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143 results for “Particle size”
BAM reference data: SEM raw data for the Particles Size Distribution of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a)
<p>The SEM images are given in the TIF format.</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>- Vasile-Dan Hodoroaba. (2021). BAM reference data: EDS raw data of Al-coated titania nanoparticles (JRCNM62001a and JRCNM62002a) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.4986420</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>In the present work, a SEM of type Supra 40 (ZEISS, Oberkochen, Germany) with a Schottky field emitter and an InLens secondary electron detector was used at a 5 kV beam acceleration voltage.</p>
Relationship between sediment particle size, compaction and penetration resistance.
<p>Data on median grain size, compaction (measured with a vane tester) and penetration resistance (measured with a light penetrometer) of intertidal sediments. These data are the source of a mathematical function showing the relationship between them presented in a paper describing a new light penetrometer for intertidal and infralittoral sediments.</p>
The data used for "Exploring how differences in dust particle size distribution and complex refractive indices affect dust direct radiative fluxes using the CAS-FGOALS-SPRINTARS global climate model"
<p>These data are used for " Exploring how differences in dust particle size distribution (PSD) and complex refractive indices (CRI) affect direct radiative effect (DRE) using the CAS-FGOALS-SPRINTARS global climate model ". </p> <p>(1) AS83+OPAC: The control experiment, dust PSD is the original AS83, and the generic CRI is from OPAC. </p> <p>(2) BFT22+OPAC: Same as the control experiment, but the PSD is updated to use BFT22.</p> <p>(3) BFT22+DB: Same as the experiment BFT22+OPAC, but the generic OPAC CRI is replaced by nine regionally dependent DB CRIs.</p> <p>(4) BFT22+DB strong abs: Same as the experiment BFT22+DB, but the generic CRI consists of 10% percentile real and 90% percentile imaginary parts and no regional dependencies.</p> <p>(5) BFT22+DB weak abs: Same as the experiment BFT22+DB, but the generic CRI consists of 90% percentile real and 10% percentile imaginary parts and no regional dependencies.</p> <p>All experiments mentioned above are run for 5 years (2010-2014). The annual average simulation results are stored here.</p> <p><strong>Note:</strong> AS83 represents the dust PSD scheme from d'Almeida and Schütz. (1983). BFT22 represents the new dust PSD developed by Meng et al. (2022) based on the improved brittle fragmentation theory. OPAC: the Optical Properties for Aerosols and Clouds dataset, DB: the CRIs from Di Biagio et al. (2017, 2019).</p> <p><strong>References</strong></p> <p>d'Almeida, G. A., & Schütz, L. (1983). Number, Mass and Volume Distributions of Mineral Aerosol and Soils of the Sahara. <em>Journal of Applied Meteorology and Climatology</em>,<em> 22</em>(2), 233-243. https://doi.org/https://doi.org/10.1175/1520-0450(1983)022<0233:NMAVDO>2.0.CO;2</p> <p>Di Biagio, C., Formenti, P., Balkanski, Y., Caponi, L., Cazaunau, M., Pangui, E., et al. (2019). Complex refractive indices and single-scattering albedo of global dust aerosols in the shortwave spectrum and relationship to size and iron content. <em>Atmospheric Chemistry and Physics</em>,<em> 19</em>(24), 15503-15531. https://doi.org/10.5194/acp-19-15503-2019</p> <p>Di Biagio, C., Formenti, P., Balkanski, Y., Caponi, L., Cazaunau, M., Pangui, E., et al. (2017). Global scale variability of the mineral dust long-wave refractive index: a new dataset of in situ measurements for climate modeling and remote sensing. <em>Atmospheric Chemistry and Physics</em>,<em> 17</em>(3), 1901-1929. https://doi.org/10.5194/acp-17-1901-2017</p> <p>Meng, J., Huang, Y., Leung, D. M., Li, L., Adebiyi, A. A., Ryder, C. L., et al. (2022). Improved Parameterization for the Size Distribution of Emitted Dust Aerosols Reduces Model Underestimation of Super Coarse Dust. Geophysical Research Letters, 49(8), e2021GL097287, https://doi.org/https://doi.org/10.1029/2021GL097287</p>
Analysis of particles size distributions in Mg(OH)2 precipitation from highly concentrated MgCl2 solutions
<p>Magnesium is a raw material of great importance, which attracted increasing interest in the last years. A promising<br> route is to recover magnesium in the form of Magnesium Hydroxide via precipitation from highly concentrated<br> Mg2+ resources, e.g. industrial or natural brines and bitterns. Several production methods and<br> characterization procedures have been presented in the literature reporting a broad variety of Mg(OH)2<br> particle sizes. In the present work, a detailed experimental investigation is aiming to shed light on the<br> characteristics of produced Mg(OH)2 particles and their dependence upon the reacting conditions. To this<br> purpose, two T-shaped mixers were employed to tune and control the degree of homogenization of reactants.<br> Particles were analysed by laser static light scattering with and without an anti-agglomerant treatment based<br> on ultrasounds and addition of a dispersant. Zeta potential measurements were also carried out to further assess<br> Mg(OH)2 suspension stability.</p>
Data to reproduce the results presented in Sehgal et al. 2022. Water Resources Research, https://doi.org/10.1029/2021WR030624 ("Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer")
<p>This repository consists data to reproduce results as presented in: "Inferring suspended sediment carbon content and particle size at high-frequency from the optical response of a submerged spectrometer", Water Resorces Research. Kindly refer to the readme.text file to navigate through the dataset.</p> <p> </p> <p> </p>
Tuning topological spin textures in size-tailored chiral magnet insulator particles
<p>The file contains the raw data and code used for the paper entitled "Tuning topological spin textures in size-tailored chiral magnet insulator particles" by Priya R. Baral et al. to be published in Journal of Physical Chemistry C. </p> <p>Requests for further information can be directed to the corresponding author: Arnaud Magrez (arnaud.magrez 'at' epfl.ch) </p>
Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach
Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters).
Data used in "Utilizing the Heliophysics/Geospace System Observatory to Understand Particle Injections: Their Scale Sizes and Propagation Directions"
<p>These are the raw data files for the data used in the paper, "Utilizing the Heliophysics/Geospace System Observatory to Understand Particle Injections: Their Scale Sizes and Propagation Directions" by Gabrielse et al. They can be read using the SPEDAS software found here: http://themis.ssl.berkeley.edu/software.shtml. Tplot variables, which are specifically read and plotted by SPEDAS, are included for pertinent THEMIS data.</p>
NanoValid D.5.47 Annex 1: Inter-laboratory comparison on measurand particle size of ~15 nm Lys-SNPs-B1 Silica Nanoparticles Particles
<p>An inter-laboratory comparison on the particle size, expressed as mean diameter <em>d</em>, of nanoscaled SiO<sub>2</sub> (#14 BAM Silica, ~15 nm diameter (see D.5.41/5.42)) has been performed. The majority of participants used Dynamic Light Scattering (DLS). A few used Electron Microscopy as method (SEM, TEM, T-SEM). Following methods had been applied by only one participant: Small Angle X-ray Scattering, Analytical Ultracentrifugation, Atomic Force Microscopy and Atomizer with electric mobility spectrometer (SMPS).</p> <p>The Task 5.4 of NanoValid is designed to test, compare and validate current methods to measure and characterize physicochemical properties of selected engineered nanoparticles. This will be achieved by inter-laboratory comparisons. The measurand of one of these round robins is <em>Particle size/Particle size distribution.</em> The measurements are to be accompanied by estimates of the uncertainties at a confidence level of 95%, deduced from the standard uncertainties. Therefore an uncertainty budget comprising statistical (Type A) and systematic (Type B) errors has to be established and delivered for each measurand. The inter-laboratry comparison protocol comprises two Annexes addressing the establishment of uncertainty budgets following GUM. The final goal of the comparison is to identify those methods of measurement which have potential as reference methods in pc characterization of nanoparticles for the determination of a given measurand (Task 5.4 of the NanoValid Project).</p>
Figure 4 in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 4. Circularity-versus-Feret's diameter plots of the MP samples collected at four stations in Sevastopol bay (the Black Sea) in 2019. Dot numbers do not correspond to the MPs abundance in the water. Dashed line represents the upper border of fibers.
Figure 5 in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 5. Distribution of MPs along Sevastopol bay (the Black Sea) in terms of average particle shape descriptors (left plots), overall abundance and weight of MP fragments, and percentage of fibers among them (right plots).
Figure 3 in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 3. Distribution of the four types of MP particles (red – rounded, violet – irregular, blue – elongated, and green – fibers) in a Circularity-versus-Feret's diameter plot (scatter). Dashed line represents the upper border of fibers.
Figure 2. A in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 2. A: Microplastic samples dried on the 'storage' filters (100-µm nylon mesh). B: Pure microplastics under an inverted microscope. C-D: Micrograph of a sample in Bogorov's camera and its b/w image processed in an image editor. E: High-contrast scan image of a microplastic sample.
Figure 6 in A new method for analyzing microplastic particle size distribution in marine environmental samples
Figure 6.Weight of a MP sample (M) as a function of the total silhouette area (S) of the MP particles.
Substrate stiffness reduces particle uptake by epithelial cells and macrophages in a size-dependent manner through mechanoregulation
<p>Cells continuously exert forces on their environment and respond to changes in mechanical forces by altering their behavior. Many pathologies such as cancer and fibrosis are hallmarked by dysregulation in the extracellular matrix, driving aberrant behavior through mechanotransduction pathways. We demonstrate that substrate stiffness can be used to regulate cellular endocytosis of particles in a size-dependent fashion. Culture of A549 epithelial cells and J774A.1 macrophages on polystyrene/glass (stiff) and polydimethylsiloxane (soft) substrates indicated that particle uptake is increased up to six times for A549 and two times for macrophages when cells are grown in softer environments. Furthermore, we altered surface characteristics through the attachment of submicron-sized particles as a method to locally engineer substrate stiffness and topography. To investigate the biomechanical changes which occurred within adherent epithelial cells, i.e. characterization of A549 cell spreading and focal adhesion maturation. Consequently, decreasing substrate rigidity and particle-based topography lead to a reduction of focal adhesion size. Moreover, expression levels of Yes-associated protein were found to correlate with the degree of particle endocytosis. A thorough appreciation of the mechanical cues may lead to improved solutions to optimize nanomedicine approaches for treatment of cancer and other diseases with abnormal mechanosignaling.</p>
Dataset accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes"
<p>The dataset in this repository is accompanying the publication "Transport and retention of micro-Polystyrene in coarse riverbed sediments: Effects of flow velocity, particle and sediment sizes" (in Microplastics and Nanoplastics, 2023, submitted 09.06.2023)</p> <p>The repository contains the raw image files of all sample filters which were scanned using the fluorescence imaging system ChemiDoc and used to analyse the infiltration behaviour of microplastic polystyrene in the manuscript. In addition, we provide the resulting data from the particle identification and geometric analysis which were derived from the raw data using ImageJ in tabular excel format. The data is structured in folders following the naming of the columns from the manuscript.</p>
SGS-LTER Paleopedology Study - soil particle size and grain size on the Central Plains Experimental Range, Nunn, Colorado, USA 1992- 1993
This data package was produced by researchers working on the Shortgrass Steppe Long Term Ecological Research (SGS-LTER) Project, administered at Colorado State University. Long-term datasets and background information (proposals, reports, photographs, etc.) on the SGS-LTER project are contained in a comprehensive project collection within the Digital Collections of Colorado (http://digitool.library.colostate.edu/R/?func=collections&collection_id=3429). The data table and associated metadata document, which is generated in Ecological Metadata Language, may be available through other repositories serving the ecological research community and represent components of the larger SGS-LTER project collection. CPER Paleopedology Study – Particle and Grain Size - Grain size data from 39 pedons were compared with modal fluvial (7) and eolian (3) samples in order to characterize the origin of CPER parent materials and distinguish the origin of CPER geomorphic features. The seven fluvial sites were located along Owl and Eastman Creeks. The three eolian sites were located on the nearest undisputed dune fields located approximately 5 km north of Roggen, CO (Muhs, 1985). For statistical analysis, the sand and coarse silt fractions were shaken in a nest of half phi(0) interval sieves ranging from -1.0 0 (10 mesh) to 4.5 0 (325 mesh) for 3 minutes. Phi intervals (-log2) were utilized to normalize the particle size data for use in conventional statistics (Krumbein, 1934). The silt and clay fractions were separated by sedimentation using the pipette method. Statistical methods adopted from Folk and Ward (1957) were applied to the -1.0 0 to 7.0 0 fractions using the Sedimentary Petrology Computer Program SEDPET (Warner, 1970) to determine mean grain size (Mz), sorting (Iz), skewness (Skz), and kurtosis (Kz). These parameters were then subjected to univariate and bivariate analysis. The clay fraction was not included in the statistical computations to avoid excessively fine skewing the
Polymer-assisted modification of metal-organic framework MIL-96 (Al): influence on particle size, crystal morphology and perfluorooctanoic acid (PFOA) removal
<p>Dataset supporting publication.</p> <p><strong>Polymer-assisted modification of metal-organic framework MIL-96 (Al): influence of HPAM concentration on particle size, crystal morphology and removal of harmful environmental pollutant PFOA</strong></p> <p>Chemosphere, <a href="https://doi.org/10.1016/j.chemosphere.2020.128072">https://doi.org/10.1016/j.chemosphere.2020.128072</a></p> <p>Preprint available from ChemRxiv, <a href="https://doi.org/10.26434/chemrxiv.12262010.v2">https://doi.org/10.26434/chemrxiv.12262010.v2</a></p> <p><strong>Abstract</strong></p> <p>A new synthesis method was developed to prepare an aluminum-based metal organic framework (MIL-96) with a larger particle size and different crystal habits. A low cost and water-soluble polymer, hydrolyzed polyacrylamide (HPAM), was added in varying quantities into the synthesis reaction to achieve >200% particle size enlargement with controlled crystal morphology. The modified adsorbent, MIL-96-RHPAM2, was systematically characterized by SEM, XRD, FTIR, BET and TGA-MS. Using activated carbon (AC) as a reference adsorbent, the effectiveness of MIL-96-RHPAM2 for perfluorooctanoic acid (PFOA) removal from water was examined. The study confirms stable morphology of hydrated MIL-96-RHPAM2 particles as well as a superior PFOA adsorption capacity (340 mg/g) despite its lower surface area, relative to standard MIL-96. MIL-96-RHPAM2 suffers from slow adsorption kinetics as the modification significantly blocks pore access. The strong adsorption of PFOA by MIL-96-RHPAM2 was associated with the formation of electrostatic bonds between the anionic carboxylate of PFOA and the amine functionality present in the HPAM backbone. Thus, the strongly held PFOA molecules in the pores of MIL-96-RHPAM2 were not easily desorbed even after eluted with a high ionic strength solvent (500 mM NaCl). Nevertheless, this simple HPAM addition strategy can still chart promising pathways to impart judicious control over adsorbent particle size and crystal shapes while the introduction of amine functionality onto the surface chemistry is simultaneously useful for enhanced PFOA removal from contaminated aqueous systems.</p>
Enhanced performance of Pr_4Ni_3O_10+_\delta - Ce_0.75Gd_0.1Pr_0.15O_2-\delta composite electrode via particle size grading
<p>The zipped file consists of original data of impedance for electrodes measured at 625 degrees and pO2 of 0.21 atm, and the corresponding DRT result, as well as peak fitting results based on DRT results. A txt file of specification is prepared for illustration.</p>
Particle number size distribution of fluorescent, hyper-fluorescent, and total aerosol particles measured during the Antarctic Circumnavigation Expedition.
<p><strong>Dataset abstract</strong></p> <p>This dataset consists of a 5-minute time series of particle number concentration of fluorescent and total aerosol particles that were measured by wideband integrated by aerosol sensor during the Antarctic Circumnavigation Expedition during the austral summer of 2016/2017. For this dataset, aerosol particles within the optical diameter range of 0.5 μm to 14.5 μm were considered. In this dataset, the time periods when samples are likely contaminated by the ship’s exhaust were removed from the time series.</p> <p><strong>Dataset contents</strong></p> <ul> <li>PSD_fluorescent.csv , data file, comma-separated values</li> <li>PSD_hyper_fluorescent.csv , data file, comma-separated values</li> <li>PSD_hyper_tot.csv , data file, comma-separated values</li> <li>data_file_header.txt, metadata, text</li> <li>README.txt, metadata, text</li> </ul> <p><strong>Dataset license</strong></p> <p>This particle number size distribution of fluorescent, hyper-fluorescent, and total aerosol particles dataset from ACE 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>
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International Brain Laboratory public data
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OpenNeuro
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