Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
151
datasets available to search
ShareScore release 0.7.1
Dataset results
151 results for “optical properties”
Mineral spectral refractive index and bulk optical property dataset for aerosol studies
<p>Version 1.3, updated 11/15/2024.</p> <p>Added a file with 27 regional dust sample mineral composition information 'NewRegionalSamples.xlsx',</p> <p>along with the refractive index data.</p> <p>All refractive index files here have 127 rows (wavelengths) and 27 columns (samples)</p> <p>'kall27_coarse.dat' is the imaginary part of the coarse mode. </p> <p>'kall27_fine.dat' is the imaginary part of the fine mode.</p> <p>'nall27_coarse.dat' is the real part of the coarse mode.</p> <p>'nall27_fine.dat' is the real part of the fine mode.</p> <p>Version 1.2, updated 04/23/2024.<br>Major changes: <br>Changed all the data file names to new format: "mix"+{property name}+{number}, rearranged the number of mixing samples</p> <p>Updated all the bulk optical property data. This version use constant values of standard deviation in the lognormal size distribution settings for the coarse mode and the fine mode respectively.</p> <p>The phase matrices are separated from the other bulk properties due to their large file sizes. The readme file is updated correspondingly. The information of scattering angles (498 angles in total) is uploaded as "TAMUdust2020_Angle.dat".</p> <p>Added supplemental file data in 'Supplemental.tar.gz'.</p> <p>Additional refractive indices are zipped in 'AdditionalRefInd.tar.gz'</p> <p>Version 1.1, updated 03/14/2024.<br>Major changes: <br>Added mixed bulk properties for "0 (99%coarse+1%fine)" and "11 (2.0 µm coarse+ 0.4 µm fine)";<br>Added "reff.dat" in the 'BulkProperties.tar.gz'. The data include four columns: fine mode fraction, bulk projected area <A>, bulk volume <V>, effective radius r_eff. The information is for mixed sample number 0 to 11, each corresponds to one row.<br>Added refractive indices for chlorite, mica, smectite, pyroxene, vermiculite and pyroxenes. These groups can be applied in some other models.</p> <p>Version 1.0, uploaded 01/02/2024.</p> <p>This database include supplemental data and files for the publication of this paper:</p> <p>Sensitivities of Spectral Optical Properties of Dust Aerosols to their Mineralogical and Microphysical Properties. Yuheng Zhang, M. Saito, P. Yang, G. L. Schuster, and C. R. Trepte, J. Geophys. Res. Atmos. 2024.</p> <p> </p> <p>*****************************************</p> <p>The supplemental data include:</p> <p>1) 'GroupRefInd.tar.gz' Mineral (group) refractive index files.<br>E. g., 1All_Illite.dat contains the complex refractive index files of illite group. Format (from left to right columns): Wavelength (unit: µm), Real part (n), Imaginary part (k), standard deviation of n, standard deviation of k.</p> <p>The file 'fine_log.dat' includes the mean and standard deviation values of n and k for all the generated fine mode dust samples at 11,044 wavelengths from 0.2 to 50 micron.</p> <p>The file 'fine_log127.dat' only includes the values at 127 wavelengths from 0.2 to 50 micron (defined in 'swav.txt' and 'lwav.txt'), and is used for the bulk property computations.</p> <p>The files 'coarse_log.dat' and 'coarse_log127.dat' are for the coarse mode dust samples.</p> <p>2) 'CompositionFraction.xlsx': Mineral composition data sources/references and composition data (mean and standard deviation values of each group).<br>'Vlog_coarse.dat': Randomly generated VOLUME FRACTION of 9 mineral groups for the coarse mode dust. Left to right: Illite, Kaolinite, Montmorillonite (Other clays), Quartz, Feldspar, Carbonate, Gypsum (Sulphate), Hematite, Goethite.</p> <p>'Vlog_fine.dat': For the fine mode dust.</p> <p>3) 'RefSources.xlsx': The data source references of mineral refractive indices. We didn't include the olivine, other silicates, soot and titanium-rich minerals in the paper, but the refractive indices are available for those who are interested. Chlorite, Mica and Vermiculite group are mentioned in some studies, and we included the refractive indices for these minerals as well.</p> <p>4) 'DustSamples.tar.gz' Dust sample refractive index files.<br>The files are enclosed in four folders: fine_sw/ fine_lw/ coarse_sw/ coarse_lw/.</p> <p>fine: fine mode. coarse: coarse mode.</p> <p>'sw' means shortwave (< 4 µm, in total 76 wavelengths defined in 'swav.txt') while 'lw' means longwave (>= 4 µm, in total 51 wavelengths defined in 'lwav.txt').</p> <p>All files start with 'rdn', which means that they are computed based on randomly generated composition (data given in sheet 2 of 'CompositionFraction.xlsx').</p> <p>The four digit number after 'rdn' is the index of each dust sample. In total, there are 5,000 samples. The sample composition is the same for the same sample index in the same size mode (fine/coarse). Data file format (from left to right columns): real part, imaginary part.</p> <p>5) 'BulkProperties.tar.gz' Bulk property files (excluding phase matrices)<br>'mixqx.dat' files format (from left to right columns): Extinction efficiency (Qext), Scattering efficiency (Qsca), Backscattering efficiency (Qbck), and Asymmetry coefficient (Qasy). To obtain asymmetry factor, use Qasy/Qsca.</p> <p>'mixbkx.dat' files format (from left to right columns): P11(pi) P12(pi) P22(pi) P33(pi) P34(pi) P44(pi).</p> <p>'x' refers to the number at the end of the file name. It can be 100 ~ 112, each represents a setting of coarse and fine mode effective radius and volume fraction (see details in "reff.dat")</p> <p>'reff.dat' contains the effective radius information of the mixture. It has 7 columns: File number "x", Fine mode volume fraction, Fine mode effective radius (µm), Coarse mode effective radius (µm), Bulk projected area (µm^2), Bulk volume (µm^3), Bulk effective radius (µm).</p> <p>6) 'PhaseMatrices.tar.gz' Phase matrices data<br>'mixphswx.dat' files contain phase matrix results at 532 nm (shortwave). From left to right: P11, P12, P22, P33, P34, P44.</p> <p>'mixphlwx.dat' files contain phase matrix results at 10.5 µm (longwave).</p> <p>There are 635,000 rows in each data file. 635,000 rows = 127 wavelengths * 5,000 samples. Row 1~127 is sample 1, row 128~254 is sample 2, etc.. Suggest to use matlab function 'reshape(property, 127, 5000)' for each column when processing the data.</p> <p>7) 'Supplemental.tar.gz'</p> <p>We also include data files mentioned in the supplemental file of the paper. The adjusted source data files of the nine mineral groups are included.</p> <p>The supplemental bulk property files are named based on the figure number.</p> <p>8) 'AdditionalRefInd.tar.gz'</p> <p>We also include additional refractive indices for chlorite, smectite, vermiculite, mica, dolomite, titanium-rich minerals, pyroxenes and soot. These data can be useful in other models.</p> <p>For more detailed information and datasets, please contact: Yuheng Zhang, yuheng98@tamu.edu or yuhengz98@qq.com.</p>
Dissolved Organic Carbon Concentration, Dissolved Organic Matter Optical Properties, and Water Quality Indicators in the Plum Island Estuary (PIE), Massachusetts, USA (2018-2023)
This is a data set of paired in situ measurements of water quality parameters, total suspended solids concentration, and concentration and optical properties (absorption coefficient spectra and fluorescence indices) of dissolved organic matter (DOM) collected between 2018 and 2023 in the Plum Island Estuary and nearshore waters. In situ water quality measurements (salinity, temperature, optical dissolved oxygen saturation, turbidity, and dissolved organic matter fluorescence) were collected with a water quality sonde from the surface (top 1 m of water column), along with corresponding samples that were processed and analyzed in the lab for dissolved organic carbon (DOC) concentration, chromophoric DOM (CDOM), absorption coefficient spectra, DOM excitation-emission matrix (EEM) fluorescence, and total suspended sediment (TSS) concentration. The data were used in multiple studies (see manuscripts listed below) focusing on the dynamics of DOC and CDOM in the Plum Island Estuary.
Limnological data from nearly 400 lakes across the Americas and New Zealand with a focus on vertical profiles of temperature, UV radiation, and optical properties
Two and a half decades of limnological data have been collected from nearly 400 lakes, encompassing a wide range of systems and a broad range of geography. This data set comprises one of the largest and most complete sets of measurements of underwater ultraviolet (UV) transparency available in the world. The data include a suite of 36 variables, with a focus on the optical characteristics. Lakes range from pristine natural lakes to manmade reservoirs. The systems represented in this data set are largely located in North America, from the northeastern United States to Alaska, and alpine and subalpine lakes in the Rocky Mountains of the United States and Canada. Lakes included range from iconic Lake Tahoe, and Castle Lake in northern California, to lakes in the South American Patagonian region, as well as New Zealand. Data were most often collected during the summer, and in some lakes span multiple years (with year-round data since 2006 in Lake Tahoe). The data here are contained in four files, including LakeData.csv, SiteInformation.csv, Methods.csv, and Variables.csv. The main data are in LakeData.csv. SiteInformation.csv, Methods.csv, and Variables.csv support the main data file with descriptions of the sampling sites, methods by which samples were processed, and descriptions of the variables that were measured, respectively. This data set complements the site-intensive limnological data that we published in EDI on 30+ years of data from 3 lakes in the Poconos Mountains region of Pennsylvania, USA. This complementary data set can be accessed at https://portal.edirepository.org/nis/mapbrowse?scope=edi&identifier=186
RCSED - A Value-Added Reference Catalog of Spectral Energy Distributions of 800,299 Galaxies in 11 Ultraviolet, Optical, and Near-Infrared Bands: Morphologies, Colors, Ionized Gas and Stellar Populations Properties
<p>We present RCSED, the value-added Reference Catalog of Spectral Energy Distributions of galaxies, which contains homogenized spectrophotometric data for 800,299 low and intermediate redshift galaxies (0.007 < z < 0.6) selected from the Sloan Digital Sky Survey spectroscopic sample. Accessible from the Virtual Observatory (VO) and complemented with detailed information on galaxy properties obtained with the state-of-the-art data analysis, RCSED enables direct studies of galaxy formation and evolution during the last 5 Gyr. We provide tabulated color transformations for galaxies of different morphologies and luminosities and analytic expressions for the red sequence shape in different colors. RCSED comprises integrated k-corrected photometry in up-to 11 ultraviolet, optical, and near-infrared bands published by the GALEX, SDSS, and UKIDSS wide-field imaging surveys; results of the stellar population fitting of SDSS spectra including best-fitting templates, velocity dispersions, parameterized star formation histories, and stellar metallicities computed for instantaneous starburst and exponentially declining star formation models; parametric and non-parametric emission line fluxes and profiles; and gas phase metallicities. We link RCSED to the Galaxy Zoo morphological classification and galaxy bulge+disk decomposition results by Simard et al. We construct the color-magnitude, Faber-Jackson, mass-metallicity relations, compare them with the literature and discuss systematic errors of galaxy properties presented in our catalog. RCSED is accessible from the project web-site and via VO simple spectrum access and table access services using VO compliant applications. We describe several SQL query examples against the database. Finally, we briefly discuss existing and future scientific applications of RCSED and prospectives for the catalog extension to higher redshifts and different wavelengths.</p>
Forward-modelled reflectance from spring and summer Baltic Sea specific inherent optical properties
<p>An extensive dataset of remote-sensing reflectance (R<sub>rs</sub>, units sr<sup>-1</sup>) spectra based on forward modelling of mean concentration-specific inherent optical properties (SIOPs) for both spring and summer optical conditions in the open Baltic Sea. The spectra are modelled using Hydrolight 5.2 for a wide range of Chlorophyll-a (Chla), Coloured Dissolved Organic Matter (CDOM), and Total Suspended Matter (TSM) concentrations as well as solar and viewing angles. The primary aim of providing this supplementary dataset is to aid evaluation of remote sensing algorithms for the Baltic Sea in future studies.</p>
Optical properties of marine aerosols with varying water content at wavelengths 532 and 1064 nm, modelled with a morphologically realistic aerosol model
<p>The data contain computational results obtained with the ADDA program at wavelengths 532 nm and 1064 nm, for particle sizes 0.04, 0.06, ..., 1.5 micrometers (where size = volume-equivalent dry radius), and for salt mass fractions 0.91, 0.94, 0.97, 1.00. The content of the data files is described in the README file.</p>
Surface inherent optical properties and phytoplankton pigment concentrations from the Atlantic Meridional Transect (2009 - 2019): NetCDF format
<p>This dataset is a compilation of particulate inherent optical properties (IOPs) and co-incident high performance liquid chromatography (HPLC) phytoplankton pigment concentrations measured underway on nine Atlantic Meridional Transect (AMT) cruises. The time period of data collection is 2009 - 2019, between Sep-Nov within each year, with measurements collected between approximately 50 degrees South to 50 degrees North. A separate netCDF file is provided for each cruise (AMT 19, and AMT 22-29), including particulate IOPs (absorption, scattering, beam attenuation), pigment concentrations, and associated metadata.</p> <p>A manuscript containing a full description of the dataset, including associated code, will soon be submitted to Earth System Science Data. A Jupytper notebook illustrating data access is provided at: https://github.com/tjor/AMT_ACSpaperplots/blob/main/AMT_DataAccess.ipynb.</p> <p>The data are also released in SeaBASS format: https://seabass.gsfc.nasa.gov/archive/PML/AMT</p>
Development of a diffuse reflectance probe for in situ measurement of inherent optical properties in sea ice
<p>Included are the data presented in the publication entitled: <em>Development of a diffuse reflectance probe for in situ measurement of inherent optical properties in sea ice</em> accepted for publication in The Cryosphere Journal (2021). The data set includes Data and codes:</p> <p>1. Data (duplicated in .xlsx and .mat):</p> <p> </p> <p>1.1 Sites coordinates- (figure 5) -Geolocalisation of both sea ice sampling sites visited for this study (1 and 4)</p> <p> </p> <p>1.2 cumu_sg- (figure 6)- cumulative signal vs depth vs source-detector distance vs scattering coefficient obtained with Monte Carlo simulations</p> <p> —cumu_sg- cumulative signal (%)</p> <p> — depth (mm)</p> <p> —standard deviation on depth where signal is cumulated</p> <p> —ddet (mm)- radial distance between source and detection point </p> <p> — b (m^-1)-scattering coefficient</p> <p> </p> <p>1.3 validation-(figure 7)- Error on IOPs vs IOP value estimated measuring on microspheres solutions </p> <p> </p> <p>—vf (-)- microspheres volume fraction (in water)</p> <p> —a_theo (m^-1) - theoretical value of the absorption coefficient</p> <p> — mean_error_a(%) - error between theoretical value and measured value</p> <p> —std_error_a_x (%) - standard deviation on theoretical value (based on the standard deviation on microspheres diameter)</p> <p> —std_error_a_y (%) -standard deviation on error_a </p> <p> —rb_theo (m^-1) - theoretical value of the reduced scattering coefficient</p> <p> —mean_error_rb(%) - error between theoretical value and measured value</p> <p> —std_error_rb_x (%) - standard deviation on theoretical value (based on the standard deviation on microspheres diameter)</p> <p> —std_error_rb_y (%)) -standard deviation on error_rb </p> <p> —gamma_theo (-) - theoretical value of gamma</p> <p> —mean_error_gamma (%) - standard deviation on theoretical value (based on the standard deviation on microspheres diameter)</p> <p> —std_error_gamma (%) - standard deviation on error_gamma</p> <p> </p> <p>-1.4 T-S-(figure 8)- Vertical profiles of temperature and bulk salinity of sampled sea ice available at both snow covered site 1 and bare ice site 4</p> <p> </p> <p> —T (celsius) - ice temperature</p> <p> —S_si (ppt) - ice bulk salinity</p> <p> —depth (cm)</p> <p> </p> <p>1.5 Rmes-(figure 9)-Vertical profiles of spatially resolved diffuse Reflectance in sea ice using different covers to shade available at both snow covered site 1 and bare ice site 4</p> <p> </p> <p> —Rmes (-) - spatially resolved diffuse Reflectance</p> <p> —Rmes_nbg (-) - spatially resolved diffuse Reflectance with no background sunlight subtraction in calculation of Rmes</p> <p> —dmes (mm) - distance between source and detecting fibre (named rho in the paper)</p> <p> —depth (cm)</p> <p> — cover - cover used to shade from the sun: te=tent,nc= no cover, ta=tarp</p> <p> </p> <p>1.6 IOPprofiles-(figure 9)-Vertical profiles of reduced scattering coefficient in sea ice using different covers to shade available at both snow covered site 1 (ice+snow) and bare ice site 4</p> <p> </p> <p> —infferedrb (m^-1) - reduced scattering coefficient</p> <p> —infferedrb_nbg (m^-1) - reduced scattering coefficient with no background sunlight subtraction in calculation of Rmes</p> <p> —cr1 (binary)— criteria determining if the measurement is kept or not</p> <p> —depth (cm)- depth from the surface . **watch out** at site 1 , the measurments start from the surface of the snow. Substract 24 cm to get measurement from surface of the ice.</p> <p> — cover - cover used to shade from the sun: te=tent,nc= no cover, ta=tarp</p> <p> </p> <p>2. Code (written in .m with MATLAB_R2018b ®) :</p> <p> </p> <p>2.1 inversion algorithm—(figure 9 ) — used to find rb from Rmes (dmes) vertical profiles in sea ice</p> <p> </p> <p>— Main_vprofiles_Rtorb-qik2019_article.m - Main script of the inversion alorithm to get rb from Rmes (dmes)</p> <p>—importfiledata.m-subfunction to import data from .csv </p> <p>—importfiledatamay8.m-subfunction to import data from .csv (specific to may 8th because file was corrupted)</p> <p>—interp1lookup_HR_enlarged_bin10.mat - lookup table of Reflectance vs dmes vs a vs b’ vs gamma used in the inversion</p> <p>—calibjune6_ha_interp1_indcalib2.mat - calibration factor with microspheres as a reference</p> <p>—site1_c20-picture of the ice core taken at site 1</p> <p>—site4_c20-picture of the ice core taken at site 4</p> <p>—may8th+othertests_fixed.csv-raw data from may 8 (site1)</p> <p>—may9day3.csv-raw data from may 9 (site4)</p> <p> </p> <p> </p>
Dataset for the optical properties of tilted surfaces in material jetting
<p>Dataset for the optical properties of tilted surfaces in material jetting:</p> <p>Including dataset for gloss, haze, scattering, specular BRDF, reflectance, transmittance, and statistical analysis</p>
Boron-, carbon-, and silicon-bridged 1,12-dihydroxy-perylene bisimides with tuned structural and optical properties
<p>Additional data to report <a href="https://doi.org/10.1039/D3CC03704E">https://doi.org/10.1039/D3QO01389H</a></p> <p>Establishing suitable design strategies to tailor the functional properties of perylene bisimide (PBI) dyes are critical for their successful application in various devices. Herein, we report a new synthetic strategy to tune their structural and fluorescence properties by employing 1,12-bay-substitution pattern that has been seldomly investigated in the past. Central to the strategy is the use of 1,12-dihydroxy-PBI as a starting compound and the subsequent bridging of these hydroxy bay-functional groups with either a boron, carbon or silicon atom resulting in derivatives with rigidified perylene core. This is followed by a detailed exploration of synthetic possibilities to functionalize the unsubstituted 6,7-positions at the opposite bay area to achieve novel perylene dyes with excellent structural and optical properties. The fluorescence color could be tuned from green to dark-orange while retaining the almost unity fluorescence quantum yield in solution. Moreover, a strong fluorescence with quantum yields as high as 40% has been observed for powders, which clearly illustrates the potential of the presented structural design to obtain new solid-state emitters.</p>
Global scale leaf broadband optical properties derived from CliMA Land and associated CESM simulations
<p>Leaf level broadband reflectance and transmittance computed from leaf traits.</p> <ul> <li>clm_refl_tran_1m_weighted.nc: monthly data (144*96 pixels)</li> <li>surfdata_CMIP6_fluspect_v3.nc: surface data to run CESM (144*96 pixels)</li> </ul> <p>Global scale simulation results</p> <ul> <li>research_data_coupled_future_v2.nc: CESM coupled future simulations</li> <li>research_data_coupled_history_v2.nc: CESM coupled historical simulations</li> <li>research_data_uncoupled_history_v2.nc: CESM uncoupled future simulations</li> <li>research_data_uncoupled_ssp_v2.nc: CESM uncoupled SSP245 and SSP585 simulations</li> </ul> <p>Code changes</p> <ul> <li>SurfaceAlbedoMod.F90: modified CLM module</li> <li>Julia-and-Python-Code.tar.gz: code used for processing the data and plot the figures</li> </ul>
Measurement and simulation of optical properties of nanostructured silicon heavily implanted with selenium
<p><strong>Summary:</strong></p> <p>This is the collection of datasets used to plot the line art figures for the journal paper “Extended Infrared Absorption in Nanostructured Si Through Se Implantation and Flash Lamp Annealing”.</p> <p><strong>Methods:</strong></p> <p>The experimental and calculation methods for generating the datasets are described in the original paper and in the supplementary materials.</p> <p><strong>File Description:</strong></p> <ul> <li>The filenames for all files match the figure captions from the original paper and supplementary materials.</li> <li>Each file represents a specific plot, with all files provided in CSV format.</li> <li>Each column in the file represents a set of variable data.</li> <li>The datasets corresponding to each curve can be identified by comparing the first-row header information with the figure legend.</li> </ul> <p><strong>Credit:</strong></p> <p>When using the dataset/figures, please cite the original paper as: Radfar, B., Liu, X., Berencén, Y., Shaikh, M.S., Prucnal, S., Kentsch, U., Vähänissi, V., Zhou, S. and Savin, H. (2024), Extended Infrared Absorption in Nanostructured Si Through Se Implantation and Flash Lamp Annealing. Phys. Status Solidi A 2400133. <a title="https://doi.org/10.1002/pssa.202400133" href="https://doi.org/10.1002/pssa.202400133" target="_blank" rel="noreferrer noopener">https://doi.org/10.1002/pssa.202400133</a></p>
Optical properties of germania and titania at 1064nm and at 1550nm
<p>This dat accompanies the publication with the same title in the Classical and Quantum Gravity Focus Issue on low-noise thin-film coatings.</p> <ul> <li>The files named Comp_... contain the RBS results shown in Fig.1/Table 1.</li> <li>The transmission spectra files show the spectra as measured for all samples and heat treatment temperatures. The summary files show an overview of the fit results for refractive index and thickness at 1550nm resulting from fits using different optical models and the software SCOUT.</li> <li>There are two tables of absorption results: one shows a summary of the individual absorption results in ppm measured on various points on each sample; the second file shows a summary of the average absorption per sample and heat treatment step, the refractive index and thickness used, and the resulting extinction coefficient k. The extincion coefficient was calculated using the software tfcalc.</li> <li>The Raman files include the raw data for Raman measurements presented in the article. </li> </ul>
Dataset: Inferring Inherent Optical Properties of Sea Ice Using 360-Degree Camera Radiance Measurements
<p>New types of compact 360-degree cameras have recently appeared on the consumer technology market. Some of these allow users to access raw imagery, offering sensor-level data that can be directly exploited for absolute light quantification. This paves the way for easy-to-use, inexpensive and accessible radiance cameras that can be operated in a wide range of natural environments. </p> <p>This dataset presents the angular radiance distributions measured with the Insta360 ONE 360-degree camera in sea ice. We report vertical profiles of the light field structure at two sites reprensentative of distinct sea ice types: High Arctic multi-year ice and Chaleur Bay (Quebec, Canada) landfast first-year ice. </p> <p>This repository contains the radiometric data stored in <strong>Hierarchical Data Format (HDF5, h5)</strong> under the following names: </p> <ul> <li><strong><a href="https://zenodo.org/api/records/14263256/draft/files/oden-08312018-imf-fluo.h5/content" target="_blank" rel="noopener noreferrer">oden-08312018-imf-fluo.h5</a></strong></li> <li><strong><a href="https://zenodo.org/api/records/14263256/draft/files/baiedeschaleurs-03232022-imf-fluo.h5/content" target="_blank" rel="noopener noreferrer">baiedeschaleurs-03232022-imf-fluo.h5</a></strong></li> </ul> <p>The High Arctic dataset (<strong>oden-08312018-imf-fluo.h5</strong>) contains only one station, while the Chaleur Bay (<strong>baiedeschaleurs-03232022-imf-fluo.h5</strong>) has four that can be accessed using these tags: "station_1", "station_2", "station_3", "station_4". The radiance measurements at each depth are reported as 2-dimensionals arrays with the azimuth directions (0-359°, 1° resolution) as columns and the zenith directions (0-180°, 1° resolution) as lines. The routines (coded in python) for the data processing can be found in the following <a href="https://github.com/RaphaelLarouche/radiance_camera_insta360/tree/master_v01" target="_blank" rel="noopener">Github repository</a> (master_v01) or the <a href="https://zenodo.org/records/4660994" target="_blank" rel="noopener">Zenodo stored version</a>. </p> <p>The methodologies to carefully calibrated the 360-degree camera for radiometry purpose are described in this <a href="https://doi.org/10.1364/AO.524122" target="_blank" rel="noopener">pulibcation</a> and the raw calibration data can be found in this Zenodo <a href="https://zenodo.org/records/10278731" target="_blank" rel="noopener">repository</a>. </p> <p>Additionnal information on the fieldwork and the data analysis are described in the <a href="https://doi.org/10.31223/X5V955" target="_blank" rel="noopener">preprint</a>.</p>
Synthesis and characterization of CsPbCl3 perovskite doped with Nd3+: structural, optical, and energy transfer properties
<div> <p>The purpose of this paper is to synthesize micrometric inorganic perovskite CsPbCl3:Nd3+ and investigate the impact of doping with rare earth ions on structural and optical properties, as well as energy transfer pathways between the host and dopant. Herein, we report the solid-state reaction synthesis of a concentration series of CsPbCl3:x%Nd3+ annealed in a nitrogen atmosphere. Additional doping of a material that already exhibits luminescence with an optically active ion increases its application potential. Structural features were determined using X-ray powder diffraction and Raman spectroscopy. Morphology studies performed with scanning electron microscopy images revealed micrometric, well-separated cubic-like crystallites with a good distribution of individual elements. Surprisingly, a photoluminescence (PL) study showed that only the blue emission appears when the material is excited with a diode operating in the UV range. Apparently, the emission of Nd3+ ions can only be obtained with direct excitation of the lanthanide. The photoluminescence excitation (PLE) spectrum monitored for Nd3+ emission confirmed the lack of energy transfer between the host and dopant. Possible explanations for this behavior have been put forth and substantiated by the first-principles electronic structure calculations in the framework of hybrid density functional theory.</p> </div>
Chemical, optical, and oxidizing properties of three kinds of water-soluble organic matter in PM2.5 from biomass and coal combustion in rural areas in Northwest China
<p>this data set is about the molecular carbon content, light absorption, infrared spectra, and oxidation activity in PM2.5</p>
DataSet: Structural and optical properties of gold nanosponges revealed via 3D nano-reconstruction and phase-field models
<p>These are the main raw and processed data for the publication "Structural and optical properties of gold nanosponges revealed<br> via 3D nano-reconstruction and phasefield models".</p> <p>Abstract:<br> Nanoporous gold nanoparticles are subject of intensive research due to their unique morphology, which leads to electric field localizations generating a strongly nonlinear optical response, allowing a wide range of applications. However, accurate predictions of physical properties require detailed knowledge of the sponges’ chaotic nanometer-sized geometrical structures, posing a metrological challenge. Therefore, a main goal is to obtain computer models with equivalent structural and optical properties. To understand the sponges’ morphology, a procedure for their accurate three-dimensional reconstruction using focused ion beam tomography is presented. Next, a small number of morphological key parameters is derived that sufficiently characterize the complex topology. Additionally, a new simulation method for the computer-aided creation of finite-sized sponges with adjustable geometric properties is presented. It is shown that if certain morphological parameters are similar for computer-generated and experimental sponges, their optical response, including number and locations of field localizations, are also similar. Finally, the anisotropy of the experimental sponges is analyzed and an easy-to-use procedure to replicate arbitrary anisotropies in computer-generated sponges is presented.</p>
Laboratory validation of a smartphone-based sensor for diffuse optical volume properties
<p>This data set contains raw image data for laboratory validation of a diffuse-optical, smartphone-based sensor. The measurements were taken using scattering phantoms with known scattering and absorption coefficient. The raw image files have been converted to an uncompressed Adobe-.dng file format, file names indicate whether the file contains data for the three scattering phantoms (One, Two, Three) or spatial calibration data using a 9mm x 9mm calibration pattern (calib). The raw images are located in the folder ./calib. Matlab code is contained in the filder ./matlab. It can be run on Matlab R2021b.</p> <p>For analyzing the raw data set, use "CameraBatchCalib.m". It wraps around the function "CameraAnalysisCalib.m", which performs the image analysis and least-square fit to resorted and rescaled data, employing in turn the model function "theosurfG.m". The resulting data is plotted for comparison with the nominal attenuation length of the scattering phantoms.</p> <p>If you wish to use this data set please contact Markus Allgaier at markusa@uoregon.edu with a description of the work and any questions so that we may offer guidance in regards to the best usage of our dataset and code. When using the data set within a publication, please cite:</p> <p>Markus Allgaier & Brian Smith, "A Smartphone-Based Sensor for Measuring the Optical Properties of Snow", in preparation, (2022).</p> <p>The underlying fit function is based on the calculations from:</p> <p>Markus Allgaier and Smith, Diffuse optics for glaciology, Opt. Express 29, 18845–18864 (2021)</p> <p> </p>
Data and original code for: A generalized approach to characterise optical properties of natural objects
<p>To understand the diversity of ways in which natural materials interact with light, it is important to consider how their reflectance changes with the angle of illumination or viewing and to consider wavelengths beyond the visible. We chose a set of existing measurements and parameters that are generalisable to any wavelength range and spectral shape and we highlight which subsets of measures are relevant to different biological questions. As a case study, we applied these measures to 30 species of Christmas beetles. Here we provide the raw spectral data of angle integrated and angle-dependent reflection by the beetle elytra. We also provide the original code used for our analysis and figures.</p>
Optical Properties of MoO3 and MoO2
<p>Files conatining the dielectric function and refractive index of crystalline MoO3 and MoO2 obtained by spectroscopic ellipsometry.</p> <p>The files are structured as:</p> <p>eV nm Real(epsilon) Imag(epsilon) n k</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.