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datasets available to search
ShareScore release 0.9.0
Dataset results
9 results for “Silicon Nanowires”
Dataset for "Tuning the thermoelectric properties of boron-doped silicon nanowires integrated in a micro-harvester"
<p>Dataset including all data used for the elaboration of the work "Tuning the thermoelectric properties of boron-doped silicon nanowires integrated in a micro-harvester" published in Advanced Materials Technologies, 2022</p> <p><a href="https://doi.org/10.1002/admt.202101715">https://doi.org/10.1002/admt.202101715</a></p> <p>The files includes:</p> <p>· INDIVIDUAL NW data:</p> <p> - I-V data of each NW at different temperatures</p> <p> - 3w data of each NW at different temperatures<br> - 4 SEM images of the NW, each of them used for assessing one NW parameter<br> - Tip: NW diameter 2<br> - Base: NW diameter 1<br> - Overall: NW length<br> - Tilted view at 45º: Relative NW heigh over substrate</p> <p>· SEEBECK MEASUREMENT data:</p> <p> - Voc versus applied dT data for each substrate temperature<br> - File containig calibration data for all resistors</p> <p>· TEM data:</p> <p>-TEM images of the studied NWs in .dm3 format.</p> <p>· X-RAY FLUORESCENCE data:</p> <p>- Maps containing one energy spectrum per pixel in .hdf files.</p> <p>· TIP-ENHANCED RAMAN SPECTROSCOPY data:</p> <p>- Maps containing one energy spectrum per pixel in a tabulated .txt file.</p> <p>· POWER HARVESTED data:</p> <p>- IV curves of each microthermocouple connection X-Y upon different substrate temperatures in tabulated separated .txt files</p>
Polarized Emission from hexagonal-Silicon Germanium Nanowires
<p>This dataset contains the polarization dependent photoluminescence intensity measurements on hexagonal-silicon germanium nanowires. This data confirms the selection rules of the fundemental direct bandgap transition of the material. </p> <p>The data is zipped and contains a README which describes the storage of the data inside the folder.</p>
Synthetic recovery of impulse propagation in myocardial infarction via silicon carbide semiconductive nanowires
<p><strong> DataSet for the publication "Synthetic recovery of impulse propagation in myocardial infarction via silicon carbide semiconductive nanowires"</strong></p> <p>Pre-processed Confocal data for Figure 3 and Supplementary Figure 3. Acquired with Leica SP8 Laser-Scanning Confocal Microscope</p> <p>Pre-processed HPICM raw data for Figure 2, Supplementary Figure 2 Acquired with Ionscope Hopping Software</p> <p>Pre-processed double-patch clamp data for Figure 2b-c. Acquired with Clampfit 10.6</p> <p>Pre-processed EP raw data for Figure 6-7-8, supplementary Figure 4. Acquired with Clampfit 10.6</p> <p>Post-processed Kinematic trajectories for Supplementary Figure 5, Supplementary Figure 6 acquired with Video Spot Tracker V 8.00</p> <p> </p> <p> </p> <p> </p>
Stimulated Emission from Hexagonal Silicon-Germanium Nanowires
<p>Data repository in companion with the publication "Stimulated Emission from Hexagonal Silicon-Germanium Nanowires"</p>
Figures of merit that characterize silicon gate-all-around nanowire FETs affected by line edge roughness variability
<p>Off-current, threshold voltage, sub-threshold slope and on-current values for two silicon gate-all-around nanowire FETs affected by line edge roughness (LER) variability, a 22 nm gate length device and a 10 nm gate length one. The LER profile that characterizes the roughness deformation is also included in the dataset. Different correlation length (CL) and root mean square (RMS) heights values are characterized.</p>
AFM interlaboratory comparison for nanodimensional metrology on silicon nanowires [Dataset]
<p>Dataset related to "AFM interlaboratory comparison for nanodimensional metrology on silicon nanowires" paper</p>
Data set for Control of Ge island coalescence for the formation of nanowires on silicon
<p>This document contains all the data and the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanaowires on silicon"</p> <p><a title="Link to landing page via DOI" href="https://doi.org/10.1039/D3NH00573A">https://doi.org/10.1039/D3NH00573A</a></p>
Hexagonal Silicon-Germanium Nanowire Branches with Tunable Composition
<p>Hexagonal SiGe-2H has been recently shown to have a direct bandgap, and holds the promise to be compatible with silicon technology. Hexagonal Si (Ge) has been grown on an epitaxial lattice matched template consisting of wurtzite GaP (GaAs). Here, we present the growth of hexagonal Si and SiGe nanowire branches grown from a wurtzite stem by the Vapor-Liquid-Solid (VLS) growth mode, which is substantiated by <em>in-situ</em> transmission electron microscopy. We show that the composition can be tuned through the whole range of stoichiometry from Si to Ge, and the possibility to realize Si and SiGe heterostructures in these branches. </p>
Fundamental aspects to localize self-catalyzed III-V nanowires on silicon
<p>Compressed zip files includes AFM raw data files, SEM images, Simulation codes.</p>
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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.