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430 results for “Hydration”
Large SEM-BSE images of hydrated alite of ages from 1 day up to 1 year
<p>This dataset contains 8-Bit SEM-BSE images of commercially available tricalcium silicate (C<sub>3</sub>S; alite, MIII polymorph; Vustah, Czech Republic). The alite was mixed with a water/binder ratio of 0.5. The paste was the cast in small sealed containers, which were submersed with water. The specimens were stored at 22 ± 2°C.</p> <p>After the desired hydration times (1, 7, 14, 28, 84, 365 days) the hydration was stopped by immersing the prisms in isopropanol and drying them at 60°C for 12 hours. The dried prisms were then embedded in low viscosity epoxy resin and mechanically polished using diamond paste with a grain size down to 0.25 µm. Finally, the specimens were coatet with a thin layer of carbon to avoid charging.</p> <p>The images were acquired at 10 kV (7 days, smaller image), 12 kV (7 - 365 days) and 15 kV (1 days) using a CBS (concentric backscatter, 14-365 days) and a ABS (1 and 7 days) detector within a Thermofischer Helios G4 UX.</p> <p><strong>Table 1</strong>: Basic information like resolution, size and phase composition of the images.</p> <table> <tbody> <tr> <td><strong>file</strong></td> <td><strong>age</strong></td> <td><strong>size</strong></td> <td><strong>size</strong></td> <td><strong>area</strong></td> <td><strong>pores</strong></td> <td><strong>hydrates</strong></td> <td><strong>clinker</strong></td> </tr> <tr> <td> </td> <td>in days</td> <td>in px</td> <td>in µm</td> <td>in mm²</td> <td>area-%</td> <td>area-%</td> <td>area-%</td> </tr> <tr> <td>C3S 1d.tif</td> <td>1</td> <td>21179 x 21495</td> <td>749.9 x 749.9</td> <td>0.56</td> <td>38.5</td> <td>38</td> <td>23.9</td> </tr> <tr> <td>C3S 7d.tif</td> <td>7</td> <td>19433 x 19320</td> <td>390.9 x 390.9</td> <td>0.15</td> <td>32.2</td> <td>48.5</td> <td>19.4</td> </tr> <tr> <td>C3S 7d_2.tif</td> <td>7</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>28.5</td> <td>52.8</td> <td>19.1</td> </tr> <tr> <td>C3S 14d.tif</td> <td>14</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>22.2</td> <td>62.7</td> <td>15.4</td> </tr> <tr> <td>C3S 28d.tif</td> <td>28</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>16.9</td> <td>74.9</td> <td>8.3</td> </tr> <tr> <td>C3S 84d.tif</td> <td>84</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>21.7</td> <td>72.7</td> <td>5.7</td> </tr> <tr> <td>C3S 365d.tif</td> <td>365</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>14.8</td> <td>83.2</td> <td>2.0</td> </tr> </tbody> </table> <p>The proportions of pores, hydrates and unhydrated clinker shown in Table 1 are the result of manual thresholding of denoised versions of these images and may therefore differ to own measurements.</p> <p>The scaling is backed into the file and can be read using ImageJ/Fiji.</p> <p>The unstitched files are provded as 7z archives. The sub-images were arranged in a 10 x 10 grid, with the exception of the 7 days image, which was arranged in a 9x9 grid. The pixel scaling of these files is the same as in the larger files. The unstitched files for the 1 day specimen can be provided on request.</p> <p><strong>Internal note</strong></p> <p>These files are included in the following MAPS datasets:</p> <ul> <li>2019_04_15 FK C3S 1d</li> <li>2019_04_23 C3S 7d 15 BIB</li> <li>2023_05_24 C32-C2S 14-84 d</li> <li>2023_06_08 C2S-C3S 28d-1year</li> <li>2023_07_18 C3S 7d, C2S 1d, 7d, 3C3S-1C2S 7d</li> </ul> <p><strong>Changelog</strong></p> <ul> <li>2023-08-03, V1.1 Added new dataset (C3S 7d_2.tif).</li> <li>2024-02-07, V1.1 modified description (error in hydrate/C<sub>3</sub>S measurement for the 14 days dataset)</li> </ul>
Dataset for: "Dynamical properties of solid and hydrated collagen: Insight from nuclear magnetic resonance relaxometry"
<p>The dataset contains a full set of 1H magnetization curves (1H magnetization versus time) for solid and hydrated collagen and collagen-based artificial tissues.</p> <p>DOI of article: <a href="https://doi.org/10.1063/5.0191409" target="_blank" rel="noopener">https://doi.org/10.1063/5.0191409</a></p> <p>This research was funded by the National Science Centre, Poland, Grant No. 2021/43/B/NZ5/01602.</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>
Dense inner C-S-H of 28 d hydrated alite, prepared using BIB at 20 °C
<p>These are images of 28 days hydtrated alite (M3 polymorph, Vustah, Czech Republic). The preparation of the specimens will be described in the corresponding Paper "<em>Argon Broad Ion beam sectioning and high resolution scanning electron microscopy imaging of hydrated alite</em>" published in Cement and Concrete Research.</p> <p>This dataset shows SEM images of the specimens prepared at <strong>20 °C</strong> in a tripple Argon Broad Ion Beam device.</p> <p>For all images described in the supplementary data of the paper, thee corresponding pore segmentation and ignored area is provided as well. This excludes the file "C3S 28d BIB 6KV 6h_019.tif".</p> <p>All files were acquired usng a Nova Nano SEM 230, FEI in SE mode at 2 KV and nearly the same magnification.</p>
Dense inner C-S-H of 28 d hydrated alite, prepared using BIB at -140 °C
<p>These are images of 28 days hydtrated alite (M3 polymorph, Vustah, Czech Republic). The preparation of the specimens will be described in the corresponding Paper "<em>Argon Broad Ion beam sectioning and high resolution scanning electron microscopy imaging of hydrated alite</em>" published in Cement and Concrete Research.</p> <p>This dataset shows SEM images of the specimens prepared at <strong>-140 °C</strong> in a tripple Argon Broad Ion Beam device.</p> <p>For all images described in the supplementary data of the paper, thee corresponding pore segmentation and ignored area is provided as well. This excludes the file "C3S 28d cryo BIB 6h_015.tif".</p> <p>All files were acquired usng a Nova Nano SEM 230, FEI in SE mode at 2 KV and nearly the same magnification.</p> <p> </p>
IonSolv-Aq Dataset for: Experimental Compilation and Computation of Hydration Free Energies for Ionic Solutes
<p>This repository includes datasets and supplementary materials for the manuscript "Experimental Compilation and Computation of Hydration Free Energies for Ionic Solutes" by Jonathan W. Zheng and William H. Green. <strong>Citations should refer directly to the manuscript:</strong></p> <blockquote> <p>Zheng, J. W., & Green, W. H. (2023). Experimental Compilation and Computation of Hydration Free Energies for Ionic Solutes. <em>The Journal of Physical Chemistry A</em>, <em>127</em>(48), 10268-10281.</p> </blockquote> <p>This compilation includes experimental and computed solvation free energies for the compounds in the IonSolv-Aq dataset, as well as .xyz files for all conformers used in the corresponding work. The lower-quality set of data described in the manuscript is also available in the "extra-anion-data.zip" archive file.</p>
Data for: Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and multi-scale material modeling
<h2>Description</h2> <p>DATA REPOSITORY FOR</p> <p>Title: Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and <br> multi-scale material modeling<br>By: Eva Jägle, Jithender J. Timothy, Daniel Jansen, Alisa Machner<br>Accepted by: Cement and Concrete Research</p> <p>This dataset presents the data of the paper 'Deriving early hydration cement paste phase assemblage, microstructure development and elastic properties using thermodynamic simulation and multi-scale material modeling' submitted to and accepted by Cement and Concrete Research. The dataset follows the structure of the paper such that the calculations described therein can be reproduced.</p> <p>Data is available on three types of cement: Two ordinary Portland cements of different grinding fineness (CEM I 42.5 R und CEM I 52.5 R) and one limestone-containing blended cement (CEM II/A-LL 42.5 R). The data refer to the first 24 hours of hydration and temperature conditions of 20°C (for CEM I 42.5 R, CEM I 52.5 R, CEM II/A-LL 42.5 R) and 35°C (for CEM I 52.5 R). All data were retrieved for cement pastes with a water-to-cement ratio of 0.45.</p> <p>The dataset contains raw and processed data from quantitative X-ray diffraction, 5PL cement dissolution fitting, thermodynamic simulation with GEMS, multi-scale material modeling, ultrasonic testing and Vicat penetration tests. The data is mainly available in .xlsx files together with short descriptions in ReadMe.txt files.</p>
Ab-initio molecular dynamics trajectories of fully hydrated TiO2 surfaces
<p>This data set contains trajectories of ab-initio molecular dynamics simulations of TiO<sub>2</sub> surfaces in water described in the paper:</p> <p>L.Agosta, E.G.Brandt and A.P.Lyubartsev<br> "Diffusion and reaction pathways of water near fully hydrated TiO<sub>2</sub> surfaces from ab initio molecular dynamics",<br> J.Chem.Phys., 147, 024704 (2107) doi: http://dx.doi.org/10.1063/1.4991381</p> <p>Trajectories of 6 fully hydrated TiO2 surfaces are stored under respective names. Each trajectory file contains 50 ps of simulation with frames saved every 0.0005 ps. Format: PDB, gzipped.</p> <p> </p>
Dynamic sparse X-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst: Raw data and reconstruction software
<pre>Dynamic sparse X-ray nanotomography reveals ionomer hydration mechanism in polymer electrolyte fuel-cell catalyst: Raw data and reconstruction software Dataset structure: <strong>- Dynamic_PEFC_data.h5</strong> # Raw projection data for dynamic tomography imaging of PEFC catalyst hydration. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /humidity_readout # Relative humidity value at the time each projection is measured, 1D array with axis (Nangle). - /Deform_X # X/Y/Z components for the deformation vector field which characterize nonrigid deformation of the sample. - /Deform_Y - /Deform_Z <strong>- liquid_simulation.h5</strong> # Numerical simulation of dynamic liquid filling process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). <strong>- phasetran_simulation.h5</strong> # Numerical simulation of gradual linear density change process. - /sinogram # Sinogram of all projections, 3-dimensional array with axes (Nangle,X axis,Y axis). - /tomo_angle # Tomography rotation angle for each projection, 1D array with axis (Nangle). - /groundtruth_tomograms # Ground truth of the simulated tomograms, 4-dimensional array with axes (Timeframe,Y axis, Z axis, X axis). Reconstruction codes: <strong>- astra_nonrigid.zip</strong> # Compressed python package of modified version of astra-toolbox with nonrigid computed tomography implementation. - /astra # Python package folder, need to be added to Python import search path (sys.path). # If the pre-compiled version doesn't work, source code of the pacakge can be downloaded: # https://github.com/zr-gao/astra-toolbox-nonrigid # Follow the instructions and requirements on the website to compile and install the package. <strong>- reconstruction_PEFC.py</strong> # Python script for sparse dynamic tomography of the PEFC dataset. # Need to be in the same folder with Dynamic_PEFC_data.h5 to load data. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra(with nonrigid)*, h5py # * <strong>!!!</strong> Nonrigid computed tomography is used for the reconstruction, therefore the astra package with nonrigid implementation (in astra_nonrigid.zip) is required. <strong>- reconstruction_simulation.py</strong> # Python script for sparse dynamic tomography of numerical simulations. # Need to be in the same folder with liquid_simulation.h5 or phasetran_simulation.h5, loaded filename is selected in the code. # Follow the instructions in the code to set reconstruction parameters and export results. # Requirements: cupy, numpy, astra**, h5py # ** Reconstruction of numerical simulations does not use nonrigid computed tomography, therefore both the astra_nonrigid.zip and the official astra-toolbox package will work. # To download and install the official astra-toolbox refer to the repository: # https://github.com/astra-toolbox/astra-toolbox</pre>
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>
"Hydration of a clay-rich unit on Mars, comparison of orbital data to rover data" supplementary data
<p>MCMC results from individual DAN measurements from sols 1814 to 3069 used in this work with material classifications from Figure 11.</p>
Datasets for Wohlfarth et al. (2023) An advanced thermal roughness model for airless planetary bodies - Implications for global variations of lunar hydration and mineralogical mapping of Mercury with the MERTIS spectrometer
<p>This document describes the datasets and modeling results presented and discussed in our full research article.<br> <br> Wohlfarth, K., Wöhler, C., Hiesinger, H., Helbert, J. 2023, An advanced thermal roughness model for airless planetary bodies - Implications for global variations of lunar hydration and mineralogical mapping of Mercury with the MERTIS spectrometer, Astronomy and Astrophysics, 672<br> <br> <a href="https://doi.org/10.1051/0004-6361/202245343">https://doi.org/10.1051/0004-6361/202245343</a><br> <br> We provide several visualization scripts that read and display the results for convenience. Access to the original MATLAB® code for the thermal model implementation is available upon request (<a href="mailto:kay.wohlfarth@tu-dortmund.de">kay.wohlfarth@tu-dortmund.de</a>).<br> <br> More info in Dataproducts.pdf</p>
Large SEM-BSE images of hydrated belite of ages from 14 days up to 1 year
<p>This dataset contains 8-Bit SEM-BSE images of commercially available dicalcium silicate (C<sub>2</sub>S; belite; Vustah, Czech Republic). The belite was mixed with a water/binder ratio of 0.5. The paste was the cast in small sealed containers, which were submersed with water. The specimens were stored at 22 ± 2°C.</p> <p>After the desired hydration times (14, 28, 84, 365 days) the hydration was stopped by immersing the prisms in isopropanol and drying them at 60°C for 12 hours. The dried prisms were then embedded in low viscosity epoxy resin and mechanically polished using diamond paste with a grain size down to 0.25 µm. Finally, the specimens were coatet with a thin layer of carbon to avoid charging.</p> <p>The images were acquired at 12 kV using a CBS (concentric backscatter) detector within a Thermofischer Helios G4 UX.</p> <p><strong>Table 1</strong>: Basic information like resolution, size and phase composition of the images.</p> <table> <tbody> <tr> <td><strong>file</strong></td> <td><strong>age</strong></td> <td><strong>size</strong></td> <td><strong>size</strong></td> <td><strong>area</strong></td> <td><strong>pores</strong></td> <td><strong>hydrates</strong></td> <td><strong>clinker</strong></td> </tr> <tr> <td> </td> <td>in days</td> <td>in px</td> <td>in µm</td> <td>in mm²</td> <td>area-%</td> <td>area-%</td> <td>area-%</td> </tr> <tr> <td>C2S 14d.tif</td> <td>14</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>31.4</td> <td>43.5</td> <td>25.2</td> </tr> <tr> <td>C2S 28d.tif</td> <td>28</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>15.9</td> <td>62.6</td> <td>21.5</td> </tr> <tr> <td>C2S 84d.tif</td> <td>84</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>19.3</td> <td>65.6</td> <td>15.2</td> </tr> <tr> <td>C2S 365d.tif</td> <td>365</td> <td>36864 x 36864</td> <td>1554.0 x 1554.0</td> <td>2.41</td> <td>23.8</td> <td>64.4</td> <td>12.0</td> </tr> </tbody> </table> <p>The proportions of pores, hydrates and unhydrated clinker shown in table 1 are the result of manual thresholding of denoised versions of these images and may therefore differ to own measurements.</p> <p>The scaling is backed into the file and can be read using ImageJ/Fiji.</p> <p>The unstitched files are provded as 7z archives. The sub-images were arranged in a 10 x 10 grid. The pixel scaling of these files is the same as in the larger files.</p> <p><strong>Internal note</strong></p> <p>These files are included in the following MAPS datasets:</p> <ul> <li>2023_05_24 C32-C2S 14-84 d</li> <li>2023_06_08 C2S-C3S 28d-1year</li> </ul> <p><strong>Funding</strong></p> <p>The research was supported by the Deutsche Forschungsgemeinschaft (DFG), grant number <a href="https://gepris.dfg.de/gepris/projekt/344069666">344069666</a>.</p>
Supplementary underlying data for "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"
<p>This dataset includes additional underlying data for the publication "Evaluating parameterization protocols for hydration free energy calculations with the AMOEBA polarizable force field"</p> <p>Contents:</p> <p>Tukey Honest Significant Difference (HSD) results for solutes 1-47 across all seven parameter sets, as *.txt. These are pairwise comparisons of results between all possible parameter sets. Significant differences are treated as p < 0.05.</p>
Proton dissociation and delocalization under stepwise hydration of zeolite HZSM-5
<p>This is a data archive for the publication: </p><p>"Proton dissociation and delocalization under stepwise hydration of zeolite HZSM-5" John H. Hack, Xinyou Ma, Yaxin Chen, James P. Dombrowski, Nicholas H. C. Lewis, Chenghan Li, Harold H. Kung, Gregory A. Voth, and Andrei Tokmakoff. The Journal of Physical Chemistry C <strong>2023</strong> <i>127</i> (32), 16175-16186. DOI: 10.1021/acs.jpcc.3c03611</p>
Data for JGR-Atmospheres Paper: Stratospheric Hydration Processes in Tropopause-Overshooting Convection Revealed by Tracer-Tracer Correlations from the DCOTSS Field Campaign
<p>Airborne 1-second data merger of observations from the NASA Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign. This merger includes subjective feature identifications analyzed in the paper referenced in the title. </p>
Raw data for: Portland and Belite cement hydration acceleration by C-S-H seeds with variable w/c ratios
<p>Raw data for: "Portland and Belite cement hydration acceleration by C-S-H seeds with variable w/c ratios".</p> <p>Includes: Calorimetry, TA, LXRPD and MIP data.</p> <p> </p> <p>doi: <a href="https://doi.org/10.3390/ma15103553">https://doi.org/10.3390/ma15103553</a></p>
Database of concrete heat of hydration parameters for concrete mixes used in piling (Grant reference EP/R511547/1)
<p>The heat of hydration parameters correspond to the model proposed by Liu et al. (2022). Parameters for five different concrete mixes are provided. They were obtained through finite element back analysis of the response of piles in the field assuming 1D axisymmetric conditions. Details of each of the concrete mixes and the thermal properties employed for soil and concrete in the FE analyses are provided. </p>
Figure 4: Determination of hydration of the skin before applying the product-STUDIES TOWARDS OBTAINING A PHOTOPROTECTIVE DERMO-COSMETIC COMPLEX PRODUCT WITH NATURAL EXTRACTS OF INORGANIC AND ORGANIC SUBSTANCES
<p>The volunteers who applied the product on the<br> skin appreciated the sensory characteristics such as: easiness of use, pleasant<br> texture, easy absorption without oily traces, appearance, odor and pleasant<br> color (¯gures 4, 5).</p>
Data for "Spectro-photometry of Phobos simulants: I. Detectability of hydrated minerals and organic bands"
<p>Data underlying the paper: "Spectro-photometry of Phobos simulants: I. Detectability of hydrated minerals and organic bands". The dataset contains visible, near-infrared, and mid-infrared spectra of various samples, including phyllosilicates, coals, and Phobos simulants. Measurements at different observation geometries are available for the Phobos simulants in the visible and near-infrared.</p>
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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)
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.