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222 results for “silicate”
Dissolved inorganic nutrients including 5 macro nutrients: silicate, phosphate, nitrate, nitrite, and ammonium from water column bottle samples collected between October and April at Palmer Station, 1991 - 2025.
The inorganic plant macronutrients dissolved phosphate, silicate, nitrate, nitrite and ammonium are the major sources of nutrition for phytoplankton growth in seawater (with sunlight and inorganic carbon). Macronutrient distributions reflect the large-scale circulation patterns in the oceans and are useful properties to delineate water masses. Dissolved inorganic nutrients samples are typically collected in every Niskin bottle sample collected at and near Palmer Station, Anvers Island, Antarctica on the Western Antarctic Peninsula. Water samples are collected throughout the water column at stations within the Palmer LTER region (primarily B and E, to 50m and 65m respectively). Beginning in the 2020-2021 season, Station B is no longer sampled. In Antarctic waters, dissolved inorganic macronutrients are seldom depleted to limiting concentrations except during heavy prolonged phytoplankton blooms. This is due to the fact that phytoplankton growth is more often limited by light or iron, and to the short growing season. Water samples are analyzed for dissolved nutrients with recognized standard oceanographic protocols for nutrient autoanalyzers (continuous flow analyzers).
Dissolved inorganic nutrients including 5 macro nutrients: silicate, phosphate, nitrate, nitrite, and ammonium from water column bottle samples collected during annual cruise along western Antarctic Peninsula, 1991 - 2024.
The inorganic plant macronutrients dissolved phosphate, silicate, nitrate, nitrite and ammonium are the major sources of nutrition for phytoplankton growth in seawater (with sunlight and inorganic carbon). Macronutrient distributions reflect the large-scale circulation patterns in the oceans and are useful properties to delineate water masses. Dissolved inorganic nutrients samples are typically collected in every CTD/Rosette cast performed on the annual LTER cruises along the western Antarctic Peninsula. In Antarctic waters, dissolved inorganic macronutrients are seldom depleted to limiting concentrations except during heavy prolonged phytoplankton blooms. This is due to the fact that phytoplankton growth is more often limited by light or iron, and to the short growing season. Water samples pre-filtered through 47mm GF/F filters upon collection and samples frozen until analysis. Water samples are analyzed for dissolved nutrients with recognized standard oceanographic protocols for nutrient autoanalyzers (continuous flow analyzers).
Thermal infrared emissivity spectral library of silicates measured under the Mercury simulated environment
<p>This is the thermal emissivity spectral library of silicates measured as a function of temperature under Mercury simulated environment. Data is measured at the Planetary Spectroscopy Laboratory (PSL), Institute of Planetary Research, German Aerospace Center (DLR), Berlin. The spectral library will be used for mineral identification of Mercury surface using MERTIS datasets. The manuscript related to this work is submitted to Icarus on the title "<strong>Thermal Infrared Spectroscopy (7-14 µm) of Silicates under Simulated Mercury Daytime Surface Conditions and their Detection: Supporting MERTIS onboard the BepiColombo Mission".</strong></p>
Supplementary data: Accurate large-scale simulations of siliceous zeolites by neural network potentials
<p><strong>Content</strong></p> <p><em>1. Zeolite databases</em></p> <ul> <li>Deem database containing 331170 hypothetical zeolite frameworks [Deem09, Pophale11] geometrically optimized at the NNPscan level (note, the first row of the database is alpha-quartz): "DEEM_NNPscan.db"</li> <li>Database of 236 exiting zeolite frameworks of the <a href="http://www.iza-structure.org/databases/">International Zeolite Association (IZA) </a>optimized at the NNPscan level: "IZA_NNPscan.db"</li> <li>Both databases are <a href="https://wiki.fysik.dtu.dk/ase/ase/db/db.html">ASE SQLite database files</a> of the <a href="https://wiki.fysik.dtu.dk/ase/index.html">Atomic Simulation Environment</a> containing the ASE <a href="https://wiki.fysik.dtu.dk/ase/ase/atoms.html">Atoms objects</a> with energies and forces (NNPscan level); readable with ASE's <a href="https://wiki.fysik.dtu.dk/ase/ase/io/io.html">I/O module</a></li> <li>Additionally, relevant quantities can be extracted with, e.g., the following queries (further information: ase db --help):</li> </ul> <pre><code class="language-bash">ase db DEEM_NNPscan.db -c id,formula,natoms,volume,mass,density,energy_per_tsite,n_tsites,relative_energy # Output id|formula|natoms| volume| mass|density|energy_per_tsite|n_tsites|relative_energy 1|O6Si3 | 9|111.161|180.249| 26.988| -31.796| 3| 0.000 2|O16Si8 | 24|433.858|480.664| 18.439| -31.638| 8| 15.265 3|O16Si8 | 24|421.114|480.664| 18.997| -31.596| 8| 19.359 4|O16Si8 | 24|426.557|480.664| 18.755| -31.614| 8| 17.613 5|O16Si8 | 24|412.410|480.664| 19.398| -31.613| 8| 17.677 6|O16Si8 | 24|393.544|480.664| 20.328| -31.594| 8| 19.546 7|O16Si8 | 24|422.400|480.664| 18.939| -31.657| 8| 13.476 8|O16Si8 | 24|394.405|480.664| 20.284| -31.581| 8| 20.797 9|O12Si6 | 18|265.201|360.498| 22.624| -31.611| 6| 17.868 10|O16Si8 | 24|357.047|480.664| 22.406| -31.581| 8| 20.785 11|O16Si8 | 24|434.894|480.664| 18.395| -31.621| 8| 16.911 12|O16Si8 | 24|384.158|480.664| 20.825| -31.657| 8| 13.448 13|O12Si6 | 18|258.977|360.498| 23.168| -31.679| 6| 11.278 14|O16Si8 | 24|466.429|480.664| 17.152| -31.593| 8| 19.588 15|O16Si8 | 24|423.469|480.664| 18.892| -31.639| 8| 15.179 16|O16Si8 | 24|450.716|480.664| 17.750| -31.628| 8| 16.219 17|O16Si8 | 24|331.528|480.664| 24.131| -31.642| 8| 14.857 18|O16Si8 | 24|458.573|480.664| 17.445| -31.635| 8| 15.572 19|O16Si8 | 24|359.298|480.664| 22.266| -31.655| 8| 13.636 20|O16Si8 | 24|464.264|480.664| 17.232| -31.612| 8| 17.750 Rows: 331171 (showing first 20) Keys: density, energy_per_tsite, n_tsites, relative_energy ase db IZA_NNPscan.db -c id,formula,natoms,volume,mass,density,energy_per_tsite,n_tsites,relative_energy,iza_code # Output id|formula |natoms| volume| mass|density|energy_per_tsite|n_tsites|relative_energy|iza_code 1|O16Si8 | 24| 435.488| 480.664| 18.370| -31.676| 8| 11.594|ABW 2|O32Si16 | 48| 961.419| 961.328| 16.642| -31.645| 16| 14.612|ACO 3|O96Si48 | 144|3154.579|2883.984| 15.216| -31.664| 48| 12.810|AEI 4|O80Si40 | 120|2102.921|2403.320| 19.021| -31.703| 40| 9.021|AEL 5|O96Si48 | 144|2417.286|2883.984| 19.857| -31.666| 48| 12.586|AEN 6|O144Si72| 216|4075.300|4325.976| 17.667| -31.674| 72| 11.831|AET 7|O96Si48 | 144|2786.810|2883.984| 17.224| -31.675| 48| 11.716|AFG 8|O48Si24 | 72|1400.247|1441.992| 17.140| -31.690| 24| 10.268|AFI 9|O64Si32 | 96|1764.823|1922.656| 18.132| -31.653| 32| 13.809|AFN 10|O80Si40 | 120|2080.330|2403.320| 19.228| -31.707| 40| 8.632|AFO 11|O64Si32 | 96|2097.384|1922.656| 15.257| -31.655| 32| 13.622|AFR 12|O112Si56| 168|3820.116|3364.648| 14.659| -31.650| 56| 14.150|AFS 13|O144Si72| 216|4732.720|4325.976| 15.213| -31.664| 72| 12.793|AFT 14|O60Si30 | 90|1897.074|1802.490| 15.814| -31.659| 30| 13.268|AFV 15|O96Si48 | 144|3154.885|2883.984| 15.214| -31.664| 48| 12.776|AFX 16|O32Si16 | 48|1137.335| 961.328| 14.068| -31.591| 16| 19.790|AFY 17|O48Si24 | 72|1283.812|1441.992| 18.694| -31.620| 24| 17.034|AHT 18|O96Si48 | 144|2479.287|2883.984| 19.360| -31.681| 48| 11.155|ANA 19|O64Si32 | 96|1797.086|1922.656| 17.807| -31.662| 32| 12.924|APC 20|O64Si32 | 96|1751.393|1922.656| 18.271| -31.678| 32| 11.422|APD Rows: 236 (showing first 20) Keys: density, energy_per_tsite, iza_code, n_tsites, relative_energy # Filtering of the database, e.g., for structures with relative energies < 10 kJ/(mol Si) ase db IZA_NNPscan.db relative_energy\<10 -c density,energy_per_tsite,n_tsites,relative_energy,iza_code # Output density|energy_per_tsite|n_tsites|relative_energy|iza_code 19.021| -31.703| 40| 9.021|AEL 19.228| -31.707| 40| 8.632|AFO 19.385| -31.695| 24| 9.802|ATV 18.778| -31.702| 34| 9.061|DOH 19.570| -31.693| 24| 9.959|EWO 18.401| -31.698| 32| 9.451|GON 18.551| -31.695| 112| 9.807|IHW 17.778| -31.693| 288| 9.972|IMF 19.154| -31.695| 6| 9.762|JBW 18.187| -31.695| 96| 9.734|MFI 19.278| -31.709| 48| 8.443|MRE 18.035| -31.698| 90| 9.481|MSO 20.417| -31.724| 44| 7.003|MTF 19.227| -31.704| 136| 8.898|MTN 18.542| -31.693| 28| 9.966|MTW 19.137| -31.695| 60| 9.798|PCR 20.037| -31.709| 144| 8.464|PSI 18.843| -31.703| 64| 9.004|SAF 18.371| -31.703| 112| 8.975|STO 19.894| -31.706| 17| 8.671|VET Rows: 20 (showing first 20) Keys: density, energy_per_tsite, iza_code, n_tsites, relative_energy</code></pre> <ul> <li>The quantities shown above are available with the keys (besides standard ASE database keys):</li> </ul> <table> <thead> <tr> <th scope="col">Key</th> <th scope="col">Quantity</th> <th scope="col">Unit</th> </tr> </thead> <tbody> <tr> <td>id</td> <td>Identifier</td> <td> </td> </tr> <tr> <td>formula</td> <td>Chemical formula of the unit cell</td> <td> </td> </tr> <tr> <td>natoms</td> <td>Number of atoms</td> <td> </td> </tr> <tr> <td>volume</td> <td>Unti cell volume</td> <td>Å<sup>3</sup></td> </tr> <tr> <td>mass</td> <td>Atomic mass of the unit cell</td> <td>amu</td> </tr> <tr> <td>density</td> <td>Framework density</td> <td>Si/nm<sup>3</sup></td> </tr> <tr> <td>energy_per_tsite</td> <td>NNPscan energy</td> <td>eV</td> </tr> <tr> <td>n_tsites</td> <td>Number of T-sites</td> <td> </td> </tr> <tr> <td>relative_energy</td> <td>Energy with respect to quartz</td> <td>kJ/(mol Si)</td> </tr> <tr> <td>iza_code</td> <td>only for 'IZA_NNPscan.db'</td> <td> </td> </tr> </tbody> </table> <ul> <li> Comma separated csv files for the quantities listed above: "DEEM_NNPscan.csv" and "IZA_NNPscan.csv"</li> </ul> <p><em>2. Neural network potentials (NNP) for silica</em></p> <ul> <li>SchNet [Schütt18,Schütt19] NNP files trained on DFT data at the PBE+D3 (NNPpbe) and SCAN+D3 level (NNPscan)</li> <li>Simulations can be performed using <a href="https://schnetpack.readthedocs.io/en/stable/getstarted/getstarted.html#references">SchNetPack</a> with its ASE calculator</li> <li>This example shows a simple single-point calculation</li> </ul> <pre><code class="language-python">import ase.io import torch from schnetpack.interfaces import SpkCalculator from schnetpack.environment import AseEnvironmentProvider # check if GPU(s) are available if torch.cuda.is_available(): device = "cuda" else: device = "cpu" # load the NNP model model = torch.load('SiOscan1', map_location=device) # read some structure atoms = ase.io.read( ... ) # define SchNetPack calculator calc = SpkCalculator(model=model, device=device, energy='energy', forces='forces', environment_provider=AseEnvironmentProvider(6.) ) # attach calculator to atoms object atoms.set_calculator(calc) # perform simulations, e.g., single-point calculation energy = atoms.get_potential_energy() print(energy)</code></pre> <p><em>3. Test set used for accuracy evaluation (ASE database: test_set_NNPscan.db)</em></p>
Biogenic silicate concentration in sea water samples, collected from the CTD in the Southern Ocean during the austral summer of 2016/2017, on board the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>Biogenic Silicate (Bsi) concentration (µmol/L) in seawater data. Water samples were collected from CTD rosette deployments, filtered on board and then analysed by flow injection following appropriate digestion.</p> <p>This data supports chemical and biological oceanography studies conducted during the Antarctic Circumnavigation Expedition.</p> <p><strong>Dataset contents</strong></p> <ul> <li>ace_biogenic_silicate_concentration_in_seawater_ctd.csv, data file, comma-separated values</li> <li>ace_biogenic_silicate_concentration_in_seawater_ctd_visual_summary.png, metadata, portable network graphics</li> <li>data_file_header.txt, metadata, text format</li> <li>README.md, metadata, text format</li> </ul> <p>All missing values where no data point exists from lack of sample, have been set to NaN.</p> <p><strong>Dataset license</strong></p> <p>This biogenic silica concentration dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Animation to visualize the electron beam damage induced in calcium silicate hydrate phases
<p>This dataset visualizes the electron beam damage induced by a scanning electron microscope (SEM) in calcium silicate hydrates (C-S-H). The specimen used is 28 days hydrated alite (water/solid = 0.5). It was scanned using a thermofischer scientific Helios G4 UX microscope at 350 V/25 pA with a stage bias of 200 V.</p> <p>This animation was an afterthought. Therefore, the dataset provides multiple magnifications and resolutions and some of the images are not in focus. Nevertheless, It can be seen, that the C-S-H needle in the right half of the image significantly deformes within a timespan of 124 seconds of constant scanning of that region.</p> <p><strong>File content:</strong></p> <ul> <li>All images ending with "raw" are the raw images provided by the SEM software including all metadata.</li> <li>The file "C3S_CSH_e-beam-damage_aligned stack.tif" contains the aligned image set using the SIFT algorithm. It contains the correct scaling if opened with ImageJ.</li> <li>The file "C3S_CSH_e-beam-damage_animation.gif" provides the final animation including a overlayed scalebar.</li> </ul>
Base images for the article "Optimization of a frosting process for soda lime silicate glass based on phosphoric acid"
<p>Raw dataset of the optimization of a frosting process for soda lime silicate glass based on phosphoric acid.</p> <p><strong>Naming scheme:</strong></p> <ul> <li>Images starting with <strong>HGr</strong> are frosted using the industrial process. These files represent the reference frosting.</li> <li>Images starting with <strong>HG</strong> are frosted manually following the industrial process.</li> <li>In all other images, the solution concentrations within the preliminary bath are noted als follows: <ul> <li><strong>[c<sub>H3PO4</sub>]-[c<sub>NH4HF2</sub>]_[specimen]_[position].jpg</strong></li> <li>For example 10-2_e_1.jpg: This specimen was treated with a preliminary bath with 10 M-% H<sub>3</sub>PO<sub>4 </sub>and 20 g/L NH<sub>4</sub>HF<sub>2</sub>. It originates from the fith specimen (e) and is the first image of this series.</li> </ul> </li> </ul> <p> </p>
Data for "Lithium isotope evidence shows Devonian afforestation may have significantly altered the global silicate weathering regime"
<p>This contains measured data for paper "Lithium isotope evidence shows Devonian afforestation may have significantly altered the global silicate weathering regime", under funding of ERC grant 682760 CONTROLPASTCO2. </p> <p>This consists all the Li isotope data obtained from brachiopods/bulk carbonate samples.</p>
Data set for "Quantification of amorphous siliceous fly ash in hydrating blended cement pastes by X-ray powder diffraction"
<p>The main data is XRD patterns originally collected as xrdml and converted into rd format.</p> <p>The data set for the manuscript:</p> <p>Quantification of amorphous siliceous fly ash in hydrating blended cement pastes by X-ray powder diffraction</p> <p>Xuerun Li<sup>a</sup>, Ruben Snellings<sup>b</sup> and Karen L. Scrivener<sup>a</sup></p> <p><sup>a</sup>Laboratory of Construction Materials, Swiss Federal Institute of Technology in Lausanne (EPFL), Station 12, CH-1015 Lausanne, Switzerland</p> <p><sup>b</sup>Sustainable Materials Management, Flemish Institute of Technological Research (VITO), Boeretang 200, 2400 Mol, Belgium<br> </p>
Measurements from CalCOFI cruises in the California Current System, including log of station information, weather, sea conditions as well as physical, chemical and biological measurements including including temperature, salinity, oxygen, density, sigma theta, phosphate, silicate, nitrite, nitrate, ammonia, chlorophyll a, integrated chlorophyll a, primary productivity, and integrated primary production. 1949 - January 2020
Since 1949, hydrographic and biological data of the California Current System have been collected on quarterly CalCOFI cruises. The 59+ year hydrographic time-series includes weather, temperature, salinity, oxygen and phosphate observations. In 1961, nutrient analysis expanded to include silicate, nitrate and nitrite; in 1973, chlorophyll was added; in 1984, C14 primary productivity incubations were added. These data are being provided here in collaboration with CalCOFI-SIO in order to provide an additional queriable interface to the data. The data are updated on a regular basis from the CalCOFI hydrographic database.
Dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) during the Austral Summer of 2016/2017.
<p><strong>Dataset abstract</strong></p> <p>This dataset contains dissolved inorganic nitrate, nitrite, silicate and phosphate concentrations of seawater sampled during the Antarctic Circumnavigation Expedition (ACE) Legs 1-3. Water samples were collected from the underway seawater supply every 3 hours, preserved and analysed for dissolved inorganic nutrient concentrations using flow injection and colorimetric methods. These samples provide an estimate of the dissolved concentrations of inorganic macronutrients essential for phytoplankton growth.</p> <p><strong>Dataset contents</strong></p> <ul> <li>README.txt, metadata, text</li> <li>data_file_header.txt, metadata, text</li> <li>ace_uw_nutrients_20200527CURRSGCMR.csv, data file, comma-separated values</li> <li>change_log.txt, metadata, text</li> </ul> <p><strong>Change log</strong></p> <p>v1.1 - changed order of authors in publication and citation in README</p> <p>v1.0 - initial release of dataset</p>
Research data for "Predicting Dynamics from Structure in a Sodium Silicate Glass"
<p>This dataset supports the paper "Predicting Dynamics from Structure in a Sodium Silicate Glass".</p> <p>The following files are provided.</p> <p>File: dataset_800.zip</p> <p>- Pickle files for:</p> <ul> <li>400 Sodium silicate glass structures of 3000 atoms</li> <li>30 Trajectories sampled eight times at various timescales up to 1 ns for each if the 400 glass structures</li> </ul> <p>File: in.comb</p> <p>- Lammps inputfile used to generate simulation from with the data in dataset was sampled</p>
Fe-bearing magnesium silicate glasses for potential supplementary cementitious applications
<p>The enclosed raw data files include various formats from multiple characterization techniques, covering XPS, BET SSA, XRF, SEM-EDS, ICP, FTIR, XRD, PSD, DSC-TG, TEM-EDS, and Mössbauer analyses. The formats and file details are as follows:</p> <ul> <li>XPS: Provided in .VGD format.</li> <li>BET SSA: Available in .xls and .xps formats.</li> <li>XRF: Data provided in .xlsx format, with filenames containing 'XRF'.</li> <li>SEM-EDS: Reports included in .xlsx format.</li> <li>ICP: Data listed in .pdf format, with filenames including the date and project information.</li> <li>FTIR: Raw data included in .dpt files.</li> <li>XRD: Data provided in .raw and .xrdml formats.</li> <li>PSD: Included in .pdf and .xlsx files, with filenames containing 'PSD'. </li> <li>DSC-TG: Data available in .xls files, with filenames indicating 'DSC_TG'.</li> <li>TEM-EDS: Elemental maps provided in .jpg and .bmp formats.</li> <li>Mössbauer: Raw data provided in .plt files.</li> </ul> <p>Please note that the percentages in the sample names do not correspond directly to the final sample codes (e.g., 25% does not equate to the final G25 sample). This discrepancy has been corrected based on the XRF results. For clarity, refer to the file 'Chuqing Jiang Fe-Mg-Si XRF 04-04-2023 - raw data and calculation.xlsx', which includes detailed renaming of the samples.</p>
Dataset for Gion and Gaillard (2025) - "The Multicomponent Exchange of Metals Between Magmatic Fluids and Silicate Melts"
<p>Dataset for the publication "The Multicomponent Exchange of Metals Between Magmatic Fluids and Silicate Melts" by Austin M. Gion and Fabrice Gaillard.</p>
APPENDIX 2 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
APPENDIX 2. — Distribution maps of all the Cholevinae species collected in the MSS of the Sierra de Guadarrama National Park, except for Choleva (Cholevopsis) punctata Brisout, 1866.
FIG. 6 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 6. — Relation between the pronotum width (PWmid) and the pronotum length (PL) of both sexes of Choleva (Cholevopsis) punctata Brisout, 1866.
FIG. 3 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 3. — Distribution of Choleva (Cholevopsis) punctata Brisout, 1866 in the MSS of the Sierra de Guadarrama National Park. Legends and symbols: ● subterranean sampling devices (SSDs); Δ, talus pitfall traps (TSP); ● and presence of C. (C.) punctata. The combination of the different manifestations of the aedeagus with the different morphologies of the metatrochanter is shown for each SSD following the classification of Figs 6; 7.
FIG. 9 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 9. — Female genitalia of Choleva (Cholevopsis) punctata Brisout, 1866: A, left lateral vision; B dorsal vision without IX ltg and IX mtg; C, dorsal vision with complete genital shield; D, ventral vision; E, detail of the female genital armor. Scale bars: A, D, 0.5 mm; E, 0.2 mm. Abbreviations: see Material and methods. The abbreviations associated with the genital shield are those used by Deuve (1993).
FIG. 8 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 8. — The morphological diversity of the Choleva (Cholevopsis) punctata Brisout, 1866 metatrochanter from Sierra de Guadarrama: A-F, external spiny angle (hollow arrow with continuous contour), inner spiny angle (hollow arrow with discontinuous contour), and medial spine (solid arrow). Scale bar: 1 mm.
FIG. 7 in Cholevinae (Coleoptera: Leiodidae) of the Sierra de Guadarrama National Park, Spain: occurrence in the MSS of a siliceous landscape
FIG. 7. — Different states of evagination of the inner sac with respect to the median lobe of the aedeagus of Choleva (Cholevopsis) punctata Brisout, 1866. Categorized in columns (I-IV states) and in rows. Abbreviations: lat, lateral view; v, ventral view. Scale bars: 1 mm.
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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)
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DANDI Archive for NWB datasets
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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
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