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144 results for “Semiconductor”
Data from: Casimir repulsion with biased semiconductors
<p>This repository provides data underlying the figures in the manuscript titled 'Casimir repulsion with biased semiconductors'.</p> <p>The data is given in the CSV-file format and it is organized into subfolders with the respective figure name. For more information see the README files in those subfolders.</p>
Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se)
<p>The structural, electrical, and optical properties of a series of six layered oxychalcogenides with general formula Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> where <em>M</em> = Ga, Sc, or In and <em>Ch</em> = S or Se have been investigated. From this set we report the structure and properties of Sr<sub>2</sub>GaO<sub>3</sub>CuSe for the first time, as well as the full structural details of Sr<sub>2</sub>ScO<sub>3</sub>CuSe, which have not previously been available. A systematic study of the suitability of all the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> phases as <em>p</em>-type conductors has been carried out, after doping with both sodium and potassium to a nominal composition of <em>A</em><sub>0.05</sub>Sr<sub>1.95</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em>, (<em>A</em> = Na or K), to increase the hole carrier concentration. Density functional theory calculations were used to determine the electronic band structure and predict the transport properties, while optical properties were determined using UV-vis spectroscopy, and structures confirmed using Rietveld refinement against powder X-ray diffraction data. Room temperature conductivity measurements were carried out on both pristine samples and doped samples, eighteen compositions in total, using four-point probe measurements. We found that the most conductive sample wasK<sub>0.05</sub>Sr<sub>1.95</sub>GaO<sub>3</sub>CuSe, with a measured conductivity of 0.46 Scm<sup>−1</sup>, collected from a sintered pellet. We have also been able to identify a relationship between the conductivity and the geometry of the copper chalcogenide layer within the Sr<sub>2</sub><em>M</em>O<sub>3</sub>Cu<em>Ch</em> series of compounds. As this geometry can be controlled through the material composition, the identification of this structure-property relationship highlights a route to selection and identification of materials with even higher conductivities.</p> <p> </p> <p>This repository contains the computational research data generated for *Transport properties of doped wide band gap layered oxychalcogenide semiconductors Sr2GaO3CuCh, Sr2ScO3CuCh and Sr2InO3CuCh (Ch = S or Se).</p> <p> </p> <p>## Folder Architecture</p> <p>The folders contain the structures relaxed with hybrid functionals (HSE06), the band structure and the uniform DOS and AMSET calculations for each system.</p> <p> </p> <p> </p>
Data for "Direct Observation of Ultrafast Exciton Localization in an Organic Semiconductor with Soft X-ray Transient Absorption Spectroscopy"
<p>Underlying data for figures 1-3 and supplementary figures S1-S7 for the paper entitled 'Direct Observation of Ultrafast Exciton Localization in an Organic Semiconductor with Soft X-ray Transient Absorption Spectroscopy'.</p>
Data and analysis for the paper "Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots"
<p>This repository contains the raw data and analysis code used to generate the figures in the manuscript <em>Nonlocal measurement of quasiparticle charge and energy relaxation in proximitized semiconductor nanowires using quantum dots</em>. </p> <p><a href="https://journals.aps.org/prb/abstract/10.1103/PhysRevB.106.064503">Link to publication</a></p> <p><a href="https://arxiv.org/abs/2110.05373">Link to arXiv</a></p>
Code and Data for "Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device"
<p><strong>Code and Data for "Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device".</strong></p> <pre>Code to analyze data produced by the Quantum-Si benchtop device and semiconductor chip is provided in a Python library <strong>qsi_algo</strong> under several submodules: - <strong>rs_caller.py</strong>: Algorithm for calling RS segments (also called ROI segments throughout code). - <strong>rs_caller_controller.py</strong>: Code framework for executing RS calling and property computation in a distributed manner - <strong>rs_properties</strong>: Code for computing properties of identified RS - <strong>rs_classifier</strong>: Algorithms for identifying peptide states (i.e. residue calls) associated with an RS - <strong>utils.py</strong>: shared helper code - <strong>pulse_reader</strong>: reader for binary pulse file - <strong>filters</strong>: ROI and pulse filtering utilities - <strong>plotting</strong>: functions for visualization of data relevant to the analyses presented Jupyter notebooks (<strong>.ipynb</strong>) files are named according to the manuscript figure they are associated with. Analysis code inside uses provided RS (recognition segment) data to demonstrate filtering and residue-calling techniques required to replicate analyses shown in manuscript figures. Please note: several methods rely on randomization for model initialization and/or data sampling which can cause small deviations from equivalent analyses in published figures. The raw data produced from the Quantum-Si benchtop device and semiconductor chip for the assays presented in the accompanying study is presented in a pulse-called binary file format. Pulses can be used as input for RS identification and peptide state identification. Pre-segmented (RS-identified) files are included for convenience. The data contained in the files include: <strong>{run_id}.bin</strong>: Binary format for storing pulse info. The reader provided in <strong>qsi_algo.pulse_reader</strong> produces the following columns: - <strong>aperture_index</strong>: unique aperture index on chip - <strong>start_f</strong>: index of first frame in pulse, counted from the beginning of the run - <strong>end_f</strong>: index of last frame in pulse, counted from the beginning of the run - <strong>dur_f</strong>: duration of pulse in frames - <strong>dur_s</strong>: duration of pulse in seconds - <strong>ipd_f</strong>: interpulse duration in frames (number of frames since end of preceding pulse) - <strong>ipd_s</strong>: interpulse duration in seconds (time in seconds elapsed since end of preceding pulse) - <strong>snr</strong>: signal-to-noise ratio (bin1_intensity / bin1_bg_std) - <strong>intensity</strong>: intensity of pulse (counts above baseline in bin1) - <strong>bin0_intensity</strong>: counts above baseline in bin0 - <strong>intensity_display</strong>: bin1_intensity + bin1_bg_mean - <strong>binratio</strong>: bin0_intensity / bin1_intensity - <strong>bg_mean</strong>: bin1 background mean in region of pulse - <strong>bg_std</strong>: bin1 background standard deviation in region pulse - <strong>bin0_bg_mean</strong>: bin0 background mean in region of pulse - <strong>bin0_bg_std</strong>: bin0 background standard deviation in region pulse <strong>{run_id}.csv.gz</strong>: Compressed comma-separated value file containing RS/ROI properties computed from raw pulses.bin file by included RS caller (example in <strong>rs_caller.py</strong>). - <strong>ap</strong>: unique aperture index on chip - <strong>ROI</strong>: ordinal ROI number in the aperture, 0-indexed - <strong>start_p</strong>: index (.loc) of first pulse in the ROI (inclusive) in pulse dataframe - <strong>end_p</strong>: index (.loc) of last pulse in the ROI (inclusive) in pulse dataframe - <strong>start_f</strong>: first frame of the first pulse in the ROI (inclusive) - <strong>end_f</strong>: Last frame of the last pulse in the ROI (exclusive) - <strong>start_s</strong>: Time (in seconds elapsed from beginning of run) of the start of the ROI - <strong>end_s</strong>: Time (in seconds elapsed from beginning of run) of the end of the ROI - <strong>dur_f</strong>: Duration in frames of the ROI - <strong>dur_s</strong>: Duration in seconds of the ROI - <strong>num_pulses</strong>: Number of pulses in the ROI (that also passed filtering during ROI-calling) - <strong>pw_mean</strong>: Mean pulse duration (in seconds) of pulses in the ROI - <strong>ipd_mean</strong>: Mean inter-pulse duration (in seconds) of pulses in the ROI - <strong>snr_mean</strong>: Mean signal-to-noise ratio of pulses in the ROI - <strong>intensity_mean</strong>: Mean intensity above baseline of pulses in the ROI - <strong>binratio_norm</strong>: Estimated pulse bin ratio of pulses in the ROI, according to the following equation: sum(bin0_intensity*dur_f) / np.sum(bin1_intensity*dur_f) - <strong>ROI_score</strong>: ROI quality score (0-1 from least to most likely to contain recognizer-peptide recognition pulsing) - <strong>binratio_skew</strong>: bin ratio correction factor accounting for binning signal timing differences across the chip. This factor has already been applied to the binratio_norm column</pre>
Data and code for article "Excitonic Emission of Monolayer Semiconductors Near-Field Coupled to High-Q Microresonators"
<p>Data, code and sample fabrication details for article "Excitonic Emission of Monolayer Semiconductors Near-Field Coupled to High-Q Microresonators".</p> <p>The code was tested with Matlab R2015b.</p>
Dataset for "Stability and electronic properties of planar defects in quaternary I2-II-IV-VI4 semiconductors"
<p>We are grateful to the UK Materials and Molecular Modelling Hub for computational resources, which is partially funded by EPSRC (EP/P020194/1). The research was supported by the Royal Society and the EU Horizon2020 Framework (STARCELL, Grant No. 720907). J.-S.P. thanks the Royal Society for Shooter International Fellowship.</p>
Data for Nguyen Le at al. ""Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices"
<p>Codes and simulation data used in Nguyen Le at al. "“Topological phases of a dimerized Fermi-Hubbard model for semiconductor nano-lattices."</p>
Dataset for "Electrical and optical control of single spins integrated in scalable semiconductor devices"
<p>Accompanying data for the main text and supplemental materials of <em>Electrical and optical control of single spins integrated in scalable semiconductor devices</em></p>
A Novel Integrated Reference-Counter Electrode for Electrochemical Measurements of HOMO and LUMO Levels in Small-Molecule Thin-Film Semiconductors for OLEDs
<p>This dataset <span>includes all raw data, processed data, and analysis scripts necessary to replicate the findings reported in the published paper.</span></p>
Ultrafast electric control of cavity mediated single-photon and photon-pair generation with semiconductor quantum dots
<p>Dataset of the publication "Ultrafast electric control of cavity mediated single-photon and photon-pair generation with semiconductor quantum dots" (10.1103/PhysRevB.104.085308)</p>
Raw data: Coherent control of a high-orbital hole in a semiconductor quantum dot
<p>This is the raw data supporting the findings in the research article titled "<em>Coherent control of a high-orbital hole in a semiconductor quantum dot</em>". DOI: 10.1038/s41565-023-01442-y</p>
Doping of molecular semiconductors through proton-coupled electron transfer
<p>Doping of molecular semiconductors through proton-coupled electron transfer was conducted. Doping levels, electronic properties, and thin film structures of doped polymeric semiconductors were evaluated through conductivity, UV-Vis-NIR absorption, photoelectron yield, x-ray photoelectron, and x-ray diffraction measurements, where proton-coupled electron transfer reaction enable precise control of doping levels depending on pH of doping solutions under ambient conditions.</p>
Design, synthesis and theoretical simulations of novel spiroindane-based enamines as p-type semiconductors
Open the record for dataset details and reuse information.
Data from: β-Phase Yb5Sb3Hx: Magnetic and thermoelectric properties traversing from an electride to a semiconductor
Open the record for dataset details and reuse information.
Improved effective equation for the Rashba spin-orbit coupling in semiconductor 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 and Elsa Prada,<em> </em><strong><em>Improved effective equation for the Rashba spin-orbit coupling in semiconductor nanowires</em></strong>, arXiv:2001.04375 (2020)".</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>
Preparation and performance of Al3+-doped BiVO4 semiconductor photocatalysts
<p><span><span>The</span> <span>xAl<sup>3+</sup>/BiVO</span><sub><span><span>4</span></span></sub> <span>(x</span><span>=</span><span>0,</span> <span>1%,</span> <span>2%,</span> <span>5%,</span> <span>10%)</span> <span>semiconductor composite photocatalysts were successfully prepared by hydrothermal method</span><span>, and t</span><span>he removal efficiency of organic pollutants was improved in</span> <span>different degrees</span> <span>under the conditions of visible light irradiation.</span> <span>The results showed that proper Al</span><sup><span><span>3+</span></span></sup><span> doping could improve the morphology of BiVO</span><sub><span><span>4</span></span></sub><span>,</span><span> n</span><span>arrow</span> <span>the</span> <span>band gap and expand the absorption range of visible light.</span><span> M</span><span>eanwhile,</span> <span>Al</span><sup><span><span>3+</span></span></sup><span> acted </span><span>as</span><span> a </span><span>capture center </span><span>for</span><span> photogenerated</span> <span>electrons,</span> <span>reducing the</span> <span>recombination rate</span> <span>of</span> <span>the</span> <span>photogenerated</span> <span>electron-hole pair.</span> <span>When the doping amount of Al</span><sup><span><span>3+</span></span></sup> <span>was</span> <span>1%,</span><span> t</span><span>he photocatalytic activity</span><span> was </span><span>maximized,</span> <span>and the removal rate</span> <span>of RhB</span><span> with</span><span>in</span> <span>90min</span> <span>was as high as 96%</span><span>, t</span><span>his </span><span>was</span><span> an improvement of about 4</span><span>3</span><span>% compared</span> <span>to</span> <span>pure BiVO</span><sub><span><span>4</span></span></sub><span>.</span> <span>In the whole reaction system</span><span>, </span><span>e</span><sup><span><span>-</span></span></sup><span>, h</span><sup><span><span>+</span></span></sup><span> and </span><span>·</span><span>OH were the main active species</span><span>, </span><span>contributing 71.92%, 18.45% and 6.53% to the degradation of RhB, respectively.</span></span></p>
Large zero-bias peaks in InSb-Al hybrid semiconductor-superconductor nanowire devices
<p>Measurement data, data processing scripts and figure generating notebooks for Zhang et al., "Large zero-bias peaks in InSb-Al hybrid semiconductor-superconductor nanowire devices".</p>
Datasets for figure files in "A map of high mobility molecular semiconductors", Nature Materials (2017)
<p>The data contained here correspond to the figure files appearing in the work "A map of high mobility molecular semiconductors", published in Nature Materials (2017)</p>
Date for Unveiling Pseudo-Inert Basal Plane for Electrocatalysis in 2D Semiconductors: Critical Role of Reversal-Activation Mechanism
<p>The dateset contains the crystal structures of monolayer CrP, CrAs, Cr2PAs and Cr2PSb, and the most stable adsorption configurations of NO, N2, O2 and CO on monolayer CrP, CrAs, Cr2PAs and Cr2PSb.</p>
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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.