Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
117
datasets available to search
ShareScore release 0.9.0
Dataset results
117 results for “viscoelasticity”
Raw data for viscoelastic anterior cruciate ligament characteristics
<p>Here, you can find three MS Excel files containing raw, statistical and analysed data for the study of viscoelastic properties of canine cranial cruciate ligaments at slow strain rates. </p> <p>The second version of this dataset has updated Hysteresis file. </p>
Simulations of Rising Air Bubbles in Viscoelastic Fluids
<p>Videos, plots and the underlying data, generated from simulations of rising air bubbles in viscoelastic fluids for varying relaxation times and bubble volumes. The underlying model for the viscoelastic fluid is the Giesekus model, which was discretized with the fully implicit log-conformation approach. The free surface is modeled using an interface-tracking method. For more details cf. Knechtges, P. <em>Simulation of Viscoelastic Free-Surface Flows</em> PhD thesis (RWTH Aachen, 2018).</p>
Data for the manuscript "Enhanced microscopic dynamics in mucus gels under a mechanical load in the linear viscoelastic regime" (PNAS).
<p>Data files for the figures published in</p> <p>D. Larobina, A. Pommella, A.-M. Philippe, M. Y. Nagazi, and L. Cipelletti, <em>Enhanced Microscopic Dynamics in Mucus Gels under a Mechanical Load in the Linear Viscoelastic Regime</em>, Proc Natl Acad Sci USA <strong>118</strong>, e2103995118 (2021).</p> <p>DOI: 10.1073/pnas.2103995118</p> <p>Each data set is available as a plain text file (description in the file __README__DataDescription.txt), and as an Excel file.<br> The Excel files typically contain the data sets of several panels of a given figure, as separated sheets. See the description<br> provided in the "GeneralInfo" sheet of each Excel file.</p>
Data for "Detachment of a rigid flat punch from a viscoelastic material"
<p>This dataset contains all the data generated for the publication</p> <p>[1] Papangelo, A., & Ciavarella, M. (2023). Detachment of a rigid flat punch from a viscoelastic material, Tribology Letters, DOI: 10.1007/s11249-023-01720-9<br> </p> <p>The provided data are those which appear in the figures of Ref. [1]. Data are stored using informative named structures in a ".mat" file. The data are easily accessible through the Commercial Software MATLAB (© 1994-2023 The MathWorks, Inc.) or by using the free software GNU Octave. An exemplary code for loading and plotting the data contained in "dataFlatPunch.mat" is the following:</p> <p>%%%%%%%%%%%%%</p> <p>load('dataFlatPunch.mat') % load workspace containing data</p> <p>figure, hold on % open a new figure</p> <p>curve_number = 1; % select the curve to plot</p> <p>plot(Fig1.x{curve_number},Fig1.y{curve_number}) % Plot the curve number "curve_number" of figure "Fig1"</p> <p>%%%%%%%%%%%%%</p> <p>The code can be easily adapted for plotting the curves of all the figures contained in Ref. [1]. </p>
Linear rheology of liquid foam - data from "Delayed elastic contributions to the viscoelastic response of foams"
<p>Linear rheological data of Gillette shaving cream "normal skin" made by Gillette UK LTD, acquired at the Department of Physics, University of Fribourg, Switzerland, between 2019 and 2022. Dataset contains elastic modulus, creep-recovery, stress relaxation, and frequency sweep experimental data, together with model data, as described in "Delayed elastic contributions to the viscoelastic response of foams", The Journal of Chemical Physics, 2022, published in the special issue <em>Slow Dynamics</em> [DOI: 10.1063/5.0085773].</p>
The Extreme Mechanics of Viscoelastic Metamaterials
<p>This dataset contains all data as used for the paper 'The Extreme Mechanics of Viscoelastic Metamaterials'. It provides example files on viscoelastic modelling in Abaqus and on deriving viscoelastic material properties,</p> <p> </p> <p><strong>Abstract:</strong></p> <p>Mechanical metamaterials made of flexible building blocks can exhibit a plethora of extreme mechanical responses, such as negative elastic constants, shape-changes, programmability and memory. To date, dissipation has largely remained overlooked for such flexible metamaterials. As a matter of fact, extensive care has often been devoted in the constitutive materials’ choice to avoid strong dissipative effects. However, in an increasing number of scenarios, where metamaterials are loaded dynamically, dissipation can not be ignored. In this review, we show that the interplay between mechanical instabilities and viscoelasticity can be crucial and can be harnessed to obtain new functionalities. We first show that this interplay is key to understanding the dynamical behaviour of flexible dissipative metamaterials that use buckling and snapping as functional mechanisms. We further discuss the new opportunities that spatial patterning of viscoelastic properties offer for the design of mechanical metamaterials with properties that depend on loading rate.</p>
Data for "Bulk and fracture process zone contribution to the rate-dependent adhesion amplification in viscoelastic broad-band materials"
<p>This dataset contains all the data generated for the publication</p> <p>[1] A. Maghami, Q. Wang, M. Tricarico et al., Bulk and fracture process zone contribution to the rate-dependent adhesion amplification in viscoelastic broad-band materials. Journal of the Mechanics and Physics of Solids (2024), doi:<br>https://doi.org/10.1016/j.jmps.2024.105844.</p> <p><br>The provided data are those which appear in the figures of Ref. [1]. Data are stored using informative named structures in a ".mat" file. The data are easily accessible through the Commercial Software MATLAB (© 1994-2023 The MathWorks, Inc.) or by using the free software GNU Octave. An exemplary code for loading and plotting the data contained in "data_Sphere_Viscoelastic_BroadBand.mat" is the following:</p> <p>%%%%%%%%%%%%%</p> <div> <div> <div> <div>clc</div> <div>clearvars</div> <div> </div> <div>close all</div> <div> </div> <div> </div> <div>% Create a new figure</div> <div>load('data_Sphere_Viscoelastic_BroadBand.mat');</div> <div> </div> <div> </div> <div>figure</div> <div> </div> <div>% Choose one of the following names:</div> <div>% Fig_3_a, Fig_3_b, Fig_3_c,</div> <div>% Fig_4, Fig_5_a, Fig_5_b, Fig_5_b_inset,</div> <div>% Fig_6, Fig_6_inset, Fig_7, Fig_7_inset,</div> <div>% Fig_8_a, Fig_8_b, Fig_10_a, Fig_10_b</div> <div> </div> <div>name=Fig_3_a;</div> <div>% Note: some plots in the manuscript are in log space.</div> <div> </div> <div>% Plot the data from the structure</div> <div> </div> <div> </div> <div>for i = 1:numel(name.x) hold on</div> <div> </div> <div>x_cell = name.x(i);</div> <div>y_cell = name.y(i);</div> <div>x = cell2mat(x_cell);</div> <div>y = cell2mat(y_cell);</div> <div> </div> <div>plot(x, y);</div> <div>end</div> <div> </div> <div> </div> <div> </div> </div> %%%%%%%%%%%%%</div> </div> <p>The code can be easily adapted for plotting the curves of all the figures contained in Ref. [1]. </p>
Source code and experimental data of human brain tissue (visual cortex, corona radiata) for poro-viscoelastic parameter identification
<p>Computer code and experimental data that we used for our inverse parameter identification of poro-viscoelastic material parameters for two different brain regions: visual cortex (gray matter) and corona radiata (white matter). The experimental data comprises large-strain cyclic loading and compression/tension relaxation. For details see the corresponding publication: "Model-driven exploration of poro-viscoelasticity in human brain tissue: Be careful with the parameters!".</p> <p>Further explanation regarding the specimen preparation, experimental setup, as well as the assignment of regions and governing regions can be found in Hinrichsen, J., Reiter, N., Bräuer, L. et al. Inverse identification of region-specific hyperelastic material parameters for human brain tissue. Biomech Model Mechanobiol (2023). <a href="https://doi.org/10.1007/s10237-023-01739-w" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s10237-023-01739-w</a>.</p> <p>The file "<span>nonlinear-poro-viscoelasticity.cc</span>" contains our C++ Finite Element code based on the open source library deal.II. It is accompanied by an exemplary parameter file.</p> <p><strong>Funding:</strong> The support from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) through the grants BU 3728/1-1, BU 3728/3-1, STE 544/70-1 as well as through project number 460333672 CRC1540 Exploring Brain Mechanics is gratefully acknowledged.</p>
Data for: Analytical transfer function for volcano deformation with T-dependent viscoelasticity
<p>Rocks can modulate the triggering, duration, and style of volcanic eruptions. When heated, the host rocks surrounding a magmatic reservoir is typically considered as a viscoelastic material. The viscoelastic rheology (viscosity especially) is temperature dependent; however, the dynamics and consequence on surface deformation resulting from heterogeneous crustal temperature and viscosity around magmatic reservoirs have not been explored systematically. </p> <p>This dataset incorporates the parameters and numerical codes used for generating results in the manuscript 'History-dependent volcanic ground deformation from broad-spectrum viscoelastic rheology around magma reservoirs' submitted to GRL and authord by Yang Liao, Leif Karlstrom, and Brittany Erickson. The dataset consists of a README file detailing the data structure, a matlab .mat file that contains the parameters assumed in the magma chamber model, and several matlab program .m files that can be applied to the .mat file to generate results presented in the manuscript. </p>
Data for: Analytical transfer function for volcano deformation with T-dependent viscoelasticity
Open the record for dataset details and reuse information.
Data and code from: Viscoelasticity explains fast adaptation in the auditory amplifiers of mammals
Open the record for dataset details and reuse information.
Data for "Friction in Rolling a Cylinder on or Under a Viscoelastic Substrate with Adhesion"
<p>This dataset contains all the data generated for the publication</p> <p>[1] R. Nazari, A. Papangelo, M. Ciavarella, Friction in Rolling a Cylinder on or Under a Viscoelastic Substrate with Adhesion, Tribology Letters, (2024), DOI: 10.1007/s11249-024-01849-1 </p> <p>The provided data are those which appear in the figures of Ref. [1]. Data are stored using informative named structures in a ".mat" file. The data are easily accessible through the Commercial Software MATLAB (© 1994-2023 The MathWorks, Inc.) or by using the free software GNU Octave. An exemplary code for loading and plotting the data contained in "dataRolling.mat" is the following:</p> <p>%%%%%%%%%%%%%</p> <div>clc</div> <div>clearvars</div> <div> </div> <div>close all</div> <div> </div> <div>% load workspace containing data</div> <div> <div>load('dataRolling.mat') </div> <div> </div> <div>% Plot the curve number 2 of Figure 7</div> <div> </div> <div>figure, hold on</div> <div>curve_number = 2;</div> <div>plot(Fig7.x(curve_number).x,Fig7.y(curve_number).y)</div> <div> </div> <div>%%%%%%%%%%%%%</div> </div>
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>
Benchmark: Axisymmetric liquid droplets on viscoelastic substrates
<p>We report on the data from a numerical benchmark of a stationary axisymmetric droplet on viscoelastic Neo-Hookean substrates obtained using FEniCS. Numerical results using our Lagrangian phase-field approach are compared with results by Van Brummelen et al. and by Aland & Mokbel.</p>
Viscoelastic properties of suspended cells measured with shear flow deformation cytometry
<p>Numerous cell functions are accompanied by phenotypic changes in viscoelastic properties, and measuring them can help elucidate higher-level cellular functions in health and disease. We present a high-throughput, simple and low-cost microfluidic method for quantitatively measuring the elastic (storage) and viscous (loss) modulus of individual cells. Cells are suspended in a high-viscosity fluid and are pumped with high pressure through a 5.8 cm long and 200 μm wide microfluidic channel. The fluid shear stress induces large, near ellipsoidal cell deformations. In addition, the flow profile in the channel causes the cells to rotate in a tank-treading manner. From the cell deformation and tank treading frequency, we extract the frequency-dependent viscoelastic cell properties based on a theoretical framework developed by R. Roscoe that describes the deformation of a viscoelastic sphere in a viscous fluid under steady laminar flow. We confirm the accuracy of the method using atomic force microscopy-calibrated polyacrylamide beads and cells. Our measurements demonstrate that suspended cells exhibit power-law, soft glassy rheological behavior that is cell cycle-dependent and mediated by the physical interplay between the actin filament and intermediate filament networks.</p>
Dataset related to "High-frequency optimally windowed chirp rheometry for rapidly evolving viscoelastic materials: Application to a crosslinking thermoset"
<p>Knowledge of the evolution in the mechanical properties of a curing polymer matrix is of great importance in composite parts or structure<br>fabrication. Conventional rheometry, based on small amplitude oscillatory shear, is limited by long interrogation times. In rapidly evolving<br>materials, time sweeps can provide a meaningful measurement albeit at a single frequency. To overcome this constraint, we utilize a combined<br>frequency- and amplitude-modulated chirped strain waveform in conjunction with a homemade sliding plate piezo-operated rheometer (PZR)<br>and a dual-head commercial rotational rheometer (Anton Paar MCR 702) to probe the linear viscoelasticity of these time-evolving materials.<br>The direct controllability of the PZR, resulting from the absence of any kind of firmware and the microsecond actuator-sensor response<br>renders this device ideal for exploring the advantages of this technique. The high frequency capability allows us to extend the upper limits of<br>the accessible linear viscoelastic spectrum and, most importantly, to shorten the length of the interrogating strain signal (OWCh-PZR) to subsecond<br>scales, while retaining a high time-bandwidth product. This short duration ensures that the mutation number (NMu) is kept sufficiently<br>low, even in fast-curing resins. The method is validated via calibration tests in both instruments, and the corresponding limitations are discussed.<br>As a proof of concept, the technique is applied to a curing vinylester resin. The linear viscoelastic (LVE) spectrum is assessed every<br>20 s to monitor the rapid evolution in the time and frequency dependence of the complex modulus. Comparison of the chirp implementation,<br>based on parameters such as duration of the experiment, sampling frequency, and frequency range, in a commercial rotational rheometer with<br>the PZR provides further information on the applicability of this technique and its limitations. Finally, FTIR spectroscopy is utilized to gain<br>insights into the evolution of the chemical network, and the gap dependence of the evolving material properties in these heterogeneous<br>systems is also investigated</p>
AI classification of normal and malignant cells on the basis of their viscoelastic properties
Open the record for dataset details and reuse information.
Dataset - Permeability and viscoelastic fracture of a model tumor under interstitial flow
<p>This includes all the experimental data which are presented in the paper titled "Permeability and viscoelastic fracture of a model tumor under interstitial flow", Soft Matter, 2018 by Quang D. Tran, Marcos and David Gonzalez-Rodriguez.</p> <p>In each data folder, we have attached a Readme file to instruct readers how to analyze or compute our data.</p>
Spatiotemporal dominance of afterslip and viscoelastic relaxation revealed by four decades of post-1973 Luhuo earthquake observations
<p>The datasets include: (1) post-processed fault-crossing short baseline data; (2) triangulation data; (3) coseismic slip models of the Zhuwo and Luhuo earthquakes; and (4) afterslip model of the Luhuo earthquake.</p>
Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth
<p>Supplementary data for the study "Unveiling the rheological control of magmatic systems on volcano deformation: the interplay of poroviscoelastic magma-mush and thermo-viscoelastic crust ", submitted in the Journal of Geophysical Research: Solid Earth</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.