Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
2,904
datasets available to search
ShareScore release 0.9.0
Dataset results
2,904 results for “Solute”
Raw data for the article entitled "Facile Solution Synthesis, Processing and Characterization of n- and p-Type Binary and Ternary Bi–Sb Tellurides"
<p>Raw data for the plots in the open access article "Facile Solution Synthesis, Processing and Characterization of n- and p-Type Binary and Ternary Bi–Sb Tellurides"</p>
Raw data for the plots in the article entitled "Thermoelectric Inks and Power Factor Tunability in Hybrid Films through All Solution Process"
<p>Raw data for the plots in the article entitled "Thermoelectric Inks and Power Factor Tunability in Hybrid Films through All Solution Process"</p> <p>https://doi.org/10.1021/acsami.1c24392 </p> <p>ACS Appl. Mater. Interfaces 2022, 14, 19295−19303</p>
Waveform data for centroid moment tensor solutions presented in publication "Bayesian seismic source inversion with a 3-D Earth model of the Japanese islands"
<p>The dataset includes waveform data for centroid moment tensor solutions inferred using Hamiltonian Monte Carlo and a 3-D Earth model in the Japanese islands. The data are provided as Green's strains at the maximum-likelihood location (indicated in the title of each text file) for all study events inverted at different periods. Inversion period is also indicated in the title. All the data are filtered between 15 s and 80 s. Additionally we provide a Python code to obtain displacement from strains given a moment tensor.</p>
End-condition for solution small angle X-ray scattering measurements by kernel density estimation
<p>The set of python scripts and some datasets for estimating the minimum X-ray exposure time for X-ray solution scattering experiments using statistical and mathematical approaches.</p> <p>We apply a statistical inequality to estimate the kernel density estimation (KDE) method’s error to determine the minimum X-ray exposure time.</p> <p>Please refer to the following article, </p> <p>End-condition for solution small angle X-ray scattering measurements by kernel density estimation<br> Science and Technology of Advanced Materials: Methods, Volume 2 Issue 1, pages 426-434 (2022)<br> DOI: 10.1080/27660400.2022.2140021<br> <a href="https://doi.org/10.1080/27660400.2022.2140021">https://doi.org/10.1080/27660400.2022.2140021</a></p>
Atomic coordinates used in the solution of a TDRD2 crystal structure
<p>These coordinates were referred to as "Coordinates from [...] an unpublished TDRD2 crystal structure" in Supporting Information of our manuscript <em>Structural basis for arginine methylation-independent recognition of PIWIL1 by TDRD2</em>. This model has not been validated for any other use.</p>
Solute particle near a nanopore: influence of size and surface properties on the solvent-mediated forces: ftDFT code
<p>This is the complete ftDFT code used to generate the results reported in our Nov 2017 Nanoscale article "Solute particle near a nanopore: influence of size and surface properties on the solvent-mediated forces",DOI: 10.1039/C7NR07218J. </p>
Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions
<div> <div>The rich information of electron energy-loss spectroscopy (EELS) comes from the complex inelastic scattering process whereby fast electrons transfer energy and momentum to atoms, exciting bound electrons from their ground states to higher unoccupied states. To quantify EELS, the common practice is to compare the cross-sections integrated within an energy window or fit the observed spectrum with theoretical differential cross-sections calculated from a generalized oscillator strength (GOS) database with experimental parameters [1].</div> <div> </div> </div> <div> <div> <div> <div>The previous Hartree-Fock-based [2] or DFT-based [3] GOS was calculated from Schrödinger's solution of atomic orbitals, which does not include the full relativistic effects. Here, we attempt to go beyond the limitations of the Schrödinger solution in the GOS tabulation by including the full relativistic effects using the Dirac equation within the local density approximation using FAC [4], which is particularly important for core-shell electrons of heavy elements with strong spin-orbit coupling. This has been done for all elements in the periodic table (up to Z = 118) for all possible excitation edges using modern computing capabilities and parallelization algorithms. The relativistic effects of fast incoming electrons were included to calculate cross-sections that are specific to the acceleration voltage. We make these tabulated GOS available under an open-source license to the benefit of both academic users as well as allowing integration into commercial solutions.</div> <div> </div> <div>If you wish to be notfied by the database updates, please register <a href="https://forms.gle/ddpJSPrCbPZNL1oH7" target="_blank" rel="noopener">here</a>.</div> <div> </div> <div>For details, you can find the paper on <a href="https://arxiv.org/abs/2405.10151">arxiv</a>.</div> </div> </div> </div> <p>Database Details:</p> <ul> <li>Covers all elements (Z: 1-108) and all edges</li> <li>Large energy range: 0.01 - 4000 eV</li> <li>Large momentum range: from minimum momentum transfer to double Bethe ridge for each edge. Adaptive momentum sampling is developed in such a manner to maximize the physical information for a given finite number of sampling points. For example, for C edge this range is 0.14 -67 Å-1 </li> <li>Fine log sampling: 128 points for energy and 256 points for momentum</li> <li>Data format: GOSH [3]</li> </ul> <p>Calculation Details:</p> <ul> <li>Single atoms only; solid-state effects are not considered</li> <li>Unoccupied states before continuum states of ionization are not considered; no fine structure</li> <li>Plane Wave Born Approximation</li> <li>Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when a core-shell</li> <li>electron is excited</li> <li>Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; A modified local density approximation is used for the correct asymptotic behavior of the exchange energy; continuum states are normalized against asymptotic form at large distances</li> <li>Both large and small component contributions of Dirac solutions are included in GOS</li> <li>Final state contributions are included until the contribution of the last states falls below 0.1%. A convergence log is provided for reference.</li> </ul> <p>Version 1.6.5 release note:</p> <ul> <li>Add a compact version of the database which uses (a) single precesion, (b) 80x80 sampling in the energy and momentum space (c) 'gzip' to compress the gos data array. This helps for user with limited bandwidth for downloading.</li> </ul> <p>Version 1.6.1 release note:</p> <ul> <li>Add missing metadata</li> </ul> <p>Version 1.6 release note:</p> <ul> <li>Improved convergence for M and N edges for some elements</li> </ul> <p>Version 1.5 release note:</p> <ul> <li>Adaptive sampling for momentum space (previously it is fixed at 0.05 -50 Å-1, now adaptive for each edge)</li> <li>Improved convergence</li> </ul> <p>Version 1.2 release note:</p> <ul> <li>Add “File Type / File version” information</li> </ul> <p>Version 1.1 release note:</p> <ul> <li>Update to be consistent with GOSH data format [3]</li> <li>All the edges are now within a single hdf5 file.</li> <li>A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å.</li> <li>Great thanks to Gulio Guzzinati for his suggestions and sending conversion script for GOSH format. </li> </ul> <p> </p> <p>[1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224.</p> <p>[2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243.</p> <p>[3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765</p> <p>[4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689.</p>
Stress regimes in the Himalaya-Karakoram-Tibet, the western part of India-Eurasia collision: stress field implications based on focal mechanism solution data
<p>This dataset contains valuable information on earthquake events, including their location, magnitude, depth, and focal mechanism solutions. This README file provides detailed explanations of each header in the dataset, as well as information about the files included in the repository.<br><br><em>"Stress regimes in the Himalaya-Karakoram-Tibet, the western part of India-Eurasia collision: stress field implications based on focal mechanism solution data"</em> <strong>(Under Review)</strong><br> </p>
Stability in water and electrochemical properties of the Na3V2(PO4)2F3 – Na3(VO)2(PO4)2F solid solution
<p>Graphitical Abstract of the publication "Stability in water and electrochemical properties of the Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> – Na<sub>3</sub>(VO)<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F solid solution" <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/science/journal/24058297/20/supp/C">Energy Storage Materials Volume 20</a>, 2019, p. 324-334 - DOI : <a href="https://doi-org.docelec.u-bordeaux.fr/10.1016/j.ensm.2019.04.010">https://doi.org/10.1016/j.ensm.2019.04.010</a></p> <p>Abstract : Polyanionic materials have been intensively studied as promising active materials for <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/engineering/positive-electrode">positive electrodes</a> in Na-ion batteries thanks to their excellent stability upon cycling and the fast ionic mobility in their structural framework. Among them, Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> and Na<sub>3</sub>(VO)<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F are two of the most promising ones due to their high voltages for Na<sup>+</sup>-ion extraction and their high energy densities: 500 mWh g<sup>−1</sup> and 495 mWh g<sup>−1</sup>, respectively. Here, we study the formation mechanism as well as the stability of these phases in <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/engineering/aqueous-medium">aqueous media</a> and the possible use of a washing step in water in order to remove undesirable <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/materials-science/impurity">impurities</a> formed during the synthesis. Furthermore, the origin of the extra capacity observed at the high voltage region for Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>3</sub> and Na<sub>3</sub>V<sub>2</sub>(PO<sub>4</sub>)<sub>2</sub>F<sub>1.5</sub>O<sub>1.5</sub> was studied by <em>operando</em> <a href="https://www-sciencedirect-com.docelec.u-bordeaux.fr/topics/materials-science/x-ray-absorption-spectroscopy">X-ray absorption spectroscopy</a>.</p> <p> </p>
Sample FITS file with non-linear wavelength solution using a Chebyshev model
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a non-linear wavelength solution using a Chebyshev model.</p> <p>This data is in its original shape.</p>
Sample FITS file with non-linear wavelength solution using a cubic spline model
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a non-linear wavelength solution using a cubic spline model.</p> <p>This data is in its original shape.</p>
Sample FITS file with log linear wavelength solution
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a log linear wavelength solution.</p>
Sample FITS file with non-linear wavelength solution using a Legendre model
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a non-linear wavelength solution using a Legendre model.</p> <p>This data is in its original shape.</p>
Sample FITS file with non-linear wavelength solution using a linear spline model
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a non-linear wavelength solution using a linear spline model.</p> <p>This data is in its original shape.</p>
Sample FITS file with linear wavelength solution
<p>This file was wavelength calibrated using IRAF and written to a FITS file using a linear wavelength solution which means it has been resample.</p>
UPS2 standard in solution converted to mzML with entrapment and decoy appended protein databases
<p>RAW data downloaded from: <a href="http://data.marcottelab.org/MSdata/Data_13/DATA/Marcotte_0909/">http://data.marcottelab.org/MSdata/Data_13/</a></p> <p>Converted to mzML with ThermoRawFileConverter.</p> <p>It is one of the datasets used in the EPIFANY publication.</p>
JOINT WEBINAR: SUSTAFUELS, Three European Solutions Working on Algal & Renewable Fuels
<p>On May 21, 2024, an informative webinar titled “SUSTAFUELS, Three European Solutions Working on Algal & Renewable Fuels” was held from 12:00 to 13:00 CET. This online event was a collaborative effort among three key projects—ALFAFUELS, COCPIT, and FUELGAE—aimed at advancing renewable fuel technologies. Attendees were introduced to the main concepts, ambitions, and methodologies behind these innovative European initiatives. The event was structured in six parts, including presentations on non-biological algal renewable fuels, detailed discussions on each project, and a Q&A session.</p> <p>The webinar was moderated by Pablo Morales Moya from Sustainable Innovations (SIE), and featured a presentation from Javier Sánchez López of CINEA, who discussed the agency’s role in supporting climate, infrastructure, and environmental initiatives. Following the introductory segments, the spotlight shifted to the project coordinators. Charis Xiros from RISE Research Institutes of Sweden presented the ALFAFUELS project, Sary Awad from IMT Atlantique showcased the COCPIT project, and Silvia Morales de la Rosa from CSIC presented the FUELGAE project. Each coordinator provided insights into their project’s objectives, impacts, and collaborative efforts.</p> <p>Participants had the opportunity to learn about groundbreaking renewable fuel solutions and their potential for carbon capture. The event underscored the importance of European collaboration in tackling environmental challenges through innovative research and development. Recordings of the session will be used for dissemination purposes, ensuring that the knowledge shared continues to benefit a wider audience interested in sustainable fuel technologies.</p>
From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation - data
<p>Data set pertaining to the manuscript "From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation", submitted for peer review.</p> <p>In this work, Liquid-jet photoelectron spectroscopy (LJ-PES) and electronic-structure theory were employed to investigate the chemical and structural properties of the amino acid L-proline in aqueous solution for its three ionized states (protonated, zwitterionic, deprotonated). Experimental data were recorded by photoemission spectroscopy from a liquid jet source using synchrotron radiation. The data set documents the experimentally recorded spectra, including the proline photoelectron spectra and spectra of the zero energy cut-off, that were used to calibrate the binding energy scale.</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard, see the<br>NeXus Data Format definition (v2024.02), https://manual.nexusformat.org/index.html<br>NXmpes expansion for FAIRmat data (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/classes/contributed_definitions/NXmpes.html<br>NXmpes_liquid expansion to NXmpes (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/mpes-liquid/classes/contributed_definitions/NXmpes_liquid.html<br>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br>* nexpy (distributed with python)<br>* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br>1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data'). <br>2. As-measured data ('raw').</p> <p>If you use these data for your scientific work we kindly ask you to send us an electronic version or the citation of your work.</p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
C2SMARTER Year 1 Project "Enhancing Transit Access and Safety Through Equitable Micromobility Solution"
<p>These 6 PDF files are the maps produced from Task 1 of the C2SMARTER Year 1 project Enhancing Transit Access and Safety Through Equitable Micromobility Solution.</p> <p>Site A and Site B are transit underserved areas (census tracts in El Paso, Texas) identified in Task 1 of this project.</p> <p>The first 2 maps shows the underserved areas overlaid with bus stops (taken from the General Transit Feed Specification or GTFS database).</p> <p>The next 2 maps shows the underserved areas overlaid with locations of crashes involving pedestrians and bicycles from 1/1/2024 to 7/30/2024..</p> <p>The last 2 maps color coded the streets in Site A and Site B with bicycle level of traffic stress (LTS).</p>
Dataset: Utilization of Novel (KNbO3)1-x(Ba2FeNbO6)x (x = 0.1, 0.2, 0.3) Solid Solutions for Efficient Photo-assisted Fenton Degradation of Methylene Blue Dye
<p>Supplemental information containing the inputs and outputs of all DFT calculations performed as part of this work.</p> <p>This archive contains the following scripts:</p> <ul> <li>defects_workup.py: a Python script for processing all calculations in a given folder. It extracts the total energy, estimated SCF accuracy (for non-converged results), and convergence status (true/false) for all cases found in each subfolder. For converged calculations, the mean Ba-Ba distance and its standard deviation as well as the mean Ba-Fe distance and its standard deviation is calculated. </li> <li>bands_plotter.ipynb: a Jupyter notebook for band structure analysis.</li> <li>ase_rdf.ipynb: a Jupyter notebook for bond distance vs energy analysis</li> </ul> <p>Furthermore, the following data is included:</p> <ul> <li>3x2x2.json: the output json file generated for the 3x2x2 dataset using defect_workup.py</li> <li>3x2x2.7z: a compressed folder containing the 3x2x2 dataset with QE input and output files.</li> <li>3x2x2-v2.7z: a compressed dataset containing some supplementary calculations used in band plotting.</li> </ul>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.