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19 results for “optical tweezer”
Optical tweezer platform for the characterization of pH-triggered colloidal transformations in the oleic acid/water system
<p>Hypothesis: Soft colloidal particles that respond to their environment have innovative potential for many fields ranging from food and health to biotechnology and oil recovery. The in situ characterisation of colloidal transformations that triggers the functional response remain a challenge.</p> <p>Experiments: This study demonstrates the combination of an optical <a href="https://www.sciencedirect.com/topics/physics-and-astronomy/micromanipulation">micromanipulation</a> platform, polarized optical video microscopy and <a href="https://www.sciencedirect.com/topics/physics-and-astronomy/microfluidics">microfluidics</a> in a comprehensive approach for the analysis of pH-driven structural transformations in emulsions. The new platform, together with <a href="https://www.sciencedirect.com/topics/physics-and-astronomy/synchrotron">synchrotron</a> small angle X-ray scattering, was then applied to research the food-relevant, pH-responsive, <a href="https://www.sciencedirect.com/topics/chemistry/oleic-acid">oleic acid</a> in water system.</p> <p>Findings: The experiments demonstrate structural transformations in individual oleic acid particles from micron-sized onion-type multilamellar oleic acid vesicles at pH 8.6, to nanostructured emulsions at pH < 8.0, and eventually oil droplets at pH < 6.5. The smooth particle-water interface of the onion-type vesicles at pH 8.6 was transformed into a rough particle surface at pH below 7.5. The pH-triggered changes of the interfacial tension at the droplet-water interface together with mass transport owing to structural transformations induced a self-propelled motion of the particle. The results of this study contribute to the fundamental understanding of the structure–property relationship in pH-responsive emulsions for nutrient and drug delivery applications.</p>
Application of optical tweezer technology reveals that PfEBA and PfRH ligands, not PfMSP1, play a central role in Plasmodium-falciparum merozoite-erythrocyte attachment, Supporting Information
<p>This repository contains the dataset and analysis scripts associated with the upcoming publication titled <em>Application of optical tweezer technology reveals that PfEBA and PfRH ligands, not PfMSP1, play a central role in Plasmodium-falciparum merozoite-erythrocyte attachment</em>. The repository includes a comprehensive collection of data and scripts related to optical tweezer experiments, growth assays, qPCR data, and supplementary information. It is organized into several sections, each detailing different aspects of the study:</p> <ul> <li><strong>Growth Assays:</strong> Includes raw and processed data on parasitemia levels, invasion rates, and growth rate assays, along with corresponding Jupyter notebooks and Python scripts for data visualization (e.g., <code>GrowthAssayPlotlib.py</code>, <code>Plot GA1.ipynb</code>, and <code>GA2_df_melted.json</code>).</li> <li><strong>qPCR Data:</strong> Contains results from multiple qPCR runs, including quantification data for various samples, as well as analysis scripts and plotted results (<code>qpcr_plotbench.ipynb</code>, <code>qPCR_plotting.py</code>, etc.). Data files such as <code>.xlsx</code> and <code>.json</code> contain gene expression data and fold changes to NF54.</li> <li><strong>Optical Tweezer Experiments:</strong> Includes detailed results and plots from optical tweezer measurements of attachment forces, time dependence, and multiple merozoite attachments. Notebooks (<code>tweezer_plots.ipynb</code>, <code>Antibody_binding_assay_plots.ipynb</code>) and data files support these analyses.</li> <li><strong>Optical Tweezer Images</strong>: Includes images that were used to measure RBC diameters for deformation and force measurements in <code>.tiff</code> format.</li> <li><strong>Supplementary Information (SI):</strong> Provides additional data and visualizations, such as scatter plots of two stretched RBCs, time post-egress vs. detachment force, and antibody GIA flow data. The accompanying figures (e.g., <code>SupFig1d_egress time vs force_3D7.svg</code>, <code>SupFig5a_GIA.svg</code>) are provided as <code>.svg</code> files.</li> </ul> <p>This repository offers all necessary resources to replicate the findings, including the complete codebase, raw data, and graphical representations of results. Researchers are encouraged to explore the included notebooks and datasets for detailed insights.</p>
Dataset of the article Optical Tweezer Arrays of Erbium Atoms
<p>Datasets of the experimental data of the article Optical Tweezer Arrays of Erbium Atoms. The dataset is organized in folders, one for each figure. The data is written as tables in text files and it includes theoretical curves and fits of the same figure. A Python script is included to reproduce the figures.</p>
On-demand entanglement of molecules in a reconfigurable optical tweezer array
<div> <div> <div> <div> <div> <div> <p>Entanglement is crucial to many quantum applications including quantum information processing, quantum simulation, and quantum-enhanced sens- ing. Because of their rich internal structure and interactions, molecules have been proposed as a promising platform for quantum science. Determinis- tic entanglement of individually controlled molecules has nevertheless been a long-standing experimental challenge. Here we demonstrate on-demand en- tanglement of individually prepared molecules. We deterministically create Bell pairs of molecules by using the electric dipolar interaction between polar molecules prepared using a reconfigurable array of optical tweezer traps. Our results demonstrate the key building blocks needed for quantum applications and may advance quantum-enhanced fundamental physics tests using trapped molecules.</p> </div> </div> </div> </div> </div> </div>
On-demand entanglement of molecules in a reconfigurable optical tweezer array
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Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers - Part II
<p>Dataset Part II for publication "Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers", in Nature Communications.</p>
Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers - Part I
<p>Dataset Part I for publication "Determining intrinsic potentials and validating optical binding forces between colloidal particles using optical tweezers", in Nature Communications.</p>
Measuring age-dependent viscoelasticity of organelles, cells and organisms with Time-Shared Optical Tweezer Microrheology
<p>Source data for Nature Nanotechnology, <span>DOI: 10.1038/s41565-024-01830-y</span></p>
Data collection that describes the calibration of the temporal and displacement characteristics of an optical tweezers in buffered saline at room temperature.
<p><strong>Introduction</strong>. This data provides the calibration of an optical tweezers within the linear Hookian region. Once the laser was aligned, the power at the objective measured and a bead trapped the instrument was calibrated. <strong>Data Collection</strong>. Calibration was performed by moving a trapped bead by supplying a periodic square wave train input (amplitude: −800 to +800 nm, period: 80 ms) to an acousto-optical device, AOD and monitoring the trajectory of the bead in the 𝑋𝑌 plane with a quadrant photo diode, QPD for ~ one minute. Data was collected at 200 kHz from three (3) QPD channels: displacement in the 𝑋 (∆𝑋<sub>𝑀</sub>) (i) and 𝑌 directions (∆𝑌<sub>𝑀</sub>) (ii) and the sum of the fluorescent intensity (∑<sub>𝐿</sub>) (iii). Typically, each bead was stimulated with a train of square waves of constant amplitude in the 𝑋 direction. This stimulation was performed four (4) times at each of the different amplitudes i.e., −800, +800, −500, and +500 nm. The QPD signal in the dark, ∆𝑋<sub>𝐷</sub>, ∆𝑌<sub>𝐷</sub>, ∑<sub>𝐷</sub> was recorded and subtracted in real time, and the gain, 𝐺 of the QPD noted. The Stokes-Faxen coefficient, 𝛽 was calculated having recorded the height of the bead above the Petri dish, ℎ and the viscosity, 𝜂 of the saline solution. The detected fluorescent bead was excited either with a Xenon lamp or TLED transmitted light source. Some calibrations were performed with a TLED light that was borrowed from the manufacturer for testing, and the signal to noise of these measurements was significantly decreased.<strong> Data Transformation</strong>. For each of the two (2) channels the measured signal was normalized by the sum, and the ~750 waves were averaged for each pulse train stimulus. The reciprocal of the time constant (s<sup>-1</sup>) was determined from the exponential rise or decay of the back-ground subtracted averaged response. Spring constant (pN/nm) was determined from the product of this reciprocal time constant and the Stokes-Faxen coefficient (pNs/nm). The net displacement of the bead (nm) was calculated by determining the resultant vector of the 𝑋 and 𝑌 components of the QPD (V/V). For the four (4) stimuli determined for each bead the normalized displacement (V/V) was plotted as a function of net bead displacement and the slope (V/V/nm) calculated from best linear fit. For each calibration the mean spring constant, reciprocal time constant, and mean slope are provided. <strong>Data Format</strong>. The data was saved in LabView with the proprietary TDMS format (National Instruments, NI, Austin, TX). It was transformed to a text file and imported into MATLAB (The Mathworks, Natick, MA) and stored as struct and analyzed with a Python script. The collection contains raw and transformed results from 69 days for a total 153 beads. The data is provided with annotated descriptions in HDF5, a standard non-proprietary container storage format. Each file is about 1.1 GBs (HDF5).</p> <p> </p> <p>The package contains:</p> <p>1. Standard Container HDF5 with custom organization format of data with annotations.</p> <p>2. Python Script (calibrateopticaltweezers.py file) that describes how data is analyzed and written to HDF5 and .MAT formats. (1 file)<br> </p>
Non-spherical particles in optical tweezers: a numerical solution
<p>We present numerical methods for modeling the dynamics of arbitrarily shaped particles trapped within optical tweezers, which improve the predictive power of numerical simulations for practical use. We study the dependence of trapping on the shape and size of particles in a single continuous wave beam setup. We also consider the implications of different particle compositions, beam types and media. The major result of the study is that for different irregular particle shapes, a range of beam powers generally leads to trapping. The trapping power range depends on whether the particle can be characterized as elongated or flattened, and the range is also limited by Brownian forces.</p> <p>This dataset supplements the publication and contains inputs and processing scripts for usage of scadyn (https://www.github.com/jherrane/scadyn) software for solving dynamical response of arbitrarily shaped particles in electromagnetic fields. Also is contained the minimal dataset (per PLos ONE standards) to reproduce the results presented.</p>
Source data for: Raman sideband cooling of molecules in an optical tweezer array
<p>Ultracold molecules, because of their rich internal structures and interactions, have been proposed as a promising platform for quantum science and precision measurement. Direct laser-cooling promises to be a rapid and efficient way to bring molecules to ultracold temperatures. For trapped molecules, laser-cooling to the quantum motional ground state remains an outstanding challenge. A technique capable of reaching the motional ground state is Raman sideband cooling, first demonstrated in trapped ions and atoms. In this work, we demonstrate for the first time Raman sideband cooling of molecules. Specifically, we demonstrate 3D Raman cooling for single CaF molecules trapped in an optical tweezer array, achieving average radial (axial) motional occupation as low as $\bar{n}_r=0.27(7)$ ($\bar{n}_z=7.0(10)$). Notably, we measure a 1D ground state fraction as high as 0.79(4), and a motional entropy per particle of $s = 4.9(3)$, the lowest reported for laser-cooled molecules to date. These lower temperatures could enable longer coherence times and higher fidelity molecular qubit gates desirable for quantum information processing and quantum simulation. With further improvements, Raman cooling could also be a new route towards molecular quantum degeneracy applicable to many laser-coolable molecular species including polyatomic ones. </p>
Source data for: Raman sideband cooling of molecules in an optical tweezer array
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Data from: Erasure-cooling, control, and hyper-entanglement of motion in optical tweezers
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Coherent acoustic frequency comb via floquet engineering of optical tweezer phonon lasers
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Data for An Optical Tweezer Array of Ultracold Molecules
<p>Data for figures</p>
Seconds-scale coherence on an optical clock transition in a tweezer array (publication data)
<p>Accompanying data for<em> Seconds-scale coherence on an optical clock transition in a tweezer array.</em></p>
Datasets for optical tweezer autoregressive hidden Markov modeling
<p>Data to regenerate figures and tables analyzing optical tweezer data with arHMM. OT_arHMM.zip contains the ot_arhmm library needed to analyze these files. scripts.zip contains all the jupyter notebooks used to analyze data and make figures and tables. data.zip contains the raw data and processed_data.zip contains data that has already been put through the HMMs for analysis. These processed files can be generated from the raw data by running the analyze_all.ipynb notebook. All other notebooks require processed files to be present before running.</p>
Data for Dipolar spin-exchange and entanglement between molecules in an optical tweezer array
<p>Data for Dipolar spin-exchange and entanglement between molecules in an optical tweezer array</p>
Data for "A quantum-network register assembled with optical tweezers in an optical cavity"
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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.