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421 results for “Polymer”
Data set for theh paper "Recovery of Polymer Electrolyte Fuel Cell exposed to sulfur dioxide" DOI:10.1016/j.ijhydene.2016.01.077
<p>This Excel file contains the data from the following publication</p> <p><br /> Biraj Kumar Kakatia, Anusree Unnikrishnan, Natarajan Rajalakshmi, RI Jafri, KS Dhathathreyan, Anthony RJ Kucernak</p> <p>Recovery of Polymer Electrolyte Fuel Cell exposed to sulfur dioxideInternational Journal of Hydrogen Energy</p> <p>2016</p> <p>DOI:10.1016/j.ijhydene.2016.01.077</p>
Dataset for paper "Investigation of convective transport in the so-called 'gas diffusion layer' used in polymer electrolyte fuel cell"
<p>Dataset containing all data for figures and supplemental material for the paper:<br /> Investigation of convective transport in the porous media of a fuel cell-like system</p> <p>O. Beruski, T. Lopes, A. R. Kucernak and J. Perez.</p>
Data file for the paper "Using corrosion-like processes to remove poisons from electrocatalysts: a viable strategy to chemically regenerate irreversibly poisoned polymer electrolyte fuel cells", Electrochimica Acta 2016, DOI: 10.1016/j.electacta.2016.11.054
<p>Data used in producing the figures in the paper described below</p> <p>If you use this data then please specify as a reference</p> <p>B. K. Kakati, A. R. J. Kucernak, and K Fahy, "Using corrosion-like processes to remove poisons from electrocatalysts: a viable strategy to chemically regenerate irreversibly poisoned polymer electrolyte fuel cells "Electrochimica ActaDOI: 10.1016/j.electacta.2016.11.054</p> <p>Supported by funding from the Engineering and Physical Sciences Research Council under project EP/I037024/1 and the Technology Strategy board under the IDP11 framework for project 102283. </p>
Confined diffusion of nanoparticles inserted into a diblock polymer membrane captured by fluorescence microscopy
<p>The membrane average pore size was 1µm with a standard deviation of 0.25µm. The video was record by 50 FPS. For more information please see </p> <p>Haramagatti CR, Schacher FH, Müller AHE, Köhler J. Diblock copolymer<br> membranes investigated by single-particle tracking. Phys Chem Chem Phys.<br> 2011;13(6):2278–2284. doi:10.1039/c0cp01658f</p>
ToPoRg-18k: dataset of single-chain radii of gyration distribution for 18,450 architecturally diverse and chemically patterned coarse-grained polymers
<blockquote> <p>Revision: This revision includes four independent trajectory values of the ensemble averages of the mean squared radii of gyration and their standard deviations, which can be used to compute statistical measures such as the standard error.</p> </blockquote> <p>This distribution provides access to 18,450 configurations of coarse-grained polymers. The data is provided as a serialized object using the `pickle' Python module and in csv format. The data was compiled using Python version 3.8. </p> <p><strong>References<br></strong>The specific applications and analyses of the data are described in <br>1. Jiang, S.; Webb, M.A. "Physics-Guided Neural Networks for Transferable Prediction of Polymer Properties"</p> <p><strong>Data<br></strong>There are seven .pickle files that contain serialized Python objects.</p> <ul> <li><strong>pattern_graph_data_*_*_rg_new.pickle</strong>: squared radii of gyration distribution from MD simulation. The number indicates the molecular weight range.</li> <li><strong>rg2_baseline_*_new.pickle</strong>: squared radii of gyration distribution from Gaussian chain theoretical prediction.</li> <li><strong>delta_data_v0314.pickle</strong>: torch_geometric training data.</li> </ul> <p><strong>Usage</strong><br>To access the data in the .pickle file, users can execute the following:</p> <blockquote> <p># LOAD SIMULATION DATA<br>DATA_DIR = "your/custom/dir/"<br>mw = 40 # or 90, 190 MWs</p> <p>filename = os.path.join(DATA_DIR, f"pattern_graph_data_{mw}_{mw+20}_rg_new.pickle")<br>with open(filename, "rb") as handle:<br> graph = pickle.load(handle)<br> label = pickle.load(handle)<br> desc = pickle.load(handle)<br> meta = pickle.load(handle)<br> mode = pickle.load(handle)<br> rg2_mean = pickle.load(handle)<br> rg2_std = pickle.load(handle) ** 0.5 # var</p> <p># combine asymmetric and symmetric star polymers<br>label[label == 'stara'] = 'star'<br># combine bottlebrush and other comb polymers<br>label[label == 'bottlebrush'] = 'comb' </p> <p># LOAD GAUSSIAN CHAIN THEORETICAL DATA<br>with open(os.path.join(DATA_DIR, f"rg2_baseline_{mw}_new.pickle"), "rb") as handle:<br> rg2_mean_theo = pickle.load(handle)[:, 0]<br> rg2_std_theo = pickle.load(handle)[:, 0]</p> </blockquote> <ul> <li><strong>graph</strong>: NetworkX graph representations of polymers.</li> <li><strong>label</strong>: Architectural classes of polymers (e.g., linear, cyclic, star, branch, comb, dendrimer).</li> <li><strong>desc</strong>: Topological descriptors (optional).</li> <li><strong>meta</strong>: Identifiers for unique architectures (optional).</li> <li><strong>mode</strong>: Identifiers for unique chemical patterns (optional).</li> <li><strong>rg2_mean</strong>: Mean squared radii of gyration from simulations.</li> <li><strong>rg2_std</strong>: Corresponding standard deviation from simulations.</li> <li><strong>rg2_mean_theo</strong>: Mean squared radii of gyration from theoretical models.</li> <li><strong>rg2_std_theo</strong>: Corresponding standard deviation from theoretical models.</li> </ul> <p><strong>Help, Suggestions, Corrections?</strong><br>If you need help, have suggestions, identify issues, or have corrections, please send your comments to Shengli Jiang at sj0161@princeton.edu</p> <p><strong>GitHub</strong><br>Additional data and code relevant for this study is additionally accessible at <a href="https://github.com/webbtheosim/gcgnn">https://github.com/webbtheosim/gcgnn</a> </p>
Effect of glycerol trilevulinate plasticizer on thermal and mechanical properties of PHB, PHBV, PLA, PVC and PCL polymers
Open the record for dataset details and reuse information.
Dataset of article : A phenazine-based conjugated microporous polymer as high performing cathode for aluminium-organic batteries
<p>Data used for preparation of the article : A phenazine-based conjugated microporous polymer as high performing cathode for aluminium-organic batteries</p><p> Abstract of article: </p><p>Here, we present one of the first examples of a phenazine-based hybrid microporous polymer, referred to as IEP-27-SR, utilized as an organic cathode in an aluminium battery with an AlCl3-EMIMCl ionic liquid electrolyte. The preliminary redox and charge storage mechanism of IEP-27-SR was confirmed by ex situ ATR-IR and EDS analyses. The introduction of phenazine active units in a robust microporous framework resulted in a remarkable rate-capability (specific capacity of 116 mAh g-1 at 0.5C with 77% capacity retention at 10C) and notable cycling stability, maintaining 75% of their initial capacity after 3440 charge-discharge cycles at 1C (127 days of continuous cycling). This superior performance compared to reported Al//n-type organic cathode RABs is attributed to the stable 3D porous microstructure and the presence of micro/mesoporosity of IEP-27-SR, which facilitates electrolyte permeability and improves kinetics.</p>
Supplemental Data for Cell Reports Physical Science article "Probing transference and field-induced polymer velocity in block copolymer electrolytes"
<p>The data and Jupyter notebook uploaded here is Supplemental Information for the article:</p><p><strong>Probing transference and field-induced polymer velocity in block copolymer electrolytes </strong></p><p>Coauthored by:</p><p>Michael D. Galluzzo, Hans-Georg Steinrück, Christopher J. Takacs, Aashutosh Mistry, Lorena S. Grundy, Chuntian Cao, Suresh Narayanan, Eric M. Dufresne, Qingteng Zhang, Venkat Srinivasan, Michael F. Toney, and Nitash P. Balsara.</p><p>Journal: Cell Reports Physical Science</p><p>Notes:</p><ul><li>This depository includes the experimental data used in Figure 2, 3, and 4 of the main text and an additional data set.</li><li>The Jupyter notebook "velocity_Echem_Data.ipynb' can be used to visualize the data in the .csv files provided in the folder 'echem' and 'XPCS_fits'.</li><li>The folder 'echem' contains the raw electrochemical data obtained from the two XPCS experiments discussed in the main text and an additional experiment set.</li><li>The folder 'XPCS_fits' contains the results of fitting the autocorrelation functions at each spatial position in the cell at each time point for the two XPCS experiments discussed in the main text and an additional experiment set. </li><li>The additional experiment included here (reffered to as Cell P in the Jupyter notebook) is not discussed in the main text, however it demonstrates that the second 'hump' in velocity (see Figure 3 and S5) that is observed after switching the direction of polarization was replicated in a separate experiment.</li></ul><p> </p>
Dataset for the paper "Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance" published in ACS Appl. Energy Mater.
<p>The data in this spreadsheet was used to produce the figures in the paper</p><p>Authors:</p><p>Colleen Jackson, Michalis Metaxas, Jack Dawson, Anthony Kucernak</p><p>Title:</p><p>Nanostructured Catalyst Layer Allowing Production of Ultralow Loading Electrodes for Polymer Electrolyte Membrane Fuel Cells with Superior Performance</p><p>Journal:</p><p>ACS Appl. Energy Mater. </p><p>DOI:</p><p>10.1021/acsaem.3c01987</p><p>Please cite the above reference if you wish to use this data</p><p>DOI of data:</p><p>10.5281/zenodo.10256698</p>
Structural and chemical changes in He+ bombarded polymers and related performance properties
<p><span>Folder zawiera pliki excel, każdy z nich odpowiada jednemu wykresowi z publikacji i zawiera dane pozwalające na wykonanie wykresu.</span></p>
Data from: Synthesis of low-molecular weight itaconic acid polymers as nanoclay dispersants and dispersion stabilizers
<p>The upload contains data associated with the publication, including raw data in the original file format whenever possible. Dataset content: SAXS, NMR, rheology, cryo-TEM, LC-MS.</p> <p>This work was financially supported by the Lead Agency bilateral a Czech-Polish project provided by the Czech Science Foundation (21-07004K) and National Science Center Poland (CEUS-UNISONO project grant no. 2020/02/Y/ST5/00021).</p>
A solid Xantphos macroligand based on porous organic polymers for the catalytic hydrogenation of CO2
<p>This dataset contains all raw data to the manuscript "A solid Xantphos macroligand based on porous organic polymers for the catalytic hydrogenation of CO2" of Nisters et al.</p> <p>The file format is based on the Software OriginLab. A free tool is available to access and visualize the data. see: https://www.originlab.com/viewer/</p>
A fluorinated 2D magnetic coordination polymer
<p>Relevant data for publication with DOI: <a title="Link to landing page via DOI" href="https://doi.org/10.1039/D1DT03734J">10.1039/D1DT03734J</a></p>
Perpendicular Crossing Chains Enable High Mobility in a Non-Crystalline Conjugated Polymer: Molecular Dynamics Forcefields and Structures
<p>This repository contains molecular dynamics forcefields and structures used to produce results described in the research article: "<em>Perpendicular Crossing Chains Enable High Mobility in a Non-Crystalline Conjugated Polymer</em>" published in <em>Proceedings of the National Academy of Sciences</em> (DOI:10.1073/pnas.2403879121)</p> <p>The following data is available:</p> <ul> <li>Coarse-grained forcefields of the conjugated polymer C16-IDTBT (12mer and 24mer).</li> <li>Coarse-grained structures of single chains of C16-IDTBT (12mer and 24mer).</li> <li>Atomistic forcefields of the conjugated polymer C16-IDTBT (12mer and 24mer).</li> <li>Atomistic structures of single chains of C16-IDTBT (12mer and 24mer).</li> <li>Bonded and non-bonded parameter files for the atomistic C16-IDTBT forcefields.</li> <li>Coarse-grained structures of thin film models (1 x C16-IDTBT 24mers, 3 x C16-IDTBT 12mers, 3 x P3HT 48mers, 3 x PffBT4T-2OD 12mers).</li> <li>Backmapped (atomistic) structures of thin film models (1 x C16-IDTBT 24mers, 3 x C16-IDTBT 12mers, 3 x P3HT 48mers, 3 x PffBT4T-2OD 12mers).</li> </ul> <p>Coarse-grained models are based on the Martini 3 forcefield: Souza, P. et al., <em>Nature Methods</em>, 2021, (https://doi.org/10.1038/s41592-021-01098-3). The bonded and nonbonded parameters may be sourced from the Martini website: https://cgmartini.nl/</p> <p>Atomistic models are based on the OPLS-AA forcefield: Kaminski, G. A. et al.,<em> J. Phys. Chem. B</em>, 2001, (https://doi.org/10.1021/jp003919d). The required bonded and nonbonded parameters have been included in this repository for convenience.</p> <p>Please note that the C16-IDTBT atomistic forcefields and single chain structures have previously been published in another repository (https://doi.org/10.11583/DTU.c.5254236.v1). They are included here for completeness.</p> <p>For any further data related to this research article, please contact the authors.</p>
Impact of Super Absorbent Polymer Treatment on Drying Process of Layered Soils
Open the record for dataset details and reuse information.
Data supporting: Assessment of the performance of nonfouling polymer hydrogels utilizing citizen scientists
<p>This dataset contains all data collected by citizen scientists in support of the publication: "Hansen N, Bryant A, McCormack R, Johnson H, Lindsay T, Stelck K, et al. (2021) Assessment of the performance of nonfouling polymer hydrogels utilizing citizen scientists. PLoS ONE 16(12): e0261817. https://doi.org/10.1371/journal.pone.0261817".</p> <p>This study evaluates the performance of several commercially available nonfouling polymers using citizen science, to identify the best performing chemistry for future applications as bacteria resistant coatings.<b> </b>The specific polymer chemistries tested were zwitterionic sulfobetaine methacrylate (SBMA), and polyampholytes composed of [2-(acryloyloxy)ethyl] trimethylammonium chloride and 2-carboxyethyl acrylate (TMA:CAA) or TMA and 3-sulfopropyl methacrylate (TMA:SA). Each polymer chemistry is known to exhibit bacteria resistance, and this study utilizes a citizen science approach to compare the performance of these chemistries.</p>
Data from: Flow imaging microscopy as a novel tool for high-throughput evaluation of elastin-like polymer coacervates
Biological and bioinspired polymer microparticles have broad biomedical and industrial applications, including drug delivery, tissue engineering, surface modification, environmental remediation, imaging, and sensing. Full realization of the potential of biopolymer microparticles will require methods for rigorous characterization of particle sizes, morphologies, and dynamics, so that researchers may correlate particle characteristics with synthesis methods and desired functions. Toward this end, we evaluated biopolymer microparticles using flow imaging microscopy. This technology is widely used in the biopharmaceutical industry but is not yet well-known among the materials community. Our polymer, a genetically engineered elastin-like polypeptide (ELP), self-assembles into micron-scale coacervates. We performed flow imaging of ELP coacervates using two different instruments, one with a lower size limit of approximately 2 microns, the other with a lower size limit of approximately 300 nanometers. We validated flow imaging results by comparison with dynamic light scattering and atomic force microscopy analyses. We explored the effects of various solvent conditions on ELP coacervate size, morphology, and behavior, such as the dispersion of single particles versus aggregates. We found that flow imaging is a superior tool for rapid and thorough particle analysis of ELP coacervates in solution. We anticipate that researchers studying many types of microscale protein or polymer assemblies will be interested in flow imaging as a tool for quantitative, solution-based characterization.
Dataset for "Investigation of convective transport in the gas diffusion layer used in polymer electrolyte fuel cell"
<p>Dataset to all the figures in the paper (including Supplementary Material):</p> <p>Investigation of convective transport in the gas diffusion layer used in polymer electrolyte fuel cell</p> <p>Beruski, O., Lopes, T., Kucernak, A. R., Perez, J.</p> <p>Phys. Rev. Fluids, 2, 103501, 2017.</p> <p> </p>
FTIR-Plastics: a Fourier Transform Infrared Spectroscopy dataset for the six most prevalent industrial plastic polymers.
<p><span><span>Two datasets are presented: FTIR-Plastics-C4 and FTIR-Plastics-C8, comprising 6,000 spectra obtained through Fourier Transform Infrared Spectroscopy (FTIR) applied to the six most used synthetic polymers: Polyethylene Terephthalate (PET), High-Density Polyethylene (HDPE), Polyvinyl Chloride (PVC), Low-Density Polyethylene (LDPE), Polypropylene (PP), and Polystyrene (PS). The key feature of the datasets lies in the FTIR analysis, which reports the percentage transmittance as the intensity measure as a function of the wavelength of an Infrared light source, expressed as wavenumber (with units in cm</span></span><sup><span><span>-1</span></span></sup><span><span>). FTIR analysis was performed using a Jasco FTIR PRO 4x spectrophotometer with a wavenumber resolution setting of 8 cm</span></span><sup><span><span>-1</span></span></sup><span><span> for FTIR-Plastics-C8 and 4 cm</span></span><sup><span><span>-1</span></span></sup><span><span> for FTIR-Plastics-C4, both employing a configuration of 32 scans and a range from 4000 to 400 cm</span></span><sup><span><span>-1</span></span></sup><span><span>. The datasets are presented in CSV (comma-separated values) format, including the following information (per each column):</span></span></p> <ul> <li> <p><span><span><strong>IDE</strong></span></span><span><span>: unique identifier of the sample.</span></span></p> </li> <li> <p><span><span><strong>Polymer: </strong></span></span><span><span>type of synthetic polymer (PET, HDPE, PVC, LDPE, PP, or PS).</span></span></p> </li> <li> <p><span><span><strong>Technique: </strong></span></span><span><span>Type of technique used (FTIR).</span></span></p> </li> <li> <p><span><span><strong>Sample: </strong></span></span><span><span>polymer sample number.</span></span></p> </li> <li> <p><span><span><strong>BR</strong></span></span><span><span>: scanning configuration (32).</span></span></p> </li> <li> <p><span><span><strong>RST</strong></span></span><span><span>: resolution configuration (8 or 4 cm</span></span><sup><span><span>-1</span></span></sup><span><span>).</span></span></p> </li> <li> <p><span><span><strong>Data (x) y Data(y): </strong></span></span><span><span>1884 pairs of columns for FTIR-Plastics-C8 and 3751 pairs of columns for FTIR-Plastics-C4, representing values on the "x" axis (wavenumber) and the "y" axis values associated with molecular vibration intensities, indicating the transmittance (%), which differentiates each polymer.</span></span></p> </li> </ul> <p><span><span>Additionally, the files generated by the Jasco spectrophotometer for each polymer are provided, which were standardized by adding a header with the following structure:</span></span></p> <ul> <li> <p><span><span>TITLE SAMPLE NAME: referring to the name of the analyzed polymer.</span></span></p> </li> <li> <p><span><span>DATA TYPE: specifying the characterization technique.</span></span></p> </li> <li> <p><span><span>MEASUREMENT INFORMATION: equipment used for data collection.</span></span></p> </li> <li> <p><span><span>MODEL NAME: name of the equipment used.</span></span></p> </li> <li> <p><span><span>SERIAL No: serial number assigned to the equipment used.</span></span></p> </li> <li> <p><span><span>ACCESSORY: complementary device integrated into the equipment.</span></span></p> </li> <li> <p><span><span>LIGHT SOURCE: standardized light source related to the DLATGS detector.</span></span></p> </li> <li> <p><span><span>RESOLUTION: parameters are used to distinguish the wavenumber in the analyzed materials.</span></span></p> </li> <li> <p><span><span>XUNIT/HORIZONTAL AXIS: referring to the unit’s title assigned on the x-axis.</span></span></p> </li> <li> <p><span><span>YUNITS/VERTICAL AXIS: referring to the unit’s title designated on the y-axis.</span></span></p> </li> <li> <p><span><span>FIRSTX: initial value set for the x-axis.</span></span></p> </li> <li> <p><span><span>FIRSTY: initial value set for the y-axis.</span></span></p> </li> <li> <p><span><span>LASTX: final value set for the x-axis.</span></span></p> </li> <li> <p><span><span>LASTY: final value set for the y-axis.</span></span></p> </li> <li> <p><span><span>NPOINTS: total data points in the file.</span></span></p> </li> </ul> <p><span><span>Data collection was carried out meticulously, following specific steps to ensure the accuracy and reliability of the results. The calibration certificates issued by the supplier (calibration_certificate.pdf) corresponding to the equipment used in the experiments and data collection that give rise to these databases are attached.</span></span></p>
Styrene monomer as potential material for functionalization and design of chromophores for new optoelectronic and NLO polymers conception: DFT study
<p>Using Density functional theory (DFT), we have studied the intrinsic properties of styrene. We determine firstly: optimized structures, structural parameters, and thermodynamic properties to make our simulations more realistic to experimental results and check the stability. We secondly investigate optoelectronic, electronic, and global descriptors, transport properties of holes and electrons, NBO analysis, absorption, and fluorescence properties. We finally study NLO:1st and 2nd order hyperpolarizability, 2nd and 3rd order optical susceptibilities, hyper-Rayleigh scattering hyperpolarizability, EOPE, DC-KERR effects, and quadratic refractive index. The bandgap energy E<sub>g</sub> = 5.146 eV and dielectric constant show that styrene is a good insulator with an average electric field value of 4.43×10<sup>8 </sup>Vm<sup>-</sup><sup>1</sup>. Thermodynamic findings show that our molecule is thermodynamically and chemically stable. Electron and hole reorganization energies of 0.393 eV and 0.295 eV, respectively, show that styrene is more favorable to hole transport than electron transport. Styrene is transparent with linear refractive index n = 1.750 and quadratic . At the NLO, styrene has a non-zero value of which confirms the existence of first-order nonlinear optical activity. Globally the study shows that the styrene monomer is suitable for the architecture design of new polymer materials for NLO applications and optoelectronic by functionalization.</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.