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127 results for “nanowire”
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>
Effects of the electrostatic environment on superlattice Majorana nanowires (dataset)
<p><strong>Description</strong></p> <p>This repository contains the dataset required to reproduce all the figures of the article "Samuel D. Escribano, Alfredo Levy Yeyati, Yuval Oreg, and Elsa Prada,<em> Effects of the electrostatic environment on superlattice Majorana nanowires</em>, arXiv:1904.10289 (2019)".</p> <p> </p> <p><strong>Structure of the dataset</strong></p> <p>All the data is saved in Matlab file-format .mat. Their file names correspond to the figure that they plot. Together with each dataset, there is a Python script .py which plots the corresponding figure. The output of every script is the corresponding figure in PDF-format .pdf. Please, read "reedme.txt" file for further information.</p> <p><br> </p>
Data for "Long-range crossed Andreev reflection in topological insulator nanowires proximitized by a superconductor"
<p>add readme into theory repo</p>
Data from: Flexible transparent electrodes based on silver nanowires synthesized via a simple method
Silver nanowires (Ag NWs) with the length of ~60 μm and the diameter of ~300 nm are prepared via a simple, cost-effective, high-yield and eco-friendly procedure under a high molar concentration ratio of silver nitrate (AgNO3) solution to Poly(vinyl pyrrolidone) (PVP) solution. The pre-synthesized Ag NWs were analyzed by scanning electron microscopy (SEM), X-ray diffraction (XRD) and UV-Visible spectrophotometer. Furthermore, the as-prepared silver nanowires were roll-coated on the surfaces of the polyethylene terephthalate (PET) substrates. By optimizing the concentration of silver nanowire solution, the flexible Ag NW/ PET transparent electrodes with a sheet resistance of 3.8 Ω sq-1 at a transmittance of 70% can be fabricated. The results reported in this paper provide a basis for optimizing the growth of silver nanowires and performances of transparent electrodes.
Full data for 'Signatures of Majorana fermions in hybrid superconductor-semiconductor nanowire devices' Science 336, 1003-1007 (2012)
<p>This Zenodo record contains full original data pertaining to </p> <p>V. Mourik, K. Zuo, S.M. Frolov, S.R. Plissard, E.P.A.M. Bakkers and L.P. Kouwenhoven</p> <p>Signatures of Majorana fermions in hybrid superconductor-semiconductor nanowire devices</p> <p>Science 336, 1003-1007 (2012)</p> <p><br> ---------------------------------------------</p> <p>Author contributions to this repository:</p> <p>Data were obtained between November 2011 and March 2012 by KZ, VM and SF. The files in the repository were organized by SF. </p> <p>LK supports making data files available but has not contributed and has not checked the quality of the files in this data repository.</p> <p>---------------------------------------------</p> <p>Original data obtained at the time of measurement are in the \Data folder. The folder also contains data selected for the paper.</p> <p>The repository also includes measurement logs (\Logs), and some plotting scripts (\Scipts)</p> <p>Folder \Analyses contains powerpoint files made at the time of measurement helpful for data overview</p> <p>---------------------------------------------</p> <p>Devices studied:</p> <p>N-nanowire-S device 1 (chip name 6F2 device 3 in this repository)<br> Device measured in the dilution refrigerator 'Oxford 200s', at the same time as device 3</p> <p>N-nanowire-S device 2 (chip name 6F4)<br> Device measured in the dilution refrigerator Frossati MCK-50 'Fristi', equipped with a 9-3-1 T vector magnet)</p> <p>M-nanowire-S device 3 (chip name 6F2 device 1 in this repository)<br> Device measured in the dilution refrigerator 'Oxford 200s', at the same time as device 1</p> <p>N-N devices (Chip name 6F8)<br> Devices measured in Frossati MNK fridge 'Big Frossati'</p> <p>S-S devices (Chip name 6E5)<br> Devices measured in the dilution refrigerator 'Oxford 200s'</p> <p>---------------------------------------------</p> <p><br> Data for devcies are obatined using QTLab: https://github.com/heeres/qtlab</p> <p>Most data for device2 are obtained using Igor Pro: https://www.wavemetrics.com/</p> <p><br> ---------------------------------------------<br> Data file types:</p> <p>data_NNN.dat - the original data file obtained at the time of the experiment<br> dataNNN.py - the original QTLab data acquisition script saved with data<br> data_NNN.set - settings of measurement instruments at the time of measurement<br> data_NNN.meta - auxillary file necessary for plotting data using SpyView (see below) </p> <p><br> NNN stands for dataset number, automatically indexex by QTLab</p> <p>--------------------------------------------</p> <p>How to plot data:</p> <p>1) Spyview - a free data plotting program written by Gary Steele</p> <p>Data in this repository can be simply dropped into Spyview for plotting. </p> <p>Spyview also produces and can read .mtx files which are available for some of the data in this repository.</p> <p>https://nsweb.tn.tudelft.nl/~gsteele/spyview/</p> <p><br> 2) QTPlot - a Python plotter written by Ruben van Gulik</p> <p>Data in this repository can be directly opened with QTPlot, which will read axis labels.</p> <p>https://github.com/Rubenknex/qtplot</p> <p>Note: requires PyQT4</p>
Raw data repository for the article: Influence of Contacts and Applied Voltage on a Structure of a Single GaN Nanowire
<p>The archive NWrawdata.zip contains information about the raw data collected at P10 beamline at PETRA III during this experiment, which is shown in Figs. 4, 5, and 6 of the main text.</p>
Merging nanowires and formation dynamics of bottom-up grown InSb nanoflakes
<p>data of paper "<strong>Merging nanowires and formation dynamics of bottom-up grown InSb nanoflakes"</strong></p>
Data from: Performance improvement of miniaturized ZnO nanowire accelerometer fabricated by refresh hydrothermal synthesis
Open the record for dataset details and reuse information.
Data from: Flexible transparent electrodes based on silver nanowires synthesized via a simple method
Open the record for dataset details and reuse information.
Silver Nanowire Exposure Results in Internalization and Toxicity to Daphnia magna
GEO Series GSE47064. Daphnia magna. 24 samples. Type: Expression profiling by array.
Exposure to different copper forms – nanoparticles, nanowires, salt and field aged: gene expression profiling in Enchytraeus crypticus
GEO Series GSE69792. Enchytraeus crypticus. 54 samples. Type: Expression profiling by array.
Urinary MicroRNA-based Diagnostic Model for Central Nervous System Tumors Using Nanowire Scaffolds
GEO Series GSE145510. Homo sapiens. 217 samples. Type: Non-coding RNA profiling by array.
Regulation of Gene Expression During Electron Acceptor Limitation and Bacterial Nanowire Formation in Shewanella oneidensis MR-1
GEO Series GSE79964. Shewanella oneidensis. 16 samples. Type: Expression profiling by high throughput sequencing.
Porous carbon nanowire array for surface-enhanced Raman spectroscopy
<p>Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for vibrational spectroscopy as it provides several orders of magnitude higher sensitivity than inherently weak spontaneous Raman scattering by exciting localized surface plasmon resonance (LSPR) on metal substrates. However, SERS can be unreliable for biomedical use since it sacrifices reproducibility, uniformity, biocompatibility, and durability due to its strong dependence on “hot spots”, large photothermal heat generation, and easy oxidization. Here we demonstrate the design, fabrication, and use of a metal-free (i.e., LSPR-free), topologically tailored nanostructure composed of porous carbon nanowires in an array as a SERS substrate to overcome all these problems. Specifically, it offers not only high signal enhancement (~10<sup>6</sup>) due to its strong broadband charge-transfer resonance, but also extraordinarily high reproducibility due to the absence of hot spots, high durability due to no oxidization, and high compatibility to biomolecules due to its fluorescence quenching capability.</p>
Does desorption affect the length distributions of nanowires?
<p>State-of-the art models for statistical properties within the nanowire ensembles consider influx of precursors, reflection and surface diffusion of adatoms. These models predict a delay in the nanowire growth start and the evolution toward an asymmetric length distribution. We demonstrate here the effect of desorption of the nanowire material, which has not been considered so far in studies of the nanowire length distributions. We show that at the very beginning of growth the length distribution should be asymmetric due to the slow nucleation of nanowires. At longer times, the length distribution acquires a symmetric Gaussian shape due to the increased weight of desorption. The width of this distribution is larger than Poissonian and increases for higher ratio of desorption over deposition rate. Our model is consistent with the length evolution of organized self-catalyzed GaAs nanowires. We outline that desorption of the nanowire material should be minimized to achieve arrays of highly identical nanowires. These results are relevant for a wide variety of material systems.</p>
Data Catalog for: Flux-induced topological superconductivity in full-shell nanowires
<p>Data Catalog for: Flux-induced topological superconductivity in full-shell nanowires</p>
Full data for 'Ubiquitous Non-Majorana Zero-Bias Conductance Peaks in Nanowire Devices'
<p>This repository contains experimental data for the following paper:<br> Ubiquitous Non-Majorana Zero-Bias Conductance Peaks in Nanowire Devices.<br> Authors: J. Chen, B. D. Woods, P. Yu, M. Hocevar, D. Car, S. R. Plissard, E. P. A. M. Bakkers, T. D. Stanescu, and S. M. Frolov.<br> Content of this repository: </p> <p>Readme file. </p> <p>/RawData/<br> Original data obtained at the time of measurement for devices 0520-840-NW5,0520-840-2,0520-840-NW1,0510-197.</p> <p>/Measurement notes/<br> All the measurement data was summarized in powerpoints, catagorized by the name of the device. Data in the main text was measured on devices 0524-840-NW5 and 0520-840-2, Data in the supplementary information was measured on all the devices.</p> <p>/Data of paper figures/<br> All the organized data files for the figures in the main text and supplementary information.</p> <p>Data file types:<br> data_NNN.dat - the original data file obtained at the time of the experiment<br> dataNNN.py - the original QTLab data acquisition script saved with data<br> data_NNN.set - settings of measurement instruments at the time of measurement<br> data_NNN.meta - auxillary file necessary for plotting data using SpyView (see below) <br> data_NNN.MTX - a simple 2D/3D matrix format developed for Spyview</p> <p>NNN stands for dataset number, automatically indexed by QTLab</p> <p>How to plot data:</p> <p>1) Spyview - a free data plotting program written by Gary Steele</p> <p>Data in this repository can be simply dropped into Spyview for plotting. </p> <p>Spyview also produces and can read .mtx files which are available for some of the data in this repository.</p> <p>https://nsweb.tn.tudelft.nl/~gsteele/spyview/</p> <p><br> 2) QTPlot - a Python plotter written by Ruben van Gulik</p> <p>Data in this repository can be directly opened with QTPlot, which will read axis labels.</p> <p>https://github.com/Rubenknex/qtplot</p> <p>Note: requires PyQT4</p>
Observation of Conductance Quantization in InSb Nanowire Networks
<p>This file contains electron transport data and code of the paper "Observation of Conductance Quantization in InSb Nanowire Networks" Nano Lett. 2017, 17, 6511-6515. </p>
Data underlying "Electric field tunable superconductor-semiconductor coupling in Majorana nanowires"
<p>This repository contains an extended dataset of raw data underlying <a href="https://www.doi.org/10.1088/1367-2630/aae61d">M. W A de Moor <em>et al.</em>, Electric field tunable superconductor-semiconductor coupling in Majorana nanowires, New J. Phys. <strong>20</strong>, 103049 (2018)</a></p> <p>It also contains python notebooks for recreating the plots in the paper, developed in 2022/23.</p>
Hard superconducting gap in PbTe nanowires
<p>This repository contains the raw data and processing code of the paper "Hard superconducting gap in PbTe nanowires".</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.