cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.24435/materialscloud:15-fs
title: Density functional theory study of silicon nanowires functionalized by grafting organic molecules

description: 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.
DOI: 10.24435/materialscloud:75-zg
title: Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

description: 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.
DOI: 10.24435/materialscloud:54-0s
title: Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

description: We present a sulfur K-edge X-ray absorption near-edge structure (XANES) database of 18 crystalline and 48 amorphous Lithium-Phosphorous-Sulfur (LPS) compounds. The database contains a total of 2681 XANES spectra of symmetrically inequivalent absorbing S sites. Structures were taken from Materials Cloud entry 2022.17 (archive.materialscloud.org/record/2022.17) and were originally generated by systematically removing Li, P and S atoms from known crystal structures using an evolutionary algorithm and an artificial neural network based interatomic potential. The details of this procedure can be found in Guo et al. (see references below). From this data set, low-energy structures were selected for spectral simulations. The excited electron and core hole method as implemented in VASP 6.2.1 was used to compute the XANES spectra for each symmetrically inequivalent Sulfur atom. The details of the VASP simulations can be found in the associated manuscript.

Acknowledgements: We acknowledge financial support by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Contract No. DE-SC0012704. These results used the computational resources of the Center for Functional Nanomaterials and the Scientific Data and Computing Center, a component of the Computational Science Initiative, at Brookhaven National Laboratory under the Contract No. DE-SC0012704. We also acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010.
DOI: 10.24435/materialscloud:6z-qm
title: Simulated sulfur K-edge X-ray absorption spectroscopy database of lithium thiophosphate solid electrolytes

description: We present a sulfur K-edge X-ray absorption near-edge structure (XANES) database of 18 crystalline and 48 amorphous Lithium-Phosphorous-Sulfur (LPS) compounds. The database contains a total of 2681 XANES spectra of symmetrically inequivalent absorbing S sites. Structures were taken from Materials Cloud entry 2022.17 (archive.materialscloud.org/record/2022.17) and were originally generated by systematically removing Li, P and S atoms from known crystal structures using an evolutionary algorithm and an artificial neural network based interatomic potential. The details of this procedure can be found in Guo et al. (see references below). From this data set, low-energy structures were selected for spectral simulations. The excited electron and core hole method as implemented in VASP 6.2.1 was used to compute the XANES spectra for each symmetrically inequivalent Sulfur atom. The details of the VASP simulations can be found in the associated manuscript.

Acknowledgements: We acknowledge financial support by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office, Contract No. DE-SC0012704. These results used the computational resources of the Center for Functional Nanomaterials and the Scientific Data and Computing Center, a component of the Computational Science Initiative, at Brookhaven National Laboratory under the Contract No. DE-SC0012704. We also acknowledge computing resources from Columbia University's Shared Research Computing Facility project, which is supported by NIH Research Facility Improvement Grant 1G20RR030893-01, and associated funds from the New York State Empire State Development, Division of Science Technology and Innovation (NYSTAR) Contract C090171, both awarded April 15, 2010.
DOI: 10.15468/dl.9jcd6y
title: Occurrence Download

description: A dataset containing 16087 species occurrences available in GBIF matching the query:
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 "Geometry POLYGON((-79.32832 43.62799,-79.32452 43.62687,-79.32102 43.63258,-79.32462 43.63364,-79.32832 43.62799))"
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 The dataset includes 16087 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067089-250525065834625/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.24435/materialscloud:gf-5j
title: Long-range electrostatic contribution to the electron-phonon couplings and mobilities of two-dimensional and bulk materials

description: Charge transport plays a crucial role in manifold potential applications of two-dimensional materials, including field effect transistors, solar cells, and transparent conductors. At most operating temperatures, charge transport is hindered by scattering of carriers by lattice vibrations. Assessing the intrinsic phonon-limited carrier mobility is thus of paramount importance to identify promising candidates for next-generation devices. Here we provide a framework to efficiently compute the  drift and Hall carrier mobility of two-dimensional materials through the Boltzmann transport equation by relying on a Fourier-Wannier interpolation. Building on a recent formulation of long-range contributions to dynamical matrices and phonon dispersions [Phys. Rev. X 11, 041027 (2021)], we extend the approach to electron-phonon coupling including the effect of dynamical dipoles and quadrupoles. We identify an unprecedented contribution associated with the Berry connection that is crucial to preserve the Wannier-gauge covariance of the theory. This contribution is not specific to 2D crystals, but also concerns the 3D case, as we demonstrate via an application to bulk SrO. We showcase our method on a wide selection of relevant monolayers ranging from SnS₂ to MoS₂, graphene, BN, InSe, and phosphorene. We also discover a non-trivial temperature evolution of the Hall hole mobility in InSe whereby the mobility increases with temperature above 150~K due to the mexican-hat electronic structure of the InSe valence bands. Overall, we find that dynamical quadrupoles are essential and can impact the carrier mobility in excess of 75%.
DOI: 10.24435/materialscloud:pb-bk
title: Long-range electrostatic contribution to the electron-phonon couplings and mobilities of two-dimensional and bulk materials

description: Charge transport plays a crucial role in manifold potential applications of two-dimensional materials, including field effect transistors, solar cells, and transparent conductors. At most operating temperatures, charge transport is hindered by scattering of carriers by lattice vibrations. Assessing the intrinsic phonon-limited carrier mobility is thus of paramount importance to identify promising candidates for next-generation devices. Here we provide a framework to efficiently compute the  drift and Hall carrier mobility of two-dimensional materials through the Boltzmann transport equation by relying on a Fourier-Wannier interpolation. Building on a recent formulation of long-range contributions to dynamical matrices and phonon dispersions [Phys. Rev. X 11, 041027 (2021)], we extend the approach to electron-phonon coupling including the effect of dynamical dipoles and quadrupoles. We identify an unprecedented contribution associated with the Berry connection that is crucial to preserve the Wannier-gauge covariance of the theory. This contribution is not specific to 2D crystals, but also concerns the 3D case, as we demonstrate via an application to bulk SrO. We showcase our method on a wide selection of relevant monolayers ranging from SnS₂ to MoS₂, graphene, BN, InSe, and phosphorene. We also discover a non-trivial temperature evolution of the Hall hole mobility in InSe whereby the mobility increases with temperature above 150~K due to the mexican-hat electronic structure of the InSe valence bands. Overall, we find that dynamical quadrupoles are essential and can impact the carrier mobility in excess of 75%.
DOI: 10.24435/materialscloud:vx-ew
title: A bridge between trust and control: Computational workflows meet automated battery cycling

description: 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.
DOI: 10.24435/materialscloud:xb-4f
title: Resolving the solvation structure and transport properties of aqueous zinc electrolytes from salt-in-water to water-in-salt using neural network potential

description: 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).
DOI: 10.24435/materialscloud:1k-qd
title: Engineering solvation in initiated Chemical Vapor Deposition (iCVD) for process-property control

description: 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.
DOI: 10.24435/materialscloud:9g-02
title: Resolving the solvation structure and transport properties of aqueous zinc electrolytes from salt-in-water to water-in-salt using neural network potential

description: 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).
DOI: 10.24435/materialscloud:98-61
title: Engineering solvation in initiated Chemical Vapor Deposition (iCVD) for process-property control

description: 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.
DOI: 10.24435/materialscloud:85-ys
title: Complex magnetic structure and spin waves of the noncollinear antiferromagnet Mn₅Si₃

description: 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.
DOI: 10.24435/materialscloud:dh-ym
title: Complex magnetic structure and spin waves of the noncollinear antiferromagnet Mn₅Si₃

description: 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.
DOI: 10.24435/materialscloud:s6-39
title: Fatigue database of high entropy alloys

description: 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.
DOI: 10.24435/materialscloud:6x-sb
title: Fatigue database of high entropy alloys

description: 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.
DOI: 10.24435/materialscloud:v8-hq
title: Unveiling the pH-dependent structure-activity relationship of Co-based catalysts toward oxygen evolution reaction

description: 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.