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149 results for “nanostructures”
Dataset for "Methodology for fast testing of carbon-based nanostructured 3D electrodes in vanadium redox flow battery"
<p>Here, we describe a technique for integrating carbon-based rod-like nanomaterials into a vanadium redox flow battery and a methodology for fast nanomaterial performance testing. The technique is based on creating a fixed nanomaterial bed sandwiched between two graphite felt electrodes, forming a 3D flow-through electrode in the battery. Performing various positive and negative control experiments, we show the beneficial effect of a nanostructured bed on the primary battery characteristics obtained from short-term electrochemical experiments. We then characterize carbon nanotubes exhibiting promising electrochemical behavior in vanadium electrolytes, as observed in our previous study. The load curves obtained from charge-discharge steps at various current densities and electrolyte flow rates revealed considerable differences in the performance of the tested materials, with few-walled carbon nanotubes reaching unsurpassable characteristics. Although developed for vanadium redox flow batteries, the method enables testing tube-like and rod-like (nano-)materials as electrodes for other flow battery systems. </p>
Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices
<p>This dataset corresponds to the following manuscript: </p> <p>Zendrini, M., Dubrovskii, V., Rudra, A., Dede, D., Fontcuberta i Morral, A., Piazza, V. “Nucleation-Limited Kinetics of GaAs Nanostructures Grown by Selective Area Epitaxy: Implications for Shape Engineering in Optoelectronics Devices” <em>ACS Applied Nano Materials 7,16 (2024):</em> 19065–19074</p> <p>DOI: <a href="http://doi.org/10.1021/acsanm.4c02765">doi.org/10.1021/acsanm.4c02765</a></p> <p>The dataset contains raw SEM images in .tif format for all the arrays of nanowires and nanomembranes discussed in the paper. The dataset also contains the AFM scans in .xyz format for all the arrays of nanowires and nanomembranes. The data for the morphological analysis are extracted from the SEM images and the AFM scans and they are collected in two separate .txt files for NWs and NMs.</p>
Hybrid Metrology for Nanostructured Optical Metasurfaces - Dataset
<p>This is the dataset of "Hybrid Metrology for Nanostructured Optical Metasurfaces", https://doi.org/10.1021/acsami.3c13923. </p>
Nanostructured La0.75Sr0.25Cr0.5Mn0.5O3–Ce0.8Sm0.2O2 Heterointerfaces as All-Ceramic Functional Layers for Solid Oxide Fuel Cell Applications
<p>Dataset for article "Nanostructured La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub>–Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2</sub> Heterointerfaces as All-Ceramic Functional Layers for Solid Oxide Fuel Cell Applications" published in <em>ACS Appl. Mater. Interfaces</em> 2022.</p> <p>The data includes:</p> <ul> <li>Schematic on the nanostructures fabricated for the work (Figure 1)</li> <li>Top view AFM images of the nanostructures studied (Figure 3)</li> <li>TEM-EDX images of the nanostructures studied (Figure 4)</li> <li>ASTAR analysis of the nanostructures studied (Figure 5)</li> <li>X-Ray Diffraction data of thin films with composition: La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub> (LSCrMn), Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2</sub> (SDC), and two La<sub>0.75</sub>Sr<sub>0.25</sub>Cr<sub>0.5</sub>Mn<sub>0.5</sub>O<sub>3</sub>–Ce<sub>0.8</sub>Sm<sub>0.2</sub>O<sub>2 </sub>(LSCrMn-SDC) nanostructures -bilayer (BL) and nanocomposite (NC)-</li> <li>Electrochemical Impedance Spectroscopy raw data for LSCrMn, SDC and LSCrMn-SDC thin films measured under air and wet hydrogen atmospheres at different temperatures (630-750 ºC)</li> <li>Arrhenius analysis of the area specific resistance (ASR) of the films under air and hydrogen atmospheres</li> <li>In-plane conductivity evolution with temperature data measured under air and 5% hydrogen atmospheres of the two LSCrMn-SDC nanostructures</li> <li>ASR evolution with time measured for over 400 h at 780 ºC</li> </ul>
data for Tunable magnonic crystal in a hybrid superconductor–ferrimagnet nanostructure
<h3><strong>General description</strong></h3> <p>The data set designed for the reconstruction of the graphs identified in the manuscript as Fig. 2, Fig. 4 and Fig. 6 has been compiled. The data were respectively described as <strong>calculations</strong> relating to the method of obtaining the data (Brandt's method then plane wave method - PWM) and <strong>simulations</strong> (finite element method - FEM). </p> <h3><strong>Fig. 2</strong></h3> <p>In the case of Fig. 2(a-f), the data marked with a black solid line have been included. The data set includes information on the (x,y) components of the magnetic field induction generated by the superconductor (expressed in millitesla) in the x-direction (expressed in metres). </p> <h3><strong>Fig. 4</strong></h3> <p>The data set for each subsection of Fig. 4 comprises the results of the simulations and calculations. The resulting data from the simulations are classified according to their respective modes. For each mod, the wave vector (expressed as part of the first Brillouin zone) and frequency (GHz) are determined. The data sets resulting from the semi-analytical calculations comprise the common axis (1st column) of the wave vector (expressed as part of the Brillouin zone) followed by columns containing frequency for each mode (GHz).</p> <p> </p> <h3><strong>Fig. 6</strong></h3> <p>The data pertaining to the subsections of Fig. 6(a) and (b) are stored in a separate set of files. The data set for Fig. 6a comprises frequencies that indicate the boundaries of bands in relation to the external magnetic field (B_{0}). Each column has been assigned a number. The numbering is from the lowest frequencies to the highest for k_{x}=0. Each line is comprised of two columns, the first of which describes the magnetic field induction (expressed in millitesla) and the second of which describes the frequency (expressed in GHz). <br>Subsection (b) contains the dependence of the band boundaries (frequencies) on the separation between superconductors (d). The lines are also numbered from lowest frequency to highest for k_{x}=0. Each line is described by two columns, named by a number. The first column is the separation (expressed in nanometres), and the second is the frequency (expressed in GHz). </p>
Dataset for Enhancing stimulated Brillouin scattering in suspended silicon waveguides through subwavelength nanostructuration [Invited]
<p>This dataset contains the raw data for the figures (Fig. 2, Fig. 5, and Fig. 7) in the publication entitled "Enhancing stimulated Brillouin scattering in suspended silicon waveguides through subwavelength nanostructuration" published by Optical Materials Express (DOI: 10.1364/OME.534474). Datafiles are in .txt format.</p> <p>All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript.</p>
Raw and analyzed data for manuscript: "Wood surface ablation and nanostructuring using a femtosecond laser"
<p><strong>Abstract</strong></p> <p>The processing of Norway spruce and European beech wood specimens by means of femtosecond laser pulses was investigated on conditioned natural samples as well as on samples coated with beeswax or a water-borne stain. Depending on laser pulse energies and processing times, this allowed for different modes of surface modification. At low laser intensities, an etching almost without thermal impact was detected, whereas higher laser intensities led to the generation of hierarchical micro and nanostructures. The usage of argon or atmospheric air as cover gases during the laser processing had only minor effects on the surface structures. Observed differences in the etching or functionalization of the wooden surfaces mostly originated in the chemical structure of the surface finish and the physical properties of the wood substrates, such as the density or moisture content.</p>
Supplementary files for "Influence of the Artificial Nanostructure on the LiF Formation at the Solid−Electrolyte Interphase of Carbon-Based Anodes"
<p>Databases containing DFT optimized structures used for the paper: ''Influence of the Artificial Nanostructure on the LiF Formation at the Solid−Electrolyte Interphase of Carbon-Based Anodes". For further details of the computational setup we refer to this paper.</p> <p>Each database contains structures for one carbon substrate. The structures can be retrieved using the Atomic Simulation Environment (ASE).</p>
Single-Step Generation of 1D FeCo Nanostructures
<p>This DOI address contains data regarding the manuscript entitled "Single-Step Generation of 1D FeCo Nanostructures", published in IOP Nano Express (2024) (Paper DOI: 10.1088/2632-959X/ad3e1c).</p> <p>Authors: Mehran Sedrpooshan,a,b Pau Ternero,a,c Claudiu Bulbucan,d Adam M. Burke,a,c Maria E. Messing,a,b,c Rasmus</p> <p>Westerström,a,b</p> <p>a NanoLund, Lund University, Box 118, 221 00 Lund, Sweden</p> <p>b Synchrotron Radiation Research, Lund University, Box 118, 221 00 Lund, Sweden</p> <p>c Solid State Physics, Lund University, Box 118, 221 00 Lund, Sweden</p> <p>d MAX IV Laboratory, Lund University, Lund, SE-22100, Sweden</p> <p> </p> <p>- This DOI contains separate figures from the manuscript</p> <p>- Data of the hysteresis loops</p> <p>- Data of the XAS and XMCD plots</p>
Dataset for "Skyrmion states in thin confined polygonal nanostructures"
<p>This dataset provides micromagnetic simulation data collected from a series of computational experiments on the effects of polygonal system shape on the energy of different magnetic states in FeGe. The data here form the results of the study ‘Skyrmion states in thin confined polygonal nanostructures.’</p> <p>The dataset is split into several directories:</p> <p><strong>Data</strong></p> <p><em>square-samples and triangle-samples</em></p> <p>These directories contain final state ‘relaxed’ magnetization fields for square and triangle samples respectively. The files within are organised into directories such that a sample of side length d = 40nm and which was subjected to an applied field of 500mT is labelled d40b500. Within each directory are twelve VTK unstructured grid format files (with file extension “.vtu”). These can be viewed in a variety of programmes; as of the time of writing we recommend either ParaView or MayaVi. The twelve files correspond to twelve simulations for each sample simulated, corresponding to twelve states from which each sample was relaxed - these are described in the paper which this dataset accompanies, but we note the labels are:</p> <p>‘0’, ‘1’, ‘2’, ‘3’, ‘4’, ‘h’, ‘u’, ‘r1’, ‘r2’, ‘r3’, ‘h2’, ‘h3’</p> <p>where:</p> <ul> <li>0 - 4 are incomplete to overcomplete skyrmions,</li> <li>h, h2 and h3 are helical states with different periodicities</li> <li>r1-r3 are different random states</li> <li>u is the uniform magnetisation</li> </ul> <p>The vtu files are labelled according to parameters used in the simulation. For<br> example, a file labelled ‘160_10_3_0_u_wd000000.vtu’ encodes that:</p> <ol> <li> <p>The simulation was of a sample with side length 160nm.</p> </li> <li> <p>The simulation was of a sample of thickness 10nm.</p> </li> <li> <p>The maximum length of an edge in the finite element mesh of the sample was 3nm.</p> </li> <li> <p>The system was relaxed from the ‘u’.</p> </li> <li> <p>‘wd’ encodes that the simulation was performed with a full demagnetizing<br> calculation.</p> </li> </ol> <p><em>square-npys and triangle-npys</em></p> <p>These directories contain computed information about each of the final states stored in square-samples and triangle-samples. This information is stored in NumPy npz files, and can be read in Python straightforwardly using the function numpy.load. Within each npz file, there are 8 arrays, each with 12 elements. These arrays are:</p> <ol> <li>‘E’ - corresponds to the total energy of the relaxed state.</li> <li>‘E_exchange’ - corresponds to the Exchange energy of the relaxed state.</li> <li>‘E_demag’ - corresponds to the Demagnetizing energy of the relaxed state.</li> <li>‘E_dmi’ - corresponds to the Dzyaloshinskii-Moriya energy of the relaxed state.</li> <li>‘E_zeeman’ - corresponds to the Zeeman energy of the relaxed state.</li> <li>‘S’ - Calculated Skyrmion number of the relaxed state.</li> <li>‘S_abs’ - Calculated absolute Skyrmion number - see paper for calculation details.</li> <li>‘m_av’ - Computed normalised average magnetisation in x, y, and z directions for relaxed state</li> </ol> <p>The twelve elements here correspond to the aforementioned twelve states relaxed from, and the ordering of the array is that of the order given above.</p> <p><em>square-classified and triangle-classified</em></p> <p>These directories contain a labelled dataset which gives details about what the final state in each simulation is. The files are stored as plain text, and are labelled with the following structure (the meanings of which are defined in the paper which this dataset accompanies):</p> <ol> <li>iSk - Incomplete Skyrmion</li> <li>Sk, or a number n followed by Sk - n Skyrmions in the state.</li> <li>He - A helical state</li> <li>Target - A target state.</li> </ol> <p>The files contain the names of png files which are generated from the vtu files in the format ‘d_165b_350_2.png’. This example, if found in the ‘Sk.txt’ file, means that the sample which was 165nm in side length and which was relaxed under a field of 350mT from initial state 2 was found at equilibrium in a Skyrmion state.</p> <p><strong>Figures</strong></p> <p><strong><em>square-pngs and triangle-pngs</em></strong></p> <p>These directories contain generated pngs from the vtu files. These are included for convenience as they take several hours to generate. Each directory contains three subdirectories:</p> <p><em>all-states</em></p> <p>This directory contains the simulation results from all samples, in the format ‘d_165b_350_2.png’, which means that the image contained here is that of the 165nm side length sample relaxed under a 350mT field from initial state 2.</p> <p><em>ground-state</em></p> <p>This directory contains the images which correspond to the lowest energy state found from all of the initial states. These are labelled as ‘d_180b_50.png’, such that the image contained in this file is the the lowest energy state found from all twelve simulations of the 180nm sidelength under a 50mT field.</p> <p><em>uniform-state</em></p> <p>This directory contains the images which correspond to the states relaxed only from the uniform state. These are labelled such that an image labelled ‘d_55b_100.png’ is the state found from relaxing a 180nm sample under a 100mT applied field.</p> <p><em><strong>phase-diagrams</strong></em></p> <p>These are the generated phase diagrams which are found in the paper.</p> <p><strong>scripts</strong></p> <p>This folder contains Python scripts which generate the png files mentioned above, and also the phase diagram figures for the paper this dataset accompanies. The scripts are labelled descriptively with what they do - for e.g. ’triangle-generate-png-all-states.py’ contains the script which loads vtu files and generates the png files. The exception here is ’render.py’ which provides functions used across multiple scripts. These scripts can be modified - for example; the function 'export_vector_field' has many options which can be adjusted to, for example, plot different components of the magnetization.</p> <p>In order to run the scripts reproducibly, in the root directory we have provided a Makefile which builds each component. In order to reproduce the figures yourself, on a Linux system, ParaView must be installed. The Makefile has been tested on Ubuntu 16.04 with ParaView 5.0.1. In addition, a number of Python dependencies must also be installed. These are:</p> <ul> <li>scipy >=0.19.1</li> <li>numpy >= 1.11.0</li> <li>matplotlib == 1.5.2</li> <li>pillow>=3.1.2</li> </ul> <p>We have included a requirements.txt file which specifies these dependencies; they can be installed by running 'pip install -r requirements.txt' from the directory.</p> <p>Once all dependencies are installed, simply run the command ‘make’ from the shell to build the Docker image and generate the figures. Note the scripts will take a long time to run - at the time of writing the runtime will be on the order of several hours on a high-specification desktop machine. For convenience, we have therefore included the generated figures within the repository (as noted above). It should be noted that for the versions used in the paper, adjustments have been made after the generation of the figures, (for e.g. to add images of states within the metastability figure, and overlaying boundaries in the phase diagrams).</p> <p>If you want to reproduce only the phase diagrams, and not the pngs, the command ‘make phase-diagrams’ will do so. This is the smallest part of the figure reproduction, and takes around 5 minutes on a high-specification desktop.</p>
Data and code associated with "Spatial wavefront shaping with a nanostructured metasurface for structured illumination microscopy"
<p>Data and code associated with the manuscript "Spatial wavefront shaping with a nanostructured metasurface for structured illumination microscopy"</p>
Self-Regeneration and Self-Healing in DNA Origami Nanostructures
<p>DNA nanotechnology and advances in the DNA origami technique have enabled facile design and synthesis of complex and<br> functional nanostructures. Molecular devices are, however, prone to rapid functional and structural degradation due to the high proportion of surface atoms at the nanoscale and due to complex working environments. Besides stabilizing mechanisms, approaches for the self-repair of functional molecular devices are desirable. Here we exploit the self-assembly and reconfigurability of DNA origami nanostructures to induce the self-repair of defects of photoinduced and enzymatic damage. We provide examples of repair in DNA nanostructures showing the difference between unspecific self-regeneration and damage-specific self-healing mechanisms. Using DNA origami nanorulers studied by atomic force and superresolution DNA PAINT microscopy, quantitative preservation of fluorescence properties is demonstrated with the direct potential for improving nanoscale calibration samples. Here we demonstrate the data on which our findings based on. </p>
Supporting information for "Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques"
<p>This deposition contains the data and analysis (Jupyter notebooks) detailed in Illuminating the nanostructure of diffuse interfaces: Recent advances and future directions in reflectometry techniques. All Jupyter notebooks have also been converted into PDF files for ease of viewing.</p><p> </p><p>All data and code (notebooks) required to reproduce the analysis can be found within the "supporting_data_analysis.zip" archive. This archive contains two sub-directories:</p><ul><li>insituAnalysis<ul><li>Jupyter notebook outlining how to perform the `on-the-fly' analysis.</li><li>Data directory containing all temporally sliced neutron reflectometry data.</li></ul></li><li>MaxEnt<ul><li>Jupyter notebook outlining how to perform the maximum entropy modelling approach for polymer volume fraction profiles.</li><li>Data directory containing relevant neutron reflectometry data and PCHIP spline modelling by Gresham et al. (<a href="www.doi.org/10.1107/S160057672100251X">10.1107/S160057672100251X</a>).</li><li>Code available on the <a href="https://github.com/refnx/refnx-models/tree/master/MaxEntVFP">refnx-models GitHub repo</a>.</li></ul></li></ul><p> </p>
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>
Quantitative results of the analysis of human native and bioengineered tissues corresponding to the work "Histological, histochemical and immunohistochemical characterization of NANOULCOR nanostructured fibrin-agarose human cornea substitutes generated by tissue engineering"
<p>Dataset containing the quantitative results of the histochemical and immunohistochemical analysis of the following human tissues:</p> <ul> <li>Control native cornea (CTR-C)</li> <li>Control native limbus (CTR-L)</li> <li>Artificial cornea generated by tissue engineering (HAC)</li> </ul> <p>Each tissue type was subjected to histochemical and immunohistochemical analyses and results were quantified using ImageJ software to determine average intensities and area fractions corresponding to positive staining signal for each marker.</p>
Research Data - Collective Spin-Wave Dynamics in Gyroid Ferromagnetic Nanostructures
<p>Source data from ferromagnetic resonance experiments and micromagnetic simulations in <em>tetmag</em> software (<a href="https://github.com/R-Hertel/tetmag">https://github.com/R-Hertel/tetmag</a>), used in the paper "Collective Spin-Wave Dynamics in Gyroid Ferromagnetic Nanostructures"<em> </em>in <em>ACS Applied Materials & Interfaces </em>(<a href="https://doi.org/10.1021/acsami.4c02366">https://doi.org/10.1021/acsami.4c02366</a>).</p>
Research Data - Nucleation and Arrangement of Abrikosov Vortices in Hybrid Superconductor-Ferromagnetic Nanostructure
<p>Source data from micromagnetic simulations performed in COMSOL Multiphysics and Python codes for data post-processing utilized in the paper "Nucleation and Arrangement of Abrikosov Vortices in Hybrid Superconductor-Ferromagnetic Nanostructure."</p> <p><strong>Square 250-250-205 (nm 3).gif<br></strong>The time evolution of normal-phase indentations and vortex structures in 3D superconducting prism with dimensions \(250 \times 250 \times 205\) nm\(^3\) is analyzed under an inhomogeneous magnetic field generated by a nearby ferromagnetic nanodot with dimensions \(250 \times 250 \times 700\) nm\(^3\), positioned at a distance of \(d\) = 10 nm.</p> <p><strong>Square 250-250-205 (nm 3)- B(H).gif</strong><br>The time evolution of normal-phase indentations and vortex structures in 3D superconducting prism with dimensions \(250 \times 250 \times 205\) nm\(^3\) is analyzed under a homogeneous magnetic field of 315 mT.</p> <p><strong>Sphere radius 200 nm.gif</strong><br>The temporal evolution of vortex structures in a 3D superconducting sphere with a radius of 200 nm is visualized under the effect of a spatially varying magnetic field generated by a ferromagnetic nanodot with dimensions \(350 \times 350 \times 700\) nm\(^3\), positioned 10 nm away.</p> <p><strong>2D_empty Comsol file<br></strong>The TDGL (Time-Dependent Ginzburg-Landau) model is implemented in COMSOL Multiphysics to simulate 2D superconducting systems, a long wire with a square cross-section and a side length of \(a = 250\) nm, under the influence of homogeneous magnetic fields.</p> <p><strong>3D-B(H)-dynamic_empty Comsol file<br></strong>The TDGL model is utilized in COMSOL to simulate a 3D superconducting prism with a square cross-section, where the side length is \(a = 250\) nm and the height is either 205 nm or 185 nm, subjected to homogeneous magnetic fields.</p> <p><strong>3D-350 nm-B(FM)_empty Comsol file</strong><br>The TDGL model is implemented in COMSOL to simulate a 3D superconducting prism with a square cross-section, where the side length is \(a = 350\) nm and the height is 320 nm. The prism is exposed to inhomogeneous magnetic fields produced by a ferromagnetic nanodot with dimensions \(350 \times 350 \times 700\) nm\(^3\), located at varying distances \(d\) from the superconducting prism.</p> <p><strong>3D-250 nm-B(FM)_empty Comsol file</strong><br>The TDGL model is implemented in COMSOL to simulate a 3D superconducting prism with a square cross-section, where the side length is \(a = 250\) nm and the height is 320 nm. The prism is exposed to inhomogeneous magnetic fields generated by a ferromagnetic nanodot with dimensions \(250 \times 250 \times 700\) nm\(^3\), positioned at varying distances \(d\) from the superconducting prism.</p> <p>The files from Comsol (.mph) are without simulation solutions due to their large size - please contact us if needed.</p>
Dataset for Femtosecond-Laser-Surface-Nanostructured Glass in BIPV Applications
<p><strong>Summary:</strong></p> <p>This is the collection of datasets for the article titled “Femtosecond-laser-surface-nanostructured glass for building integrated solar concentrator”, published in Materials&Design (ISSN 0264-1275).</p> <p><strong>Methods:</strong></p> <p>The experimental and calculation methods for generating the datasets are described in the original paper.</p> <p><strong>File Description:</strong></p> <p>Unzip "Laser glass.7z" using free and open source software 7-zip. The file contains following content:</p> <p>\IMG_SEM_1\<br>- This folder comprises raw Scanning Electron Microscope (SEM) images captured from the surface normal perspective. Each image is in .tif format with a resolution of 1024 × 768 pixels. The file name begins with the laser scan speed, ranging from 200 to 2000 (in mm/s). The laser scan speed is followed by the zooming rate. Some file names include "_2" at the end, signifying images taken from a different area or captured with adjusted brightness/contrast settings. Partial sections of images taken at a 5000x zoom level were used in Figure 1 in original paper.</p> <p>\IMG_SEM_2\<br>- This folder comprises raw cross-sectional Scanning Electron Microscope (SEM) images taken after cutting the sample through laser textured area. Each image is in .tif format with a resolution of 1024 × 768 pixels. The file name begins with the laser scan speed, ranging from 200 to 1800 (in mm/s). </p> <p>\XRD\<br>- This folder contains raw X-ray Diffraction (XRD) data utilized for creating Figure 2a. Additionally, the folder includes automatically generated metadata files that detail the measurement conditions. Within this folder, Ref.csv provides the XRD spectrum of the unprocessed substrate, while Main.csv contains the spectrum of a sample processed with a laser at a speed of 200 mm/s.</p> <p>\PL\<br>- This folder contains photoluminescence (PL) spectra data. The file PL_1.csv was used to generate Figure 2c, while PL_2.csv was used for Figure 2d. The data in both files are organized in an X-Y-Y... format, with each dataset labeled according to the corresponding figure legend. Note that signals below 450 nm were filtered.</p> <p>\RAMAN.csv<br>- contains raw Raman spectroscopy data used to generate Figure 2b. The dataset includes three columns: the first represents the wavenumber values, which serve as the X-axis for the plot. The second and third columns correspond to the Y-axis data, labeled as "Ref" and "Main." "Ref" represents the Raman spectrum of the unprocessed substrate, while "Main" corresponds to the spectrum of a sample processed with a laser at a speed of 200 mm/s. Note the signal before ~80 cm-1 is filtered and the sharp peak at 416.433 cm-1 is due to noise and excluded from the plot. </p> <p>\Spectrophotometry\<br>- The folder contains Spectrophotometry data used to generate Figure 3. The file Spectra_1.csv includes datasets for reflectance (%R), transmittance (%T), and absorptance (%A), each labeled according to the legends of Figures 3a, 3b, and 3c, respectively. Spectra_2.csv provides data on total reflectance (R_tot_*), diffuse reflectance (R_dif_*), and their ratio (R_*%), corresponding to Figure 3d. The datasets in Spectra_2.csv are organized by processing speed *(mm/s) of the samples.</p> <p>\IV\<br>- The folder contains current-voltage (I-V) measurement data. The file IV_1.csv was used to plot Figure 4c and to calculate the relative photocurrent presented in Figure 4d. The file IV_2.csv was used to plot Supplementary Figure S2 and to calculate the optical power efficiency.</p> <p>\Contact_angle\<br>- The folder contains contact angle measurement data. Stat.csv includes advancing and receding angles shown in Figure 5c. 400_Adv.mp4 and 400_Rec.mp4 contain the advancing and receding angle of the 400 mm/s sample, respectively. </p> <p><strong>Credit:</strong></p> <p>When using the dataset/figures, please cite the original paper.</p>
Long-Lived Ensembles of Shallow NV− Centers in Flat and Nanostructured Diamonds by Photoconversion
<p>Shallow, negatively charged nitrogen-vacancy centers (NV−) in diamond have been proposed for high-sensitivity magnetometry and spin-polarization transfer applications. However, surface effects tend to favor and stabilize the less useful neutral form, the NV0 centers. Here, we report the effects of green laser irradiation on ensembles of nanometer-shallow NV centers in flat and nanostructured diamond surfaces as a function of laser power in a range not previously explored (up to 150 mW/μm2). Fluorescence spectroscopy, optically detected magnetic resonance (ODMR), and charge-photoconversion detection are applied to characterize the properties and dynamics of NV− and NV0 centers. We demonstrate that high laser power strongly promotes photoconversion of NV0 to NV− centers. Surprisingly, the excess NV− population is stable over a timescale of 100 ms after switching off the laser, resulting in long-lived enrichment of shallow NV−. The beneficial effect of photoconversion is less marked in nanostructured samples. Our results are important to inform the design of samples and experimental procedures for applications relying on ensembles of shallow NV− centers in diamond.</p>
Data and code from: Evolution of brilliant iridescent feather nanostructures
<p>The brilliant iridescent plumage of birds creates some of the most stunning color displays known in the natural world. Iridescent plumage colors are produced by nanostructures in feathers and have evolved in a wide variety of birds. The building blocks of these structures—melanosomes (melanin-filled organelles)—come in a variety of forms, yet how these different forms contribute to color production across birds remains unclear. Here, we leverage evolutionary analyses, optical simulations and reflectance spectrophotometry to uncover general principles that govern the production of brilliant iridescence. We find that a key feature that unites all melanosome forms in brilliant iridescent structures is thin melanin layers. Birds have achieved this in multiple ways: by decreasing the size of the melanosome directly, by hollowing out the interior, or by flattening the melanosome into a platelet. The evolution of thin melanin layers unlocks color-producing possibilities, more than doubling the range of colors that can be produced with a thick melanin layer and simultaneously increasing brightness. We discuss the implications of these findings for the evolution of iridescent structures in birds and propose two evolutionary paths to brilliant iridescence.</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.