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20 results for “Pore size”
XCT data of metallic feedstock powder with pore size analysis
<p><strong>X-Ray computed tomography (XCT) scan of 11 individual metallic powder particles, made of (Mn,Fe)<sub>2</sub>(P,Si) alloy</strong></p> <p>The data set consists of 4 single XCT scans which have been stitched together [3] after reconstruction.<br> The powder material is an (Mn,Fe)<sub>2</sub>(P,Si) alloy with an average density of 6.4 g/cm³. The particle size range is about 100 - 150 µm with equivalent pore diameters up to 75 µm. The powder and the metallic alloy are described in detail in [1, 2].</p> <p><strong>Data acquisition</strong></p> <p>The data was acquired using a Zeiss Xradia 620 Versa X-ray microscope which provides the opportunity of optical magnification.</p> <table> <caption><strong>Tomographic imaging parameters</strong></caption> <tbody> <tr> <td>XCT system</td> <td>Zeiss Xradia 620 Versa</td> </tr> <tr> <td>Voltage</td> <td>80</td> <td>kV</td> </tr> <tr> <td>Power</td> <td>10</td> <td>W</td> </tr> <tr> <td>Source filtering</td> <td>"<em>LE2</em>" (system specific)</td> <td>-</td> </tr> <tr> <td>Source-object distance</td> <td>10</td> <td>mm</td> </tr> <tr> <td>Object-detector distance</td> <td>10</td> <td>mm</td> </tr> <tr> <td>Geom. magnification</td> <td>2</td> <td>-</td> </tr> <tr> <td>Optical magnification</td> <td>20</td> <td>-</td> </tr> <tr> <td>Native pixel size</td> <td>13.5</td> <td>µm</td> </tr> <tr> <td>Binning</td> <td>2x2</td> <td>px</td> </tr> <tr> <td>Voxel size</td> <td>0.68</td> <td>µm</td> </tr> <tr> <td>No. of projections per scan</td> <td>801</td> <td>1</td> </tr> <tr> <td>No. of scans</td> <td>4</td> <td>-</td> </tr> <tr> <td>Exposure time per projection</td> <td>5</td> <td>s</td> </tr> </tbody> </table> <p> </p> <p><strong>Projection data</strong> (801 single TIFF-files each):</p> <ul> <li>proj_00</li> <li>proj_01</li> <li>proj_02</li> <li>proj_03</li> </ul> <p><strong>Reconstructed data</strong>:</p> <ul> <li>raw-volume (MnFePSi-Powder_80kV_10W_LE2_20x_5s_801_0p68_BHC=2_Stitch_U16_966x1020x2916.raw + header.txt)</li> <li>analyzed data as Volume Graphics Studio MAX 3.4.5 project</li> </ul> <p><strong>Stitched 2D data</strong> (images stitched with ImageJ-Plugin described in [3]<strong>:</strong></p> <ul> <li>Stitched_0deg_Projections.tif</li> <li>Pores+Particles_Analysis.tif</li> </ul> <p> </p> <p>[1] G.-R. Jaenisch, U. Ewert, A. Waske, and A. Funk, “Radiographic Visibility Limit of Pores in Metal Powder for Additive Manufacturing,” Metals, vol. 10, no. 12, p. 1634, Dec. 2020. https://doi.org/10.3390/met10121634</p> <p>[2] X. Miao et al., “Printing (Mn,Fe)2(P,Si) magnetocaloric alloys for magnetic refrigeration applications,” J. Mater. Sci., vol. 55, no. 15, pp. 6660–6668, May 2020. https://doi.org/10.1007/s10853-020-04488-8</p> <p>[3] S. Preibisch, S. Saalfeld, and P. Tomancak, “Globally optimal stitching of tiled 3D microscopic image acquisitions,” Bioinformatics, vol. 25, no. 11, pp. 1463–1465, Jun. 2009.</p>
Dataset for publication "Importance of Substrate Pore Size and Wetting Behavior in Gas Diffusion Electrodes for CO2 Reduction"
<p>Dataset for the publication "Importance of Substrate Pore Size and Wetting Behavior in Gas Diffusion Electrodes for CO2 Reduction" containing war and processed data used to compose the various figures. </p> <p>DOI Publication: <a href="https://doi.org/10.1021/acsaem.2c03054">https://doi.org/10.1021/acsaem.2c03054</a> </p>
Data set related to the manuscript "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons"
<p>Graphical files in the agr format for all the figures in the main text of the manuscript entitled "Ionic liquids under confinement: From systematic variations of the ion and pore sizes towards an understanding of structure and dynamics in complex porous carbons" (10.1021/acsami.9b16740). Example of input file for one of the systems simulated.</p>
Functionalized graphene via a one pot reaction enabling exact pore sizes, modifiable pore functionalization and precision doping - JACS
<p>The dataset uploaded herein is associated with the paper published under the title "<em>Functionalized graphene via a one pot reaction enabling exact pore sizes, modifiable pore functionalization and precision doping</em>" with the American Chemical Society - Jouranl of the American Chemical Society. This dataset includes the .vasp files for all modeled structures, the INCAR for geometry optimizations, the KPOINTS for the generated band structure diagrams, the input script for the Zeo++ calculations, and the integrated Python notebook (.ipynb) that was used to read, analyze and plot the semiconducting data (.xlsx). This data has been made available to the scientific community in the interest of open-source and accessible data. The authors request that you please cite the associated paper and Zenodo dataset if used.</p> <h3>Abstract</h3> <p>Functionalizing graphene with exact pore size, specific functional groups, and precision doping poses many significant challenges. Current methods lack precision and produce random pore sizes, site of attachments and amounts of dopant leading to compromised structural integrity and affecting graphene’s applications. In this work, we report a strategy for the synthesis of functionalized graphitic materials with modifiable nanometer sized pores via a Pictet-Spengler polymerization reaction. This one-pot, four step synthesis uses concepts based on Covalent Organic Frameworks (COFs) synthesis to produce crystalline two-dimensional materials that were confirmed by pXRD, TEM measurements and DFT studies. These new materials are structurally analogous to doped graphene and graphene oxide (GO) but unlike GO maintain their semi-conductive properties when fully functionalized.</p>
Data, Figures and Codes for "Experimental analyses of pore-size dependent biomineralization in porous media under various flow rate and bacterial density scenarios"
<pre>This repository contains the data, codes and figures for the manuscript <br>"Experimental analyses of pore-size-dependent biomineralization in porous media under various flow rate and bacterial density scenarios". <br><br>Comments welcome. </pre>
PoreScript: Semi-automated Pore Size Analysis Algorithm Data Set
<p>This data set contains files related to the PoreScript semi-automatic pore size image analysis algorithm. The three MATLAB files needed for the PoreScript algorithm are named the following: </p> <p>(<a href="https://zenodo.org/api/files/47f5a723-b2de-41b6-baed-f1a6335c4b84/Jenkins_RelativeIntensityFinder_no_crop.m">Jenkins_RelativeIntensityFinder_no_crop.m</a>, <a href="https://zenodo.org/api/files/47f5a723-b2de-41b6-baed-f1a6335c4b84/Jenkins_UserInterface_no_crop.m">Jenkins_UserInterface_no_crop.m</a>, <a href="https://zenodo.org/api/files/47f5a723-b2de-41b6-baed-f1a6335c4b84/Jenkins_PoreSizeCalculator_no_crop.m">Jenkins_PoreSizeCalculator_no_crop.m</a>).</p> <p>Access the latest version of the program here:<a href="https://github.com/djenkins95/PoreScript_Update_9_26_23"> <strong>https://github.com/djenkins95/PoreScript_Update_9_26_23</strong></a></p> <p>Updated MATLAB files are more accessible to a wider range of SEM software. The updated version asks for the known length of your scale bar in pixels. There are many ways to measure the length of your scale bar. I recommend using the free software FIJI. Use the *Straight* (drawing tool to trace your scale bar), then click Analyze > Measure to determine the length in pixels. It should be noted that the length in pixels will be the same for any image taken on the same instrument, at the same magnification, and saved as the same file type (e.g., .tiff), so you can reference the length in future data sets without needed to remeasure the scale bar.</p> <p>The Zenodo repository includes the unanalyzed SEM images, analyzed images, raw pore size data, analyzed pore size data, and older .m versions.</p>
Data set related to the manuscript "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance"
<p>Graphical files in the agr format and xyz files for the figures in the manuscript entitled "Carbon-carbon supercapacitors: Beyond the average pore size or how electrolyte confinement and inaccessible pores affect the capacitance". Examples of input files for the two systems simulated.</p>
Harnessing Pore Size in COF Membranes: A Concentration Gradient-Driven Molecular Dynamics (CGD-MD) Study on Enhanced H₂/CH₄ Separation
Open the record for dataset details and reuse information.
FIGURE3. Taxonomic illustration of Paraputo blackmani Joshi sp.n., adult female. A. Body overview; B. Antenna; C. Anal ring; D. Tarsal and claw digitules, claw without a denticle; E. Coxa with translucent pores; F. Trilocular pores; G. Anal lobe cerarius (C18); H. Penultimate cerarius (C17); I. Antepenultimate cerarius (C); J. Setae at ocular position (C3); K. Setae at 16 frontal position (C1); L. Dorsal seta; M. Discoidal pore; N. Ventral setae; O. Multilocular disc-pore; P. Oral collar tubular ducts of two sizes. in --A--new--species--of--Paraputo--Laing--1929--(Hemiptera:--Coccomorpha:-- Pseudococcidae)--from--India
FIGURE3. Taxonomic illustration of Paraputo blackmani Joshi sp.n., adult female. A. Body overview; B. Antenna; C. Anal ring; D. Tarsal and claw digitules, claw without a denticle; E. Coxa with translucent pores; F. Trilocular pores; G. Anal lobe cerarius (C18); H. Penultimate cerarius (C17); I. Antepenultimate cerarius (C); J. Setae at ocular position (C3); K. Setae at 16 frontal position (C1); L. Dorsal seta; M. Discoidal pore; N. Ventral setae; O. Multilocular disc-pore; P. Oral collar tubular ducts of two sizes.
Data from: Mouthpart conduit sizes of fluid-feeding insects determine the ability to feed from pores
Fluid-feeding insects, such as butterflies, moths and flies (20% of all animal species), are faced with the common selection pressure of having to remove and feed on trace amounts of fluids from porous surfaces. Insects able to acquire fluids that are confined to pores during drought conditions would have an adaptive advantage and increased fitness over other individuals. Here, we performed feeding trials using solutions with magnetic nanoparticles to show that butterflies and flies have mouthparts adapted to pull liquids from porous surfaces using capillary action as the governing principle. In addition, the ability to feed on the liquids collected from pores depends on a relationship between the diameter of the mouthpart conduits and substrate pore size diameter; insects with mouthpart conduit diameters larger than the pores cannot successfully feed, thus there is a limiting substrate pore size from which each species can acquire liquids for fluid uptake. Given that natural selection independently favoured mouthpart architectures that support these methods of fluid uptake (Diptera and Lepidoptera share a common ancestor 280 Ma that had chewing mouthparts), we suggest that the convergence of this mechanism advocates this as an optimal strategy for pulling trace amounts of fluids from porous surfaces.
Data from: Cell wall microstructure, pore size distribution and absolute density of hemp shiv
This paper, for the first time, fully characterises the intrinsic physical parameters of hemp shiv including cell wall microstructure, pore size distribution and absolute density. Scanning Electron Microscopy revealed microstructural features similar to hardwoods. Confocal Microscopy revealed three major layers in the cell wall: middle lamella, primary cell wall and secondary cell wall. Computed tomography improved the visualisation of pore shape and pore connectivity in three dimensions. Mercury intrusion porosimetry showed the average accessible porosity was 76.67 ± 2.03 % and pore size classes could be distinguished into micropores (3-10 nm) and macropores (0.1-1 µm and 20-80 µm). The absolute density was evaluated by helium pycnometry, mercury intrusion porosimetry (MIP) and Archimedes' methods. The results show that these methods can lead to misinterpretation of absolute density. The MIP method showed a realistic absolute density (1.45 g/cm3) consistent with the density of the known constituents: including lignin, cellulose and hemi-cellulose. However, helium pycnometry and Archimedes' methods gave falsely low values due to 10% of the volume being inaccessible pores, which require sample pretreatment in order to be filled by liquid or gas. This indicates that the determination of the cell wall density is strongly dependent on sample geometry and preparation.
Supplementary material 5 from: Deiner K, Lopez J, Bourne S, Holman LE, Seymour M, Grey EK, Lacoursière-Roussel A, Li Y, Renshaw MA, Pfrender ME, Rius M, Bernatchez L, Lodge DM (2018) Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: the effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics 2: e28963. https://doi.org/10.3897/mbmg.2.28963
Alternative statistical model :
Supplementary material 4 from: Deiner K, Lopez J, Bourne S, Holman LE, Seymour M, Grey EK, Lacoursière-Roussel A, Li Y, Renshaw MA, Pfrender ME, Rius M, Bernatchez L, Lodge DM (2018) Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: the effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics 2: e28963. https://doi.org/10.3897/mbmg.2.28963
4_NTC :
Supplementary material 2 from: Deiner K, Lopez J, Bourne S, Holman LE, Seymour M, Grey EK, Lacoursière-Roussel A, Li Y, Renshaw MA, Pfrender ME, Rius M, Bernatchez L, Lodge DM (2018) Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: the effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics 2: e28963. https://doi.org/10.3897/mbmg.2.28963
Bioinformatic pipeline and thresholds :
Supplementary material 3 from: Deiner K, Lopez J, Bourne S, Holman LE, Seymour M, Grey EK, Lacoursière-Roussel A, Li Y, Renshaw MA, Pfrender ME, Rius M, Bernatchez L, Lodge DM (2018) Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: the effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics 2: e28963. https://doi.org/10.3897/mbmg.2.28963
Profiling tables for all libraries :
Supplementary material 1 from: Deiner K, Lopez J, Bourne S, Holman LE, Seymour M, Grey EK, Lacoursière-Roussel A, Li Y, Renshaw MA, Pfrender ME, Rius M, Bernatchez L, Lodge DM (2018) Optimising the detection of marine taxonomic richness using environmental DNA metabarcoding: the effects of filter material, pore size and extraction method. Metabarcoding and Metagenomics 2: e28963. https://doi.org/10.3897/mbmg.2.28963
Extraction protocols :
Data from: Cell wall microstructure, pore size distribution and absolute density of hemp shiv
Open the record for dataset details and reuse information.
Data from: Mouthpart conduit sizes of fluid-feeding insects determine the ability to feed from pores
Open the record for dataset details and reuse information.
Study Evaluating the Impact of Mesh Pore Size on Chronic Pain After Lichtenstein Hernioplasty
ClinicalTrials.gov study NCT02500056. IPD Sharing: Not stated. Countries: 0. Publications: 0.
Water Film Thickness in Unsaturated Porous Media: Effect of Pore Size, Pore Solution Chemistry, and Mineral Type
<p>Data set used in figures.</p>
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