AndreaBozzo/ceres-open-data-index huggingface dataset:
Single in-situ interface characterization composed of niobium and a selectively grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

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

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

Tags: density-functional-theory, experiment, majorana, superconductivity, topological-materials, topological-superconductor, transport
Characterization of single in situ prepared interfaces composed of niobium and a selectively-grown (Bi1-xSbx)2Te3 topological insulator nanoribbon

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

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

Tags: density-functional-theory, experiment, majorana, superconductivity, topological-materials, topological-superconductor, transport
Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

The accurate description of the structural and thermodynamic properties of ferroelectrics has been one of the most remarkable achievements of Density Functional Theory (DFT). However, running large simulation cells with DFT is computationally demanding, while simulations of small cells are often plagued with non-physical effects that are a consequence of the system's finite size. Therefore, one is often forced to use empirical models that describe the physics of the material in terms of effective interaction terms, that are fitted using the results from DFT, to perform simulations that do not suffer from finite size effects. In this study we use a machine-learning (ML) potential trained on DFT, in combination with accelerated sampling techniques, to converge the thermodynamic properties of Barium Titanate (BTO) with first-principles accuracy and a full atomistic description. Our results indicate that the predicted Curie temperature depends strongly on the choice of DFT functional and system size, due to the presence of emergent long-range directional correlations in the local dipole fluctuations. Our findings demonstrate how the combination of ML models and traditional bottom-up modeling allow one to investigate emergent phenomena with the accuracy of first-principles calculations and the large size and time scales afforded by empirical models.

Tags: dielectric-correlations, ferroelectrics, finite-size-effects, hybrid-dft-ml, machine-learning-potentials, marvel, metadynamics, phase-transitions, sinergia, snsf
Density functional theory study of silicon nanowires functionalized by grafting organic molecules

Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs.   
This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on SiNWs using the slab models for the Si facets since our reference are samples with diameters of SiNWs around 50 nm, while the quantum confinement effects are important for diameters below 10 nm.  For each configuration, structural characterization was conducted by calculating quantities including the bond distance between the two carbons closest to the surface and their respective bond angle relative to the z-axis, the carbon-silicon bond distance and its respective bond angle relative to the z-axis, along with the molecule's rotation angle in the xy plane. The values obtained are summarized in the main folder. The version v1 of dataset contains data related to the Si(111) surface and alkanes, alkenes, and alkynes with lengths from C2 to C10. The dataset will be extended to characterize the Si110 surface of the nanowire and explore longer molecules ranging from C12 to C18. For each system the most stable configuration will be identified, and the analysis of the electronic properties will be conducted.

Tags: aliphatic-molecules, dft, nanowires, silicon, surface-adsorption
Resolving the solvation structure and transport properties of aqueous zinc electrolytes from salt-in-water to water-in-salt using neural network potential

This database contains the neural network potential (NNP) model and training data for aqueous ZnCl₂ solutions from 1 m to 30 m. The NNP model can be used to compute total energies and atomic forces, with one of its major applications being large-scale molecular dynamics (MD) simulations. The model was trained using DeePMD-kit v2.2.1, with training data generated through an active learning approach implemented in DP-GEN. The energies and forces in the training set were obtained from density functional theory (DFT) calculations using the SCAN exchange-correlation functional performed using Quantum ESPRESSO. Further details on the ab initio calculation procedures and model training methodology are available in the associated manuscript (see reference below).

Tags: deepmd, neural-network-potential, water, water-in-salt, zncl2-solution
Engineering solvation in initiated Chemical Vapor Deposition (iCVD) for process-property control

Organic solvents are widely used in polymer synthesis, despite their use lengthening purification steps and generating chemical waste. All-dry synthesis techniques, such as initiated Chemical Vapour Deposition (iCVD) polymerization, eliminate the use of solvents, however, only a narrow palette of material properties is accessible. Inspired by the principles of solvent engineering in solution synthesis, we report a strategy to broaden this palette by vapour-phase complexing (namely, vapour-phase solvation) mediated by hydrogen-bonding. Broad ranges of polymer chain length, as well as the mechanical strength and variety of film surface morphology are demonstrating using this strategy. We further achieve an unprecedented solvation modality; more specifically, interfacial solvation. The molecular interactions, locations of solvation, and kinetics of the coupled solvation-adsorption-polymerization process are investigated using molecular dynamic simulations and experimental validation of a theoretical kinetic model. The strategy can be applied to various methacrylate and vinyl monomers. Solvation in all-dry polymerization offers a new degree of freedom in polymer design and synthesis with improved environmental benignness, pointing to accelerated discovery of polymer thin films by simply introducing active solvents in the vapour phase. Here we provided the code for data processing to the result of the molecular dynamic simulation.

Tags: icvd, molecular-dynamics-simulation, polymer-thin-film
Complex magnetic structure and spin waves of the noncollinear antiferromagnet Mn₅Si₃

Mn₅Si₃ displays an unusual and complex magnetic ground state, which is considered to be the origin of the anomalous transport and thermodynamic properties that it exhibits. We report the magnetic exchange couplings of the noncollinear antiferromagnetic phase of Mn₅Si₃ using inelastic neutron scattering measurements and density functional theory calculations. We determine the ground-state spin configuration and compute its magnon dispersion relations which are in good agreement with the ones obtained experimentally. Furthermore, we investigate the evolution of the spin texture under the application of an external magnetic field to demonstrate theoretically the multiple field-induced phase transitions that Mn₅Si₃ undergoes. Finally, we model the stability of some of the material's magnetic moments under a magnetic field and we find that very susceptible magnetic moments in a frustrated arrangement can be tuned by the field. This data set contains the data relevant to perform the DFT calculations with the JuKKR code, the spin dynamics simulations with the Spirit code, the spin-wave calculations with the SWIS code, and the neutron scattering experimental data.

Tags: antiferromagnetism, frustration, inelastic-neutron-scattering, intersect, marvel, noncollinear-magnetism, spin-waves
Fatigue database of high entropy alloys

Fatigue failure of metallic structures is of great concern to industrial applications. A material will not be able to practically useful if it is prone to fatigue failure. To take the advantage of lately emerged high entropy alloys (HEAs) for designing novel fatigue-resistant alloys, we compiled a fatigue database of HEAs from the literature reported till the yearend of 2021. The database is subdivided into three categories, i.e., low-cycle fatigue (LCF), high-cycle fatigue (HCF), and fatigue crack growth rate (FCGR), which contains 15, 23, and 28 distinct data records, respectively. Each data record in any of three categories is characteristic of a summary, which is comprised of alloy composition, key fatigue properties, and additional information influential to or interrelated with fatigue (e.g., material processing history, phase constitution, grain size, uniaxial tensile properties, and fatigue testing conditions), and an individual dataset, which makes up the original fatigue testing curve.

Tags: fatigue-crack-growth-rate, high-cycle-fatigue, high-entropy-alloy, low-cycle-fatigue
Unveiling the pH-dependent structure-activity relationship of Co-based catalysts toward oxygen evolution reaction

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

Tags: acidic-oxygen-evolution, co-oxidation-state, cobalt-based-catalyst, spin-state, structure-activity-relationship
Influence of the triangular Mn-O breathing mode on magnetic ordering in multiferroic hexagonal manganites

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

Tags: ab-initio, dftu, erc, h-rmno3, marvel
Density functional theory study of silicon nanowires functionalized by grafting organic molecules

Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs.  
This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on SiNWs using the slab models for the Si facets since our reference are samples with diameters of SiNWs around 50 nm, while the quantum confinement effects are important for diameters below 10 nm.  For each configuration, structural characterization was conducted by calculating quantities including the bond distance between the two carbons closest to the surface and their respective bond angle relative to the z-axis, the carbon-silicon bond distance and its respective bond angle relative to the z-axis, along with the molecule's rotation angle in the xy plane. The values obtained are summarized in the main folder. The version v1 of dataset contains data related to the Si(111) surface and alkanes, alkenes, and alkynes with lengths from C2 to C10. This version (v2) extends the dataset to moieties from C12 to C18. The dataset will be extended to characterize the Si(110) surface of the nanowire. For each system the most stable configuration will be identified, and the analysis of the electronic properties will be conducted.

Tags: aliphatic-molecules, dft, nanowires, silicon, surface-adsorption
The optimal resolution level of a protein is an emergent property of its structure and dynamics

Molecular dynamics simulations provide a wealth of data whose in-depth analysis can be computationally demanding and, sometimes, even unnecessary. Dimensionality reduction techniques are thus routinely employed to simplify and improve the interpretation of trajectories focusing on specific subsets of the system's atoms; a key issue, in this context, is to determine the optimal resolution level, i.e. the smallest number of atoms needed to preserve the largest information content from the full atomistic trajectory. Here, we introduce the protein optimal resolution identification method (PROPRE), an unsupervised approach built on information theory principles that determines the smallest number of atoms that need to be retained to attain a synthetic yet informative description of a protein. By applying the method to a protein dataset and two particular case studies, we show that this number is typically between 1.5 and 2 times the number of residues in a protein; nonetheless, the degree of conformational variability of the system influences the specific number importantly, in that a broader range of large-scale conformations correlates with fewer retained sites. The PROPRE method is implemented in efficient and user-friendly python scripts, which are made available for download on a github repository.
Here, the raw data employed for the preparation of the associated manuscript are made available.

Tags: coarse-graining, model-resolution, molecular-dynamics
A bridge between trust and control: Computational workflows meet automated battery cycling

Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We successfully interface off-the-shelf battery cycling hardware with the computational workflow management software AiiDA, allowing us to control experiments, while ensuring trust in the data by tracking its provenance. We design user interfaces compatible with this tooling, which span the inventory, experiment design, and result analysis stages. Other features, including monitoring of workflows and import of externally generated and legacy data are also implemented. Finally, the full software stack required for this work is made available in a set of open-source packages.

Tags: aurora, battery, big-map, cycling, marvel, premise, robot, workflow
Phononic origin of the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, Ho, Lu) compounds

Understanding the phononic origin of the infrared dielectric properties of yttria (Y₂O₃) and other rare-earth sesquioxides (RE₂O₃) is a fundamental task in the search of appropriate RE₂O₃ materials that serve particular infrared optical applications. We herein investigate the infrared dielectric properties of RE₂O₃ (RE = Y, Gd, Ho, Lu) using DFT-based phonon calculations and Lorentz oscillator model. The abundant IR-active optical phonon modes that are available for effective absorption of photons result in high reflectance of RE₂O₃, among which four IR-active modes originated from large distortions of REO₆ octahedra are found to contribute dominantly to the phonon dielectric constants. Particularly, the present calculation method by considering one-phonon absorption process is demonstrated with good reliability in predicting the infrared dielectric parameters of RE₂O₃ at the far-infrared as well as the vicinity of mid-infrared region, and the potential cutoff frequency/wavelength of its applicability is disclosed as characterized by the maximum frequency of IR-active longitudinal phonon modes. The results deepen the understanding on infrared dielectric properties of RE₂O₃, and aid the computational design of materials with appropriate infrared properties.

Tags: first-principles, infrared, phonon, sesquioxides
Density functional theory study of silicon nanowires functionalized by grafting organic molecules

Functionalizing Silicon Nanowires (SiNWs) through covalent attachment of organic molecules offers diverse advantages, including surface passivation, introduction of new functionalities, and enhanced material performance in applications like electronic devices and biosensors. Given the wide range of available functional molecules, systematic large-scale screening is crucial. Therefore, we developed an automated computational workflow using Python scripts in conjunction with the AiiDa framework to explore structural configurations of functional molecules adsorbed onto silicon surfaces. This workflow generates multiple adhesion configurations corresponding to different binding orientations using surface and functional molecule structures as inputs.  
This dataset contains data related to the structural optimization of molecules with single, double, and triple carbon-carbon bonds attached to the nanowire surface in various adhesion configurations. We describe the chemisorption on SiNWs using the slab models for the Si facets since our reference are samples with diameters of SiNWs around 50 nm, while the quantum confinement effects are important for diameters below 10 nm.  For each configuration, structural characterization was conducted by calculating quantities including the bond distance between the two carbons closest to the surface and their respective bond angle relative to the z-axis, the carbon-silicon bond distance and its respective bond angle relative to the z-axis, along with the molecule's rotation angle in the xy plane. The values obtained are summarized in the main folder. The version v1 of dataset contains data related to the Si(111) surface and alkanes, alkenes, and alkynes with lengths from C2 to C10. The version v2 extends the dataset to moieties from C12 to C18. This version (v3) extends the dataset with new configurations for moieties from C2 to C18. The dataset will be extended to characterize the Si(110) surface of the nanowire. For each system the most stable configuration will be identified, and the analysis of the electronic properties will be conducted.

Tags: aliphatic-molecules, dft, nanowires, silicon, surface-adsorption