Find research datasets worth reusing

opencc-by-4.0Jul 2024View details →

A Novel Model Hierarchy Isolates the Limited Effect of Supercooled Liquid Cloud Optics on Infrared Radiation

This dataset contains data used in and resulting from an upcoming paper. For further detail on methodology and experiments, see that paper. <h2>Supercooled liquid water optics</h2> <h3>Complex refractive indices (CRIs)</h3> <ul> <li>Water_DW_300.txt</li> <li>water_RFN_240K.txt</li> <li>water_RFN_253K.txt</li> <li>water_RFN_263K.txt</li> <li>water_RFN_273K.txt</li> </ul> Water_DW_300.txt is sourced from Downing & Williams 1975 (https://doi.org/10.1029/JC080i012p01656). water_RFN_240K.txt, water_RFN_253K.txt, water_RFN_263K.txt, and water_RFN_273K.txt are sourced from Rowe et al. 2020 (https://doi.org/10.1029/2020JD032624). <h3>CESM lookup tables of liquid water optics</h3> <ul> <li>CESM_CRI_RFN_240K.nc</li> <li>CESM_CRI_RFN_253K.nc</li> <li>CESM_CRI_RFN_263K.nc</li> <li>CESM_CRI_RFN_273K.nc</li> </ul> These optics sets were created from the corresponding Rowe et al. 2020 CRI.   <h2>SCAM output</h2> History files for the four MPACE SCAM runs. <ul> <li>Control: tutorial.FSCAM.mpace.cam.h0.2004-10-05-07171.nc</li> <li>240K optics: cri240K_test.FSCAM.mpace.cam.h0.2004-10-05-07171.nc</li> <li>263K optics: cri263K_test.FSCAM.mpace.cam.h0.2004-10-05-07171.nc</li> <li>273K optics: cri273K_test.FSCAM.mpace.cam.h0.2004-10-05-07171.nc</li> </ul>   <h2>F1850_UVnudge1980 data</h2> Data used to create graphs shown in PAPER from the F1850_UVnudge1980 experiment. For each optics set there is a mean, count (n), and standard deviation file. These statistics are calculated over the 1 year of the model run and across all 10 ensemble members for the variable FLDS (downwelling longwave flux at the surface). Control optics: <ul> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul> 240K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri240K_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri240K_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri240K_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul> 263K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul> 273K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri273K_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri273K_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri273K_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul>   <h2>F1850_UVnudge1980-2018 data</h2> Data used to create graphs shown in PAPER from the F1850_UVnudge1980-2018 experiment. For the variable FLDS (downwelling longwave flux at the surface), each optics set has a mean, count (n), and standard deviation file. These statistics are calculated over the 39 years of the model run and across all 3 ensemble members.  Control optics: <ul> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge_long.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge_long.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test_nudge_long.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul> 263K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge_long.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge_long.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test_nudge_long.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul>   <h2>B1850_UVnudge1980 data</h2> Data used to create graphs shown in PAPER from the B1850_UVnudge1980 experiment. For each optics set there is a mean, count (n), and standard deviation file. These statistics are calculated over the 1 year of the model run and across all 10 ensemble members for the variable FLDS (downwelling longwave flux at the surface). Control optics: <ul> <li>b.e22.B1850.f09_g17.control_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>b.e22.B1850.f09_g17.control_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>b.e22.B1850.f09_g17.control_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul> 263K optics: <ul> <li>b.e22.B1850.f09_g17.cri263K_test_nudge.FLDS.avg.Mean.All_data.non_filtered.nc</li> <li>b.e22.B1850.f09_g17.cri263K_test_nudge.FLDS.n.Mean.All_data.non_filtered.nc</li> <li>b.e22.B1850.f09_g17.cri263K_test_nudge.FLDS.std.Mean.All_data.non_filtered.nc</li> </ul>   <h2>F1850 data</h2> Data used to create graphs shown in PAPER from the F1850 experiment. For each optics run there is a mean, count (n), and standard deviation file. These statistics are calculated over the 40 years of the model run for the variable FLDS (downwelling longwave flux at the surface). Control optics: <ul> <li>f.e22.F1850.f09_f09_mg17.control_test.FLDS.avg.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test.FLDS.n.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.control_test.FLDS.std.All_data.non_filtered.nc</li> </ul> 240K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri240K_test.FLDS.avg.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri240K_test.FLDS.n.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri240K_test.FLDS.std.All_data.non_filtered.nc</li> </ul> 263K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri263K_test.FLDS.avg.All_data.non_filtered.nc </li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test.FLDS.n.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri263K_test.FLDS.std.All_data.non_filtered.nc</li> </ul> 273K optics: <ul> <li>f.e22.F1850.f09_f09_mg17.cri273K_test.FLDS.avg.All_data.non_filtered.nc </li> <li>f.e22.F1850.f09_f09_mg17.cri273K_test.FLDS.n.All_data.non_filtered.nc</li> <li>f.e22.F1850.f09_f09_mg17.cri273K_test.FLDS.std.All_data.non_filtered.nc</li> </ul>

opencc-by-4.0Oct 2023View details →

All-Optical Data Processing with Photon-Avalanching Nanocrystalline Photonic Synapse

<h2>Abstract</h2>Data processing and storage in electronic devices are typically performed as a sequence of elementary binary operations. Alternative approaches, such as neuromorphic or reservoir computing, are rapidly gaining interest where data processing is relatively slow, but can be performed in a more comprehensive way or massively in parallel, like in neuronal circuits. Here, time-domain all-optical information processing capabilities of photon-avalanching (PA) nanoparticles at room temperature are discovered. Demonstrated functionality resembles properties found in neuronal synapses, such as: paired-pulse facilitation and short-term internal memory, in situ plasticity, multiple inputs processing, and all-or-nothing threshold response. The PA-memory-like behavior shows capability of machine-learning-algorithm-free feature extraction and further recognition of 2D patterns with simple 2 input artificial neural network. Additionally, high nonlinearity of luminescence intensity in response to photoexcitation mimics and enhances spike-timing-dependent plasticity that is coherent in nature with the way a sound source is localized in animal neuronal circuits. Not only are yet unexplored fundamental properties of photon-avalanche luminescence kinetics studied, but this approach, combined with recent achievements in photonics, light confinement and guiding, promises all-optical data processing, control, adaptive responsivity, and storage on photonic chips.

Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities

Dataset for publication Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities

Ultrafast laser-induced magneto-optical changes in resonant magnetic x-ray reflectivity

Datasets for the publication "Ultrafast laser-induced magneto-optical changes in resonant magnetic x-ray reflectivity", published in Physical Review B 108, 054439 (2023).

Polymer Electrolyte Membrane Water Electrolyzer Oxygen Bubble Evolution Optical Video Recording For Deep Learning-Enhanced Characterization of Bubble Dynamics in Proton Exchange Membrane Water Electrolyzer by André Colliard-Granero, Keusra A. Gompou, Christian Rodenbücher, Kourosh Malek, Michael H. Eikerling, and Mohammad J. Eslamibidgoli

Dataset used for the training of the segmentation model employed in the work "Deep Learning-Enhanced Characterization of Bubble Dynamics in Proton Exchange Membrane Water Electrolyzer" by André Colliard-Granero, Keusra A. Gompou, Christian Rodenbücher, Kourosh Malek, Michael H. Eikerling, and Mohammad J. Eslamibidgoli. This dataset consists in 35 images and the corresponding manual annotated masks of diverse bubbly scenarios extracted from the optical video recording of a PEMWE with a transparent flow field.

Dataset related to the publication "Sub-Doppler optical-optical double-resonance spectroscopy using a cavity-enhanced frequency comb probe"

The files contain 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.2. Binary file with 45 normalized and interleaved double-resonance spectra recorded with pump on the R(2, F2) transition and parallel relative pump-probe polarization.2. Data for Figures 4, S1 and S3 in the paper.

opencc-by-nc-nd-4.0May 2024View details →

Measurement and simulation of optical properties of nanostructured silicon heavily implanted with selenium

Summary: 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”. Methods: The experimental and calculation methods for generating the datasets are described in the original paper and in the supplementary materials. File Description: <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> Credit: 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>

Optical properties of germania and titania at 1064nm and at 1550nm

This dat accompanies the publication with the same title in the Classical and Quantum Gravity Focus Issue on low-noise thin-film coatings. <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>

Accompanying dataset for: "IBEX: A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues"

Mouse datasets were acquired using the manual IBEX multiplex imaging protocol and accompany the manuscript “IBEX: A versatile multiplex optical imaging approach for deep phenotyping and spatial analysis of cells in complex tissues”, A. Radtke et al., 2020, PNAS. All image data are stored using the <a href="https://imaris.oxinst.com/support/imaris-file-format">Imaris file format</a>. To view these multi-channel images, you can either use one of these free viewers, <a href="https://imaris.oxinst.com/imaris-viewer">Imaris viewer</a>, <a href="https://imagej.net/Fiji">Fiji</a>. Each experiment has an associated imaging meta-data file in xlsx format and the resulting image in Imaris format. Mouse spleen (Manual) Dataset is a 16 parameter IBEX experiment performed on a mouse spleen section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse thymus (Manual) Dataset is a 26 parameter IBEX experiment performed on a mouse thymus section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse lung (Manual) Dataset is a 23 parameter IBEX experiment performed on a mouse lung section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.379 µm), y (0.379 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse small intestine (Manual) Dataset is a 20 parameter IBEX experiment performed on a mouse small intestine section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse liver (Manual) Dataset is an 18 parameter IBEX experiment performed on a liver section from a LysM-tdtomato reporter mouse labeled with antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse naive lymph node (Manual) Dataset is a 41 parameter IBEX experiment performed on a mouse lymph node section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976). Mouse immunized lymph node (Manual) Dataset is a 41 parameter IBEX experiment performed on a mouse lymph node section labeled with the nuclear marker JOJO-1 and antibodies directed against the indicated markers. Images were acquired using an inverted Leica TCS SP8 X confocal microscope equipped with a 40X objective (NA 1.3), 4 HyD and 1 PMT detectors, a white light laser that produces a continuous spectral output between 470 and 670 nm as well as 405, 685, and 730 nm lasers. All images were captured at an 8-bit depth, with a line average of 3, and 1024x1024 format with the following pixel dimensions: x (0.284 µm), y (0.284 µm), and z (1 µm). Images were tiled and merged using the LAS X Navigator software (LAS X 3.5.5.19976).

opencc-by-4.0Apr 2024View details →

Investigations on single and multi-grain optically stimulated luminescence (OSL) sensitivity and electron spin resonance (ESR) signals in quartz derived from sandstones: Insights on provenance of quartz in ancient depositional systems

Trapped charge techniques of luminescence and electron spin resonance (ESR) are classic tools for dating Quaternary deposits. Over the past decade, these techniques have been routinely applied to investigate provenance and /or the sedimentary history of grains based on the different luminescence and ESR characteristics of quartz. Of these, optically stimulated luminescence (OSL) sensitivity is one of the most widely investigated parameter for luminescence-based provenance approach. A majority of studies on this parameter are based on evaluation of multi-grain OSL sensitivity of the samples. This is particularly concerning because single-grain quartz luminescence studies have shown that the luminescence signal of a multi-grain aliquot is contributed by less than ~1-10% of the total grains. Since the sole criteria for discrimination of sources based on luminescence sensitivity relies on its intensity, therefore the results based on multi-grain analysis will most likely be skewed depending on the proportion and ‘brightness’ of a few grains. This demands a need to evaluate the potential of single-grain quartz OSL sensitivity in provenance studies. In this study, we investigate single and multi-grain quartz OSL sensitivities from compositionally different sandstones with well-characterised sources based on U-Pb zircon ages. We further complement this analysis with characterisation of ESR centres commonly used in quartz provenance, namely E’1 and [AlO4]0 centres. Our study shows that single-grain quartz OSL sensitivity can help distinguish between sediments that have a predominant input from a single source as compared to those with contribution from multiple sources, which otherwise cannot be inferred from multi-grain studies. Moreover, our results on characterisation of quartz-based ESR intensity of E’1 and saturated [AlO4]0 centres successfully differentiates between sandstones and further complements the luminescence-based characterisation.

Source code and simulation results: Efficient rational approximation of optical response functions with the AAA algorithm

This publication provides data published in the article "Efficient rational approximation of optical response functions with the AAA algorithm" [1] in tabulated form along with the Matlab scripts that have been used to produce them. These scripts interface the finite element method solver JCMsuite [2,3]. The article presents rational approximations of optical response functions based on an extended version of the AAA algorithm [4] that allows to efficiently reconstruct sensitivty spectra and gives access to sensitivities of poles, residues, and zeros. Furthermore, the rational approximation of a scalar observalbe is used to construct solutions of the source free Maxwell's equation, i.e., a nonlinear eigenvalue problem.  The physical Structure The example is based on the chiral metasurface introduced in [5]. For the sake of simplicity we added infinite layers of SiO\(_2\) to the top and the bottom of the structure. The original structure has a SiO\(_2\) substrate and a layer of PMMA polymethyl methacrylate (PMMA)  deposited on top. PMMA can be modelled with the same refractive index of 1.45 as SiO\(_2\). Furthermore, our simulations include the 13 nm indium tin oxide (ITO) coating which drastically reduces the Q-factor as it is slightly absorbing. The accuracy of the discrete model is verified by assessing reflection, transmission, and absorption at 241 evenly spaced points within the specified range. Energy conservation requires that the discrepancy between their sum and the energy entering the system is zero. The numerical discretization is chosen such that the maximum relative error is less than \(3\times10^{−5}\). Dispersion Tabulated data for ITO has been taken from the <a href="https://refractiveindex.info/?shelf=other&book=In2O3-SnO2&page=Konig">refractiveindex.info</a> database (T. A. F. König et al., 2014, https://doi.org/10.1021/nn501601e) and the data for TiO2 was kindly provided the authors of [5]. The permittivity \(\varepsilon = (n+ik)^2\) is locally approximated as a rational function, i.e., only data in a vicinity of the frequency range of interest is considered. As we aim for a function with the symmetry \(f^\ast(\omega) = f(-\omega^\ast)\) we add the complex conjugated data at negative frequencies and enforce the symmetry in a second step. The partial fraction decomposition of the required function is of the form: \(\varepsilon(\omega) = \varepsilon_\infty + \sum_{j=1}^{4}a_j/(\omega-\omega_j) - a_j^\ast/(\omega+\omega_j^\ast)\) with the residues \(a_j\) and the poles \(\omega_j\). We expect 4 pairs of poles to sufficiently approximate the data within the range of interest (4 with positive and 4 with negative real parts). <h4>Requirements</h4> <ul> <li>JCMsuite (at least 6.2.0)</li> <li>MATLAB (tested with version R2023b)</li> </ul> In order to run the simulations with JCMsuite you must replace corresponding place holders with a path to your installation of JCMsuite. Free trial licenses are available, please refer to the homepage of <a href="https://jcmwave.com/">JCMwave</a>. Usage With the content of 'spectra.zip' you can reproduce results presented in the paper. Running the script 'plots.m' will not start any expensive simulation but use the provided data. With 'dispersion.m' the fits to the material data can be reproduced. Additionally, tabulated data is contained in 'data/ascii'. The archive 'eigenmodes.zip' must be extracted in the same directory as 'spectra.zip'. References [1] Fridtjof Betz, Martin Hammerschmidt, Lin Zschiedrich, Sven Burger, Felix Binkowski: Efficient rational approximation of optical response functions with the AAA algorithm, https://doi.org/10.48550/arXiv.2403.19404. [2] Jan Pomplun, Sven Burger, Lin Zschiedrich, Frank Schmidt, Adaptive finite element method for simulation of optical nano structures, Physica Status Solidi B 244, 3419 (2007), http://dx.doi.org/10.1002/pssb.200743192. [3] Fridtjof Betz, Felix Binkowski, Sven Burger, RPExpand: Software for Riesz projection expansion of resonance phenomena, SoftwareX 15, 100763 (2021), https://doi.org/10.1016/j.softx.2021.100763. [4] Y. Nakatsukasa, O. Sète, and L. N. Trefethen, The AAA Algorithm for Rational Approximation, SIAM Journal on Scientific Computing 40, A1494 (2018), http://dx.doi.org/10.1137/16M1106122. [5]  X. Zhang, Y. Liu, J. Han, Y. Kivshar, and Q. Song, Chiral emission from resonant metasurfaces, Science 377, 1215 (2022), http://dx.doi.org/%2010.1126/science.abq7870.

opencc-by-4.0Jul 2021View details →

Solution-processed PbS quantum dot infrared laser with room-temperature tuneable emission in the optical telecommunications window - Open Data

This is a supplementary upload attached to the paper titled "Solution-processed PbS quantum dot infrared laser with room-temperature tuneable emission in the optical telecommunications window" 10.1038/s41566-021-00878-9. Figures All figure data from the publication can be obtained from the original MATLAB .fig files. If one does not have access to MATLAB the figures can be opened using the open source software GNU Octave. FDFD Simulation Also in the upload is the original matlab code used to perform the simulations presented in the paper. "FDFD_2D_Ez_Hz_DFB_laser_UPLOAD" - Variable gain FDFD solver is uploaded as .mat and .pdf files. To run the code the functions "Dgen" and "gen2xDFB" are required and the .mat files containing the refractive indices "PbS1520" and "Al2O3". Parameters to vary can be found in the "DASHBOARD" section of the code. The uploaded code solves for the out-of-plane electric field (Ez Mode).

opencc-by-sa-4.0Nov 2024View details →

refering rawdata and code of "Ultrahigh-throughput single-pixel complex-field microscopy with frequency-comb acousto-optic coherent encoding (FACE)"

Corresponding raw data and codes that produce all relative video and imaging results for real-time monitoring the physicochemical phenomena of microfluidics, microorganism's group, and chemical reactions, supporting and verifying the research article "Ultrahigh-throughput single-pixel complex-field microscopy with frequency-comb acousto-optic coherent encoding (FACE)".

opencc-by-4.0Dec 2024View details →

Dataset of the publication: Interplay between optical emission and magnetism in the van der Waals magnetic semiconductor CrSBr in the two-dimensional limit

Dataset of the publication: Interplay between optical emission and magnetism in the van der Waals magnetic semiconductor CrSBr in the two-dimensional limit DOI: 10.1021/acsnano.3c00375 F. Marques-Moros, C. Boix-Constant, S. Mañas-Valero, J. Canet-Ferrer, E. Coronado ACS Nano, 17, 14, 13224-13231 (2023)

opencc-by-4.0Dec 2024View details →

Dataset: Inferring Inherent Optical Properties of Sea Ice Using 360-Degree Camera Radiance Measurements

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.  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.  This repository contains the radiometric data stored in Hierarchical Data Format (HDF5, h5) under the following names:  <ul> <li><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></li> <li><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></li> </ul> The High Arctic dataset (oden-08312018-imf-fluo.h5) contains only one station, while the Chaleur Bay (baiedeschaleurs-03232022-imf-fluo.h5) 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>.   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>.  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>.

Data and code associated with "Fourier synthesis optical diffraction tomography for kilohertz rate volumetric imaging"

Imaging data and derived analysis data used in the figures of the manuscript "Fourier synthesis optical diffraction tomography for kilohertz rate volumetric imaging"

opencc-by-4.0Aug 2023View details →

Synthesis and characterization of CsPbCl3 perovskite doped with Nd3+: structural, optical, and energy transfer properties

<div> 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. </div>

opencc-by-4.0Oct 2021View details →

Data for: "High-resolution Soil Moisture Evolution in Hyper-arid Regions: A Comparison of InSAR, SAR, Microwave, Optical, and Data Assimilation Systems in the southern Arabian Peninsula"

Data accompanying the publication: High-resolution Soil Moisture Evolution in Hyper-arid Regions: A Comparison of InSAR, SAR, Microwave, Optical, and Data Assimilation Systems in the southern Arabian Peninsula. For filenames starting with T: Exponential fit parameters time0 and mag0 for InSAR coherence data. they are binary files, where fit  = a*exp(-b*x); a = -log(mag0); b = 1/time0. timeerr contains the uncertainty of the time0 parameter, and maghigh/maglow contain the high and low uncertainty for the mag0 parameter, respectively.  For for each frame or overlap region (T101, T28, T130, T28_T101, T130_T28), there is a vrt file (T..._20180524.time0.vrt), which is the metadata file applicable to all files of the same frame. Files starting with mags_times: Exponential fit parameters for ASCAT/SMAP/GLDAS data. the same parameters (time0, timeerr, mag0, maghigh, maglow) can be found in these matlab structure files. In addition, the .mat files contain the offset parameter and related uncertainty, as well as lat/lon information.