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144 results for “Semiconductor”
Semiconductor Porous Hydrogen-Bonded Organic Frameworks Based on Tetrathiafulvalene Derivatives
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Qué son las bandas de Energía en semiconductores
<p>Qué son las bandas de Energía en semiconductores, breve comentario del sólido cristalino y los niveles de energía.</p>
Dataset: VanEck Semiconductor ETF (SMH) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Band gap of the III-V semiconductors as a function of lattice parameter
<p><strong>Copyright notice 1</strong>: reuse of this figure must be accompanied by appropriate attribution to Miguel Caro's PhD thesis as follows:</p> <blockquote> <p>Caro, Miguel A. Theory of elasticity and electric polarization effects in the group-III nitrides. PhD Thesis, University College Cork (2013).</p> </blockquote> <p><strong>Copyright notice 2</strong>: you may modify this figure as long as the text stating the copyright ownership on the left lower corner of the figure is not removed. This applies for the usage cases not covered by the attached CC license, e.g., commercial use, cf. "notice 3" below.</p> <p><strong>Copyright notice 3</strong>: if you wish to use this figure for commercial purposes, contact the author directly.</p> <p><strong>Description</strong>:</p> <p>This figure shows the band gap <span class="math-tex">\(E_\text{g}\)</span> of the technologically important III-V binaries as a function of lattice parameter (in-plane lattice parameter in the case of WZ nitrides). Solid circles indicate a direct gap material while empty circles indicate an indirect gap. The curves show the band gap for some of the ternaries, where solid lines indicate direct gap and dashed lines indicate indirect gap. The data for the cubic III-Vs has been taken from Ref. [1], except for ZB nitrides, which is from Ref. [2]. The data for the WZ nitrides is from Wu's review paper [3]. The band gap of the ZB ternaries has been calculated as the minimum of the gaps at <span class="math-tex">\(\Gamma\)</span>, <span class="math-tex">\(X\)</span> and <span class="math-tex">\(L\)</span> from the respective band gap bowing parameters provided in Refs. [1,2], using an interpolation with bowing parameter (Eq. (3.8) of Miguel Caro's thesis). The variation of <span class="math-tex">\(E_\text{g}\)</span> with composition for the WZ nitride ternaries has been calculated using the same equation from the bowing parameters recommended by Wu [3]. See Chapter 3 of Miguel Caro's thesis for a discussion on III-N bowing parameters, AlInN in particular. A linear interpolation (Végard's law) is assumed for the lattice parameters of the ternaries.<br> All data is for the zero-temperature limit <span class="math-tex">\(T = 0\)</span>.</p> <p>[1] I. Vurgaftman, J. R. Meyer, and L. R. Ram-Mohan. Band parameters for III-V compound semiconductors and their alloys. J. Appl. Phys., 89:5815, 2001.</p> <p>[2] I. Vurgaftman and J. R. Meyer. Band parameters for nitrogen-containing semiconductors. J. Appl. Phys., 94:3675, 2003.</p> <p>[3] J. Wu. When group-III nitrides go infrared: New properties and perspectives. J. Appl. Phys., 106:011101, 2009.</p>
High-Performance Multilevel Nonvolatile Organic Field-Effect Transistor Memory Based on Multilayer Organic Semiconductor Heterostructures
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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>
Microscopic simulations of high harmonic generation from semiconductors
<p>Dataset of the publication “Microscopic simulations of high harmonic generation from semiconductors” by A. Trautmann, R. Zuo, G. Wang, W.-R. Hannes, S. Yang, L. H. Thong, C. Ngo, J. T. Steiner, M. Ciappina, M. Reichelt, H. T. Duc, X. Song, W. Yang, and T. Meier, Proc. SPIE 11999, Ultrafast Phenomena and Nanophotonics XXVI, 1199909 (2022) ( <a href="https://doi.org/10.1117/12.2607447">https://doi.org/10.1117/12.2607447</a> ). The zip file includes the data on which the plots are based.</p>
Raw data of "Heterogeneous integration of superconducting thin films and epitaxial semiconductor heterostructures with Lithium Niobate"
<p>Raw data used to produce figures</p>
Data from: Occurrence of spintronics behaviour (half-metallicity, spin gapless semiconductor and bipolar magnetic semiconductor) depending on the location of oxygen vacancies in BiFe 0.83 Ni 0.17 O 3
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Data from: Convenient fabrication of conjugated polymer semiconductor nanotubes and their application in organic electronics
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Data from: Double-digest RAD Sequencing using Ion Proton semiconductor platform (ddRADseq-ion) with non-model organisms
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Data from: Less is more: extreme genome complexity reduction with ddRAD using Ion Torrent semiconductor technology
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Semiconductor-based sequencing of genome-wide DNA methylation states
GEO Series GSE61968. Homo sapiens. 9 samples. Type: Methylation profiling by high throughput sequencing.
Semiconductor based DNA sequencing of histone modification states
GEO Series GSE49477. Homo sapiens; Mus musculus. 17 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Neuromorphic Electro-Stimulation Based on Atomically Thin Semiconductor for Damage-Free Inflammation Inhibition
GEO Series GSE253300. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Low-cost, low-bias and low-input RNA-seq with High Experimental Verifiability based on Semiconductor Sequencing
GEO Series GSE87660. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing.
Figure 1 from: Yilmaz H (2020) Ferroelectric-Semiconductor Solar Cells: An Alternative Configuration With High-Efficiency. Research Ideas and Outcomes 6: e50013. https://doi.org/10.3897/rio.6.e50013
Figure 1 Illustration of the proposed solar cell.
Data and code for figures: Frequency division using a soliton-injected semiconductor gain-switched frequency comb
<p>This dataset contains the figures and data presented in the paper <Frequency division using a soliton-injected semiconductor gain-switched frequency comb>.</p>
Electrostatic control of the proximity effect in the bulk of semiconductor-superconductor hybrids
<p>The proximity effect in semiconductor-superconductor nanowires is expected to generate an in-<br> duced gap in the semiconductor. The magnitude of this induced gap, together with the semicon-<br> ductor properties like the spin-orbit coupling and g - factor, depends on the coupling between the<br> materials. It is predicted that this coupling can be adjusted through the use of electric fields. We<br> study this phenomena in InSb/Al/Pt hybrids using nonlocal spectroscopy. We show that these<br> hybrids can be tuned such that the semiconductor and superconductor are strongly coupled. In this<br> case, the induced gap is similar to the superconducting gap in the Al/Pt shell and closes only at<br> high magnetic fields. In contrast, the coupling can be suppressed which leads to a strong reduction<br> of the induced gap and critical magnetic field. At the crossover between the strong-coupling and<br> weak-coupling regimes, we observe the closing and reopening of the induced gap in the bulk of a<br> nanowire. Contrary to expectations, it is not accompanied by the formation of zero-bias peaks in<br> the local conductance spectra. As a result, this cannot be attributed conclusively to the anticipated<br> topological phase transition and we discuss possible alternative explanations.</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>
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.