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45 results for “magnetic properties”
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>
The LILY Database: Linking Lithology to IODP Physical, Chemical, and Magnetic Properties Data
<p>During each expedition of the International Ocean Discovery Program and its precursor, the Integrated Ocean Drilling Program (jointly referred to as IODP), vast arrays of data are collected from drill cores. These data, which are accessible from the IODP LIMS (Laboratory Information Management System) database, include physical, chemical, and magnetic properties collected semi-continuously along cores using automated track systems, as well as a variety of analyses conducted on discrete subsamples taken from the cores. In addition, the lithology of all cores is described based on visual characteristics of the surface of split cores, visual examination of smear slides and thin sections, and compositional or mineralogical information derived from geochemical analyses. We extract basic lithologic information from this complex array of descriptive information and then tie that information to all other measurements. This new database is referred to as <strong>LI</strong>MS with <strong>L</strong>itholog<strong>y</strong> (LILY). LILY currently contains over 34 million data from 89 km of core recovered on 42 expeditions conducted 2009-2019. Some uses of LILY include identifying the abundance of different lithologies, finding data from core intervals with a specific lithology, assessing the efficacy of coring systems in different lithologies, or characterizing and analyzing physical, chemical, and magnetic properties based on lithology. We illustrate the use of LILY by computing the grain density by lithology from over 24,000 moisture and density measurements and then use those grain densities, along with the large IODP bulk density dataset, to compute a new high-resolution porosity dataset with over 3.7 million new porosity estimates.</p> <h2>CONTENT DESCRIPTION:</h2> <p><strong>The main LILY database is stored in the files with the suffix DataLITH.csv.</strong> Each file contains IODP LIMS data with lithology and other metadata added. The file prefix gives the type of data. For example, AVS_DataLITH.csv contains the Automated Vane Shear (AVS) shear strength data paired with lithology and other metadata. A list of all data types is given in Supporting Information Table S1 of Childress et al. (2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>). There are a total of 23 DataLITH files.</p> <ul> <li>AVS_DataLITH.csv: automated vane shear; shear strength measurements.</li> <li>CARB_DataLITH.csv: total carbon, hydrogen, nitrogen, and sulfur, inorganic carbon (carbonate), and organic carbon measured on discrete samples.</li> <li>GE_DataLITH.csv: gas elements from gas chromatography.</li> <li>GRA_DataLITH.csv: gamma ray attenuation bulk density from the Whole-Round Multisensor Logger (WRMSL).</li> <li>ICP_DataLITH.csv: Inductively-coupled plasma data.</li> <li>IW_DataLITH.csv: interstitial water chemistry.</li> <li>JR6A_DataLITH.csv: discrete magnetic measurements from the JR6A spinner magnetometer.</li> <li>KAPPA_DataLITH.csv: Kappabridge susceptibility meter measurements.</li> <li>MAD_DataLITH.csv: moisture and density from discrete samples.</li> <li>MS_DataLITH.csv: magnetic susceptibility from the WRMSL.</li> <li>MSP_DataLITH.csv: point magnetic susceptibility from the Section Half Multisensor Core Logger (SHMSL).</li> <li>NGR_DataLITH.csv: natural gamma radiation from the Natural Gamma Radiation Logger (NGRL).</li> <li>PEN_DataLITH.csv: pocket penetrometer compressional strength measurements.</li> <li>PWB_DataLITH.csv: P-wave velocity from the bayonet system.</li> <li>PWC_DataLITH.csv: P-wave velocity from the caliper system.</li> <li>PWL_DataLITH.csv: P-wave velocity from the WRMSL.</li> <li>RGB_DataLITH.csv: Red-Green-Blue color from the Section Half Imaging Logger (SHIL).</li> <li>RSC_DataLITH.csv: reflectance spectroscopy from the SHMSL.</li> <li>SRA_DataLITH.csv: source rock analyzer measurements.</li> <li>SRM_DataLITH.csv: Superconducting Rock Magnetometer (SRM) measurements of split-core sections.</li> <li>SRMD_DataLITH.csv: SRM measurements of discrete samples.</li> <li>TCON_DataLITH.csv: thermal conductivity measured with the Teka Berlin TK04 probe.</li> <li>TOR_DataLITH.csv: Torvane shear strength measurements.</li> </ul> <p>Other compressed data folders contain multiple files used in creating the LILY database:</p> <p>RawDESC.zip: Contains 7,940 .csv files derived from the raw text content of the DESClogik Excel worksheets that was extracted, converted to comma separated value (.csv) format, and put into files with a consistent naming convention, without applying any corrections or conversions to the original text. Each file is the direct extraction of a tab from the DESC workbooks, available at <a href="https://web.iodp.tamu.edu/DESCReport/">https://web.iodp.tamu.edu/DESCReport/</a></p> <p>CoreSUMM.zip: Contains one file with Core Summary information, which includes the expedition, site, hole, core, coring type, top and bottom depths drilled, advances and recoveries, time and date of recovery, and the number of sections. These data are further paired with additional metadata (expanded core type, latitude, longitude, and water depth). Coordinates and water depth for each hole are derived from LIMS (and the JANUS database at <a href="http://www-odp.tamu.edu/database/">http://www-odp.tamu.edu/database/</a> for older expeditions).</p> <p>RawDATA.zip: Contains the raw track/discrete dataset downloaded by expedition from IODP LIMS database and placed in folders for each type of data (AVS, CARB, SRM, etc.) </p> <p>RawLITH.zip: Contains 42 .csv files, with one file for each expedition. Each file contains all lithologic description (prefix, principal and suffix, etc.) information for an entire expedition, as it was originally described. These have been transformed to a consistent format and paired with consistent identification information and additional metadata. Headers are normalized across all expeditions and SampleID information is standardized.</p> <p>CleanLITH: Contains 42 .csv files. Each file contains all lithologic description (prefix, principal and suffix) information for an entire expedition. The lithologic descriptions have been standardized to a consistent nomenclature using the dictionary given in Support Information Table S4 of Childress et al. (2024, <a href="https://doi.org/10.1029/2023GC011287">https://doi.org/10.1029/2023GC011287</a>). These data are further paired with additional metadata (e.g., degree of consolidation, expanded core type, latitude, longitude, and water depth).</p> <h2>GitHub Repository:</h2> <ul> <li>Contains a few notebooks to demonstrate how to work with the LILY database</li> <li><a href="https://github.com/IODP/LILY">IODP LILY GitHub Repository</a></li> </ul>
BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution
<p><strong>BigBrain-MR</strong> is a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI contrasts and properties that affect image generation. This phantom was generated from the publicly available <a href="https://bigbrainproject.org/">BigBrain histological dataset</a> and from lower-resolution in-vivo 7T-MRI data, using a new image processing framework that allows mapping the general properties of in-vivo data into the fine anatomical scale of BigBrain.</p> <p>The <strong>dataset</strong> includes:</p> <ul> <li>BigBrain original contrast and a new atlas with 20 ROIs;</li> <li>T<sub>1</sub>-weighted image and T<sub>1</sub> map;</li> <li>T<sub>2</sub>*-weighted images and R<sub>2</sub>* map;</li> <li>Magnetic susceptibility map (QSM);</li> <li>Background magnetic field map;</li> <li>Complex coil sensitivity maps (32ch-receive RF array);</li> <li>Bias field map.</li> </ul> <p>Information about each image/map (including data type and amplitude scaling) is provided in <em>data_info.txt</em>.</p> <p>Additionally, we have included a script with <strong>usage examples</strong> in Python that illustrate how the data can be loaded, processed and combined for diverse simulation purposes.</p> <p>BigBrain-MR is presented, described and tested in the following <strong>peer-reviewed article</strong>:</p> <p>C. Sainz Martinez, M. Bach Cuadra, J. Jorge. <em>BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development</em>. NeuroImage 2023. <strong>DOI:</strong> <a href="https://doi.org/10.1016/j.neuroimage.2023.120074">10.1016/j.neuroimage.2023.120074</a></p> <p> </p>
Magnetic properties and chemical analysis of remagnetised carbonates of South America
<p>We investigate the magnetic properties and chemical composition of remagnetised carbonate rocks in South America. These rocks play a crucial role in understanding past climates and the behaviour of Earth's magnetic field. Unfortunately, the primary remanence of these rocks is often altered by secondary components in a process known as remagnetisation. In South America, we observe evidence of a continent-wide remagnetisation event in Neoproterozoic carbonates from sedimentary basins separated by significant distances. To shed further light on this phenomenon, we employ both traditional macroscopic rock magnetic analysis and advanced synchrotron-based nano/micro imaging and chemical analysis techniques.</p>
Data_paper_Influence of buffer/protective layers on the structural and magnetic properties of SmCo films on Silicon
<p>Integration of Samarium Cobalt hard magnets on silicon requires buffer/protective layers that can enhance the magnetic properties of the magnet while preserving its structure and chemical composition after post-annealing treatments needed for the formation of the magnetically hard phase. In this work, a comparison of Samarium-Cobalt films for five different buffer/protective layers, namely Ti, W, TiW, Ta, Cr and two different annealing temperatures, 650°C and 750°C, is presented. Depending on materials and annealing temperatures, magnetic properties such as saturation and coercivity of the SmCo film can be finely tuned. We show that coercivity up to 3.65 T or saturation magnetization up to 0.95 T can be reached by proper choice of the relevant process parameters: deposition temperature, material for the buffer/protective layer and annealing temperature. Such value of coercivity is among the highest found in literature for thin films of SmCo.</p>
Numerical Calculation of the Thermodynamic Properties of Silver Erbium Alloys for Use in Metallic Magnetic Calorimeters - Data
<p>Data from simulations of the specific heat and magnetization of Ag:Er alloys. The parameter range we consider are temperatures between 1mK and 1K, external magnetic fields of up to 20mT, and erbium concentrations of up to 2000ppm.</p>
A Theoretical Window into the Wind Clumping Properties of Magnetic Hot Star Winds
<p>Winds from hot, massive OB stars are driven by scattering and absorption of the stellar radiation by spectral lines. The standard line-driven wind theory of CAK predicts a smooth, steady outflow but neglects a strong radiation instability, resulting in strong shocks and a highly structured, clumped wind. Treating clumping arising from this line-deshadowing instability (LDI) is of key importance in accurately interpreting observed spectral diagnostics of massive star winds. Indeed, if not correctly accounted for, such wind clumping may lead to quite dramatic errors in inferred mass-loss properties and to correspondingly large errors in massive-star evolution predictions. So far theory and observation of the LDI have only investigated wind clumping for non-magnetic OB stars. Meanwhile, quantitative wind clumping behaviour for magnetic massive stars has not been established. However, by now there is ample evidence from spectropolarimetric surveys that a subset of OB stars in our Galaxy possesses strong, global surface magnetic fields believed to be of primordial origin. This magnetic field leads to a quenching of mass loss and can significantly alter stellar evolution, with speculations that it may even lead to formation of high stellar mass black holes. Such mass-loss rates have up until now relied on smooth wind predictions, hence do not take into account the intrinsic clumpy structures. In this contribution I present the first results of 2D numerical simulations on magnetic LDI winds that self-consistently predict the wind clumping phenomenon. I show the possible pathways to structure formation and discuss this in light of our recently carried out analytical perturbation analysis. Finally, I discuss the resulting wind clumping properties and the possible effects on observational diagnostics.</p>
Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group
<p>Example datasets and code for the recommended implementation of Quantitative Susceptibility Mapping (QSM) in "Recommended Implementation of Quantitative Susceptibility Mapping for Clinical Research in The Brain: A Consensus of the ISMRM Electro-Magnetic Tissue Properties Study Group".</p>
Magnetic and sedimentologic properties of siliciclastic cave sediments from the Muierilor Cave (Romania)
<p>Rock-magnetic and sedimentologic data of the siliciclastic sediments from the Muierii Cave (Southern Carpathians, Romania). These data were published by Mirea et al. (2021), Last deglaciation flooding events in the Southern Carpathians as revealed<br> by the study of cave deposits from Muierilor Cave, Romania, Palaeogeography, Palaeoclimatology, Palaeoecology, 562,110084 (https://doi.org/10.1016/j.palaeo.2020.110084).</p>
Magnetic properties of siliciclastic sediments from the Zăton Lake
<p>Magnetic properties of siliciclastic sediments from the Zăton Lake ((Mehedinţi Plateau, South Carpathians, Romania; 44.972782° N, 22.75433° E, 343 m ).: paleomagnetic directions, magnetic susceptibility measured at two frequencies, anisotropy of magnetic susceptibility.</p>
Magnetic and sedimentological properties of siliciclastic cave sediments from the Peștera cu Oase Cave
<p>Magnetic and sedimentological properties of siliciclastic cave sediments from the Peștera cu Oase Cave (South Carpathians, Romania: 45.030009° N, 21.835320° E, 617 m). Further details can be found in Panaiotu et al. (2013).</p>
Low temperature magnetic properties of variably oxidized natural and synthetic siderite Dekkers et al., 2023, G-cubed
<p>The data magnetometric measurements performed on natural and synthetic iron carbonates presented in Dekkers et al. (2023) submitted to G-cubed. Details on the samples and methods can be found in the manuscript and the Additional Supporting Information</p> <p> </p>
Data for "Electronic and magnetic properties of single chalcogen vacancies in MoS2/Au(111)"
<p>Here, we provide the original data to the manuscript "Electronic and magnetic properties of single chalcogen vacancies in MoS2/Au(111)". We also provide the fits to the data, including fit parameters.</p>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - accompanying figures
<p>Differential isotropic shielding density isosurfaces (isovalues at +0.53 ppm (red) and -0.53 ppm (blue)) for XH2 - H2O systems X = Se, Te, Po (shield_dens_x_0_01.png) and Hb (shield_dens_h2_0_01.png), calculated as a difference between supermolecule shielding densities and the sum of subsystem shielding densities approximated as: (a) isolated fragments (b) FDE(4)[0] (c) FDE(4)[v] (d) FDE(4)[v+w_u] (e) FDE(4)[v+w_all]. Color of atoms: X (blue), O(red), H(grey).</p> <p> </p>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - supplementary information
<p>Supplementary information to the publication "On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework"</p> <p>The attached 'supplementary_info_fde_mag.zip' unpacks to three directories:</p> <ul> <li>'optimized_structures' directory contains optimized molecular structures in xyz format</li> <li>'results' directory contains all the results obtained in this work, collected in <ul> <li>gnumeric and xlsx spreadsheets with complete results from DIRAC and from ADF</li> <li>csv files (data involving heavy atoms, X, and hydrogen-bonded H atoms, Hb)</li> <li>'supplementary_tables' latex and pdf files</li> </ul> </li> <li>'visualization' directory contains the data for plotting the NMR shielding density and prepared plots; for the explanation of files in this directory open the 'visualization/visualization.html' document in your browser or read the corresponding jupyter notebook (visualization/visualization.ipynb')</li> </ul>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - supplementary information
<p>Supplementary information to the publication "On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework"</p> <p>The attached 'supplementary_info_fde_mag.tar.gz' unpacks to three directories:</p> <ul> <li>'optimized_structures' directory contains optimized molecular structures in xyz format</li> <li>'results' directory contains all the results obtained in this work, collected in <ul> <li>spreadsheets with complete results from DIRAC and from ADF (in *xlsx and *gnumeric format)</li> <li>csv files (data involving heavy atoms, X, and hydrogen-bonded H atoms, Hb obtained with DC and ZORA Hamiltonians and TZ-type basis sets)</li> <li>'supplementary_tables' latex and pdf files</li> </ul> </li> <li>'visualization' directory contains the data for plotting the NMR shielding density and prepared plots; for the explanation of files in this directory open the 'visualization/visualization.html' document in your browser or read the corresponding jupyter notebook (visualization/visualization.ipynb')</li> </ul>
Coseismic frictional heating with concomitant hydrothermal fluid circulation revealed by rock magnetic properties of fault rocks from the rupture of the 2008 Wenchuan earthquake, China
<p>This repository contains the rock magnetic data associated with the manuscript entitled "Coseismic frictional heating with concomitant hydrothermal fluid circulation revealed by rock magnetic properties of fault rocks from the rupture of the 2008 Wenchuan earthquake, China" by Yan et al. published in <i>Geochemistry, Geophysics, Geosystems, </i>24, e2023GC011223. https://doi.org/10.1029/2023GC011223</p>
Data for gravity and magnetic property inversion with tetrahedral grids
<p>These are the matlab code and data to analyzing the accuracy of gravity and magnetic property inversion with tetrahedral grids.</p>
Metadata - Exploring the Luminescence, Redox, and Magnetic Properties in a Multivariate Metal–Organic Radical Framework
Open the record for dataset details and reuse information.
Cubic, hexagonal and tetragonal FeGex phases (x = 1, 1.5, 2): Raman spectroscopy and magnetic properties
<p>Raw data associated to the manuscript “Cubic, hexagonal and tetragonal FeGe<sub>x</sub> phases (x = 1, 1.5, 2): Raman spectroscopy and magnetic properties", <em>CrystEngComm</em> 2021, XXXX, XXX, XXX-XXX</p> <p>Abstract:</p> <p>There is currently an emerging drive to computational materials design and fabrication of the predicted novel materials. One of the keys for developing appropriate fabrication methods is determination of the composition and phase. Here we explore the FeGe system and establish reference Raman signatures for the distinction between the FeGe hexagonal and cubic structures, as well as FeGe<sub>2</sub> and Fe<sub>2</sub>Ge<sub>3</sub> phases. The experimental results are substantiated by first principles lattice dynamics calculations as well as by complementary structural characterizations such as transmission electron microscopy and X-Ray diffraction, along with the magnetic measurements.</p>
ScienceDex guides
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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.