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Dataset results
144 results for “Semiconductor”
Gate-tunable subband degeneracy in semiconductor nanowires
<p>This repository contains the raw data and processing codes within the paper "Gate-tunable subband degeneracy in semiconductor nanowires".</p>
Semiconductor Porous Hydrogen-Bonded Organic Frameworks Based on Tetrathiafulvalene Derivatives
<p>Relevant data for publication with DOI:</p> <table> <tbody> <tr> <td><a href="https://doi.org/10.1021/jacs.1c07802"><span>https://doi.org/10.1021/jacs.1c07802</span></a></td> </tr> </tbody> </table>
In Vivo Near-Infrared Imaging Using Ternary Selenide Semiconductor Nanoparticles with an Uncommon Crystal Structure
<p>Dataset of </p> <table> <tbody> <tr> <td>https://zenodo.org/record/5793282#.YcCG4GjMJPY</td> </tr> </tbody> </table>
Data for: "Exciton transport in molecular organic semiconductors boosted by transient quantum delocalization"
<p>Data: Figure 2 (all panels), Figure 3 (all panels), Figure 4 (all panels), Figure 5 (all panels)</p>
Data underlying "Ballistic superconductivity in semiconductor nanowires"
<p>This repository contains the raw data underlying <a href="https://dx.doi.org/10.1038/ncomms16025">H. Zhang <em>et al</em>. Ballistic superconductivity in semiconductor nanowires. Nat. Commun. <strong>8,</strong> 16025 (2017)</a></p> <p>It also contains python notebooks for plotting data as shown in the paper, as well as additional plots, developed in 2022.</p>
Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '
<p>Data of "Universal platform for scalable semiconductor-superconductor nanowire networks '</p>
Data and analysis scripts for the paper 'Phase flip code with semiconductor spin qubits'
<p>Data and analysis scripts for the paper:</p> <p>Phase flip code with semiconductor spin qubits.</p> <p>Authors: F. van Riggelen, W. I. L. Lawrie, M. Russ, N. W. Hendrickx, A. Sammak,<br> M. Rispler, B. M. Terhal, G. Scappucci, and M. Veldhorst</p> <p>data for the figures for the version of this paper to be published in npj Quantum Information</p> <p>preprint on arXiv: https://arxiv.org/abs/2202.11530, for data supporting the preprint see: https://doi.org/10.5281/zenodo.6413948</p>
Kerr nonlinearity and parametric amplification with an Al-InAs superconductor-semiconductor Josephson junction
<h1>Brief description</h1> <p><br>This repository contains data, code, and other materials for "Kerr nonlinearity and parametric amplification with an Al-InAs superconductor-semiconductor Josephson junction". Files are zipped by types (data, fabrication, measurement code and results) and experiments (Kerr nonlinearity measurements and parametric amplifier experiment).</p> <h1><br>Data formats:</h1> <p>.db: database file storing all measured data. QCoDeS version 0.39.1, QCoDeS github repo: https://github.com/microsoft/Qcodes. Please refer to 'plottr' tool to view the database files: https://github.com/toolsforexperiments/plottr . Plottr version: 0.0<br>.gds: GDSII pattern files for Litography<br>.ipynb: ipython notebooks that run measurements<br>.py: python scripts for generating the GDSII patterns or conducting measurements<br>.emz: AWR projects (model and data), AWR design environment version is 22.1<br>others: figures, etc..</p> <h1><br>File structure and instruction:</h1> <p>GDS patterns << GDS files for simulations and device fabrication<br> 4cavtunable_nocost_Q150-300_top-GND_bot-OP.gds << the GDS for device B, used in AWR simulation for BBQ model.<br> Distributed_JJFET_sim_v12.gds << the GDS for device A, used in AWR simulation for BBQ model.<br> Distributed_JJFET_sim_v12.py << the python script to generate the 'sim' GDS<br> Distributed_JJFET_v12.gds << the GDS pattern for fabrication (e-beam lithography)<br> Distributed_JJFET_v12.py << the python script to generate the 'fab' GDS<br>AWR_simulation << files of microwave simulations<br> Compare_P1db.ipynb << simulate P1dB of AlOx based JPA and Al-InAs based JPA<br> plots << Raw plots from Compare_P1db.ipynb<br> 202312 single JJ compression power.emz << AWR project for simulating P1dB of AlOx based JPA and Al-InAs based JPA<br> extra data << extra AWR data (user-defined format) to plot the gain versus pump frequency and power for Al-InAs based JPA - AWR tends to run out of system memory, therefore I manually divided the simulation task into small segements, and save data after each small tasks.<br> Series BBQ - device B.emz << AWR project to derive the BBQ model for device B<br> Series BBQ - device A.emz << AWR project to derive the BBQ model for device A<br>Code-Kerr-measurement<br> Compute and compare c4c2 << code that takes the measured Kerr into the c4/c2 ratio <br> Kerr fit device A.ipynb << code to analyze Kerr of device A, database file needed is jjfeta0425.db<br> Kerr fit device B.ipynb << code to analyze Kerr of device B, database file needed is 0722.db<br> Data_analysis_IMD.ipynb << code to analyze Kerr of device B using intermodulation spectroscopy, data needed is Data_IMD<br> Data_analysis_plots << Raw plots from data analysis codes<br>Code-Parametric_amp<br> Data_acquisition.ipynb << code to take measurements<br> Data_analysis_parametric_noise_ratio_plot.ipynb << code for analyzing the noise visibility ratio of the 4WM amp, database files needed are jjfeta0226.db <br> Data_analysis_parametric_amp.ipynb << code for analyzing the parametric amplification, including gain, bandwidth etc., database files needed are jjfeta0226.db, jjfeta0225.db, jjfeta0223.db, jjfetamp0113-3.db<br> Data_analysis_plots << Raw plots from data analysis codes<br>Data << raw data for analysis<br> Data-4WM_parametric_amplifier << data for the parametric amplifier<br> jjfeta0226.db <br> jjfeta0225.db<br> jjfeta0223.db<br> jjfetamp0113-3.db<br> Data-Kerr_measurement << data for the Kerr measurement (Stark shift)<br> jjfeta0425.db<br> 0722.db<br> Data_IMD << data for the Kerr measurement on device B (IMD)</p>
Quantized Andreev conductance in semiconductor nanowires
<p>This repository contains the raw data and processing codes within the paper "Quantized Andreev conductance in semiconductor nanowires".</p>
Strain fingerpringting of exciton valley character in 2D semiconductors
<p>Raw data which are used to generate the figures in the publication 'Strain fingerpringting of exciton valley character in 2D semiconductors'.</p> <p>Abstract of the paper:</p> <p>Intervalley excitons with electron and hole wavefunctions residing in different valleys determine the long-range transport and dynamics observed in many semiconductors. However, these excitons with vanishing oscillator strength do not directly couple to light and, hence, remain largely unstudied. Here, we develop a simple nanomechanical technique to control the energy hierarchy of valleys via their contrasting response to mechanical strain. We use our technique to discover previously inaccessible intervalley excitons associated with K, Γ, or Q valleys in prototypical 2D semiconductors WSe2 and WS2. We also demonstrate a new brightening mechanism, rendering an otherwise “dark” intervalley exciton visible via strain-controlled hybridization with an intravalley exciton. Moreover, we classify various localized excitons from their distinct strain response and achieve large tuning of their energy. Overall, our valley engineering approach establishes a new way to identify intervalley excitons and control their interactions in a diverse class of 2D systems.</p>
Fundamentals of cathodoluminescence in a STEM: The impact of sample geometry and electron beam energy on light emission of semiconductors_experimental dataset
<p>This dataset contains the raw underlying data for the paper "Fundamentals of cathodoluminescence in a STEM: The impact of sample geometry and electron beam energy on light emission of semiconductors" available in open acess under DOI 10.5281/zenodo.2668222. The archive contains experimental files titled with references to the figures as they appear in the paper. </p>
Supporting Data for the Manuscript "Anionic Disorder and its Impact on the Surface Electronic Structure of Oxynitride Photoactive Semiconductors"
<p>This data repository provides additional data for the manuscript "Anionic disorder and its impact on the surface electronic structure of oxynitride photoactive<br>semiconductors". The data sets comprise the PES raw data files in *.h5 format, the results from RBS/ERDA measurements, and quantification of the surface N:O ratios using TEM in EDX mode.</p> <ul> <li>"BT8c" labels the BTON sample before PEC.</li> <li>"BT8a" labels the BTON sample after PEC.</li> </ul>
Data underlying the paper titled "Strong coupling in metal-semiconductor microcavities featuring Ge quantum wells: a perspective study"
Open the record for dataset details and reuse information.
Ion sensors based on organic semiconductors acting as quasi-reference electrodes
<p>We report electric double-layer transistors with organic semiconductors in single-crystal forms for ion sensing. High operational stability of our transistors enabled them to serve as quasi-reference electrodes, which show one-to-one relationship between the source electrode potential and device resistance. Differential measurements between our sensing and reference transistors demonstrated ion concentration sensing without a conventional reference electrode.</p>
Dataset of Semiconductor WO3 Thin Films Deposited by Pulsed Reactive Magnetron Sputtering
<p>A detailed description of the files related to each image with graphs is included in README.pdf and README.txt. All data were measured and calculated as outlined in the manuscript, with no additional non-standard data filtering applied. Measurement errors are indicated in the graphs and discussed in the manuscript, with references provided.</p>
Data and analysis for the paper Qubits made by advanced semiconductor manufacturing
<p>Data and analysis scripts for the paper:</p> <p>Qubits made by advanced semiconductor manufacturing</p> <p>by A.M.J. Zwerver,<em> et al.</em></p>
Charting the Lattice Thermal Conductivities of I-III-VI2 Chalcopyrite Semiconductors
<p>Dataset of VASP and ShengBTE calculations for the chalcopyrites collection considered in the article.</p>
Quantum-optical excitations of semiconductor nanostructures in a microcavity using a two-band model and a single-mode quantum field
<p>Dataset of the publication "Quantum-optical excitations of semiconductor nanostructures in a microcavity using a two-band model and a single-mode quantum field" H. Rose, A. N. Vasil’ev, O. V. Tikhonova, T. Meier, and P. R. Sharapova, Phys. Rev. A <strong>107</strong>, 013703 (2023). ( https://doi.org/10.1103/PhysRevA.107.013703 ). The zip file includes the data on which the plots shown in figures 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, and 11 are based.</p>
Dataset for "Lateral Charge Migration in 1D Semiconductor-Metal Hybrid Photocatalytic Systems"
<p>This is the dataset including absorption, photoluminescence quantum yield, and transient absorption spectroscopy.</p>
Theoretical analysis of four-wave mixing on semiconductor quantum dot ensembles with quantum light
<p>Dataset of the publication "Theoretical analysis of four-wave mixing on semiconductor quantum dot ensembles with quantum light" H. Rose, S. Grisard, A. V. Trifonov, R. Reichhardt, M. Reichelt, M. Bayer, I. A. Akimov, and T. Meier, Proc. SPIE 12419, Ultrafast Phenomena and Nanophotonics XXVII, 124190H (2023). ( <a href="https://doi.org/10.1117/12.2647700">https://doi.org/10.1117/12.2647700</a> ). The zip file includes the data on which the plots shown in figures 1 and 2 are based.</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.