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1,041 results for “Spectroscopy”
IS471 - Decay spectroscopy data from the CRIS francium campaign 2014
<p>Decay spectroscopy data from the November 2014 campaign of the experiment IS471 on francium isotopes with the CRIS experimental setup at CERN ISOLDE.</p>
The APO-K2 Catalog. I. ~7,500 Red Giants with Fundamental Stellar Parameters from APOGEE DR17 Spectroscopy and K2-GAP Asteroseismology
<p><strong>Abstract: </strong>We present a catalog of fundamental stellar properties for ~7,500 evolved stars, including stellar radii and masses, determined from the combination of spectroscopic observations from the Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey IV (SDSS), and asteroseismology from K2. The resulting APO-K2 catalog provides spectroscopically derived temperatures and metallicities, asteroseismic global parameters, evolutionary states, and asteroseismically-derived masses and radii. Additionally, we include kinematic information from <em>Gaia</em>. We investigate the multi-dimensional space of abundance, stellar mass, and velocity with an eye toward applications in Galactic archaeology. The APO-K2 sample has a large population of low metallicity stars (~288 at [M/H] ≤ -1), and their asteroseismic masses are larger than astrophysical estimates. We argue that this may reflect offsets in the adopted fundamental temperature scale for metal-poor stars rather than metallicity-dependent issues with interpreting asteroseismic data. We characterize the kinematic properties of the population as a function of α-enhancement and position in the disk and identify those stars in the sample that are candidate components of the <em>Gaia-Enceladus</em> merger. Importantly, we characterize the selection function for the APO-K2 sample as a function of metallicity, radius, mass, νmax, color, and magnitude referencing Galactic simulations and target selection criteria to enable robust statistical inferences with the catalog.</p> <p><strong>Included Files:</strong></p> <ul> <li>The publicly available APO-K2 catalog, the is provided in the publication.</li> <li>The APO-K2 catalog without truncation to any numbers. </li> <li>The selection function relative density tables for the mass-radius parameter space. </li> <li>The selection function relative density tables for the metallicity-mass parameter space. </li> <li>The selection function relative density tables for the magnitude-color parameter space. </li> <li>The selection function relative density tables for the ν<sub>max</sub>-mag parameter space. </li> </ul>
Seasonal trends in leaf level physiological parameters, obtained through gas exchange, reflectance spectroscopy and, functional trait analysis
This data package contains leaf level gas exchange, reflectance spectroscopy, and functional trait measurements collected in six common deciduous tree species across the full 2021 growth season (May -October) at the Black Rock Forest in Cornwall, New York, USA. Branches were sampled predawn using the shotgun method of branch retrieval, and re-cut under water to preserve hydraulic function before transport to the lab. Gas exchange data included in this package are stomatal response curves (irradiance response) which can be used to estimate stomatal slope and intercept. Spectroscopic data are full-range (350 – 2500 nm) leaf reflectance spectra collected on all leaves sampled for gas exchange and traits. Leaf level trait measurements include leaf mass per area (LMA), leaf dry matter content (LDMC), elemental nitrogen and carbon expressed on a per mass basis, and fitted values of Asat, Vcmax, and Rdark scaled to a reference temperature of 25C. Data from these three data tables (stomatal responce, spectra, leaf traits) can be cross referenced using the unique SampleID. Additional data tables include stomatal anatomy (stomatal density, length, and width of the guard cells), hydraulic properties estimated from pressure volume curves (relative water deficit at the turgor loss point), and predawn water potential for all sampled branches. Site level data includes the dGPS location of each sampled tree, its species, and DBH. Each tabular data file (*.csv) is accompanied by a data description (*_dd.csv) which includes relevant metadata (unit, definition, data type). Copies of all raw instrument output (spectroradiometer, LICOR, pressure chamber) and included as .zip files.
Dataset used in manuscript Tailored Nanoscale Plasmon-Enhanced Vibrational Electron Spectroscopy
<p>This file contains the raw dataset used in the manuscript "Tailored Nanoscale Plasmon-Enhanced Vibrational Electron Spectroscopy" published in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659)</p> <p><br> Data has been acquired using Nion Swift (https://nionswift.readthedocs.io/en/stable/). Experimental details can be found in L. H. G. Tizei et al Nano Letters, 2020 (doi: 10.1021/acs.nanolett.9b04659).<br> <br> The dataset has been analyzed using the following Python libraries:</p> <p>Numpy, Scipy, Hyperspy, Matplotlib</p> <p>EELS hyperspectral images have been aligned using the Hyperspy "align1D" method. Aligned EELS hyperspectral images are saved in files finished with "_Aligned.hspy":</p> <p>For the strong coupling experiments:<br> Tip 1 is on hBN<br> Tip 2 is on vacuum</p> <p>For each of the nanowires tips, a file with the fitted coefficients are available, as well as a plot of the data and the fitted curve.</p> <p>Datasets have been fitted with gaussian and/or lorentizan functions, as described in the published text.</p> <p>Any question can be forwarded to the corresponding authors of the published text.</p> <p> </p>
Variability of OB stars from TESS southern Sectors 1-13 and high-resolution IACOB and OWN spectroscopy
<p>Typical MESA and GYRE inlists associated with <a href="https://arxiv.org/abs/2005.09658">Burssens et al. 2020</a>. MESA v. 12155, GYRE version v. 5.2.</p> <p><em>Context:</em> Lack of high-precision long-term continuous photometric data for large samples of stars has prevented the large-scale exploration of pulsational variability in the OB star regime. As a result, the candidates for in-depth asteroseismic modelling remained limited to a few tens of dwarfs. The TESS nominal space mission has surveyed the southern sky, including parts of the galactic plane, yielding continuous data of at least 27 d for hundreds of OB stars.<br> <em>Aims:</em> We aim to couple TESS data in the southern sky with ground-based spectroscopy to study the variability in two dimensions, mass and evolution. We focus mainly on the presence of coherent pulsation modes that may or may not be present in the predicted theoretical instability domains and unravel all frequency behaviour in the amplitude spectra of the TESS data.<br> <em>Methods: </em>We compose a sample of 98 OB-type stars observed by TESS in Sectors 1-13 and with available multi-epoch, high-resolution spectroscopy gathered by the IACOB and OWN surveys. We present the short-cadence 2-min light curves of dozens of OB-type stars, that have one or more spectra in the IACOB or OWN database. Based on these light curves and their Lomb-Scargle periodograms we perform variability classification and frequency analysis. We place the stars in the spectroscopic Hertzsprung-Russell diagram to interpret the variability in an evolutionary context.<br> <em>Results:</em> We deduce diverse origins of the mmag-level variability found in all of the 98 OB stars in the TESS data. We find among the sample several new variable stars, including three hybrid pulsators, three eclipsing binaries, high frequency modes in a Be star, and potential heat-driven pulsations in two Oe stars. <br> <em>Conclusions:</em> We identify stars for which future asteroseismic modelling is possible, provided mode identification is achieved. By comparing the position of the variables to theoretical instability strips we discuss the current shortcomings in non-adiabatic pulsation theory, and the distribution of pulsators in the upper Hertzsprung-Russell diagram.</p> <p> </p> <p> </p>
Data for: On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy
<p>Data for publication: T. Begusic, J. Vanicek, On-the-fly ab initio semiclassical evaluation of third-order response functions for two-dimensional electronic spectroscopy, <em>J. Chem. Phys.,</em> <strong>153</strong>, 184110 (2020).</p> <p>Contains simulated linear and two-dimensional spectra of the S<sub>1</sub> - S<sub>0</sub> electronic transition of phenol, excited-state and ground-state ab initio trajectories at the PBE0/6-311G(d,p) level of theory, and other supporting data related to the abovementioned publication.</p>
Time- and angle-resolved photoemission spectroscopy data and time-resolved X-ray diffraction data of TbTe3
<p>Time- and angle-resolved photoemission spectroscopy data of bulk terbium tritelluride (TbTe3, unidirectional charge-density-wave phase, T=100K) using a laser-based femtosecond XUV source and a hemispherical analyzer for photoelectron detection at the Fritz-Haber-Institute, Berlin, Germany. The 3D (angle, energy, pump-probe-delay) datasets include the photoemission intensities for various pump-laser fluences.</p> <p>The time-resolved X-ray diffraction data were obtained at the Femto hard X-ray slicing source at the Swiss Light Source, and include the charge-density-wave superlattice (2 10 1+q_CDW) peak intensities as functions of pump-probe-delay for various pump-laser fluences.</p> <p>The data and associated metadata are stored in the NeXus data format (https://www.nexusformat.org/).</p>
Reduced spectroscopy objects WDJ181417.84-735459.83 and VHS 472908521370
<p>Files Spec_WD1814-2011-LKR_XSHOOTER.txt, WDex_SCI_SLIT_FLUX_MERGE1D_UVB.fits and WDex_SCI_SLIT_FLUX_MERGE1D_VIS.fits are the .txt and .fits versions of the reduced X-SHOOTER spectrum of object WDJ181417.84-735459.83, observed under European Southern Observatory ESO programme 087.C$-$0639(B) in 2011, with PI Dr Avril Day-Jones. Files GaiaJ1814-7355_SCI_SLIT_FLUX_MERGE1D_UVB.fits, GaiaJ1814-7355_SCI_SLIT_FLUX_MERGE1D_VIS.fits, GaiaJ1814-7355_SCI_SLIT_FLUX_MERGE1D_UVB-1.fits and GaiaJ1814-7355_SCI_SLIT_FLUX_MERGE1D_VIS.fits-1 are the reduced X-SHOOTER spectra of the same object (two exposures taken) observed under ESO programme 0103.C-0431(B) in 2019, with PI Dr Siyi Xu. Spec_WD1814-2019-LKR_XSHOOTER.txt is the mean flux from the two exposures. The raw data of both spectra was processed by Laura Rogers.</p> <p>File Spec182-189A_xtc_FIRE.fits is the reduced spectrum of the object VHS 472908521370, observed with the Folded-port InfraRed Echellette (FIRE) at the Magellan Baade telescope, Las Campanas observatory, on the night of June 02 2019. The raw data was processed by Juan Carlos Beamin.</p> <p> </p> <p> </p> <p> </p> <p> </p>
Biochemical Characterization of Mouse Retina of an Alzheimer's Disease Model by Raman Spectroscopy
<p>Raman raw data for the paper "Biochemical Characterization of Mouse Retina of an Alzheimer’s Disease Model by Raman Spectroscopy"</p> <ul> <li>two datasets of Raman images from cross-sectional and en face mouse retinas without processing</li> </ul>
Computational atomic coordinate files for Quantification of Ni-N-O bond angles and NO activation by X-ray emission spectroscopy
<p>Geometry optimized coordinates and other atomic coordinate files in xyz format used to calculate X-ray emission spectra of beta-diketiminate nickel nitrosyl complexes.</p>
Research data supporting "Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy"
<p>Research data supporting the publication:</p> <p>M. Bergholt, 2017, Online quantitative monitoring of live cell engineered cartilage growth using diffuse fiber-optic Raman spectroscopy, Biomaterials, Volume 140, September 2017, Pages 128–137, DOI: 10.1016/j.biomaterials.2017.06.015</p>
Magellan/M2FS Spectroscopy of Galaxy Clusters: Stellar Population Model and Application to Abell 267
<p>supplementary data products, including all sky-subtracted spectra from individual galaxies, as well as random draws from posterior PDFs for model parameters (see included README file)</p>
High-resolution neutron spectroscopy of La1.855Sr0.145CuO4
<p>Data from a high-resolution neutron spectroscopy investigation of the low-energy incommensurate spin excitations in the high-temperature superconductor La1.855Sr0.145CuO4. The study was conducted using the IN5 time-of-flight neutron spectrometer at the Institut Laue-Langevin. The sample consisted of two crystals with a combined mass of 3.5 g and a superconducting transition temperature of 36 K. These crystals were prepared from a single rod grown via the traveling-solvent floating-zone method and aligned within a deviation of less than a degree. The lattice parameters are a = b = 3.81 Å and c = 13.2 Å, in the notation of the high-temperature tetragonal unit cell. Measurements were performed on the sample in a standard cryostat. Magnetic excitation spectra were acquired with a fixed sample orientation (b-axis perpendicular to the horizontal scattering plane) over 12 or 24 hours at various temperatures. Two distinct experimental configurations were utilized, employing incident wavelengths λ_i = 3.3 Å and 5 Å. The shorter wavelength was used to validate the magnitude of the superconducting spin gap (4 meV) at a base temperature of T = 2 K. The λ = 5 Å setup was employed to gather spectra at temperatures of T = 40, 30, 25, and 20 K, with an elastic full-width at half maximum resolution of ΔE = 80 μeV.</p>
The UltracoolSheet: Photometry, Astrometry, Spectroscopy, and Multiplicity for 4000+ Ultracool Dwarfs and Imaged Exoplanets
<p>The UltracoolSheet is a catalog of 4000+ ultracool dwarfs (spectral types M6 and later) and imaged exoplanets, including photometry, absolute astrometry, proper motions, parallaxes, multiplicity, spectroscopic classifications, memberships, and ages.</p> <p>The catalog lives in a Google spreadsheet at</p> <p> <a href="http://bit.ly/UltracoolSheet"><strong>http://bit.ly/UltracoolSheet</strong></a></p> <p>where it will receive future updates. The README tab in the spreadsheet contains a detailed description of the contents of the catalog.</p> <p>UltracoolSheet started as a catalog of all spectroscopically confirmed objects of spectral type L0 or later in the extended solar neighborhood (out to ~100 pc) that were known as of April 15, 2015. It has subsequently been extended to include many late-M dwarfs and also augmented with more recent discoveries spanning all ultracool spectral types.</p> <p>The component spreadsheets of UltracoolSheet are posted here as CSV files, along with summary figures and (.dat) files containing ASCII tables to simplify figure plotting for users. The Summary Plots.pdf file shows the sky map, age distribution, publication dates, and proper motion since publication for all objects in UltracoolSheet, as well as the distribution of projected separations of companions.</p> <p>When using data from the UltracoolSheet, please cite the individual papers from which the data comes. Citations codes are included for all the data in the tables, and the References table translates the citation codes into ADS bibcodes, Papers citekeys, and publication titles.</p> <p>For research that benefits from this compilation, please cite this Zenodo post and include the following acknowledgment:</p> <p>"This work has benefited from The UltracoolSheet at <a href="http://bit.ly/UltracoolSheet">http://bit.ly/UltracoolSheet</a>, maintained by Will Best, Trent Dupuy, Michael Liu, Aniket Sanghi, Rob Siverd, and Zhoujian Zhang, and developed from compilations by <a href="http://adsabs.harvard.edu/abs/2012ApJS..201...19D">Dupuy & Liu (2012)</a>, <a href="http://adsabs.harvard.edu/abs/2013Sci...341.1492D">Dupuy & Kraus (2013)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2014ApJ...792..119D/abstract">Deacon et al. (2014)</a>, <a href="http://adsabs.harvard.edu/abs/2016ApJ...833...96L">Liu et al. (2016)</a>, <a href="http://adsabs.harvard.edu/abs/2018ApJS..234....1B">Best et al. (2018)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2021AJ....161...42B/abstract">Best et al. (2021)</a>, <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...959...63S">Sanghi et al. (2023)</a>, and <a href="https://ui.adsabs.harvard.edu/abs/2023AJ....166..103S">Schneider et al. (2023)</a>."</p> <p>The UltracoolSheet itself can be cited by this Zenodo DOI: 10.5281/zenodo.4169084 </p> <p>Questions, comments, suggestions, or contributions?<br>Please send them to <a href="mailto:ultracool.sheet@gmail.com">ultracool.sheet@gmail.com</a> (especially contributions!)</p> <p> </p>
Catalyst sites and active species in the early stages of MTO conversion over cobalt AlPO-18 followed by IR spectroscopy
<p>Supplementary material: Ex-situ DR-UV-visible spectroscopy, Ex-situ FT-IR Spectroscopy. In-situ FT-IR Spectroscopy, In continuo FT-IR Spectroscopy, Brønsted acidity of SAPO-18 </p>
Dataset for paper "Multidetection scheme for transient-grating-based spectroscopy" by Brioschi M. et al.
<p>This dataset complements the publication "Multidetection scheme for transient-grating-based spectroscopy" by Brioschi M. et al.</p><p>The data hierarchy is explained in the file "Readme.docx", which also reports relevant metadata.</p>
Dataset related to the publication "Sub-Doppler optical-optical double-resonance spectroscopy using a cavity-enhanced frequency comb probe"
<p>The files contain </p><p>1. Binary files with normalized and interleaved double-resonance spectra recorded with three different pump transitions and two different relative pump-probe polarizations, indicated in the file name. These spectra are the results of 5 measurements.</p><p>2. Binary file with 45 normalized and interleaved double-resonance spectra recorded with pump on the R(2, <i>F2</i>) transition and parallel relative pump-probe polarization.</p><p>2. Data for Figures 4, S1 and S3 in the paper.</p><p> </p>
Data for: Raman microspectroscopy and laser-induced breakdown spectroscopy for the analysis of polyethylene microplastics in human soft tissues
<p>Data from Raman microspectrometry, LIBS, XRF, and particle sizer analysis supports the findings in the published article named Raman microspectroscopy and laser-induced breakdown spectroscopy to analyze polyethylene microplastics in human soft tissues. The aim of this research is to present the optimized protocol for the detection and analysis of microplastics in biological samples.</p> <p><strong> </strong></p> <p>The tonsil tissue is used for this experiment, and the workflow consists of a few steps: 1. digestion, 2. filtration, 3. analysis. </p> <p>The presented dataset includes the data for verifying the validity of this proposed protocol and the data from clinical experiments done on tonsils where the protocol is applied. We are focusing only on PE microplastics as they are one of the most frequent plastic types in the environment. </p> <p>Firstly, the data from the particle sizer show the size distribution before and after KOH treatment, which is necessary for digestion. We are testing if the particles are not affected by the KOH solution. The data are listed in an Excel sheet where the individual detected PE particle size [µm] and their frequencies [%] are annotated. The data are separated into 2 tables in one sheet - 1st represents data collected before KOH and the 2nd after KOH treatment. </p> <p>To test the limits of our selected systems for microplastic detection, we included the data from Raman and LIBS under the file ‘limitations.’ The different sizes of PE particles, from tens to 1 µm, were analyzed, and the spectra can be retrieved in the folders. The signal intensity can be observed to see the detection limits. For the Raman analysis, the particles were located on the filter. For LIBS, the particles were embedded in epoxy to enable the detection of PE particles in tens of microns. The Raman data are in .txt files and can be opened in any adequate software (Matlab, R, Python, etc.). LIBS data are in specific .libsdata format, which can be opened by LibsAnalyzer software by Lightigo. </p> <p><strong> </strong></p> <p>The clinical experiment was done on tonsil tissue. The tissue was disgusted and filtered. Then, the filters were analyzed. The dataset presents two sample groups: 1. control-native tissue and 2. test-spiked tissue with PE particles. The data from Raman analysis include both, with the aim to confirm the presence of PE particles in the test sample and to exclude the contamination in the control sample. The spectra are again in .txt files. In the case of control, spectra from unclassified particles are presented. For these reasons, the LIBS and XRF were run to exclude the possibility of the presence of polymeric material on the filter of the control sample. The analyzed chemical elements by LIBS for both samples are in the ASC file. Furthermore, individual PE particles were also analyzed on LIBS to obtain reference results for test samples with added PE microplastics. In the case of XRF, data from the empty filter, control, and test samples are included, each in a .txt file. Individual detected chemical elements and their intensities can be retrieved in the tables. </p> <p> </p>
Infrared Spectroscopy for Diagnosing Superlattice Minibands in Magic-angle Twisted Bilayer Graphene
Open the record for dataset details and reuse information.
Data from: Non-invasive estimation of absorbed ionizing radiation dose in mice using Near-Infrared Spectroscopy (NIRS) and aquaphotomics
<p>Accurate measurement of ionizing radiation exposure, whether therapeutic or accidental, is of utmost importance in various scenarios. This paper presents a study that addresses this critical need by utilizing near-infrared (NIR) spectroscopy and aquaphotomics to estimate radiation dose exposure in mouse models subjected to X-ray irradiation. The analysis of NIR spectra acquired from the mouse abdomen enabled non-invasive estimation of radiation doses ranging from 0.5 to 6.5 Gy, immediately following the irradiation exposure. The findings were consistent with the impact of total body irradiation in mice, as evidenced by measures such as animal survival rate, alterations in body weight observed over a 30-day post-exposure period, and changes in hematocrit levels. The spectroscopic measurements were based on detecting changes in the molecular structure of body water after radiation exposure, utilizing the water spectral pattern as a multidimensional biomarker. While further validation in nonhuman primates is necessary, the findings demonstrate a simple, non-destructive, and rapid method that holds promise for the estimation of radiation exposure across a range of doses, applicable to both clinical applications and catastrophic radiation events. These advancements in radiation dose quantification have significant implications for the timely and precise assessment of radiation exposure in humans.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.