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.
52
datasets available to search
ShareScore release 0.9.0
Dataset results
52 results for “Particle Size Distribution”
Particle number size distributions associated with secondary organics
<p>We provide the model data used to reproduce the figures in our manuscript titled "secondary organic aerosol formation regulates cloud condensation nuclei in the global remote troposphere". </p>
Data to reproduce the results presented in Lake et al. 2022. Hydrological processes, https://doi.org/10.1002/hyp.14726 ("Using particle size distributions to fingerprint suspended sediment sources – evaluation at laboratory and catchment scales")
<p>This repository contains data on particle size distribution data obtained from the laboratory and field experiments as described in Lake et al., 2022. </p> <p>The data contains the input files as needed for the modelling:</p> <p>- In the excel files the particle size distribution data for the target SS</p> <p>- In the text file the particle size distribution data from the sources.</p> <p> </p> <p>Furthermore, the data contains the resulting output files.</p> <p> </p>
Modeling the hydrological cycle in the atmosphere of Mars: Influence of a bimodal size distribution of aerosol nucleation particles
<p>Data from figures.</p>
Data set related to the manuscript "Investigating the effect of particle size distribution and complex exchange dynamics on NMR spectra of ions diffusing in disordered porous carbons through a mesoscopic model"
<p>Graphical files in the agr format for all the figures in the manuscript entitled "Investigating the effect of particle size distribution and complex exchange dynamics on NMR spectra of ions diffusing in disordered porous carbons through a mesoscopic model". XYZ files giving the particles and bulk positions in the lattices are also provided.</p>
Data from: Environmental DNA particle size distribution and quantity differ across taxa and organelles
Open the record for dataset details and reuse information.
2020 IMPACTS HVPS Individual Particle Measurements, Habits, and Size Distributions
<p>Morphological measurements for particles detected by the vertical channel of the High Volume Precipitation Spectrometer (HVPS) during seven flights of the 2020 IMPACTS field campaign, in netCDF format. Some flights have multiple files. Files ending in V_1.nc are individual particle files, while files ending in V.HVPS.nc are size distribution files. The numbers in all filenames represent the file start times, in format YYMMDDHHMMSS (in UTC). The individual particle data files include habit classifications as were used in Schima et al. 2024 (citation pending publication), and similarly, habit size distributions are available within the size distribution files. These files were created using University of Illinois/Oklahoma Optical Array Probe Processing Software (UIOPS, https://doi.org/10.5281/zenodo.1285968).</p> <p> </p> <p><strong>Some additional notes on habits</strong></p> <p>The size distribution files have a "habit" dimension of length 10. Along this dimension, indices in the files correspond to the following habits:</p> <div>0: sphere</div> <div>1: column/needle</div> <div>2: rejected</div> <div>3: tiny</div> <div>4: plate</div> <div>5: irregular</div> <div>6: graupel</div> <div>7: dendrite</div> <div>8: aggregate</div> <div>9: center-out</div> <div> </div> <div> </div> <div>The individual particle files have numeric codes for various habits. These codes refer to the following habits:</div> <div> </div> <div>77: missing</div> <div>67: center-out</div> <div>116: tiny</div> <div>111: rejected</div> <div>108: column/needle</div> <div>97: aggregate</div> <div>103: graupel</div> <div>115: sphere</div> <div>104: plate<br>105: irregular<br>100: dendrite</div> <div> </div>
2020 IMPACTS 2DS Individual Particle Measurements, Habits, and Size Distributions
<p>Morphological measurements for particles detected by the horizontal channel of the 2-Dimensional Stereo Probe (2DS) during seven flights of the 2020 IMPACTS field campaign, in netCDF format. Some flights have multiple files. Files ending in H_1.nc are individual particle files, while files ending in H.2DS.nc are size distribution files. The numbers in all filenames represent the file start times, in format YYMMDDHHMMSS (in UTC). The individual particle data files include habit classifications as were used in Schima et al. 2024 (citation pending publication), and similarly, habit size distributions are available within the size distribution files. These files were created using University of Illinois/Oklahoma Optical Array Probe Processing Software (UIOPS, https://doi.org/10.5281/zenodo.1285968).</p> <p> </p> <p><strong>Some additional notes on habits</strong></p> <p>The size distribution files have a "habit" dimension of length 10. Along this dimension, indices in the files correspond to the following habits:</p> <div>0: sphere</div> <div>1: column/needle</div> <div>2: rejected</div> <div>3: tiny</div> <div>4: plate</div> <div>5: irregular</div> <div>6: graupel</div> <div>7: dendrite</div> <div>8: aggregate</div> <div>9: center-out</div> <div> </div> <div> </div> <div>The individual particle files have numeric codes for various habits. These codes refer to the following habits:</div> <div> </div> <div>77: missing</div> <div>67: center-out</div> <div>116: tiny</div> <div>111: rejected</div> <div>108: column/needle</div> <div>97: aggregate</div> <div>103: graupel</div> <div>115: sphere</div> <div>104: plate<br>105: irregular<br>100: dendrite</div>
Laser Disdrometer Particle Size and Velocities Distributions Raw data (2014-2017) for Melbourne, Australia
<p>This dataset includes raw data obtained from Laser Disdrometers installed in the proximity of Melbourne, Australia. It includes data from 2 Thies LPM and 2 OTT Parsivel. The description of this dataset as well as a first step in the processing are described in Guyot et al. (under review) at Hydrology and Earth Sciences Systems (publisher EGU) under an open-source Discussion format. </p>
Figure 1 in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 1. Sampling sites in Sevastopol Bay, the Black Sea.
Particle size distribution of polycyclic aromatic hydrocarbons in the city of Venice
<p>Polycyclic aromatic hydrocarbons (PAHs) are important air contaminants, especially in urban areas, characterised by large emissions by road traffic, industries, and domestic heating. In air, PAHs can partition between the gas and the particulate phase because of their relative low vapor pressure.</p> <p>Previous studies focusing on the PAHs size distribution evidenced that PAHs tend to accumulate in fine particles (Hien et al., 2007; Li et al., 2019; Ren et al., 2017). The size of particles where a contaminant is mainly located is a key information for estimating the impact to human health. In fact, the smaller the particles, the deeper they can penetrate the respiratory system: nanoparticles (<100 nm) are small enough to pass from the pulmonary epithelium to the circulation, causing more sever damages on human health, with respect to those caused by fine and coarse particles.</p> <p>Several works studied the size distribution of PAHs in aerosol, but most of them focused on a small number of dimensional classes. Since PAHs have been identified as probable or possible carcinogenic compounds, deepening the knowledge about their size distribution becomes essential.</p> <p>In this work the particulate size distribution of PAHs was measured in Autumn 2020 using a cascade impactor MOUDI 110, obtaining twelve different dimensional classes of particles.</p> <p>PAHs were mainly distributed in fine particles (PM<sub>1</sub>). They showed a bi- or tri-modal distribution, with peaks in the coarse, in the accumulation, and in the Aitken modes (Figure 1). Passing from low to high molecular weight PAHs, peaks in the coarse and accumulation mode progressively reduce, and the peak in the Aitken mode increases. The same behaviour has been previously observed (Lv et al., 2016; Ren et al., 2017; Wu et al., 2006).</p> <p>Rarely in previous works a peak of PAHs at particle dimensions so close to nanoparticles has been measured. This can be due to the variety of releasing sources, particle aging processes, and meteorological conditions occurring in different places or to the different dimensional resolution of the conducted measurements. </p> <p>This means that a thorough investigation of the dimensional distribution of carcinogenic compounds can shed light on their actual danger, which depends not only on their concentration, but also on the size distribution. These preliminary results will be soon integrated with further samples in different seasons.</p> <p>We thank Giada D’Errico for her help in the experimental activities (sampling and analysis).</p> <p> </p>
Particle-size distribution of Iberian unfired potsherds from the Late Iron Age
<p>This data set contains 38 particle-size distributions (PSD) of unfired potsherds from the Iberian workshop of the Mas de Moreno (Teruel, Spain). The distributions were obtained by laser diffraction.</p> <p><strong>Method</strong></p> <p>The PSDs were measured using a LA-950V2 (HORIBA) laser granulometer.</p> <p>All the samples were pre-treated with hydrogen peroxide to remove organic matter. The samples were then dispersed in water using sodium hexametaphosphate and ultrasonication.</p> <p>The PSDs were calculated using the Mie solution to Maxwell's equation, with 1.33 as the water refractive index and 1.55-0.1i as the sediment refractive index.</p> <p><strong>Data description</strong></p> <ul> <li><em>sample:</em> sample reference;</li> <li><em>date:</em> date of the analysis;</li> <li><em>laboratory:</em> analysis laboratory;</li> <li><em>H2O2:</em> has the sample been pre-treated with hydrogen peroxide?</li> <li><em>HCl:</em> has the sample been pre-treated with chloridic acid?</li> <li><em>HMP:</em> has the sample been dispersed with sodium hexametaphosphate?</li> <li><em>ultrasonication:</em> duration of ultrasonic dispersion (seconds);</li> <li><em>0.011</em> to <em>3000.000: </em>relative amount (percent) for the given grain size (micrometers).</li> </ul>
Oceanic particle size distributions for the PacAtl and Arctic datasets
Open the record for dataset details and reuse information.
Data and model output for figures in "Variable particle size distributions reduce the sensitivity of global export flux to climate change"
<p><strong>Associated publication</strong></p> <p>This dataset was used to generate analyses and figures in the following publication:</p> <p>Leung, S., Weber, T., Cram, J. A., & Deutsch, C. Variable particle size distributions reduce the sensitivity of global export flux to climate change. <em>Submitted to Biogeosciences.</em></p> <p><strong>Associated code</strong></p> <p>After downloading this dataset, run the associated MATLAB code at the following link to generate the figures and analyses in the above publication:</p> <p>https://doi.org/10.5281/zenodo.4117382</p>
Particle Number Size Distributions from Rochester NY 2002-2019
Open the record for dataset details and reuse information.
Influence of calcination temperature and particle size distribution on the physical properties of SrFe12O19 and BaFe12O19 hexaferrite powder - part 2
Open the record for dataset details and reuse information.
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>7_experiments.zip contains modified model code and output data of each experiment in this study.</li> <li>off-line test.zip contains off-line test code and output data.</li> <li>plot_scripts.zip are the NCL scripts used for figures in the paper.</li> </ul>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The model codes, data, and plot scripts used in the paper, "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>Figs&Table are the NCL scripts used for figures and table in the paper.</li> <li>Model_Results contains output data of each experiment in this study.</li> <li>Mods_Scripts contains modified model code.</li> <li>Offline_Code contains off-line test code.</li> </ul>
Experimental modelling of tsunamis generated by pyroclastic density currents: the effects of particle size distribution on wave generation
<p><strong>Data set for experimental videos modelling the entrance of a fluidised granular flow into the water.</strong></p> <p>The data set includes:</p> <ul> <li>a MATLAB script to calculated theoretical volume and density of a non-fluidised mixture.</li> <li>Properties of the fluidised granular flows on the fluidising ramp: volume, density, thickness, flow and impact Froude numbers, kinetic energy of the fluidised flows.</li> <li>Properties of the surface elevation: surface elevation at x = 1.6m away from the shoreline, velocity of the leading wave, maximum/minimum amplitudes, potential energy of the generated waves and the energy transfer between the flow and the water column.</li> <li>Properties of the underwater gravity current - displacement, velocity and thickness of the underwater velocity current.</li> <li>a MATLAB script to visualise the surface elevation.</li> </ul>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The code, scripts, and data used in the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>All Figures&Table and their corresponding NCL scripts are under the directory of Figs&Table. </li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The code, data, and NCL scripts used for the figures and table in the Appendix are under the directory of Appendix.</li> </ul>
Particle Size Distribution in the 3-100 micron size range derived from an Imaging FlowCytoboy for 4 transect cruises across the Pacific Ocean
<p>Surface, Underway Imaging FlowCytobot (IFCB) differential_particle_size_distribution (PSDn, images per L per micron for each size bin) or differential_particle_volume_concentration (VDn, microliters per L per micron for each size bin) for 50 log-spaced size bins in the ~3-100 micrometer size range. Size distribution data collected from surface waters using the ship"s flowthrough system (~ 7m) during SCOPE cruises Gradients 2, 3, 4, and 5 (http://scope.soest.hawaii.edu/data/gradients/gradients.html). The IFCB triggers on both scattering and fluorescence so both living and non-living particles are included in the binned estimates. Note that the particle abundances and/or concentrations in the first few and last size bins may be underestimated. Please use care when comparing results across cruises, since different settings per cruise may result in different sensitivity and detection levels. Particle size of individual particles was calculated from estimated biovolume using the distance-map algorithm of Moberg and Sosik (2012). Particles are assumed spherical and are binned over 50 logarithmically-spaced size classes centered between 3.11 micrometers and 98.15 micrometers. See metadata in each excel spreadsheet for information on binwidth of each size class as well as other relevant information. This dataset was not converted to Carbon units. Timestamp is in UTC.</p>
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.