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431 results for “nano”
Fast and long-term super-resolution imaging of ER nano-structural dynamics in living cells using a neural network
<p>Datasets acquired and generated for the manuscript "Fast and long-term super-resolution imaging of ER nano-structural dynamics in living cells using a neural network". The datasets include test, training and time series datasets each containing the raw data and the predicted data where it applies. </p>
Data for "Measurement of the atom-surface van der Waals interaction by transmission spectroscopy in a wedged nano-cell"
<p>The data presented in publication <a href="http://arxiv.org/abs/1905.02783">"Measurement of the atom-surface van der Waals interaction by transmission spectroscopy in a wedged nano-cell"</a> . Published version: <a href="https://doi.org/10.1103/PhysRevA.100.022503">https://doi.org/10.1103/PhysRevA.100.022503</a></p> <p>The data are in HDF5 format, with associated metadata.</p> <p>To see examples of how to use the data, and the theoretical model for analysis, see <a href="https://github.com/thermal-vapours/TAS-Transmission-Atom-Surface">https://github.com/thermal-vapours/TAS-Transmission-Atom-Surface </a></p>
Data for "Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy"
<p>This dataset contains data used in the publication entitled "<strong>Nano-scale characterisation of sheared β'' precipitates in a deformed Al-Mg-Si alloy</strong>". This publication concerns how β'' precipitates are sheared by dislocations during deformation. The data contained in this repository are data acquired on various transmission electron microscopes of specimens of the aluminium alloy AA6060 in peak aged condition after uniaxial compression to 5%, 10%, and 20%, in addition to the undeformed reference alloy.</p> <p>There are five main types of data:</p> <ul> <li>Transmission electron microscopy (TEM) images</li> <li>High-resolution TEM images</li> <li>High angle annular dark field (HAADF) scanning TEM (STEM) images</li> <li>Scanning precession electron diffraction (SPED) data.</li> <li>Cross-sectional data of precipitates in undeformed and 20% compressed conditions.</li> </ul> <p>Data for the TEM, HRTEM, and STEM images are kept in zipped folders due to the large number of images (several hundreds for each compression condition). Folders are named following the format of "<alloy>_<compression>_<technique>", where technique refers to TEM, HRTEM, or STEM. Images are provided in both .hdf format and .jpg format (to aid in navigating the data). Please see <a href="https://www.hdfgroup.org/">HDF Group</a> for more information regarding the HDF file format, and <a href="https://www.hdfgroup.org/downloads/hdfview/">HDF View</a> for softaware to read and show HDF data. The Python package <a href="http://hyperspy.org/">HyperSpy</a>, is also useful for loading the HDF data for inspection, analysis, and presentation.</p> <p>For some STEM images, a stack of short-exposure STEM images acquired and analysed using the <a href="http://lewysjones.com/software/smart-align/"><em>SmartAlign</em></a> plugin to <a href="http://www.gatan.com/products/tem-analysis/gatan-microscopy-suite-software"><em>Gatan Digital Micrograph</em></a> is available. SmartAlign offers the possibility of rigidly and non-rigidly aligning the STEM images in the stack in order to reduce effect of specimen drift and scan noise during acquisition. The conventional STEM images are found in the zip archive labelled "STEM". When the filenames of the STEM images include "SAstack" and/or "SAimage", a STEM SmartAlign stack or the average through a non-rigidly aligned stack is available of the same field of view. In such cases, both the SmartAlign stack and the through-stack image is provided in the metadata in the .hdf file (note that not all stacks have been aligned, and in such cases no through-stack image is available). In addition, the SmartAlign stacks themselves are available in the subfolder "STEM\SmartAlign\" within each STEM folder. The through-stack images of the smart align stacks are also provided separately in the subfolder "STEM\SmartAlign\Aligned\". For the 20% compressed case, a lowloss electron energy loss spectroscopy (EELS) spectrum and thickness maps of the imaged areas are also provided, in the subfolder "STEM\EELS\".</p> <p>The SPED data, acquired using the <em>ASTAR</em> system of <em><a href="https://www.nanomegas.com/">NanoMegas</a></em>, is provided as .hdf5 files in the root directory of the repository. They should be read using and <a href="https://github.com/pyxem/pyxem">pyXem</a>. The attached Jupyter Notebook "SPED_data_inspection.ipynb" can be used to access the SPED datasets. These datasets are 4D datasets, with two spatial and two reciprocal dimensions. They have been decomposed using the non-negative matrix factorization algorithm (NMF) used in HyperSpy. These decomposition results are included in the .hdf5 files. In addition, parameters used in the preprocessing of the datasets are attached in the metadata in these files. The metadata of these files are also provided separately as .txt files.</p> <p>Finally, measurements of the precipitate cross-sectional area and circularity is available as .csv files with the first column being the row index, the second the cross-sectional areas of precipitates measured in nanometers squared, the third column is the perimeters of the precipitates measured in nanometers, and column four is the <a href="https://imagej.nih.gov/ij/plugins/circularity.html">circularity</a> of the precipitates.</p>
Abundance, biovolume, and biomass of Synechococcus and eukaryote pico- and nano- plankton from continuous underway flow cytometry during NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic and eukaryotic picoplankton and nanoplankton sampled continuously underway during Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were obtained with an Attune NxT Flow Cytometer sampling at approximately 2-min intervals from the underway science seawater. Cells were identified and enumerated from the flow cytometry data files based on their scattering, phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals.
Abundance, biovolume, and biomass of Synechococcus, eukaryote pico- and nano- phytoplankton, and heterotrophic bacteria from flow cytometry for water column bottle samples on NES-LTER Transect cruises, ongoing since 2018
These data represent the abundance, biovolume, and biomass of prokaryotic phytoplankton, eukaryotic pico- and nano- phytoplankton, and heterotrophic bacteria from discrete flow cytometry samples collected during the Northeast U.S. Shelf Long-Term Ecological Research (NES-LTER) Transect cruises, ongoing since 2018. Samples were collected and preserved from the water column at multiple depths using Niskin bottles on a CTD rosette system along the NES-LTER transect, and analyzed post cruise. Cells were identified and enumerated from the flow cytometry data files based on their scattering, SYBR (525 nm), phycoerythrin (575 nm) and chlorophyll (680 nm) fluorescence signals. Gating was completed manually in the Attune NXT software interface.
Dataset supporting the paper "Doublet-Singlet-Doublet Transition in a Single Organic Molecule Magnet On-Surface Constructed with up to 3 Aluminum Atoms. Nano Letters 21, 8317 (2021)"
<p>Dataset corresponding to theoretical calculations in the paper "Doublet-Singlet-Doublet Transition in a Single Organic Molecule Magnet On-Surface Constructed with up to 3 Aluminum Atoms" Nano Letters 21, 8317 (2021), <a href="https://doi.org/10.1021/acs.nanolett.1c02881">https://doi.org/10.1021/acs.nanolett.1c02881</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <ul> <li>.siesta files: STM images in WsXM format (http://www.wsxm.eu/) simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>).</li> <li>CONTCAR and POSCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).<br> </li> </ul>
Raw data for manuscript A. Dey et. al., ACS Nano 2023, 17, 16, 16080–16088.
<p><strong>Scan_00165.zip</strong>: This compressed file contains the raw X-ray data collected at beamline P06 at PETRA III, DESY, relevant for the manuscript. From this dataset that includes Bragg diffraction and X-ray fluorescence data from the indium Kα, gallium Kα, and arsenic Kα lines, all figures containing X-ray data in the manuscript were created. For viewing, use, e.g., <a href="https://ncnr.nist.gov/ncnrdata/view/nexus-hdf-viewer.html">https://ncnr.nist.gov/ncnrdata/view/nexus-hdf-viewer.html</a>.</p> <p><strong>W795_29a.tif</strong>: This data file is the raw SEM image from which the high magnification cut-out in the manuscript figure was taken. The SEM image was collected at an acceleration voltage of 15 kV using a trough-lens detector in secondary electron imaging mode. The field of view is 2.12 µm. For viewing, use any standard image viewer.</p> <p><strong>W795_InGaAsQDs.0_00023.spm</strong>: This data file is the raw AFM image from which after processing the AFM figures and AFM height information given in the manuscript were obtained. The image size is 200 nm × 200 nm, and was obtained at a scanning speed of 1 Hz with a resolution of 512 × 512 pixels. For viewing, install, e.g., <a href="http://gwyddion.net/download.php">http://gwyddion.net/download.php</a>.</p>
Dataset supporting the paper "Thioetherification of Br-Mercaptobiphenyl Molecules on Au(111). Nano Letters 23, 1350 (2023)"
<p>Dataset corresponding to theoretical calculations in the paper "Thioetherification of Br-Mercaptobiphenyl Molecules on Au(111). Nano Letters 23, 1350 (2023)" DOI: <a href="https://doi.org/10.1021/acs.nanolett.2c04619">https://doi.org/10.1021/acs.nanolett.2c04619</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain:</p> <ul> <li>.dat files: STM images simulated using STMpw (<a href="https://doi.org/10.5281/zenodo.3581159">https://doi.org/10.5281/zenodo.3581159</a>). They can be processed with the programs and scripts in the Utils directory of STMpw.</li> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>).</li> <li>.agr: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).</li> </ul>
All-atom 500-nano seconds Molecular Dynamics Simulations of SARS-CoV-2 Spike Receptor-binding Domain bound with ACE2
<p>Data includes all of the trajectories (1000) of classical all-atom molecular dynamics (MD) simulations of of SARS-CoV2 Spike Protein/ACE2 complex (PDB ID: 6M0J). In order to decrease the size of the file only protein rajectories were provided. Simulation has been performed with Desmond. Protein was placed in the cubic boxes with explicit TIP3P water models that have 10.0 Å thickness from surfaces of protein. The system is neutralized by adding counter ions, and salt solution of 0.15M NaCl was also used to adjust the concentration of the systems. The long-range electrostatic interactions were calculated by the particle mesh Ewald method. A cutoff radius of 9.0 Å was used for both van der Waals and Coulombic interactions. The temperature was set as 310K initially, and Nose–Hoover thermostat was used for adjustment. Martyna–Tobias–Klein protocol was employed to control the pressure, which was set at 1.01325 bar. The time-step was assigned as 2.0 fs. The default values were used for minimization and equilibration steps, and finally 500 nano-seconds (ns) production run was performed for the simulation.</p>
Nano-sized calcium carbonate particles in cement mortars (DS18)
<p>This dataset will provide the selection of the optimal mix-design of cement mortars, optimizing the characteristics of nanoCaCO3 particles (additional percentages, morphology, particle size distribution, crystal phase) according to their use in cement-based composites. These commercial nanoparticles have characteristics comparable with those of the synthesized particles used up to now in the RECODE project.</p>
Data for "Nano onions based on an amphiphilic Au3(pyrazolate)3 complex"
<p>This upload contains raw data (NMR, DLS, Zeta Potential) files for the article: </p> <p><strong>Nano onions based on an amphiphilic Au<sub>3</sub>(pyrazolate)<sub>3</sub> complex</strong></p> <p>Nanoscale, 2024, Advance Article, <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D4NR03901G">https://doi.org/10.1039/D4NR03901G</a></p>
Dataset associated to Picone, A. et al., ACS Appl. Nano Mater. 2021, 4, 12, 12993–13000
<p>Dataset associated to paper published under the SINFONIA project</p> <p>Picone, A. et al., ACS Appl. Nano Mater. 2021, 4, 12, 12993–13000</p>
Nano-FTIR Investigation of the CM Chondrite Allan Hills 83100
<p>This is supporting data for the paper titled "Nano-FTIR Investigation of the CM Chondrite Allan Hills 83100." ALH 83100 nanoFTIR spectra.xlsx contains all of the nano-IR phase and amplitude spectra presented in the paper. ALH83100_172_0_Normalized.dat and ALH83100_172_0_Normalized.hdr are the ENVI-readable data and header files for the micro-FTIR hyperspectral image presented in Figure 1. ALH83100_xaxis.cxv contains the x axis in wavenumber units for the micro-FTIR hyperspectral image. Six .gsf files, readable with the free Gwyddion software, are the single wavelength O2A images used to create Figures 3, 4, and 5.</p>
Dataset supporting the paper "Molecular Approach for Engineering Interfacial Interactions in Magnetic/Topological Insulator Heterostructures. ACS Nano 14, 6285 (2020)"
<p>Dataset corresponding to theoretical calculations in the paper "Molecular Approach for Engineering Interfacial Interactions in Magnetic/Topological Insulator Heterostructures" ACS Nano 14, 6285 (2020), DOI: <a href="https://doi.org/10.1021/acsnano.0c02498">10.1021/acsnano.0c02498</a></p> <p>List of files:</p> <p>Several folders corresponding to the figures of the paper. They contain the following files:</p> <ul> <li>CONTCAR files: relaxed structures in VASP format. They can be visualized with VESTA (<a href="https://jp-minerals.org/vesta/en/">https://jp-minerals.org/vesta/en/</a>)</li> <li>.agr files: grace files (<a href="https://plasma-gate.weizmann.ac.il/Grace/">https://plasma-gate.weizmann.ac.il/Grace/</a>).<br> </li> </ul>
Biogenic supported lipid bilayers as a tool to investigate nano-bio interfaces
<p>Colorimentric Nanoplasmonic Assay (CONAN) assay of EVs from TRAMP cells. UV/VIS spectrophotometer analysis of samples of EVs from TRAMP cell line incubated with gold nanoparticles, following the protocol described in Montis et al. <a href="https://doi.org/10.1016/j.jcis.2020.03.014">https://doi.org/10.1016/j.jcis.2020.03.014</a></p>
Hybrid Deep Learning Techniques for Securing Bioluminescent Interfaces in Internet of Bio Nano Things
<p>The data-set presents normal and anomalous values of twelve traffic parameters, generated by <strong>Bioluminescent bio-cyber Interfacing </strong>(BBI) in the I<strong>nternet of Bio Nano Things </strong>(IoBNT) based systems.</p> <p>The traffic parameters included in the data-set represent bio-electric and electro-bio transduction unit operation of BBI incorporating normal, as well as abnormal data to train and test machine/deep learning classifiers in discriminating attack scenarios.</p> <p>The parameters considered include the following: <strong>Cumulative concentration of released molecules, Elimination rate, Michaelis-Menten constant, Kinetic constant, Forward rate constant, Catalytic reaction constant, Ligand-receptor binding constant, Concentration of ATP, Concentration of information molecules, Release rate Reverse kinetic constant,</strong> and <strong>Reverse forward rate constant.</strong></p> <p>The data set is divided into training and testing data for simplified analysis, and application.</p>
Scripts for quantifying the effect of diamond nano-pillars on the fluorescence of NV centers
<p><strong>Summary</strong></p> <p>Scripts and data can be used to reproduce and build on the numerical results published under the title: "<a href="http://doi.org/10.3390/nano12091516">Optical and Spin Properties of NV Center Ensembles in Diamond Nano-Pillars</a>" by Kseniia Volkova, Julia Heupel, Sergei Trofimov, Fridtjof Betz, Rémi Colom, Rowan W. MacQueen, Sapida Akhundzada, Meike Reginka, Arno Ehresmann, Johann P. Reithmaier, Sven Burger, Cyril Popov, and Boris Naydenov (Nanomaterials 12(9), 1516, 2022).</p> <p><strong>Method</strong></p> <p>The dipole emitters are assumed to be distributed uniformly 30 nm below the top surface of the nano-pillars. They are first integrated with a trapezoidal rule along the azimuth (because of the periodicity this results in a geometrical convergence) and with a 15 point Gauss-Kronrod quadrature rule in radial direction.</p> <p>The main source of error results from the dipole positions being integrated only from 0 to R - min_dist, as it is challenging to model a dipole emitter located only few nanometers from the curved material interface. Further numerical parameters can be adjusted in the input files for JCMsuite. Both, a 3D setup and a 2D setup are provided. The letter exploits the rotational symmetry which results in a smaller memory footprint. Yet, as the distance of the dipole from the symmetry axis increases, many Fourier components are required which leads to long computation times.</p> <p>For further quantitative studies we propose the 3D setup that is the default in the script 'integration.m', which allows to integrate closer to the side walls without increasing the costs. Furthermore in the second data set, shipped together with the data published in the paper, the height has been kept constant. In the paper the height has been chosen according to the fabricated samples. The 90° angle has been assigned to the [111] samples and the correspondingt height of 1400 nm and the 35.3° angle was assigned to the [100] samples and a height of 2200 nm.</p> <p><strong>Structure</strong></p> <p>The directories <strong>scattering2D</strong>, <strong>scattering3D </strong>and <strong>scatteringFlat</strong> contain input files for JCMsuite. The script 'integration.m' can be used to produce new data. With 'plotresults.m' you can either plot the results produced with 'integration.m' or those which were published in the related paper. Please note that the provided example produced with the script 'integration.m' differs from the published data, which has been computed with slightly different parameters.</p> <p><strong>Requirements</strong></p> <ul> <li>JCMsuite 5.2.0</li> <li>Matlab R2019b</li> </ul> <p>In order to produce new data, you must replace the corresponding place holders in the files by 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>.</p>
The Delayed Box: Biphenyl Bisimide Cyclophane, a Supramolecular Nano‒environment for Efficient Generation of Delayed Fluorescence
<p>Additional data to report <a title="DOI URL" href="https://doi.org/10.1021/jacs.4c07730">https://doi.org/10.1021/jacs.4c07730</a>:</p> <p>Activating delayed fluorescence emission in a dilute solution via a non-covalent approach is a formidable challenge. In this report, we propose a strategy for efficient delayed fluorescence generation in dilute solution using a non-covalent approach via supramolecularly engineered cyclophane-based nanoenvironments that provide sufficient binding strength to π-conjugated guests and that can stabilize triplet excitons by reducing vibrational dissipation and lowering the singlet–triplet energy gap for efficient delayed fluorescence emission. Toward this goal, a novel biphenyl bisimide-derived cyclophane is introduced as an electron-deficient and efficient triplet-generating host. Upon encapsulation of various carbazole-derived guests inside the nanocavity of this cyclophane, emissive charge transfer (CT) states close to the triplet energy level of the biphenyl bisimide are generated. The experimental results of host–guest studies manifest high association constants up to 10<sup>4</sup> M<sup>–1</sup> as the prerequisite for inclusion complex formation, the generation of emissive CT states, and triplet-state stabilization in a diluted solution state. By means of different carbazole guest molecules, we could realize tunable delayed fluorescence emission in this carbazole-encapsulated biphenyl bisimide cyclophane in methylcyclohexane/carbon tetrachloride solutions with a quantum yield (QY) of up to 15.6%. Crystal structure analyses and solid-state photophysical studies validate the conclusions from our solution studies and provide insights into the delayed fluorescence emission mechanism.</p>
Computational models for kaolinite nano-particles (Generations 1-3) and their comprehensive FTIR spectra
<p>The dataset contains a large number of computational models and detailed spectral comparison, fitting, and deconvolution of a large set of FTIR data for crystalline and exfoliation kaolinite, nano-kaolinite and halloysite, nano-halloysite samples.<br> The <strong>G1.xyz</strong>, <strong>G2.xyz</strong>, and <strong>G3.xyz</strong> files contain the initial structures for the first three generations of nano-kaolinite molecules.<br> The compressed folder <strong>SVP-def2TZVP.zip</strong> contains the structural information relevant for comparing and contrasting the performance a double-zeta (SVP) and triple-zeta (TZVP) basis sets.<br> The <strong>edge_protonation.zip</strong> folder guides the reader through the stepwise evaluation of various edge protonation models and shows the final converged results.<br> The <strong>full_optimization.zip</strong> folder summarizes the stationary structure calculations at various levels of theory carried out for the G2 model.<br> </p>
Comparing the integration of bone cells on an even and a nano structured surface
<p>Bone cells develop better on a nano structured surface.</p> <p>Successful cellular integration is extremely important to the long-term viability of dental implants. The sooner cells can attach and surround the implant, the faster the patient recovers, and the lower the incidence of infection and site contamination. The specific biological response of the surrounding tissues depends enormously on the surface characteristics of the particular biomaterial. Moreover mouth infections are currently regarded as the main reason why dental implants fail. Therefore, antibacterial properties are another requirement for preventing potential bacterial infection.</p> <p>The multi-beam optical module developed within LASER4SURF, will be able to obtain functionalized metallic surfaces with textures around 1μm or less, enabling the required tolerances to reach the best cell adhesion and antibacterial properties. Thus, it will lead to extended implant life, reduced rejection and improved overall quality of life for patients.</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.