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43 results for “vacancy”
Database on vacancies in selected non-EU countries
<p>This database is a revised version of the deliverable D3.1 of the Horizon Europe project 'Global Strategy for Skills, Migration and Development' (GS4S). For more information, please see the associated working paper: Locating Shortages in Migrants’ Origin Countries: A Big Data Approach, authored by Friedrich Poeschel. </p>
Characterization of the angular-dependent emission of nitrogen-vacancy centers in nanodiamond
<p>We report on the characterization of the angular-dependent emission of single-photon emitters based on single nitrogen-vacancy (NV-) centers in nanodiamond at room temperature. A theoretical model for the calculation of the angular emission patterns of such an NV-center at a dielectric interface will be presented. For the first time, the orientation of the NV-centers in nanodiamond was determined from back focal plane images of NV-centers and by comparison of the theoretical and experimental angular emission pattern. Furthermore, the orientation of the NV-centers was also obtained from measurements of the fluorescence intensity in dependence on the polarization angle of the linearly polarized excitation laser. The results of these measurements are in good agreement. Moreover, the collection efficiency in this setup was calculated to be higher than 80% using the model of the angular emission of the NV-centers.</p>
Data Steward Professional: Reference dataset of Data Steward related job vacancies for competences assessment
<p>Data Stewardship vacancies collection to support FAIRsFAIR Data<br> Stewardship Professional Competence Framework<br> <br> This dataset is provided to validate and support the analysis of Data<br> Stewardship competences.<br> The dataset includes a collection of vacancies from the popular job search<br> website <a href="http://indeed.com/">indeed.com</a> that responded to the search term "Data Steward".<br> <br> <strong>Acknowledgment</strong><br> The research leading to these results has received<br> funding from the Horizon2020 projects FAIRsFAIR<br> (grant number 831558)<br> <br> <strong>References</strong><br> FAIRsFAIR Project Deliverable D7.3 Data Stewardship<br> Professional Competence Framework, Work in Progress.<br> To be published Feb 2021<br> Yuri Demchenko, Lennart Stoy, Research Data Management and Data<br> Stewardship Competences in University Curriculum, In Proc. Data Science<br> Education (DSE), Special Session, EDUCON2021 – IEEE Global Engineering<br> Education Conference, 21-23 April 2021, Vienna, Austria</p>
Dataset for "Unravelling the Origin of Ultra-Low Conductivity in SrTiO3 Thin Films: Sr Vacancies and Ti on A-Sites Cause Fermi Level Pinning"
<p>Raw data used in the paper "Unravelling the Origin of Ultra-Low Conductivity in SrTiO3 Thin Films: Sr Vacancies and Ti on A-Sites Cause Fermi Level Pinning", available at DOI: 10.1002/adfm.202202226.</p> <p>Data include impedance spectra, extracted conductivities and defect chemical mdoel calculations:</p> <p>Impdance.csv: Impedance data for differently doped STO thin films</p> <p>Fe_04_10.csv: Conductivity vs. temperature for differntly depoed Fe:STO films<br> UD_Al_Ni.csv: Conductivity vs. temperature for undoped, Al-doped and Ni-doped films<br> 0_4Fe.csv: Conductivity vs. temperature for 0.4 % Fe doped films<br> pO2.csv: Conductivity vs. pO2 at different temperatures for 0.4 % Fe doped films</p> <p>Optimal_Brouwer.csv: Brouwer diagram for STO where A site Ti counterbalances Sr vacancies<br> Buffer_Curve.csv: Variation in the ratio of Sr vacancies to A site Ti<br> Site_Equilibrium.csv: Equilibrium defect concentrations for varying standard Gibbs free energy of the site change reaction<br> Ti_Switch: Total Gibbs free energy (and defects) for varying extent of site change reaction (amount of Ti on A site)<br> ParameterSpace.csv: Conductivity as a function of Standard Gibbs free energy of site change and energy level of Sr vacancies<br> ParameterSpaceXsi.csv: Conductivity as a function of extent of site change and energy level of Sr vacancies</p> <p>Fe_Optimal_Brouwer.csv: Brouwer diagram for Fe:STO where A site Ti counterbalances Sr vacancies<br> Fe_Buffer_Curve.csv: Variation in the ratio of Sr vacancies to A site Ti<br> ParameterSpaceIronG.csv: Conductivity as a function of Fe doping and Standard Gibbs free energy of site change</p>
Data from article: "Wide‑field magnetometry using nitrogen‑vacancy color centers with randomly oriented micro‑diamonds"
<p>This repository contains the dataset obtained from the CW-ODMR magnetic imaging experiment with nitrogen-vacancy (NV) centers using a custom-built wide-field setup.</p> <p><strong>Related publication: </strong></p> <p>Sengottuvel, S., Mrózek, M., Sawczak, M. <em>et al.</em> Wide-field magnetometry using nitrogen-vacancy color centers with randomly oriented micro-diamonds. <em>Sci Rep</em> <strong>12</strong>, 17997 (2022). <a href="https://doi.org/10.1038/s41598-022-22610-5">https://doi.org/10.1038/s41598-022-22610-5</a>.</p> <p><strong>Authors:</strong></p> <ul> <li>Saravanan Sengottuvel, (Institute of Physics, Jagiellonian University in Krakow, Poland)</li> <li>Mariusz Mrózek, (Institute of Physics, Jagiellonian University in Krakow, Poland)</li> <li>Mirosław Sawczak, (Szewalski Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Poland)</li> <li>Maciej J. Głowacki, (Gdańsk University of Technology, Poland)</li> <li>Mateusz Ficek, (Gdańsk University of Technology, Poland)</li> <li>Wojciech Gawlik (Institute of Physics, Jagiellonian University in Krakow, Poland)</li> <li>Adam M. Wojciechowski (Institute of Physics, Jagiellonian University in Krakow, Poland)</li> </ul> <p><strong>Abstract: </strong></p> <p>Magnetometry with nitrogen-vacancy (NV) color centers in diamond has gained significant interest among researchers in recent years. Absolute knowledge of the three-dimensional orientation of the magnetic field is necessary for many applications. Conventional magnetometry measurements are usually performed with NV ensembles in a bulk diamond with a thin NV layer or a scanning probe in the form of a diamond tip, which requires a smooth sample surface and proximity of the probing device, often limiting the sensing capabilities. Our approach is to use micro- and nano-diamonds for wide-field detection and mapping of the magnetic field. In this study, we show that NV color centers in randomly oriented submicrometer-sized diamond powder deposited in a thin layer on a planar surface can be used to detect the magnetic field. Our work can be extended to irregular surfaces, which shows a promising path for nanodiamond-based photonic sensors.</p> <p><strong>Funding: </strong></p> <p>The research was carried out within the TEAM NET programme of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund, project POIR.04.04.00-00-1644/18. This research was funded in part by National Science Centre, Poland grant number 2020/39/I/ST3/02322<strong>. </strong></p> <p><strong>Description of the data: </strong></p> <p>The dataset consists of 24 individual data files labelled chronologically, starting from f0.fits to f24.fits. The data format is Flexible Image Transport System (FITS). Each FITS file consists of a header and 3-dimensional image data. The header contains the experimental parameters set during data acquisition, which may also be helpful for data analysis. The FITS file can be read using any software (e.g., MATLAB, Python) that supports the FITS file format.</p> <p><strong>An example header:</strong></p> <p> {'STARFREQ'} {[ 2700]} {' in MHz '}<br> {'STOPFREQ'} {[ 3000]} {' in MHz '}<br> {'STEPSIZE'} {[ 1.500000000000000]} {' Frequency interval '}<br> {'MWPOWER'} {[ 5]} {' in dBm '}<br> {'NSCANS'} {[ 5]} {' Total number of scan repetitions '}<br> {'EXPOSURE'} {[ 20]} {' in ms '}<br> {'FPS'} {[ 20]} {' no. of frames per second '}<br> {'LEDCURR'} {[ 0.990000000000000]} {' LED current in mA }<br> {'EXPTIME'} {[1.942112698000000e+02]} {' Measurement time in seconds '}<br> {'END' } {0×0 char } {0×0 char }</p> <p><strong>Table:</strong> Data file name and the associated current value set in the wire during the magnetic imaging measurement</p> <table> <thead> <tr> <th>File name</th> <th>Current value (mA)</th> <th>File name</th> <th>Current value (mA)</th> </tr> </thead> <tbody> <tr> <td>f0.fits</td> <td>0</td> <td>f13.fits</td> <td>-300</td> </tr> <tr> <td>f1.fits</td> <td>+50</td> <td>f14.fits</td> <td>-550</td> </tr> <tr> <td>f2.fits</td> <td>+100</td> <td>f15.fits</td> <td>-250</td> </tr> <tr> <td>f3.fits</td> <td>-50</td> <td>f16.fits</td> <td>+550</td> </tr> <tr> <td>f4.fits</td> <td>-100</td> <td>f17.fits</td> <td>+350</td> </tr> <tr> <td>f5.fits</td> <td>-150</td> <td>f18.fits</td> <td>+400</td> </tr> <tr> <td>f6.fits</td> <td>+250</td> <td>f19.fits</td> <td>-400</td> </tr> <tr> <td>f7.fits</td> <td>+450</td> <td>f20.fits</td> <td>-450</td> </tr> <tr> <td>f8.fits</td> <td>+600</td> <td>f21.fits</td> <td>-500</td> </tr> <tr> <td>f9.fits</td> <td>-200</td> <td>f22.fits</td> <td>+150</td> </tr> <tr> <td>f10.fits</td> <td>-350</td> <td>f23.fits</td> <td>+300</td> </tr> <tr> <td>f11.fits</td> <td>+200</td> <td>f24.fits</td> <td>-600</td> </tr> <tr> <td>f12.fits</td> <td>+500</td> <td> </td> <td> </td> </tr> </tbody> </table> <p>For more information on the data analysis methods and results, we recommend you to read the article.</p>
Data for "Atomic-scale perspective on individual thiol-terminated molecules anchored to single S vacancies in MoS2"
<p>This repository provides the original datasets for the manuscript "Atomic-scale perspective on individual thiol-terminated molecules anchored to single S vacancies in MoS2". It includes the original experimental data as well as the iPython Notebooks used to treat it in "<a href="../api/records/10160204/draft/files/Data_and_Analysis.zip/content" target="_blank" rel="noopener noreferrer">Data_and_Analysis.zip</a>" (see readme in individual folders for precise information), the datasets for the structure search and molecular dynamics calculations in "<a href="../api/records/10160204/draft/files/structure_search_and_MD.zip/content" target="_blank" rel="noopener noreferrer">structure_search_and_MD.zip</a>", as well as the data for the DFT calculations for the projected electronic density of states (PDoS) and the orbital densities of Fig.5 and 8 in "<a href="../api/records/10160204/draft/files/fig5.zip/content" target="_blank" rel="noopener noreferrer">fig5.zip</a>" and "<a href="../api/records/10160204/draft/files/fig8.zip/content" target="_blank" rel="noopener noreferrer">fig8.zip</a>", respectively.</p> <p> </p>
The Phonon-Modulated Jahn–Teller Distortion of the Nitrogen Vacancy Center in Diamond
<p>The data in this repository consists of three data sets that yielded transient absorption spectra, 2D electronic spectra, and 3D coherence spectra for the nitrogen vacancy (NV) center. These data supported the conclusions of the published report, namely that the LO Phonon of the diamond lattice modulates the Jahn-Teller distortion of the NV center and influences its excited-state dynamics. The data were taken between 2016 and 2020 and reflect the advancements made to the ultrafast instrumentation of te Turner Lab during this time period. The Matlab scripts and data are presented "as is", however we have attempted to include processed datasets legible to any open-source programming language when possible. Please consult the README.md file for further information.</p>
Dataset for: Visualization of oxygen vacancies and self-doped ligand holes in La3Ni2O7-δ
<p>This repository contains representative four-dimensional scanning transmission electron microscopy (4D-STEM) datasets supporting the findings in the related paper, <em>Visualization of oxygen vacancies and self-doped ligand holes in La3Ni2O7-δ</em>. (<em>Nature</em> <strong>630</strong>, 847–852 (2024)).</p> <p>Region01 is one of the datasets from the regions with δ~0.04. Region02 is one of the datasets from the regions with δ~0.17. Region03 is one of the datasets from the regions with δ~0.34. </p>
Supplementary data for "Vacancy defect configurations in the metal-organic framework UiO-66: Energetics and electronic structure"
<p>Optimised structures for UiO-66 with various defect configurations in VASP POSCAR format. For naming see the associated paper (DOI:10.1039/c7ta11155j).</p>
Data Supporting The role of dopant segregation on the oxygen vacancy distribution and oxygen diffusion in CeO2 grain boundaries
<p>Data supporting the article "The role of dopant segregation on the oxygen vacancy distribution and oxygen diffusion in CeO<sub>2</sub> grain boundaries, accepted for publication in the Journal of Physics: Energy (<a href="https://doi.org/10.1088/2515-7655/ab28b5">doi.org/10.1088/2515-7655/ab28b5</a>). Data includes inputs for molecular dynamics simulations using the DL_POLY classic code.Simulations can be rerun from the inputs provide. </p> <p>Input data required for the generation of the grain boundary structures is included and uses the METADISE code. </p>
DataSET for: Control of spintronic and electronic properties of bimetallic and vacancy-ordered vanadium carbide MXenes via surface functionalization
<p>This data set contains the minimal file necessary to reproduce the DFT calculations contained in the publication:<br> Control of spintronic and electronic properties of bimetallic and vacancy-ordered vanadium carbide MXenes via surface functionalization.</p> <p>the dataset is available on GitLab: <a href="https://gitlab.com/praguelab/shuo2019_work1">https://gitlab.com/praguelab/shuo2019_work1</a> (Project ID: 13583566) Final Latest tag at moment of submission: <a href="https://gitlab.com/praguelab/shuo2019_work1/-/tags/Accepted_manuscript">https://gitlab.com/praguelab/shuo2019_work1/-/tags/Accepted_manuscript</a></p> <p>The paper has been received for review on 16th October 2019, and accepted for publication 11th November 2019 in Journal of Physical Chemistry Chemical Physics</p> <p>DOI: 10.1039/c9cp05638f</p> <p>Preprint available on arXiv <a href="https://arxiv.org/abs/1910.01509">https://arxiv.org/abs/1910.01509</a></p> <p>The work has been financed by Grantova´ Agentura, Univerzita Karlova (Grantova´ Agentura, Univerzita Karlova), OP VVV ‘‘Excellent Research Teams’’, project CUCAM, and International Mobility of Researchers at Charles University (CZ.02.2.69/0.0/0.0/16_027/0008495)</p>
A database of vacancy formation enthalpies for materials discovery
<p><strong>A database of vacancy formation enthalpies for materials discovery</strong></p> <p>Matthew Witman<sup>a</sup>, Anuj Goyal<sup>b</sup>, Tadashi Ogitsu<sup>c</sup>, Anthony McDaniel<sup>a</sup>, Stephan Lany<sup>b</sup></p> <p><sup>a</sup> Sandia National Laboratories, <sup>b</sup> National Renewable Energy Laboratory, <sup>c</sup> Lawrence Livermore National Laboratories</p> <p><strong>Abstract</strong></p> <p>This dataset provides DFT calculations of cation and oxygen vacancy defects in oxides which can be used to derive efficient data-driven models for vacancy formation enthalpy. DFT calculations were performed as described in <DOI: 10.26434/chemrxiv-2022-frcns>, where a graph neural network surrogate model was trained and used to screen the Materials Project for promising solar thermochemical water splitting materials. The data, models, scripts and code needed to reproduce the results in <DOI: 10.26434/chemrxiv-2022-frcns> are described below.</p> <p><strong>Data & Models</strong></p> <p>1) data_01_03_22/* corresponds to oxide compounds used in model training</p> <p>2) known_cmpds/* corresponds to known STCH compounds</p> <p>3) screeningMP/* corresponds to the screening related data</p> <ul> <li>screening_inelements/* stores only Materials Project oxides whose composition is a subset of the training elements and contains all the vacancy defect predictions</li> <li>MP_O_PDs/* stores offline PDs from Materials Project so that adjusting oxide stability metrics can be done somewhat rapidly</li> <li>MP_O_Compounds/* stores possible MP oxide compounds to screen</li> </ul> <p>In general, the above folders contain:</p> <ul> <li>DFT data/structures are included in sub-directories: poscars, magnetic moments, oxidation states, and csvs (containing the vacancy enthalpy for each unique site)</li> <li>cgcnn/* contains the processed DFT data for use in the CGCNN code (see <strong>Scripts</strong> for how to prepare this) <ul> <li>id_prop.csv.* contains [cif name, defect formation enthalpy] pairs <ul> <li>Different id_prop.csv.* files correspond to different K-fold stratifications</li> <li>in the screening directory, defect formation enthalpy is omitted since it has not been computed with DFT</li> </ul> </li> <li>model-(X1)k(X2)_(X3)_(X4) corresponds to different CV models for <ul> <li>X1 different training set sizes (i.e., try to train with only 10%, 40%, or 100% of the data)</li> <li>X2 different k folds</li> <li>X3 = "struct" or "" for "structure-wise validation" or "defect-wise validation", respectively</li> <li>X4 for different encoding strategies</li> </ul> </li> <li>structure X-Yz.cif indicates structure X, defect element Y, symmetry site z, where one instance of that site has been re-ordered to be the first atom in the cif file</li> <li>*.locals contains a one-hot encoding of oxidation states of all sites in that crystal</li> <li>*.locals_continuous contains a continuous encoding of oxidation state in that crystal</li> <li>*.globals contains global properties of the host structure</li> </ul> </li> </ul> <p><strong>Scripts</strong></p> <ul> <li>scripts/*.sh scripts to rerun the screenings for different k-folds, encodings, etc.</li> <li>scripts/*.ipynb to analyze results</li> <li>scripts/prepare_cgcnn.py for translating the data in (poscars/*, csvs/*, oxstate/*, mags/*) to the ML input needed in cgcnn/*</li> </ul> <p><strong>Code</strong></p> <ul> <li>Install CGCNN and its defect modifications from https://github.com/mwitman1/cgcnndefect</li> </ul> <p><strong>Questions/Collaborations</strong></p> <ul> <li>Please contact <a href="mailto:mwitman@sandia.gov">mwitman@sandia.gov</a></li> </ul> <p><strong>Acknowledgements</strong></p> <ul> <li>This material is based upon work supported by the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), specifically the Hydrogen and Fuel Cell Technologies Office. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. Part of the work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under contract No.~DE- AC52-07NA27344. The National Renewable Energy Laboratory (NREL) is operated by the Alliance for Sustainable Energy, LLC, for the DOE under Contract No.~DE-AC36-08GO28308. This work used High-Performance Computing resources at NREL, sponsored by DOE-EERE. The views expressed in this article do not necessarily represent the views of the U.S. Department of Energy or the United States Government.</li> </ul>
Data for "Two-stage, low noise quantum frequency conversion of single photons from silicon-vacancy centers in diamond to the telecom C-band"
<p>The silicon-vacancy center in diamond holds great promise as a qubit for quantum communication networks. However, since the optical transitions are located within the visible red spectral region, quantum frequency conversion to low-loss telecommunication wavelengths becomes a necessity for its use in long-range, fiber-linked networks. This work presents a highly efficient, low-noise quantum frequency conversion device for photons emitted by a silicon-vacancy (SiV) center in diamond to the telecom C-band. By using a two-stage difference-frequency mixing scheme SPDC noise is circumvented and Raman noise is minimized, resulting in a very low noise rate of 10.4(7) photons per second as well as an overall device efficiency of 35.6 %. By converting single photons from SiV centers we demonstrate the preservation of photon statistics upon conversion.</p>
Data for "Electronic and magnetic properties of single chalcogen vacancies in MoS2/Au(111)"
<p>Here, we provide the original data to the manuscript "Electronic and magnetic properties of single chalcogen vacancies in MoS2/Au(111)". We also provide the fits to the data, including fit parameters.</p>
A dataset of DFT-computed oxygen vacancy formation energies of metal oxides
<p>This dataset contains DFT-computed oxygen vacancy formation energies of different oxygen sites in over 1000 metal oxides present on the Open Quantum Materials Database (OQMD). Entries in the Data.csv file are indexed using the OQMD entry ID of the pristine structure, and list, alongside the oxygen vacancy formation energy, a number of other properties used as features in machine learning models. An exemplary code allowing to test the performance of a random forest regressor using different sets of features to predict the vacancy formation energy, as a function of training set size, is provided in Test_Models.py. More details on the dataset and machine learning models can be found in: arXiv:2309.01160. </p><p> </p><p><strong>Acknowledgments</strong></p><p>The work was funded by the U.S. Department of Energy under Grant DE-EE0008089. S. G. acknowledges the Air Force Office of Scientific Research for support under Award No. FA9550-18-1-0136 (OQMD database). A. G. acknowledges the Center for Hierarchical Materials Design (ChiMaD) under Award No. 70NANB19H005 (ML models). A. J.A. S.-C. acknowledges the financial support to National Agency for Research and Development (ANID)/DOCTORADO BECAS CHILE/2018 - 56180024. A. J.A. S.-C. and T. L. acknowledge funding from the Toyota Research Institute through the Accelerated Materials Design and Discovery program (ML representations). The data was produced relying on the computing power provided by Quest high performance computing facility at Northwestern University.</p>
Oxygen vacancy substitution linked to ferric iron in bridgmanite at 27 GPa
<p>1.1.1 The article file in gold open access publication and supplementary information</p> <p>1.1.2 Data of electron microprobe analysis, Mossbauer spectrscopy and power X-ray diffraction are added</p> <p>1.1.3 SEM images are added</p>
Elemental vacancy diffusion database from high-throughput first-principles calculations for fcc and hcp structures
<p><br /> This work demonstrates how databases of diffusion-related properties can be developed from high-throughput ab initio calculations. The formation and migration energies for vacancies of all adequately stable pure elements in both the face-centered cubic (fcc) and hexagonal close packing (hcp) crystal structures were determined using ab initio calculations. For hcp migration, both the basal plane and z-direction nearest-neighbor vacancy hops were considered. Energy barriers were successfully calculated for 49 elements in the fcc structure and 44 elements in the hcp structure. These data were plotted against various elemental properties in order to discover significant correlations. The calculated data show smooth and continuous trends when plotted against Mendeleev numbers. The vacancy formation energies were plotted against cohesive energies to produce linear trends with regressed slopes of 0.317 and 0.323 for the fcc and hcp structures respectively. This result shows the expected increase in vacancy formation energy with stronger bonding. The slope of approximately 0.3, being well below that predicted by a simple fixed bond strength model, is consistent with a reduction in the vacancy formation energy due to many-body effects and relaxation. Vacancy migration barriers are found to increase nearly linearly with increasing stiffness, consistent with the local expansion required to migrate an atom. A simple semi-empirical expression is created to predict the vacancy migration energy from the lattice constant and bulk modulus for fcc systems, yielding estimates with errors of approximately 30%.</p> <p>Files:</p> <p>figure_excel_files.zip:</p> <p>Excel files for figures in the publication, and excel files of main data tables for FCC and HCP vacancy formation energies and vacancy migration energies.</p> <p>fcc_hvf_hvm.tar.gz and hcp_hvf_hvm.tar.gz:</p> <p>Raw VASP files corresponding to FCC and HCP vacancy formation energies and vacancy migration energies.<br /> <br /> bulk_modulus.tar.gz:</p> <p>Raw VASP files corresponding to FCC bulk modulus calculations.<br /> </p>
Data for A miniaturized magnetic field sensor based on nitrogen-vacancy centers
<p>Here, data sets as plotted in the preprint "A miniaturized magnetic field sensor based on nitrogen-vacancy centers" are uploaded. <br><br>The zip file Data_Zenodo_v3.zip contains a folder for each figure and one additional table supporting the findings in the preprint/publication. Folders of figures containing only images include the images in the preprint/publication as .png and .svg or .pdf data. Folders of figures containing plots include the plot as .png and .pdf aswell as the data points and fit parameters collected in a .xlsx, .csv or .h5 file.</p>
Defect tolerance of lead-halide perovskite (100) surface relative to bulk: band bending, surface states, and characteristics of vacancies (dataset)
<p>This repository contains an input data set as well as the output data that were used in a study of surface and bulk defects in cubic CsPbI<sub>3</sub>. using a Vienna ab initio simulation package (VASP) and PyDEF 2 package for processing of defect calculations. More details about organization of the dataset can be found within REDME.txt files</p>
Data sets for "Pressure destabilizes oxygen vacancies in bridgmanite" by H.Fei et al.
<p>This is EPMA, XRD, and Mossbauer datasets for the article "Pressure destabilizes oxygen vacancies in bridgmanite" by H. Fei et al.</p>
ScienceDex guides
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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.