well as for shifted Fermi level into valence and conduction band which models different experimental conditions. The impurities were embedded into different layers throughout a 6 quintuple layer thick film which allows to investigate the effect of the topological surface state (localized at the surface) on impurity properties. The JuDiT database allows to uncover chemical trends in impurity properties and can help optimizing the next generation of topological materials.

[1] https://jukkr.fz-juelich.de and www.judft.de
[2] https://github.com/JuDFTteam/aiida-kkr

Tags: aiida-kkr, density-functional-theory, impurities, impurity, impurity-density-of-states, impurity-properties, judit, kkr, max, ml4q, quantum-anomalous-hall-insulator, topological-insulator, viti
Molecular Recognition and Specificity of Biomolecules to Titanium Dioxide from MD Simulations

Titania (TiO2) is used extensively in biomedical applications; efforts to boost the biocompatibility of TiO2 include coating it with the titania binding hexamer, RKLPDA. To understand the binding mechanism of this peptide, we employ molecular dynamics simulations enhanced by metadynamics to study three amino acids present in the peptide – arginine (R), lysine (K), and aspartate (D), on four TiO2 variants that have different degrees of surface hydroxyl groups. We find that binding is a function of both sidechain charge and structure, with R binding to all four surfaces, whereas the affinity of K and D is dependent on the distribution of hydroxyl groups. Informed by this, we study the binding of the titania binding hexamer and 12mer (RKLPDAPGMHTW) on two of the four surfaces, and we see strong correlations between the binding free energy and the primary binding residues, in agreement with prior experiments and simulations. We propose that the discrepancies observed in prior work stem from distribution of surface hydroxyl groups that may be difficult to precisely control on the TiO2 interface.

Tags: biomaterials, metal-oxide, surface-hydroxylation
High energy barriers for edge dislocation motion in body-centered cubic high entropy alloys

Recent theory proposes that edge dislocations in random body-centered cubic (BCC) high entropy alloys have high barriers for motion, conveying high strengths up to high temperatures. Here, the energy barriers for edge motion are computed for two model alloys, NbTaV and MoNbTaW as represented by interatomic potentials, using the Nudged Elastic Band method and compared to theoretical predictions. The average magnitude of the barriers and the average spacing of the barriers along the glide direction agree well with the analytical theory, with no adjustable parameters. The evolution of the barriers versus applied stress is modeled, and the mean strength is in reasonable agreement with the predicted zero-temperature strength. These findings validate the analytic theory. A reduced analytic model based on solute misfit volumes is then applied to Hf-Mo-Nb-Ta-Ti-Zr and Mo-Nb-Ta-Ti-V-W alloys, rationalizing the observed significant strength increases at room temperature and 1000 ∘C upon addition of solutes with large misfit into a base alloy. The analytic theory for edge motion is thus a powerful validated tool for guiding alloy selection.

Tags: atomistic-models, high-entropy-alloys, snsf, solute-strengthening
Reverse dark current in organic photodetectors and the major role of traps as source of noise

Organic photodetectors have promising applications in low-cost imaging, health monitoring and near infrared sensing. Recent research on organic photodetectors based on donor-acceptor systems has resulted in narrow-band, flexible and biocompatible devices, of which the best reach external photovoltaic quantum efficiencies approaching 100%. However, the high noise spectral density of these devices limits their specific detectivity to around 10^13 Jones in the visible and several orders of magnitude lower in the near-infrared, severely reducing performance. Here, we show that the shot noise, proportional to the dark current, dominates the noise spectral density, demanding a comprehensive understanding of the dark current. We demonstrate that, in addition to the intrinsic saturation current generated via charge-transfer states, dark current contains a major contribution from trap-assisted generated charges and decreases systematically with decreasing concentration of traps. By modeling the dark current of several donor-acceptor systems, we reveal the interplay between traps and charge-transfer states as source of dark current and show that traps dominate the generation processes, thus being the main limiting factor of organic photodetectors detectivity.

Tags: dark-current, detectivity, organic-photodetectors, traps
Crystal-graph attention networks for the prediction of stable materials

Graph neural networks have enjoyed great success in the prediction of material properties for both molecules and crystals. These networks typically use the atomic positions (usually expanded in a Gaussian basis) and the atomic species as input. Unfortunately, this information is in general not available when predicting new materials, for which the precise geometrical information is unknown. In this work, we circumvent this problem by predicting the thermodynamic stability of crystal structures without using the knowledge of the precise bond distances. We replace this information with embeddings of graph distances, allowing our networks to be used directly in high-throughput studies based on both composition and crystal structure prototype. Using these embeddings, we combine the newest developments in graph neural networks and apply them to the prediction of the distances to the convex hull. To train these networks, we curate a dataset of over 2 million density-functional calculations of crystals with consistent calculation parameters from various sources. The new dataset allows for the creation of a high quality convex hull and a large scale transfer learning approach. We apply the resulting model to the high-throughput search of 15 million tetragonal perovskites of composition ABCD2. As a result, we identify several thousand potentially stable compounds and demonstrate that transfer learning from the newly curated dataset reduces the required training data by 50%.

Tags: density-functional-theory, high-throughput, pbe
Gas adsorption and process performance data for MOFs

Reticular chemistry provides materials designers with a practically infinite playground on different length scales. However, the space of all plausible materials for a given application is so large that it cannot be explored using a brute-force approach. One promising approach to guide the design and discovery of materials is machine learning, which typically involves learning a mapping of structures onto properties from data. 
To advance the data-driven materials discovery of metal-organic frameworks (MOFs) for gas storage and separation applications we provide a dataset of diverse gas separation properties (CO2, CH4, H2, N2, O2 isotherms); H2S, H2O, Kr, Xe Henry coefficients (computed using grand canonical Monte-Carlo with classical force fields) as well as parasitic energy for carbon capture from natural gas and a coal-fired power plant (computed using a simple process model) for the relaxed structures in the QMOF dataset with their DDEC charges.

Tags: aiida, erc, marvel, mof, nanoporous
Controlling the TiN electrode work function at the atomistic level: a first principles investigation

The paper reports on a theoretical description of work function of TiN, which is one of the most used materials for the realization of electrodes and gates in CMOS devices. Indeed, although the work function is a fundamental quantity in quantum mechanics and also in device physics, as it allows the understanding of band alignment at heterostructures and gap states formation at the metal/semiconductor interface, the role of defects and contaminants is rarely taken into account. Here, by using first principles simulations, we present an extensive study of the work function dependence on nitrogen vacancies and surface oxidation for different TiN surface orientations. The results complement and explain a number of existent experimental data, and provide a useful tool to tailoring transport properties of TiN electrodes in device simulations.

Tags: defects, dft, electrodes, gates, intersect, oxidation, titanium-nitride
HP - A code for the calculation of Hubbard parameters using density-functional perturbation theory

We introduce HP, an implementation of density-functional perturbation theory, designed to compute Hubbard parameters (on-site U and inter-site V) in the framework of DFT+U and DFT+U+V. The code does not require the use of computationally expensive supercells of the traditional linear-response approach; instead, unit cells are used with monochromatic perturbations that significantly reduce the computational cost of determining Hubbard parameters. HP is an open-source software distributed under the terms of the GPL as a component of Quantum ESPRESSO. As with other components, HP is optimized to run on a variety of different platforms, from laptops to massively parallel architectures, using native mathematical libraries (LAPACK and FFTW) and a hierarchy of custom parallelization layers built on top of MPI. The effectiveness of the code is showcased by computing Hubbard parameters self-consistently for the phospho-olivine LixMn0.5Fe0.5PO4 (x=0, 0.5, 1) and by highlighting the accuracy of predictions of the geometry and Li intercalation voltages.

Tags: cscs, density-functional-perturbation-theory, hubbard-parameters, linear-response-theory, marvelosp, open-science, open-source-software, quantum-espresso, self-interaction-corrections, transition-metal-compounds
Scaling properties of RNA as a randomly branching polymer

Formation of base pairs between the nucleotides of a ribonucleic acid (RNA) sequence gives rise to a complex and often highly branched RNA structure. While numerous studies have demonstrated the functional importance of the high degree of RNA branching—for instance, for its spatial compactness or interaction with other biological macromolecules—RNA branching topology remains largely unexplored. Here, we use the theory of randomly branching polymers to explore the scaling properties of RNAs by mapping their secondary structures onto planar tree graphs. Focusing on random RNA sequences of varying lengths, we determine the two scaling exponents related to their topology of branching. Our results indicate that ensembles of RNA secondary structures are characterized by annealed random branching and scale similarly to self-avoiding trees in three dimensions. We further show that the obtained scaling exponents are robust upon changes in nucleotide composition, tree topology, and folding energy parameters. Finally, in order to apply the theory of branching polymers to biological RNAs, whose length cannot be arbitrarily varied, we demonstrate how both scaling exponents can be obtained from distributions of the related topological quantities of individual RNA molecules with fixed length. In this way, we establish a framework to study the branching properties of RNA and compare them to other known classes of branched polymers. By understanding the scaling properties of RNA related to its branching structure, we aim to improve our understanding of the underlying principles and open up the possibility to design RNA sequences with desired topological properties.

Tags: polymer-physics, rna, scaling, statistical-mechanics
Time-resolved oxidation state changes are key to elucidating the bifunctionality of perovskite catalysts for oxygen evolution and reduction

In a unified regenerative fuel cell (URFC) or reversible fuel cell the oxygen bifunctional catalyst must switch reversibly between the oxygen reduction reaction (ORR), fuel cell mode, and the oxygen evolution reaction (OER), electrolyzer mode. However, it is often unclear what effect alternating between ORR and OER has on the electrochemical behavior and physiochemical properties of the catalyst. Herein, operando X-ray absorption spectroscopy (XAS) is utilized to monitor the continuous and dynamic evolution of the Co, Mn, and Fe oxidation states of perovskite catalysts Ba0.5Sr0.5Co0.8Fe0.2O3-δ (BSCF) and La0.4Sr0.6MnO3-δ (LSM), while the potential is oscillated between reducing and oxidizing potentials with cyclic voltammetry. The results reveal the importance of investigating bifunctional catalysts by alternating between fuel cell and electrolyzer operation and highlight the limitations and challenges of bifunctional catalysts. It is shown that the requirements for ORR and OER performance are divergent and that the oxidative potentials of OER are detrimental to ORR activity. These findings are used to give guidelines for future bifunctional catalyst design. Additionally, it is demonstrated how sunlight can be used to reactivate the ORR activity of LSM after rigorous cycling.

Tags: alkaline, experimental, oer, orr, snsf
Extensive benchmarking of DFT+U calculations for predicting band gaps

Accurate computational predictions of band gaps are of practical importance to the modeling and development of semiconductor technologies, such as (opto)electronic devices and photoelectrochemical cells. Among available electronic-structure methods, density-functional theory (DFT) with the Hubbard U correction (DFT+U) applied to band edge states is a computationally tractable approach to improve the accuracy of band gap predictions beyond that of DFT calculations based on (semi)local functionals. At variance with DFT approximations, which are not intended to describe optical band gaps and other excited-state properties, DFT+U can be interpreted as an approximate spectral-potential method when U is determined by imposing the piecewise linearity of the total energy with respect to electronic occupations in the Hubbard manifold (thus removing self-interaction errors in this subspace), thereby providing a (heuristic) justification for using DFT+U to predict band gaps. However, it is still frequent in the literature to determine the Hubbard U parameters semiempirically by tuning their values to reproduce experimental band gaps, which ultimately alters the description of other total-energy characteristics. Here, we present an extensive assessment of DFT+U band gaps computed using self-consistent ab initio U parameters obtained from density-functional perturbation theory to impose the aforementioned piecewise linearity of the total energy. The study is carried out on 20 compounds containing transition-metal or p-block (group III-IV) elements, including oxides, nitrides, sulfides, oxynitrides, and oxysulfides. By comparing DFT+U results obtained using nonorthogonalized and orthogonalized atomic orbitals as Hubbard projectors, we find that the predicted band gaps are extremely sensitive to the type of projector functions and that the orthogonalized projectors give the most accurate band gaps, in satisfactory agreement with experimental data. This work demonstrates that DFT+U may serve as a useful method for high-throughput workflows that require reliable band gap predictions at moderate computational cost.

Tags: band-gap, dftu, hubbard-correction, lowdin-orthogonalization, marvelosp, self-interaction, snsf
Interpretations of ground-state symmetry breaking and strong correlation in wavefunction and density functional theories

Strong correlations within a symmetry-unbroken ground-state wavefunction can show up in approximate density functional theory as symmetry-broken spin-densities or total densities, which are sometimes observable. They can arise from soft modes of fluctuations (sometimes collective excitations) such as spin-density or charge-density waves at non-zero wavevector. In this sense, an approximate density functional for exchange and correlation that breaks symmetry can be more revealing (albeit less accurate) than an exact functional that does not. The examples discussed here include the stretched H2 molecule, antiferromagnetic solids, and the static charge-density wave/Wigner crystal phase of a low-density jellium. Time-dependent density functional theory is used to show quantitatively that the static charge density wave is a soft plasmon. More precisely, the frequency of a related density fluctuation drops to zero, as found from the frequency moments of the spectral function, calculated from a recent constraint-based wavevector- and frequency-dependent jellium exchange-correlation kernel.

This record contains all raw data used in this project. The second version contains better-converged data for the frequency moments. The parameters used to generate this data are included in a text file.

Tags: density-functional-theory, exchange-correlation-kernel, jellium, time-dependent-density-functional-theory
Radial spin texture of the Weyl fermions in chiral tellurium

In the present record we provide the theoretical calculations used in the article: G. Gatti et al., Radial Spin Texture of the Weyl Fermions in Chiral Tellurium, Phys. Rev. Lett. 125, 216402. It consist of a detailed analysis of the electronic structure and spin textures at different points of the Brillouin zone. We provide the band structure and spin expectation values along different high-symmetry lines, Fermi surface contour plots in the ΓMLA plane, and spin texture in small sphere around two points of the Brillouin zone. The data is provided as the output format of the Quantum Espresso package. We also include the pseudopotential used in these calculations.

Tags: chiral-symmetry, cscs, electronic-structure, erc, snsf, spin-texture, topological-materials