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89 results for “plasmonics”
Screening compounds of interest against USP5 Zf-UBD with a surface plasmon resonance assay
<p>The determination of binding affinities of compounds of interest against USP5 zinc finger ubiquitin binding domain (Zf-UBD) with a surface plasmon resonance (SPR) assay. </p>
Dataset used in manuscript: "Monolayer and thin h–BN as substrates for electron spectro-microscopy analysis of plasmonic nanoparticles "
<p>This file contains raw data for the manuscript:<br> "Monolayer and thin h–BN as substrates for electron spectro-microscopy analysis of plasmonic nanoparticles"<br> Tizei LHG et al, Applied Physics Letters 113, 231108 (2018).</p> <p>The data is electron energy loss spectroscopy (EELS) hyperspectral images of gold nanotriangles on different substrates.</p> <p>Data can be opened and manipulated using Hyperspy (www.hyperspy.org), Numpy and Matploplib libraries available in Python 3. The file formats used were HSPY (based HDF5 open standard) and MSA.</p> <p>Each folder contains the following data for all the triangles used in the manuscript:</p> <p>1) One annular dark field image of the triangle in HSPY format;<br> 2) One spectrum image aligned (the zero-loss speak is set to 0 eV) in HSPY format;<br> 3) Three spectra, one for each tip, already after deconvolution (20 steps using a home-made script in Digital Micrograph) in MSA format;<br> 4) The zero-loss spectrum used for the deconvolution of the data in MSA format;</p> <p>The file names have a specific format to facilite scripting:</p> <p>1) finishes with "Calibrated.hspy";<br> 2) finishes with "aligned.hspy";<br> 3) finishes with "TipX.msa" where X is 1, 2 or 3;<br> 4) finishes with "Summed.msa";</p> <p>Data acquisition parameters are described in the manuscript: Tizei LHG et al APL 113, 231108 (2018).</p>
Data set for the manuscript 'Studying the different coupling regimes for a plasmonic particle in a plasmonic trap'
<p>This repository includes data set and Matlab scripts, which support the manuscript entitled 'Studying the different coupling regimes for a plasmonic particle in a plasmonic trap', published in Optics Express. We include the data set necessary to reproduce the results of the paper in the 'RawData.zip' file. We provide Matlab scripts and functions in the 'PostProcessing.zip' file to process the raw data. We also attach HTML documents explaining the data and how we process them. </p> <p><strong>Raw data visualization with python.html</strong>: This is the first HTML file containing all the information to understand and visualize the raw data. It is generated by Jupyter Notebook, and it includes python scripts to visualize the raw data.</p> <p><strong>Post-processing raw data using Matlab.html</strong>: This is the second HTML file, which gives you a guideline to the data processing routines with the explanations of the Matlab scripts and functions. </p> <p><strong>RawData.zip</strong>: the data set used to produce the results in the manuscript. </p> <p><strong>PostProcessing.zip</strong>: Matlab scripts and functions for data post-processing.</p> <p><strong>python.zip</strong>: python files</p> <p>Note: This version update includes the additional data set for the revision of the manuscript. </p>
Data for "Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators"
<p>This upload includes the data presented and analyzed in the article "Controlling Plasmonic Catalysis via Strong Coupling with Electromagnetic Resonators" by Jakub Fojt, Paul Erhart, and Christian Schäfer.</p> <p>The codes for reproducing the data are provided at <a href="https://doi.org/10.5281/zenodo.13374591">doi:10.5281/zenodo.13374591</a>.</p> <p>See <em>README.md</em> in <em>data.zip</em> for a detailed description.</p>
Reports and Dataset of SUPRAMOLECULAR POLYMERS AS MOULDS FOR THE SYNTHESIS OF CHIRAL PLASMONIC NANOPARTICLES
<p>This dataset contains some research data on supramolecular polymers as templates for the synthesis of chiral plasmonic nanoparticles. Project PID2020-117885GA-I00, especifically the more related to the use of cysteine and cystine. </p>
Plasmonic Metasurface Resonators to Enhance Terahertz Magnetic Fields for High-Frequency Electron Paramagnetic Resonance _experimental dataset
<p>This dataset contains the raw experimental data for Tesi et al., Plasmonic Metasurface Resonators to Enhance Terahertz Magnetic Fields for High-Frequency Electron Paramagnetic Resonance, Small Methods 2021, 2100376, DOI <a href="https://doi.org/10.1002/smtd.202100376">10.1002/smtd.202100376</a>. </p>
Time-Resolved Plasmon-Assisted Generation of Arbitrary Optical-Vortex Pulses- Dataset
<p>This folder contains raw data and information to reproduce the findings of the article titled 'Time-Resolved Plasmon-Assisted Generation of Arbitrary Optical-Vortex Pulses' . Each folder corresponds to a figure in the article.</p> <p>Raw data is provided for the calculations along with the input file and output log of the calculation. When raw data is too large, it is possible to reproduce the calculation from the provided input file. Calculations are performed with <a href="https://octopus-code.org/documentation/12/">Octopus code</a> , the related version and commit number of the code can be retrieved from output log file provided in calculation folder.</p>
Plasmonic Nanophotothermal Therapy of Atherosclerosis
ClinicalTrials.gov study NCT01270139. IPD Sharing: YES. Countries: 2. Publications: 6.
Data from: Robust purcell effect of CsPbI3 quantum dots using nonlocal plasmonic metasurfaces
Open the record for dataset details and reuse information.
Data from: Acoustic wave modulation of gap plasmon cavities
Open the record for dataset details and reuse information.
Data for "Hot-Carrier Generation in Plasmonic Nanoparticles: The Importance of Atomic Structure"
<p>This upload includes the data presented and analyzed in the article "Hot-Carrier Generation in Plasmonic Nanoparticles: The Importance of Atomic Structure" by Tuomas P. Rossi, Paul Erhart, and Mikael Kuisma.</p> <p>The codes for reproducing the data are provided at <a href="http://doi.org/10.5281/zenodo.3964229">doi:10.5281/zenodo.3964229</a>.</p> <p>See <em>README.md</em> in <em>data.zip</em> for a detailed description.</p>
Vibrational Probe at the Electrochemical Interface: Dependence on Plasmon Coupling and Potential on the Lineshape in Two-Dimensional Infrared Spectroscopy
<p>These files contain the data presented in the research article: Vibrational Probe at the Electrochemical Interface: Dependence on Plasmon Coupling and Potential on the Lineshape in Two-Dimensional Infrared Spectroscopy by Melissa Bodine, Vepa Rozyyev, Jeffrey W. Elam, Andrei Tokmakoff and Nicholas H. C. Lewis J. Phys. Chem. Lett., (2023)</p>
Plasmonic Au@Ag@mSiO2 Nanorattles for In Situ Imaging of Bacterial Metabolism by Surface-Enhanced Raman Scattering Spectroscopy
<p>Related publication: De Marchi, S; García-Lojo, D; Bodelón, G; Pérez-Juste, J; Pastoriza-Santos, I. Plasmonic Au@Ag@mSiO<sub>2</sub> Nanorattles for In Situ Imaging of Bacterial Metabolism by Surface-Enhanced Raman Scattering Spectroscopy. <em>ACS Applied Materials & Interfaces</em> 2021. <a href="http://doi.org/10.1021/acsami.1c21812">DOI: 10.1021/acsami.1c21812</a>.</p> <p> </p> <p>Abstract:</p> <p>It is well known that microbial populations and their interactions are largely influenced by their secreted metabolites. Noninvasive and spatiotemporal monitoring and imaging of such extracellular metabolic byproducts can be correlated with biological phenotypes of interest and provide new insights into the structure and development of microbial communities. Herein, we report a surface-enhanced Raman scattering (SERS) hybrid substrate consisting of plasmonic Au@Ag@mSiO<sub>2</sub> nanorattles for optophysiological monitoring of extracellular metabolism in microbial populations. A key element of the SERS substrate is the mesoporous silica shell encapsulating single plasmonic nanoparticles, which furnishes colloidal stability and molecular sieving capabilities to the engineered nanostructures, thereby realizing robust, sensitive, and reliable measurements. The reported SERS-based approach may be used as a powerful tool for deciphering the role of extracellular metabolites and physicochemical factors in microbial community dynamics and interactions.</p>
Applications of machine learning tools for ultra-sensitive detection of lipoarabinomannan with plasmonic grating biosensors in clinical samples of tuberculosis
Background <p>Tuberculosis is one of the top ten causes of death globally and the leading cause of death from a single infectious agent. Eradicating the Tuberculosis epidemic by 2030 is one of the top United Nations Sustainable Development Goals. Early diagnosis is essential to achieving this goal because it improves individual prognosis and reduces transmission rates of asymptomatic infected. We aim to support this goal by developing rapid and sensitive diagnostics using machine learning algorithms to minimize the need for expert intervention. </p> Methods and Findings <p>A single-molecule fluorescence immunosorbent assay was used to detect the Tuberculosis biomarker lipoarabinomannan from a set of twenty clinical patient samples and a control set of spiked human urine. Tuberculosis status was separately confirmed by GeneXpert MTB/RIF and cell culture. Two machine learning algorithms, an automatic and a semiautomatic model, were developed and trained by the calibrated lipoarabinomannan titration assay data and then tested against the ground truth patient data. The semiautomatic model differed from the automatic model by an expert review step in the former, which calibrated the lower threshold to determine single molecules from background noise. The semiautomatic model was found to provide 88.89% clinical sensitivity, while the automatic model resulted in 77.78% clinical sensitivity.</p> Conclusions <p>The semiautomatic model outperformed the automatic model in clinical sensitivity as a result of the expert intervention applied during calibration and both models vastly outperformed manual expert counting in terms of time-to-detection and completion of analysis. Meanwhile, the clinical sensitivity of the automatic model could be improved significantly with a larger training dataset. In short, semiautomatic, and automatic Gaussian Mixture Models have a place in supporting rapid detection of Tuberculosis in resource-limited settings without sacrificing clinical sensitivity.</p>
Second Harmonic Generation from Grating-Coupled Hybrid Plasmon-Phonon Polaritons - Experimental and Simulation Data
<p>Experimental and simulation data for "Second Harmonic Generation from Grating-Coupled Hybrid Plasmon-Phonon Polaritons" by Marcel Kohlmann et al., recently (10/22) accepted for publication in Applied Physics Letters. A preprint is available on the <a href="https://arxiv.org/abs/2209.00375">arXiv</a>. </p> <p>Content:<br> We provide matlab code to generate the figures from the experimental and simulated data.</p> <p>fig1.m: generates fig1c,d of the paper<br> fig2_4.m generates fig 2 and 4<br> fig3.m generates fig3</p> <p>experimental_data.zip contains all experimental data, please unzip before running the scripts<br> comsol_data.zip contains all Comsol simulation output data. Please unzip before running the scripts.</p> <p>The remaining matlab scripts are needed in the process. "passler_epsTarray_generator.m" is also part of the transfer matrix implementation available on <a href="https://doi.org/10.5281/zenodo.7034720">Zenodo</a>.</p> <p>Please contact <a href="mailto:alexander.paarmann@fhi-berlin.mpg.de">Alex Paarmann</a> for any questions.</p>
Lysozyme-sensitive plasmonic hydrogel nanocomposite for colorimetric dry-eye inflammation biosensing_[Biosensing]
<p>Biosensing of a lysozyme-sensitive plasmonic hydrogel</p>
Lysozyme-sensitive plasmonic hydrogel nanocomposite for colorimetric dry-eye inflammation biosensing_[Photoresponsivity]
<p>Photoresponsivity of a lysozyme-sensitive plasmonic hydrogel</p>
Lysozyme-sensitive plasmonic hydrogel nanocomposite for colorimetric dry-eye inflammation biosensing_[Colorimetric Tests]
<p>Colorimetric tests for a lysozyme-sensitive plasmonic hydrogel.</p>
Dataset for "Full-wave Modelling of Terahertz Frequency Plasmons in Two-Dimensional Electron Systems"
<p>Dataset underpinning the paper "Full-wave Modelling of Terahertz Frequency Plasmons in Two-Dimensional Electron Systems" by A. Dawood et al 2019 <em>J. Phys. D: Appl. Phys.</em> https://doi.org/10.1088/1361-6463/ab0ab7</p>
Dataset underpinning the paper "Terahertz plasmon resonances in two-dimensional electron systems: Modeling approaches" by S. Siaber et al 2019 Phys. Rev. Appl.
<p>Dataset underpinning the paper "Terahertz plasmon resonances in two-dimensional electron systems: Modeling approaches" by S. Siaber et al 2019 Phys. Rev. Appl.</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.