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1,175 results for “coating”
Datasets of "Carbide coating on nickel to enhance the stability of supported metal nanoclusters" Nanoscale, 2022, 14, 3589-3598
<p>These are the datasets related to the publication "Carbide coating on nickel to enhance the stability of supported metal nanoclusters", Nanoscale, 2022, 14, 3589-3598 (<a href="https://doi.org/10.1039/D1NR06485A">https://doi.org/10.1039/D1NR06485A</a>). They are saved as NeXus/HDF5 files according to the nxstm NeXus application definition (<a href="https://doi.org/10.5281/zenodo.5792930">https://doi.org/10.5281/zenodo.5792930</a>).</p>
BAM reference data: XPS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The raw data are given as VAMAS-File. The measurement condtions are given in the file. The C1s-fits are provided as ascii-files.</p> <p>For further information please look at Radnik, J. Kersting, R., Hagenhoff, B., Bennet, F., Ciornii, D.; Nymark, P., Grafström R. and Hodoroaba, V.-D. <em>Nanomaterials </em><strong>2021</strong>, <em>11</em>, 639. https://doi.org/10.3390/nano11030639.</p> <p>The transmission function is obtained as ascii-file trm.dat. The energy scale is kinetic energy.</p> <p> </p> <p>Measurement conditions:</p> <p>XPS measurements were performed at an Axis Ultra DLD (KRATOS, Manchester, UK) with monochromatic Al K radiation (E = 1486.6 eV). The electron emission angle was 0° and the source-to-analyzer angle was 60°. The binding energy scale of the instrument was calibrated following a Kratos analytical procedure, which uses ISO 15472 binding energy data. The setting of the instrument was the hybrid lens mode and the slot mode with an analysis area of approximately 300x700 m². Furthermore, charge neutralization with a flood gun was used. All spectra were recorded in the fixed analyzer transmission (FAT) mode. The samples were measured as powders prepared on a special stainless-steel sample holder.</p> <p> </p> <p> </p> <p> </p>
Phytochemical Screening, Antioxidant and Antimicrobial Activity of Fabric Coated with Catharanthus Roseus Ethanolic Flowers Extract
<p>The aim of the present study was to evaluate the free radical scavenging and antimicrobial activity of fabric coated of the Catharanthus Roseus. Ethanol flowers extract. Free radical scavenging was determined by using 1, 1-diphenyl-2-picrylhydrazyl (DPPH), Reducing power, Hydroxyl radical scavenging assay and antimicrobial activity of Staphylococcus aureus, Escherichia coli and standard drug of Streptomycin using disc diffusion method. This inhibition was observed with the individual extracts and when they were used in lower concentrations with ineffective antibiotics. The present investigation clearly indicates that the Catharanthus Roseus possesses antioxidant properties and serve as free radical inhibitors or scavengers, acting possibly as primary antioxidants.</p><p>Keywords</p><p>Catharanthus Roseus, Fabric coated, DPPH, Staphylococcus aureus Escherichia coli, Streptomycin, Antioxidant,</p>
Application and characterization of poly(vinyl alcohol) reinforced with cellulose nanofibrils as a coating for wood – Supplementary material
<p>Supplementary material to the article "Application and characterization of poly(vinyl alcohol) reinforced with cellulose nanofibrils as a coating for wood"</p>
A multi-method study of femtosecond laser modification and ablation of amorphous hydrogenated carbon coatings
<p>We report here the optical constants of ECR (MW) and RF generated a-C:H layers before and after laser irradiation. The work is described in the following publication:</p> <p><a title="A multi-method study of femtosecond laser modification and ablation of amorphous hydrogenated carbon coatings" href="https://doi.org/10.1007/s00339-024-07980-z" target="_blank" rel="noopener">https://doi.org/10.1007/s00339-024-07980-z</a></p> <p>The data uploaded are the optical constants (n and k) of the a-C:H layers before (base) and after (ROIx) laser irradiation. Please see the article for the nomenclature of the data and for the methods applied ot produce the layers, laser shots, and OK data.</p>
DATASET: characterization of the seed coat extractable phenolic profile and color in 308 common bean lines of the Spanish Diversity Panel
<p>Characterizarion of the seed coat extractable phenolic profile and color in 308 common bean lines of the Spanish Diversity Panel</p>
Research data for Investigation of coatings and metallic materials for icephobic properties, dataset
<p>This dataset is used in deliverable 3.5, 'Investigation of coatings and metallic materials for icephobic properties', where you can get more information.</p> <p>The Dataset includes:</p> <table> <tbody> <tr> <td>Coating Data</td> </tr> <tr> <td>Metalic materials data</td> </tr> <tr> <td>Coating Freezing spike</td> </tr> <tr> <td>Coating Atmospheric freezing</td> </tr> <tr> <td>Coating contact angle</td> </tr> <tr> <td>Coating Ice adhesion</td> </tr> <tr> <td>Submerged freeze depression</td> </tr> <tr> <td>Metalic materials droplet freezing</td> </tr> <tr> <td>Metalic materials Droplet contact angle</td> </tr> <tr> <td>Coating freeze depression brine test</td> </tr> <tr> <td>Coating freeze depression CFT</td> </tr> <tr> <td>Metalic amorphous materials freeze depression</td> </tr> <tr> <td>Metalic pure materials freeze depression</td> </tr> </tbody> </table>
Dataset for "InGaN Nanohole Arrays Coated by Lead Halide Perovskite Nanocrystals for Solid-State Lighting"
<p>In this work, we demonstrate efficient light downconversion via FRET in InGaN/GaN multiple quantum well (MQW) nanohole arrays, coated with green-emitting CsPbBr3 and FAPbBr3 nanocrystals (NCs) and near-infrared (IR) FAPbI3 NC overlayers for solid-state lighting. Patterning the InGaN MQW into nanohole arrays allows a minimum nitride−NC separation while increasing the heterointerfacial area, thus improving simultaneously the nonradiative and radiative transfer efficiencies. Detailed spectroscopic studies of steady-state and time-resolved photoluminescence indicate a significant reduction in the quantum well photoluminescent decay time in the presence of NCs, accompanied by a significant concurrent increase of the NC integrated emission, providing evidence of efficient light down-conversion mediated by FRET with efficiencies as high as ∼83 ± 6% in the green and ∼74 ± 5% in the near-IR.</p>
AFM Surface Coating
<p><strong>AFM Surface Coating - AFMBioMed Summer School 2020</strong></p> <p>This 7 minutes video tutorial shows how to properly label, handle, incubate (coat), rinse and store AFM surfaces (cantilevers and coverslips) during a multi-stage coating process.</p>
The top performer: towards optimized parameters for Reduced graphene oxide uniformity by Spin coating
<p>This dataset contains the raw data used for the publication:</p> <p>-------------------------------------------------------------------------------------------------------------------------------------------------------<br> "The top performer: towards optimized parameters for Reduced graphene oxide uniformity by Spin coating"<br> by C. Reiner-Rozman, R. Hasler, J. Andersson, T. Rodrigues, A. Bozdogan and P. Aspermair<br> --------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p><br> It consists of the SEM images (in .tif format) and the determined surface coverages (in .dat format) as well as the measured electrical data (in .dat format) of the prepared graphene field-effect transistor chips. Headers/information in the data files are in English. When using this data in any form please refer to the above-mentioned publication.</p> <p>The data is structured according to the figures of the paper. Each folder contains the data relevant to validate the results presented in the respective figure of the publication. The files are labeled according to the following description:</p> <p>"measurement-type"_"chip-number"_"GO-concentration"_"spin-coating speed"</p> <p>"measurement-type": SEM, IDVG, baseline<br> "chip-number": an increasing number of fabricated device (only used when needed)<br> "GO-concentration": 143/214/285 µg/mL of graphene oxide (GO) in solution<br> "spin-coating speed": in rpm</p>
Raw and analyzed data for manuscript: "An open-source surface barrier discharge plasma pretreatment for reduced cracking of outdoor wood coatings"
<p><strong>Highlights:</strong></p> <ul> <li>Surface barrier discharges are an affordable and available plasma technology for industrial, laboratory and home-workshop applications.</li> <li>Plasma pretreatments had no impact on the appearance of different protective wood coating for outdoor usage.</li> <li>The weathering performance of outdoor wood coatings improved by plasma, showing less cracks and less biotic factors.</li> </ul>
BAM reference data: EDS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The EDS spectra are given in the EMSA/MAS format as defined by ISO 22029:2012 Microbeam analysis — EMSA/MAS standard file format for spectral-data exchange. The exact locations of the sample areas measured with EDS are indicated in the SEM images.</p> <p>For further information please look at:</p> <p>- Radnik, J. Kersting, R., Hagenhoff, B., Bennet, F., Ciornii, D.; Nymark, P., Grafström R. and Hodoroaba, V.- D. <em>Nanomaterials </em><strong>2021</strong>, <em>11</em>, 639. https://doi.org/10.3390/nano11030639, and</p> <p>- Radnik, Jörg. (2021). BAM reference data: XPS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a) [Data set]. Nanomaterials. Zenodo. http://doi.org/10.5281/zenodo.4986068</p> <p>Measurement conditions:</p> <p>The EDS analysis in the present study has been performed with a QUANTAX 400 EDS system (BRUKER, Berlin, Germany), which is equipped with an SDD (Silicon Drift-Detector) of the 10 mm2 nominal area. An excitation of 10 keV was applied for the analysis of the titania samples prepared as a thick dry powder layer on an aluminum stub, so that the substrate cannot be coexcited. The analysis reas were selected as large as 5 x 5 µm<sup>2</sup> on sample agglomerates of about 1eng0 µm size.</p>
MXene and MoS3−x Coated 3D-Printed Hybrid Electrode for Solid-State Asymmetric Supercapacitor
<p>All raw dataset of the published article "MXene and MoS3−x Coated 3D-Printed Hybrid Electrode for Solid-State Asymmetric Supercapacitor", DOI: 10.1002/smtd.202100451</p>
Diffuse reflectance spectra of coated plates and corresponding plots transformed Kubelka-Munk function versus the energy of light (eV)
<p>The link contains UV-DRS results of TiO<sub>2</sub>/Fe<sub>2</sub>O<sub>3</sub> layered composites (from commercial nanoparticles) and corresponding bandgap energies</p>
Data: Homochiral metal-organic frameworks coated double-plasmon active optical fiber for in-situ enantioselective detection
<p>This dataset is focused on utilization of optical fiber with double-plasmon activity (ensured by a spatially separated gold and silver nanocoating of the fiber core) and subsequent surface grafting by HMOFs for enantioselective capture of organic enantiomers.</p>
Tensile Properties of Flax Fibre Bundles with Graphene Oxide Coating
<p>In the current datasheet, authors report the effect of graphene oxide treatment on tensile behaviour of single flax fibre bundles. As graphene oxide is hydrophilic with many hydroxyl functional groups, it is expected to bond with technical fibres and increase the stress transfer in a flax yarn.</p> <p> Graphene oxide (GO) aqueous dispersion with 1.2 wt % is prepared based on the modified Hummer’s method. GO is physically adsorbed on fibres by immersion of flax yarns into the aqueous dispersion for 24 hr. Fibres are dried at 80 C for 2 hr followed by 48 hr at 60 C. To differentiate between the effect of GO treatment and the potential loss in the tensile strength and tensile stiffness of fibres, authors report the data in 4 subclasses:</p> <ul> <li>As received flax yarns (dried at 60 C for 48 hr): labelled ‘as received’</li> <li>Kept in deionised water for 30 min: tagged ’30 min’</li> <li>Placed in deionised water for 24 hr: marked ’24 hr’</li> <li>Flax fibres immersed in 1.2 wt % GO aqueous dispersion for 24 hr: labelled ‘GO’</li> </ul> <p>Tensile test of single natural fibres is a challenging measurement. This is mainly due to the hierarchical and nonhomogenous structure of single fibres and difficulty in their extraction. The test methods are not standard, and the final data is very scattered. As an alternative method, we report the tensile properties of flax fibre bundles based on the impregnated fibre bundle test (IFBT) [1].</p> <p>Materials and brief description of the methodology can be found in the datasheet under ‘method’ tab. Flax fibre bundles were extracted from AmpliTex 5009 flax fabrics kindly provided by Bcomp. The matrix was Epikote 828 LVEL epoxy resin with Dytek DCH-99 hardener.</p> <p>Impregnated fibre bundle tests were performed with Instron 5567 and 30 kN loadcell, with 120 mm gauge length and 4% min <sup>-1</sup> strain rate. The strain was measured by a 50 mm clip-on extensometer. The abrasive paper was placed without glue in between the testing clamps and the samples. All samples were stored one week before test in a controlled environment of RH 50 % and 25 C.</p> <p>In the current datasheet, authors report the effect of graphene oxide treatment on tensile behaviour of single flax fibre bundles. As graphene oxide is hydrophilic with many hydroxyl functional groups, it is expected to bond with technical fibres and increase the stress transfer in a flax yarn.</p> <p> Graphene oxide (GO) aqueous dispersion with 1.2 wt % is prepared based on the modified Hummer’s method. GO is physically adsorbed on fibres by immersion of flax yarns into the aqueous dispersion for 24 hr. Fibres are dried at 80 C for 2 hr followed by 48 hr at 60 C. To differentiate between the effect of GO treatment and the potential loss in the tensile strength and tensile stiffness of fibres, authors report the data in 4 subclasses:</p> <ul> <li>As received flax yarns (dried at 60 C for 48 hr): labelled ‘as received’</li> <li>Kept in deionised water for 30 min: tagged ’30 min’</li> <li>Placed in deionised water for 24 hr: marked ’24 hr’</li> <li>Flax fibres immersed in 1.2 wt % GO aqueous dispersion for 24 hr: labelled ‘GO’</li> </ul> <p>Tensile test of single natural fibres is a challenging measurement. This is mainly due to the hierarchical and nonhomogenous structure of single fibres and difficulty in their extraction. The test methods are not standard, and the final data is very scattered. As an alternative method, we report the tensile properties of flax fibre bundles based on the impregnated fibre bundle test (IFBT) [1].</p> <p>Materials and brief description of the methodology can be found in the datasheet under ‘method’ tab. Flax fibre bundles were extracted from AmpliTex 5009 flax fabrics kindly provided by Bcomp. The matrix was Epikote 828 LVEL epoxy resin with Dytek DCH-99 hardener.</p> <p>Impregnated fibre bundle tests were performed with Instron 5567 and 30 kN loadcell, with 120 mm gauge length and 4% min <sup>-1</sup> strain rate. The strain was measured by a 50 mm clip-on extensometer. The abrasive paper was placed without glue in between the testing clamps and the samples. All samples were stored one week before test in a controlled environment of RH 50 % and 25 C.</p>
Coat protein (CP) and trimmed replication-associated protein (Rep) amino acid alignments, phylogenetic analyses, and associated metadata for ICTV-approved begomovirus RefSeq species exemplars
<p>DATA RETRIEVAL</p> <p>Annotated begomovirus coding sequences corresponding to each begomovirus species exemplar with a RefSeq accession number listed in the ICTV Virus Metadata Resource (VMR #18, 2021-10-19, <a href="https://ictv.global/vmr">https://ictv.global/vmr</a>) were downloaded from GenBank in protein FASTA file format. CP and Rep amino acid sequences were extracted and split into separate data sets for analysis. We confirmed the identity of misannotated ORF products by performing a BLAST search. For exemplar sequences missing ORF annotations (listed in metadata spreadsheet), ORFfinder (<a href="https://www.ncbi.nlm.nih.gov/orffinder/">https://www.ncbi.nlm.nih.gov/orffinder/</a>) was used to identify CP and Rep ORFs that were subsequently translated and added to each corresponding data set after BLAST confirmation.</p> <p>ALIGNMENTS</p> <p>Multiple sequence alignments were constructed using the MUSCLE method (Edgar, 2004) as implemented in MEGA 11 (Tamura et al., 2021) and manually corrected using AliView v1.26<strong> </strong>(Larsson, 2014). After an initial alignment inspection, exemplars with either severely truncated (i.e., length < 50% of the average length of the protein) or very divergent (i.e., causing us to doubt protein homology) CP or Rep sequences were excluded from the data set. Due to the difficulties in aligning the Rep sequences at the N- and C- terminal ends, the Rep alignment was trimmed to eliminate all residues prior to the iteron related domain (i.e., the known Rep functional region closest to the Rep start (Arguello-Astorga & Ruiz-Medrano, 2001)) in the N-terminus and after a conserved geminivirus motif found near the C-terminus, which corresponds to where other circular, Rep-encoding single-stranded DNA viruses possess an arginine finger motif (Kazlauskas et al., 2019; Krupovic et al., 2020). In total, our CP and Rep data sets contained amino acid sequences from 432 begomovirus species exemplars that met our inclusion criteria.</p> <p>PHYLOGENETIC ANALYSIS</p> <p>Maximum likelihood (ML) trees were inferred with IQ-Tree v2.0.7 (Minh et al., 2020) using the best fitting substitution model identified by the built-in ModelFinder feature (Kalyaanamoorthy et al., 2017). Tree inference was performed with 3000 ultrafast bootstrap (UFBoot) replicates, a perturbation strength of 0.2 and a stopping rule requiring an iteration interval of 500 iterations between unsuccessful improvements to the local optimum. The -bnni flag was enabled to reduce the risk of overestimating branch supports with UFBoot due to severe model violations. The provided phylogenies in NEXUS format are midpoint-rooted and branches are colored based on traditional begomovirus geographic groupings: exemplars sampled in the Americas in orange and exemplars sampled in the 'Africa, Asia, Europe and Oceania' (AAEO) region in blue. </p> <p>METADATA</p> <p>Metadata associated with each ICTV-approved species exemplar (n=445) – including country of isolation, geographic designation (i.e., AAEO/Americas), genome segmentation (i.e., monopartite/bipartite), presence/absence of V2/AV2 gene and length of genome/DNA-A segments – are included. Exemplars not incorporated into the other analyses are highlighted in red on the spreadsheet.</p> <p> </p>
Data to Single fibre coating of viscose filaments with cellulose acetate
<p>Evaluation data for the manuskript with the preliminary title:</p> <p>Single fibre coating of viscose filaments with cellulose acetate for partially hydrophobic hybrid fibres</p>
In Situ Photoluminescence Imaging Dataset of Blade-Coated Perovskite Photovoltaics
<p><strong>Content:</strong></p> <p>The dataset contains time-resolved in situ images acquired during the formation of the perovskite layer which is then built into a perovskite solar cell. The image time series in the dataset encompass the drying and crystallization of the blade-coated perovskite thin-films. An initial exploration of the data presented in the dataset is conducted in the paper <strong><a href="https://doi.org/10.1002/solr.202201114">Process Insights into Perovskite Thin-Film Photovoltaics from Machine Learning with In Situ Luminescence Data</a>.</strong></p> <p>A total of 1,129 solar cells were fabricated using the blade coating deposition method. To monitor the vacuum quenching process of the perovskite layer, a photoluminescence (PL) imaging setup was used to capture four channels of image data. These channels included time series images (2D+t) captured through various spectral filters, with one channel showing reflectance and the other three showing different parts of the PL spectrum. The three PL channels with different spectral transmissions were also used to compute a image time series of spatially resolved PL peak wavelengths. All images were cropped into smaller patches of 65x56 pixels each, which only included the active area of a single solar cell.</p> <p>Different metrics are available as target variables. For each solar cell in the dataset, the photovoltaic performance parameters, namely (1) power conversion efficiency (PCE), (2) open-circuit voltage (<em>V<sub>OC</sub></em>), (3) short-circuit current density (<em>J<sub>SC</sub></em>), and (4) fill factor (FF)), are available (measured backward and forward, as well as the average between forward and backward). Furthermore, information about the perovskite layer thickness of each solar cell’s active area is provided: mean thickness, root-mean-square thickness, and peak-2-valley thickness. Also, additional information like substrate ID and the position of each solar cell within its substrate is provided.</p> <p>All solar cells were fabricated using the same materials, methods, and experimental parameters. As a result, the dataset can be used to apply machine learning techniques to identify variations in the fabrication process between iterations, improve understanding of the process, and predict performance in-line before completing the half-stack into a functional solar cell.</p> <p>Further information on the experimental acquisition procedure can be found in the paper <a href="https://doi.org/10.1002/solr.202201114"><strong>Process Insights into Perovskite Thin-Film Photovoltaics from Machine Learning with In Situ Luminescence Data</strong>.</a></p> <p> </p> <p><strong>Usage:</strong></p> <p>The dataset is made available as a single hdf5-file. The npy-data can be extracted using the notebook “00_extract_data_from_hdf5_file.ipynb” which is provided in the GitHub repository <a href="https://github.com/AI-InSu-Pero/ML-PerovskitePV-InSituLuminescene">https://github.com/AI-InSu-Pero/ML-PerovskitePV-InSituLuminescene</a> </p> <p>The structure of the dataset after extraction from the hdf5-file is depicted below. The dataset (1,129 solar cells) is split into two subfolders, containing train (780 solar cells) and test data (349 solar cell), respectively. For training and test data, the corresponding labels are listed in csv files. In the train and test folders, there are subfolders for each of the substrate assigned to either of the two sets. In the substrate folders, the data for all the patches of a substrate is saved in npy-format with the shape (719, 5, 65, 56), representing (time step, channel, image height, image width). It can be loaded using numpy.load(path_to_file). The order of the five channels is as follows: (0) reflectance, (1) entire PL spectrum, (2) filtered PL spectrum – longer wavelengths remaining, (3) filtered PL spectrum – shorter wavelengths remaining, (4) computed peak wavelength of PL spectrum.</p> <p>In the train folder, an additional folder “cv_splits_5fold” gives the train and validation splits for the 5-fold cross-validation used in the dataset exploration paper. For each fold, the labels are given as csv-files for train and validation split.</p> <p> </p> <pre><code>dataset ├── train │ ├── ACA │ │ ├── 11.npy │ │ ├── 12.npy │ │ ├── 13.npy │ │ ├── 14.npy │ │ ├── 21.npy │ │ └── ... (all other patches of this substrate) │ ├── ACA │ │ ├── 11.npy │ │ ├── 12.npy │ │ ├── 13.npy │ │ ├── 14.npy │ │ ├── 21.npy │ │ └── ... (all other patches of this substrate) │ ├── ... (all other train substrates) │ ├── cv_splits_5fold │ │ ├── fold0 │ │ │ ├── train.csv │ │ │ └── val.csv │ │ └── ... (all other folds) │ └─── labels.csv └── test ├── ACE │ ├── 11.npy │ ├── 12.npy │ ├── 13.npy │ ├── 14.npy │ ├── 21.npy │ └── ... (all other patches of this substrate) ├── ... (all other test substrates) └── labels.csv </code></pre> <p> </p>
Raw Data: Gold Coated ZnO Microstructures by Bragg Coherent X-Ray Diffraction Imaging
<p>Two sets of raw data from gold coated ZnO microstructure (rod) investigated by Bragg coherent X-ray diffraction imaging used in publication: "Visualizing Intrinsic 3D-Strain Distribution in Gold Coated ZnO Microstructures by Bragg Coherent X-Ray Diffraction Imaging and Transmission Electron Microscopy with Respect to Piezotronic Applications" (<a href="https://doi.org/10.1002/aelm.202100546">https://doi.org/10.1002/aelm.202100546</a>)</p> <p>Included is data from two different spatial positions along the c-axis of the ZnO rod. Futher on called position 1 (P1) and position 2 (P2). For each position there is a .nxs file of a rocking scan around the {10-10} Bragg reflection, collected by a 2D detector and other recorded values, e.g. motor positions, counter values. </p>
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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.