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421 results for “Polymer”
Benchmarking Study of Deep Generative Models for Inverse Polymer Design: Generation Results
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Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study - dataset
<p>Abstract:<br>from [1]</p> <p>Polymer nanocomposites (PNCs) have shown great potential to meet the ever-growing requirements of modern engineering applications. Nowadays, molecular dynamics (MD) simulations are increasingly employed to complement experimental work and thereby gain a deeper understanding of the complex structure–property relations of PNCs. However, with respect to the thermoplastic’s mechanical behavior, the role of its average molar mass is rarely addressed, and many MD studies only consider uniform (monodispersed) polymers. Therefore, this contribution investigates the impact that and the dispersity Đ have on the stiffness and strength of PNCs through coarse-grained MD. To this end, we employed a Kremer–Grest bead–spring model and observed the expected increase in the mechanical performance of the neat polymer for larger . Our results indicated that the unimodal molar mass distribution does not impact the mechanical behavior in the investigated dispersity range Đ. For the PNC, we obtained the same -dependence and Đ-independence of the mechanical properties over a wide range of filler sizes and contents. This contribution proves that even simple MD models can reproduce the experimentally well researched effect of the molar mass. Hence, this work is an important step in understanding the complex structure–property relations of PNCs, which is essential to unlock their full potential.</p> <p>Contact:</p> <p>Maximilian Ries<br>Institute of Applied Mechanics<br>Friedrich-Alexander-Universität Erlangen-Nürnberg<br>Egerlandstr. 5<br>91058 Erlangen</p> <p>Software:</p> <p>All MD simulations were performed with LAMMPS [2,3], version: 23 Oct 2022 / 20220623</p> <p>Compiled with<br>Compiler: GNU C++ 11.2.0 with OpenMP not enabled<br>C++ standard: C++11</p> <p>Active compile time flags:<br>-DLAMMPS_GZIP<br>-DLAMMPS_SMALLBIG</p> <p>Installed packages:<br>CLASS2 DPD-BASIC EXTRA-DUMP INTEL KSPACE MANYBODY MC MISC MOLECULE MOLFILE MPIIO NETCDF OPT PERI</p> <p>Polymer and polymer composite samples generated with self-avoiding random-walk algorithm [4]</p> <p>Post-processing Matlab R2019b</p> <p>License:</p> <p>Creative Commons Attribution 4.0 International</p> <p>Context:</p> <p>Data set supplementing journal paper:</p> <p>[1] M. Ries, L. Laubert, P. Steinmann, & S. Pfaller, “Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study,” European Journal of Mechanics - A/Solids, vol. 107, p. 105 379, 2024.</p> <p>Content:</p> <p>structure of data set:</p> <p> -01_neat <br> containing the neat polymer simulations<br> -01_uniform<br> containing samples with uniform chain lengths<br> -02_distributed<br> containing samples with distributed chain lengths<br> -100-dist<br> samples with mean molar mass 100<br> -200-dist<br> samples with mean molar mass 200<br> -02_PNC<br> containing the polymer nanocomposite simulations<br> -01_uniform<br> containing samples with uniform chain lengths<br> -T_0.2<br> simulations at temperature 0.2<br> -T_0.3<br> simulations at temperature 0.3<br> -T_0.4<br> simulations at temperature 0.4<br> -02_distributed<br> containing samples with distributed chain lengths<br> -T_0.2<br> simulations at temperature 0.2<br> -T_0.3<br> simulations at temperature 0.3<br> -T_0.4<br> simulations at temperature 0.4<br> </p> <p>naming convention for simulation folders</p> <p> - neat polymer simulations<br> example: GTP_UT_num_chains-80_num_beads_per_chain-500-8<br> * num_chains: number of polymer chains<br> * num_beads_per_chain: molar mass (chain length)<br> * distribution: standard deviation of gauss distribution govering dispersity<br> * "trailing number": batch number of sample<br> <br> - polymer nanocomposite simulations<br> example: GTP_rF-5_nF-10_chainlen-5_7-T_0.2<br> * rF: nanofiller radius<br> * nF: number of nanofillers<br> * chainlen: molar mass (chain length)</p> <p> </p> <p>Each simulation directory contains:</p> <p> lammps input file (*.in) of the specific simulation</p> <p> data file (*.data) containing the initial sample configuration</p> <p> input.prm: input parameters of the specific simulation (read by the input file)</p> <p> meta.info: meta data of the specific simulation run</p> <p> LAMMPS_out:<br> simulation results (lammps thermo_out) in tabulated form, an overview of columns is given below</p> <p> thermo_out.Dat: raw output </p> <p> thermo_out_SG.Dat: smoothed output (Savitzky-Golay filter)</p> <p> thermo_out_STD.Dat: standard deviation of raw output</p> <p>Output quantities (columns of *.Dat files):<br>Please note that the normalized Lennard-Jones unit set is used, so all quantities are normalized to fundamental mass, length, energy, time and the Boltzmann constant. Thus all entries are unitless [1].</p> <p> Step: time step </p> <p> Time: time </p> <p> TotEng: total energy </p> <p> PotEng: potential energy</p> <p> KinEng: kinetic energy </p> <p> E_pair: pair energy </p> <p> E_bond: bond energy </p> <p> E_angle: angle energy </p> <p> E_dihed: dihedral energy </p> <p> Temp: temperature</p> <p> Press: hydrostatic pressure</p> <p> Pxx: xx component of pressure tensor </p> <p> Pyy: yy component of pressure tensor </p> <p> Pzz: zz component of pressure tensor </p> <p> Pxy: xy component of pressure tensor</p> <p> Pxz: xz component of pressure tensor</p> <p> Pyz: yz component of pressure tensor</p> <p> Volume: volume of simulation box </p> <p> Lx: box length in x direction </p> <p> Ly: box length in y direction </p> <p> Lz: box length in z direction </p> <p> Density: density </p> <p> c_RG: radius of gyration scalar </p> <p> c_RG[1]: squared radius of gyration tensor (xx component) </p> <p> c_RG[2]: squared radius of gyration tensor (yy component) </p> <p> c_RG[3]: squared radius of gyration tensor (zz component) </p> <p> c_RG[4]: squared radius of gyration tensor (xy component) </p> <p> c_RG[5]: squared radius of gyration tensor (xz component) </p> <p> c_RG[6]: squared radius of gyration tensor (yz component) </p> <p> c_bondave[1]: bond energy averaged over all atoms </p> <p> c_bondave[2]: bond distance averaged over all atoms </p> <p> c_bondave[3]: squared bond distance averaged over all atoms </p> <p> c_angleave[1]: angle energy averaged over all atoms </p> <p> c_angleave[2]: angle averaged over all atoms degree</p> <p> c_angleave[3]: cosine of angle </p> <p> c_angleave[4]: squared cosine of angle </p> <p> c_MSD[1]: mean squared displacement x-direction </p> <p> c_MSD[2]: mean squared displacement y-direction </p> <p> c_MSD[3]: mean squared displacement z-direction </p> <p> c_MSD[4]: total mean squared displacement </p> <p> c_COM[1]: x coordinate of center of mass </p> <p> c_COM[2]: y coordinate of center of mass </p> <p> c_COM[3]: z coordinate of center of mass </p> <p> v_strain_xx: xx component of engineering strain tensor </p> <p> v_strain_yy: yy component of engineering strain tensor </p> <p> v_strain_zz: zz component of engineering strain tensor </p> <p> v_vMisesequivstress: von Mises equivalent stress </p> <p> v_Cauchy_xx: xx component of stress tensor </p> <p> v_Cauchy_yy: yy component of stress tensor</p> <p> v_Cauchy_zz: zz component of stress tensor</p> <p> v_Cauchy_xy: xy component of stress tensor </p> <p> v_Cauchy_xz: xz component of stress tensor </p> <p> v_Cauchy_yz: yz component of stress tensor </p> <p> v_strain_xy: xy component of engineering strain tensor </p> <p> v_strain_xz: xz component of engineering strain tensor </p> <p> v_strain_yz: yz component of engineering strain tensor </p> <p>References:</p> <p>[1] M. Ries, L. Laubert, P. Steinmann, & S. Pfaller, “Impact of the unimodal molar mass distribution on the mechanical behavior of polymer nanocomposites below the glass transition temperature: A generic, coarse-grained molecular dynamics study,” European Journal of Mechanics - A/Solids, vol. 107, p. 105 379, 2024.</p> <p>[2] S. Plimpton, “Fast parallel algorithms for short-range molecular dynamics,” Journal of computational physics, 1995, 117, 1-19.</p> <p>[3] A. P. Thompson et al., “LAMMPS - a flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales,” Computer Physics Communications, vol. 271, p. 108171, 2022.</p> <p>[4] J. Roksvaag, M.Ries . “A fast self-avoiding random walk algorithm (SARW) for generic thermoplastic polymers and nanocomposites”, manuscript in preparation</p>
Matlab files for: Mathematical Modelling of Polymer Trajectory during Electrospinning
<p>Matlab files used within this publication to be able to replicate the results.</p>
Dataset with segmentations of 75 stained cell images over P3HBV polymer films
<div> <p>We segmented 75 images of stained cells, divided in 5 folders according the thickness of the <strong>Poly-3-hydroxyvalerate</strong> films.</p> <p>P3HBV polymer films of different thicknesses were prepared by casting solution technique.</p> <p>For this, P3HBV was dissolved in chloroform to obtain homogeneous solutions with concentration of <strong>1.0, 1.5, 2.0, 2.5 and 3.0%</strong>. The films were dried at room temperature for 48 hours in a dust-free environment, allowing the chloroform to evaporate completely and resulting in solid films. Upper surfaces of the films were used for cell cultivation.</p> <p>Linear culture of mice fibroblasts NIH 3T3 was used to obtain the visual data of cell adhesion on P3HBV film samples. To assess the cytocompatibility of PHA samples, cells were seeded onto sterile polymer films samples at a density of 2 × 104𝑐𝑒𝑙𝑙𝑠/𝑐𝑚2 and cultured for 72 hours. After the incubation, the samples were washed with phosphate-buffered saline and cells were fixed with 4% paraformaldehyde solution.</p> <p>Cell membranes were permeabilized with 0.2% Triton-X, and the cytoplasm was stained with fluorescein isothiocyanate, FITC (green) (Sigma-Aldrich, USA), for 1 hour in the dark at room temperature. The nuclei were visualized using 4’,6-diamidino-2-phenylindole, DAPI (blue) (Sigma-Aldrich, USA).</p> <p>Cells were visualized using a Leica DMI8 fluorescent microscope with corresponding LAS X software.</p> <p>Per each sample, we include: A raw image (.tif) with 2 subfolders containing the segmented masks of their cells and nuclei respectively.</p> </div>
Simple, highly-stable transfer cavity for laser stabilization based on a carbon-fiber reinforced polymer spacer
<p>Data corresponding to the article "Simple, highly-stable transfer cavity for laser stabilization based on a carbon-fiber reinforced polymer spacer"</p>
Investigating fracture mechanisms in glassy polymers using coupled particle-continuum simulations
<p>This repository contains public data for the publication "Investigating fracture mechanisms in glassy polymers using coupled atomistic-continuum simulations" [1].</p> <p>These scripts, force fields, topologies and other files may be used to reproduce the simulations and calculations that led to the above publication.</p> <p>The folder "md simulations" contains data files for pure MD simulations that were used as a reference for understanding molecular fracture mechanisms in our model.</p> <p>The folder "coupled simulations" contains data files for coupled MD-FE simulations which are the highlight of our publication.</p> <p> </p> <p>Reference:</p> <p>[1] W. Zhao, Y. Jain, F. Müller-Plathe, P. Steinmann, S. Pfaller, "Investigating fracture mechanisms in glassy polymers using coupled particle-continuum simulations", Journal of the Mechanics and Physics of Solids, 2024, 105884. DOI: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.jmps.2024.105884" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.jmps.2024.105884</span></span></a></p>
Molecular Dynamics Simulations of PEO-LiTFSI Polymer Electrolytes With Various Chain Lengths and Salt Concentrations in the Bulk
<p>Data set containing molecular dynamics (MD) simulations performed with <a href="https://www.gromacs.org/">Gromacs</a> to investigate the effect of polymer chain length and salt concentration on the atomistic structure and dynamics of PEO-LiTFSI polymer electrolytes in the bulk.</p> <p>PEO = Methoxy-terminated poly(ethylene oxide), sometimes also abbreviated as PEGDME for polyethylene glycol dimethyl ether<br>LiTFSI = Lithium bis(trifluoromethanesulfonyl)imide, sometimes also abbreviated as Li[NTf2].</p> <p>The data set contains:</p> <ul> <li>Gromacs input and output files (except trajectories due to their huge filesize)</li> <li>Processed data</li> <li>Various plots of the data</li> </ul> <p>The zip archives contain:</p> <ul> <li><code>coiling.zip</code>: MD simulations of single PEO chains in vacuum that were performed to produce coiled PEO chains, which were used to generate the starting structures for the bulk simulations.</li> <li><code>bulk.zip</code>: MD simulations of PEO-LiTFSI polymer electrolytes in the bulk.</li> <li><code>plots.zip</code>: Plots of various structural and dynamic quantities as function of the PEO chain length and the salt concentration.</li> </ul>
Unravelling the Molecular Structure and Confining Environment of an Organometallic Catalyst Heterogenized within Amorphous Porous Polymers
<p>Raw data corresponding to Figure 4c of the following publicaiton: </p> <div> <div> <div>Jabbour, R.; Ashling, C. W.; Robinson, T. C.; Khan, A. H.; Wisser, D.; Berruyer, P.; Ghosh, A. C.; Ranscht, A.; Keen, D. A.; Brunner, E.; Canivet, J.; Bennett, T. D.; Mellot-Draznieks, C.; Lesage, A.; Wisser, F. M. Unravelling the Molecular Structure and Confining Environment of an Organometallic Catalyst Heterogenized within Amorphous Porous Polymers. <em>Angewandte Chemie International Edition</em> <strong>2023</strong>, <em>62</em> (44), e202310878. <a href="https://doi.org/10.1002/anie.202310878">https://doi.org/10.1002/anie.202310878</a>.</div> </div> </div>
Data from: High-molecular-weight polymers from dietary fiber drive aggregation of particulates in the murine small intestine
The lumen of the small intestine (SI) is filled with particulates: microbes, therapeutic particles, and food granules. The structure of this particulate suspension could impact uptake of drugs and nutrients and the function of microorganisms; however, little is understood about how this suspension is re-structured as it transits the gut. Here, we demonstrate that particles spontaneously aggregate in SI luminal fluid ex vivo. We find that mucins and immunoglobulins are not required for aggregation. Instead, aggregation can be controlled using polymers from dietary fiber in a manner that is qualitatively consistent with polymer-induced depletion interactions, which do not require specific chemical interactions. Furthermore, we find that aggregation is tunable; by feeding mice dietary fibers of different molecular weights, we can control aggregation in SI luminal fluid. This work suggests that the molecular weight and concentration of dietary polymers play an underappreciated role in shaping the physicochemical environment of the gut.
Research data supporting: K. Tashiro, K. Katayama, K. Tamaki, L. Pesce, N. Shimizu, H. Takagi, R. Haruki, R. Heenan, M. J. Hollamby, G. M. Pavan, S. Yagai, "Non-uniform Photoinduced Unfolding of Supramolecular Polymers Leading to Topological Block Nanofibers"
<p>Raw research data supporting the article K. Tashiro, K. Katayama, K. Tamaki, L. Pesce, N. Shimizu, H. Takagi, R. Haruki, R. Heenan, M. J. Hollamby, G. M. Pavan, S. Yagai, "Non-uniform Photoinduced Unfolding of Supramolecular Polymers Leading to Topological Block Nanofibers".</p>
Training data and prediction results for predicting water diffusion in various polymers using MD-GAN
<p>Training data and prediction results for predicting water diffusion in various polymers using MD-GAN.</p> <p>MD trajectories used as input, MSDs calculated from MD, predicted MSDs, and diffusion coefficient values.</p> <p>MD trajectories were obtained from the following paper.<br> Kojima, H.; Handa, K.; Yamada, K.; Matubayasi, N. Water Dissolved in a Variety of Polymers Studied by Molecular Dynamics Simulation and a Theory of Solutions. <em>The Journal of Physical Chemistry B</em> 2021, 125, 9357-9371.</p> <p> </p>
Onset of criticality in hyper-auxetic polymer networks
<p>Data from the figures presented in the article entitled <strong>Onset of criticality in hyper-auxetic polymer networks</strong>.</p>
Data set for graphene/GO polymer molecular dynamics simulation
<p>Lammps input files and log files for molecular dynamics simulations of graphene and graphene-oxide nano ribbons for paper "Molecular dynamics reveals the origin of the enhancement of polymer properties by graphene". Log files include stress-strain behaviour during uniaxial strain. </p> <p> </p>
Adsorbed polymer conjugates to adaptively inhibit blood coagulation activation by medical membranes
<p>Dataset to the manuscript</p> <p><strong>'Adsorbed polymer conjugates to adaptively inhibit blood coagulation activation by medical membranes'</strong></p> <p>Tina Helmecke, Dominik Hahn, André Ruland, Mikhail V. Tsurkan, Manfred F. Maitz, Carsten Werner</p>
Data for: Preceramic polymer assisted nucleation and growth of copper sulfide nanoplates
<p>In this work, a novel synthesis technique is presented in which a functionalized pre-ceramic polymer is used to stably assist the formation of a copper sulfide nanoplate and act as the end graft molecule in a one-pot approach. This is significant, as it offers a one-pot nanofiller precursor synthesis that should more easily disperse into similar preceramic polymer polysiloxane matrices than conventional nanoparticles for advanced polymer-derived ceramic nanocomposite formation. We have used a wide range of characterization techniques to probe the nanoparticle core formed in the synthesis, the final graft molecule, and the role of the pre-ceramic polymer during synthesis. This includes synchrotorn X-ray difffraction and pair distribution functions, transmission electron microscopy, Fourier transform infrared spectroscopy, in-situ small-angle X-ray scattering, and nuclear magnetic resonance spectroscopy. All of which are included in this data repository, labeled with the figure numbers from the corresponding article through Communications Materials.</p>
Fiber Orientation Estimation from X-ray Dark Field Images of Fiber Reinforced Polymers using Constrained Spherical Deconvolution: Data
<p>The data was simulated in GATEv8.0. The macro's and other files for the simulation can be found in the folders: Sim_50_40, Sim80_60 and Sim90_70. Here, the different files to perform the simulation are given, as well as the output data, found in the folders Flats and Projs (flatfields and projections) in the form of a csv-file. The csv-file contains 5000 rows (one for each image), and each row contains a flattened 450x450 image.</p> <p>The files for visualization of the fiber directions are given in the folder MRtrix. This folder contains the reconstructed scatter magnitudes and their respective directions in a mat-file. On this set of directions the constrained spherical deconvolution is applied using the sf_dirs.mif, sf_mask.mif, sf_response.mif and data.mif files. This returns the orientation density function in each voxel as output (odf_csd_14.mif). An alternative approach is performing a Funk-Radon transform on the coefficients of the scatter function (data_coeffs_10.mif) to obtain odf_frt_10.mif.</p> <p>Using a peak finding algorithm the fiber orientations are extracted from these odf-files and written to peaks_x.mif files, with or without a threshold (10% of largest amplitude).</p>
Dataset for "Structure and Properties of Metallosupramolecular Polymers with a Nitrogen-Based Bidentate Ligand"
<p>Source data of the study reported in the publication entitled "Structure and Properties of Metallosupramolecular Polymers with a Nitrogen-Based Bidentate Ligand". The data should be considered together with the published manuscript and the supplementary information file.</p>
Harmonizing Optimal Strategy for Treatment of Coronary Artery Diseases Trial - Comparison of REDUCTION of PrasugrEl Dose & POLYmer TECHnology in ACS Patients (HOST REDUCE POLYTECH RCT Trial)
ClinicalTrials.gov study NCT02193971. IPD Sharing: Not stated. Countries: 1. Publications: 5.
Short-term Dual Antiplatelet Therapy After Deployment of Bioabsorbable Polymer Everolimus-eluting Stent
ClinicalTrials.gov study NCT03447379. IPD Sharing: NO. Countries: 1. Publications: 1.
Intra-patient Study With Polymer Free Drug Eluting Stent Versus Abluminal Biodegradable Polymer Drug Eluting Stent With Early OCT (Optical Coherence Tomography) Follow up
ClinicalTrials.gov study NCT02785237. IPD Sharing: Not stated. Countries: 1. Publications: 32.
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