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569 results for “spectrometer”
A MEMBRANE INLET LASER SPECTROMETER FOR IN SITU MEASUREMENT OF TRIPLE WATER ISOTOPOLOGUES
<p>This dataset contains laboratory test results characterizing the performance of a new instrument designed for in situ measurement of water isotopes. The system combines Optical Feedback Cavity-Enhanced Absorption Spectroscopy (OFCEAS) with a dual inlet pervaporation system. </p>
Magnetic Field Boundaries in Cassini Plasma Spectrometer Data
<p>This dataset consists of:</p> <ul> <li><em>get_files.sh</em> - a bash script to download ELS data (.DAT and .LBL) files.</li> <li><em>crossing_events_urls.txt</em> - a text file containing URLs for each of the ELS<br> data files. <em>get_files.sh</em> reads this file directly.</li> <li><em>crossing_events.txt</em> - a text file containing the list of crossing events<br> with associated data, obtained by processing Table S1 in [1].</li> <li><em>labels.zip</em> - a zip file containing directory with events for each DAT file,<br> in YAML format.</li> <li><em>plotter.py</em> - a plotting script in Python.</li> <li><em>requirements.txt</em> - a file indicating dependencies for the plotting script.</li> </ul> <p><strong>Data</strong></p> <p>This dataset spans 1259 observations from CAPS ELS, each with a .LBL file and a<br> .DAT file. Together, these take 128 GB of space. To download these files, do:</p> <pre>./get_files.sh</pre> <p>in a Bash shell/terminal. The files are stored in the 'data/' folder (created if<br> not present) in the current directory.</p> <p>ELS data files are obtained from NASA's Planetary Data System at<br> <a href="https://pds-ppi.igpp.ucla.edu/search/view/?f=yes&id=pds://PPI/CO-E_J_S_SW-CAPS-3-CALIBRATED-V1.0/DATA/CALIBRATED">https://pds-ppi.igpp.ucla.edu/search/view/?f=yes&id=pds://PPI/CO-E_J_S_SW-CAPS-3-CALIBRATED-V1.0/DATA/CALIBRATED</a></p> <p>For help in understanding the ELS data files, see the CAPS User Guide at<br> <a href="https://pds-ppi.igpp.ucla.edu/ditdos/download?id=pds://PPI/COCAPS_1SAT/DOCUMENT/CAPS_USER_GUIDE/CAPS_PDS_USER_GUIDE_V1_00.PDF">https://pds-ppi.igpp.ucla.edu/ditdos/download?id=pds://PPI/COCAPS_1SAT/DOCUMENT/CAPS_USER_GUIDE/CAPS_PDS_USER_GUIDE_V1_00.PDF</a>.</p> <p><strong>Labels</strong></p> <p>Unzipping the <em>labels.zip</em> file will create a <em>labels/</em> folder in the current<br> directory, requiring 28MB of space.</p> <p>Within <em>labels/</em>:</p> <ul> <li><em>bs/</em> - includes bow shock crossing events.</li> <li><em>mp/</em> - includes magnetopause crossing events.</li> <li><em>dg/</em> - includes known data-gap events. See [1].</li> <li><em>sc/</em> - includes unreliable data events. See [1].</li> <li><em>valid/</em> - union of all files in <em>bs/</em> and <em>mp/</em>.</li> <li><em>all/</em> - union of all files in <em>bs/</em>, <em>mp/</em>, <em>dg/</em> and <em>sc/</em>.</li> </ul> <p>Within the <em>labels/bs/</em> and <em>labels/mp/</em> folders:</p> <ul> <li><em>in/</em> - crossing events with the transition direction as inward.</li> <li><em>out/</em> - crossing events with the transition direction as outward.</li> <li><em>all/</em> - union of all files in in/ and out/.</li> </ul> <p>Each label file is a YAML file containing a 'change_points' field. The entries<br> under this field each indicate the time of a transition event. The other fields<br> ('bimodality' and 'negative_ions') are not relevant for this dataset.</p> <p><strong>Plotting the Data (and Labels)</strong></p> <p>To help visualize the data and labels, we supply a plotting script<br> <em>plotter.py</em>, in Python (version 2.7). First, install dependencies with:</p> <pre>pip install -r requirements.txt</pre> <p>and then run:</p> <pre>./plotter.py -h</pre> <p>to see the available options. Example usage (after downloading data and<br> unzipping labels):</p> <pre>./plotter.py data/ELS_200418018_V01.DAT -l labels/mp/all/ELS_200418018_V01.yaml --interpolated -f max_filter -fsize 100 --title "An Observation from CAPS ELS" </pre> <p>will open up a new window with a plot of the data.<br> To directly save to a file, use the '-o <em>savefilename</em>' option. For example,</p> <pre>./plotter.py data/ELS_200418018_V01.DAT -l labels/mp/all/ELS_200418018_V01.yaml --interpolated -f max_filter -fsize 100 --title "An Observation from CAPS ELS" -o ELS_200418018_V01.png </pre> <p><strong>References</strong></p> <p>[1] Jackman, C. M., Thomsen, M. F., & Dougherty, M. K. (2019). Survey of<br> Saturn's magnetopause and bow shock positions over the entire Cassini mission:<br> Boundary statistical properties and exploration of associated upstream<br> conditions. Journal of Geophysical Research: Space Physics, 124, 8865– 8883.<br> <a href="https://doi.org/10.1029/2019JA026628">https://doi.org/10.1029/2019JA026628</a></p> <p>The original table of magnetopause and bow shock crossing events can be found at<br> <a href="https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1029%2F2019JA026628&file=jgra55251-sup-0001-Table_SI-S01.txt">https://agupubs.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1029%2F2019JA026628&file=jgra55251-sup-0001-Table_SI-S01.txt</a></p> <p><strong>Grants</strong></p> <ul> <li>NASA Contract through JPL with South West Research Institute. Grant Number: 1243218</li> <li>Science and Technology Facilities Council. Grant Number: ST/L004399/1</li> <li>NASA. Grant Number: 1243218</li> <li>Diamond Jubilee Fellowship</li> <li>STFC. Grant Number: ST/L004399/1</li> </ul>
1H NMR Data of Commercial Honey Analysed by 400 and 700 MHz Spectrometers
<p>Datasets (*.xlsx) contain the 1H NMR Raw (.fid) and Binning data (.xlsx) of commercial honey analysed using 400 MHz and 700 MHz NMR spectrometers</p>
Dataset for the refractory aerosol thermal desorption mass spectrometer (rTDMS)
<p>A particle mass spectrometer to quantify non-refractory and refractory aerosols (referred to as refractory aerosol thermal desorption mass spectrometer: rTDMS) has been developed. The combination of a graphite particle collector and a carbon dioxide laser enables high desorption temperature. Ion signals originating from evolved gas molecules are detected by a quadrupole mass spectrometer.</p>
Data from: Non-Adiabatic Acceleration of Injected Electrons in the Inner Magnetosphere: Joint Observations by the Van Allen Probe and the BeiDa Imaging Electron Spectrometer
<p>The dataset is associated with the study entitled "Non-adiabatic acceleration of injected electrons in the inner magnetosphere: Joint observations by the Van Allen Probe and the BeiDa Imaging Electron Spectrometer"</p> <p>The file includes directional electron flux data obtained by the BeiDa Imaging Electron Spectrometer and follows NASA's Common Data Format (CDF).</p>
Dataset for "Characterization of a modified printed optical particle spectrometer for high-frequency and high-precision laboratory and field measurements."
<p><strong>The folder includes scripts and data to create figures in the manuscript titled "Characterization of a modified printed optical particle spectrometer for high-frequency and high-precision laboratory and field measurements."</strong></p>
Nonlinear self calibrated spectrometer with single GeSe-InSe heterojunction device
<p>Computational spectrometry is an emerging field that employs photodetection in conjunction with numerical algorithms for spectroscopic measurements. Compact single photodetectors made from layered materials are particularly attractive since they eliminate the need for bulky mechanical and optical components used in traditional spectrometers and can easily be engineered as heterostructures to optimize device performance. However, such photodetectors are typically nonlinear devices, which adds complexity to extracting optical spectra from their response. Here, we train an artificial neural network (ANN) to recover the full nonlinear spectral photoresponse of a single GeSe-InSe p-n heterojunction device. The device has a spectral range of 400-1100 nm, a small footprint of ~25×25 〖μm〗^2, and a mean reconstruction error of 〖2×10〗^(-4) for the power spectrum at 0.35 nm. Using our device, we demonstrate a solution to metamerism, an apparent matching of colors with different power spectral distributions, which is a fundamental problem in optical imaging.</p>
Data set: A solid-state high harmonic generation spectrometer with cryogenic cooling
<p>Solid-state high harmonic generation (sHHG) spectroscopy is a promising technique for studying electronic structure, symmetry, and dynamics in condensed matter systems. Here, we report on the implementation of an advanced sHHG spectrometer based on a vacuum chamber and closed-cycle helium cryostat. Using an in situ temperature probe, it is demonstrated that the sample interaction region retains cryogenic temperature during the application of high-intensity femtosecond laser pulses that generate high harmonics. The presented implementation opens the door for temperature-dependent sHHG measurements down to a few Kelvin, which makes sHHG spectroscopy a new tool for studying phases of matter that emerge at low temperatures, which is particularly interesting for highly correlated materials.</p>
LIBS-wallscanner dataset related to "Scanning laser-induced breakdown spectrometer for mine walls" thesis
<p>This is a LIBS dataset published alongside the thesis in related identifiers. For better description see the thesis publication.</p>
Dataset for "Constraining the response factors of an extractive electrospray ionization mass spectrometer for near-molecular aerosol speciation"
<p>Online characterization of aerosol composition at the near-molecular level is key to understanding chemical reaction mechanisms, kinetics, and sources under various atmospheric conditions. The recently developed extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF) is capable of detecting a wide range of organic oxidation products in the particle phase in real time with minimal fragmentation. Quantification can sometimes be hindered by a lack of available commercial standards for aerosol constituents, however. Good correlations between the EESI-TOF and other aerosol speciation techniques have been reported, though no attempts have yet been made to parameterize the EESI-TOF response factor for different chemical species. Here, we report the first parameterization of the EESI-TOF response factor for secondary organic aerosol (SOA) at the near-molecular level based on their elemental composition. SOA was formed by ozonolysis of monoterpenes or OH-oxidation of aromatics inside an oxidation flow reactor (OFR) using ammonium nitrate as seed particles. A Vocus proton-transfer reaction mass spectrometer (Vocus-PTR) and a high-resolution aerosol mass spectrometer (AMS) were used to determine the gas phase molecular composition and the particle phase bulk chemical composition, respectively. The EESI response factors towards bulk SOA coating and the inorganic seed particle core were constrained by intercomparison with the AMS. The highest bulk EESI response factor was observed for SOA produced from 1,3,5-trimethylbenzene, followed by those produced from <em>d</em>-limonene and <em>o</em>-cresol, consistent with previous findings. The near-molecular EESI response factors were derived from intercomparisons with Vocus-PTR measurements, and were found to vary from 10<sup>3</sup> to 10<sup>6</sup> ions s<sup>-1</sup> ppb<sup>-1</sup>, mostly within ±1 order of magnitude of their geometric mean of 10<sup>4.6</sup> ions s<sup>-1</sup> ppb<sup>-1</sup>. For aromatic SOA components, the EESI response factors correlated with molecular weight and oxygen content, and inversely correlated with volatility. The near-molecular response factors mostly agreed within a factor of 20 for isomers observed across the aromatics and biogenic systems. Parameterization of the near-molecular response factors based on the measured elemental formulae could reproduce the empirically determined response factor for a single VOC system to within a factor of 5 for the configuration of our mass spectrometers. The results demonstrate that standard-free quantification using EESI-TOF is possible. </p>
Arecibo Observatory Ebert Fastie Spectrometer data (Feb-Apr 2005)
<p>The raw nightglow scan files obtained with the Ebert Fastie Spectrometer (EFS) operated from the Arecibo Observatory (AO) and rotational temperatures derived from these raw data files are available here. Here only those raw data files are available which were not affected by the haze condition or clouds.</p> <p>The naming convention of the raw EFS data files is: "sp"-yyyymmdd-hhmmss-hhmmssLT ;</p> <p>where, sp stands for spectrometer. The first and second time mention the start and end time of the scan. LT stands for local time which represent the Atlantic Standard Time (AST). The first header file in the data mentions which airglow emission has been recorded whenever it is available. The second header file contains 12 numbers. They convey the following details of the scan. 1) Date (ddmmyy); 2) Start Time of Scan (AST); 3) End Time of Scan (AST); 4) Number of data points in a scan; 5) Start Step Position in Scan; 6) End Step Position in Scan; 7) Delta Step of scan; 8) Number of Summed Records; 9) Integration Time per Data Point in seconds; 10) Azimuth angle (deg); 11) Elevation angle (deg); 12) A code (3 denotes the Sky)</p> <p>The remaining numbers in the raw data file denotes nightglow intensity counts for each data points.</p> <p>The naming convention of the rotational temperature files is: "EFS rotational temperature-",yyyymmdd.</p> <p>The file header in the rotational temperature files describe the contents of these files. The times shown in the first column is the average of the start and end time of a raw data scan. Error denotes uncertainties in the rotational temperature estimation in degree Kelvin.The Chi-square fit coefficients denote goodness of the linear fit in the Boltzmann plot. Rotational temperatures are estimated from the slope of this linear fit.</p>
Data Set to doi.org/10.3390/app13042747 "Robot Assisted THz Imaging with a Time Domain Spectrometer"
<p>Data set to article "Robot Assisted THz Imaging with a Time Domain Spectrometer" in Applied Sciences 2023, 13, 2747.</p>
Dataset for paper "X-ray spectra emitted by electronic brachytherapy unit Papillon 50 measured with CdTe spectrometer"
<p>This dataset contains:</p> <p>1) raw ".mca" files with pulse-height spectra of Papillon 50 unit obtained with X-123CdTe spectrometer.<br> 2) Unfolded photon fluence spectra.</p> <p>The dataset related to the paper "X-ray spectra emitted by electronic brachytherapy unit Papillon 50 measured with CdTe spectrometer."</p>
Data for "Upgrade of the MARI spectrometer at ISIS"
<p>This file contains Python and Matlab scripts to reproduce the figures in the paper "Upgrade of the MARI spectrometer at ISIS", as well as the experimental raw data and McStas calculations used in the figures.</p>
Data from: Optimal control pulses for the 1.2 GHz (28.2 T) NMR spectrometers
<p>The ability to measure NMR spectra with a large sample volume is crucial for concentration limited biological samples in order to attain adequate signal-to-noise (S/N) ratio. The possibility to measure with a 5 mm cryoprobe is currently absent at the 1.2 GHz NMR instruments due to the exceedingly high radio frequency power demands, which is four times compared to a 600 MHz instruments. Here, we overcome the high power demands by designing optimal control (OC) pulses with up to 20 times lower power requirements than currently necessary at a 1.2 GHz spectrometer. We show that multidimensional biomolecular <span>NMR experiments constructed using these OC pulses can bestow improvement in the S/N ratio of up to 26%. With the expected power limitations of a 5 mm cryoprobe, we observe an enhancement in the S/N ratio of more than 240% using our OC sequences. This motivates the development of a cryoprobe with a larger volume than the current 3 mm cryoprobes. </span></p>
Data set: A solid-state high harmonic generation spectrometer with cryogenic cooling
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Nonlinear self calibrated spectrometer with single GeSe-InSe heterojunction device
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Data from: Optimal control pulses for the 1.2 GHz (28.2 T) NMR spectrometers
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A sensitive method for atmospheric sulfur dioxide determination by reaction cell inductively coupled plasma mass spectrometer
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DREP and micro-burst events measured with the Compton Spectrometer and Imager COSI
<p>The Compton Spectrometer and Imager, COSI, is a Compton telescope operating in the 0.2-5 MeV energy range and capable of imaging, spectroscopy and polarimetry of astrophysical sources. Such capabilities are made possible by COSI's twelve germanium cross-strip detectors, which provide for high efficiency, high resolution spectroscopy, and precise 3D positioning of photon interactions. This directory gathers the heliophysics data observed during the 2016 COSI balloon flight. In May 2016, COSI took flight from Wanaka, New Zealand, on a NASA super-pressure balloon. For 46 days, COSI floated at a nominal altitude of 33.5 km, continually telemetering science data in real-time. The payload made a safe landingin Peru, and the hard drives containing the full raw data set were recovered.<br> <br> The following files are included in this directory:</p> <p>megalib_v3.02.zip:<br> All the software (MEGAlib) to analyze this data</p> <p>massmodel.tar.gz:<br> The COSI-2016 mass model to analyze this data</p> <p>COSI2016_GeD_L3EventList_DREP_20160521_v04.fits.gz:<br> A level 3 event list from May 21th 2016 containing a multi-peak DREP event.</p> <p>COSI2016_GeD_L3EventList_DREP_20160530_v04.fits.gz<br> A level 3 event list from May 30th 2016 containing 2 DREP complexes and a micro-burst event.<br> <br> <br> The latest version of the data analysis software can be found here:<br> https://github.com/zoglauer/megalib.git<br> Documentation on how to use the software can be found in the "doc" directory of MEGAlib, especially in the file Mimrec.pdf. Before usage with MEGAlib, the data needs to be converted into MEGAlib's tra file format, for example:<br> <br> TraFitsConverter -f COSI2016_GeD_L3EventList_DREP_20160530_v04.fits.gz -g COSI.DetectorHead.geo.setup<br> <br> The mass model files "COSI.DetectorHead.geo.setup" can be found in the massmodel.zip file.<br> <br> </p>
ScienceDex guides
Understand access before you commit
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.