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.
73
datasets available to search
ShareScore release 0.9.0
Dataset results
73 results for “Mechanical characterization”
Soil Organic Matter Mechanisms of Stabilization (SOMMOS) - enhanced soil characterization data from 40 National Ecological Observatory Network (NEON) sites
Soil organic matter (SOM) is a critical linkage among many ecosystem services that sustain our society and life on Earth. It is the primary energy source for microbes and the principal storehouse of water necessary for plant growth. SOM also stores nutrients for plants and sorbs pollutants that otherwise could contaminate food and water supplies. Soils also help regulate climate by storing carbon that would otherwise be released to the atmosphere and contribute to climate change. The SOMMOS project investigated processes in the soil that protect SOM from being decomposed by microbes, processes that increase its sensitivity to environmental changes, and how changes in climate and land management influence the amount and stability of SOM. The project, which was a collaboration between scientists from the National Ecological Observatory Network (NEON), University of Colorado, University of Michigan, Oregon State University, Virginia Polytechnic Institute and State University, and the USDA-Forest Service, took advantage of soil samples collected across NEON, a major NSF investment in environmental monitoring that covers the entire United States. This continental-scale soil sample set was analyzed for a wide array of physical and chemical properties, well beyond those typically measured on such a large-scale sample set, including radiocarbon, extractable metals, organic matter chemistry by pyrolysis-GCMS, liquid extract fluorescence spectroscopy, and more. In addition to this dataset, archived samples are available from the project for sharing with interested researchers.
Dataset for a publication: "A zinc phosphate layered biodegradable Zn-0.8Mg-0.2Sr alloy: Characterization and mechanism of hopeite formation"
<p>These data are published as part of the paper: A zinc phosphate layered biodegradable Zn-0.8Mg-0.2Sr alloy: Characterization and mechanism of hopeite formation. The structure and organization of the data are outlined in the readme file. </p> <p> </p>
A coupled MD-FE methodology to characterize mechanical interphases in polymeric nanocomposites: pseudo-experimental data
<p>readme.txt</p> <p><strong>Abstract:</strong><br> (from [1])</p> <blockquote> <p>This contribution introduces an unconventional procedure to characterize spatial profiles of elastic and inelastic properties inside polymer interphases around nanoparticles. Interphases denote those regions in the polymer matrix whose mechanical properties are influenced by the filler surfaces and thus deviate from the bulk properties. They are of particular relevance in case of nano-sized filler particles with a comparatively large surface-to-volume ratio and hence can explain the frequent observation that the overall properties of polymer nanocomposites cannot be determined by classical mixing rules, which only consider the behavior of the individual constituents.<br> <br> Interphase characterization for nanocomposites poses hardly solvable challengesto the experimenter and is still an unsolved problem in many cases. Instead of real experiments, we perform pseudo experiments using our recently developed Capriccio method, which is an MD-FE domain-decomposition tool specifically designed for amorphous polymers. These pseudo-experimental data then serve as input for a typical inverse parameter identification. With this procedure, spatially varying mechanical properties inside the polymer are, for the first time, translated into intuitively understandable profiles of continuum mechanical parameters.</p> <p><br> As a model material, we employ silica-enforced polystyrene, for which our procedure reveals exponential saturation profiles for Young’s modulus and the yield stress inside the interphase, where the former takes about seven times the bulk value at the particle surface and the latter roughly triples. Interestingly, hardening coefficient and Poisson’s ratio of the polymer remain nearly constant inside the interphase. Besides gaining insight into the constitutive influence of filler particles, these unexpected and intriguing results also offer interesting explanatory options for the failure behavior of polymer nanocomposites.</p> </blockquote> <p> </p> <p><strong>Contact:</strong></p> <p>Maximilian Ries<br> Institute of Applied Mechanics<br> Friedrich-Alexander-Universiät Erlangen-Nürnberg<br> Egerlandstr. 5<br> 91058 Erlangen</p> <p> </p> <p><strong>License:</strong></p> <p>Creative Commons Attribution 4.0 International</p> <p> </p> <p><strong>Context:</strong></p> <p>Data set supplementing journal paper:<br> [1] Ries, M.; Possart, G.; Steinmann, P. & Pfaller, S., "A coupled MD-FE methodology to characterize mechanical interphases in polymeric nanocomposites," <em>International Journal of Mechanical Sciences, </em><em>Elsevier, </em><strong>2021</strong>, 106564.</p> <p>This dataset contains the results of a multiscale study on polystyrene-silica nanocomposites using an atomistic-continuum coupling approach. 120 polystyrene samples, each containing 2 nano-sized silica particles are subjected to uniaxial tension. Here we use coarse-grained molecular dynamics (MD) domain embedded into a larger finite element (FE) region. These two resolutions are coupled in a concurrent multiscale fashion using the so-called Capriccio method. We observe the deformation state of the MD and FE domain, as well as the relative displacement of the two nanoparticles with respect to each other. Based on this pseudo-experimental data, we derive the material properties (Young's modulus, Poisson's ratio, yield stress, hardening) of the interphase forming in the proximity of the nanoparticles in [1].</p> <p>A more detailed description of the used methods can be found in Ries et al. [1].</p> <p> </p> <p><strong>Content:</strong></p> <p>The attached text file contains the following quantities (columns) for all samples (rows):</p> <ul> <li>sample: [initial nanoparticle distance]-ID</li> <li>d0_NP: initial distance of nanoparticles in nm</li> <li>rot_x: rotation of nanoparticles with respect to x-axis in degree</li> <li>d_NP: distance of nanoparticles in nm (after equilibration)</li> <li>Elements: number of finite elements</li> <li>Element_warnings: number of element warnings by Abaqus</li> <li>LS: loadstep 1-6</li> <li>eps_NP(LS): tensile strain of nanoparticles in loadstep LS in %</li> <li>eps_MD(LS): tensile strain of MD domain in loadstep LS in %</li> <li>eps_NP_MD(LS): tensile strain of nanoparticles normalized to eps_MD(LS) in loadstep LS</li> <li>eps_FE(LS): tensile strain of FE domain in loadstep LS in %</li> <li>eps_NP_FE(LS): tensile strain of nanoparticles normalized to eps_FE(LS) in loadstep LS</li> <li>eps_NP_FE(LS): tensile strain of nanoparticles normalized to eps_FE(LS) in loadstep LS</li> <li>u_max(LS): maximum displacement of FE nodes in load step LS in nm</li> <li>F_ext(LS): external force in load step LS in E-11 N</li> </ul> <p> </p>
Mechanical Properties and Fracture Characterization of Additive Manufacturing Polyamide 12 After Accelerated Weathering
<p>A dataset for the publication: T. Puttonen, M. Salmi, J. Partanen, Mechanical Properties and Fracture Characterization of Additive Manufacturing Polyamide 12 After Accelerated Weathering, 2021.</p> <p>The paper studies the mechanical properties and fracture mechanics of Additive Manufacturing (AM) polyamide 12 (PA12) in two build orientations exposed to a 1500-hour accelerated weathering cycle (ISO-4982-3) followed by tensile testing (ISO-527). Fracture surfaces of X and Z build orientation AM PA12 and X build orientation AM glass-filled PA12 were studied with scanning electron microscopy. The tested AM materials were PA12, glass-filled PA12, and carbon-reinforced PA12. The reference materials cut from sheet included glass-filled and molybdenum disulfide-filled PA66, PMMA, ABS, PC, and cast PA12.</p> <p>The dataset contains:</p> <p>- Full tensile test results in PDF format, and individual CSV files</p> <p>- A python script for tensile CSV data plotting</p> <p>- Overall pictures of all samples after tensile tests</p> <p>- 3D models and drawings for tensile samples, manufacturing files for a custom QUV holder assembly</p> <p>- SEM images of fracture surfaces for AM polyamide 12 (SLS), X and Z build orientation, and glass-filled polyamide 12 (SLS) in the X build orientation</p> <p> </p> <p>Version history:</p> <p>1.0.1: A partially corrupted version of the tensile test results PDF file replaced (Tensile_test_results.pdf)</p>
Data from: A pioneering experimental investigation of a novel in-situ dynamic characterization of the tensile/compression stress-strain mechanism on human plantar soft tissue
<p><span>We have conducted the first in-situ and in-vivo dynamic mechanical test on human plantar soft tissue. A dynamic mechanical analysis (DMA)-like device has been invented to perform the in-situ and in-vivo stress-strain tests on living plantar in order to characterize the material mechanism of biological soft tissue, whereas it is nearly impossible to prepare a sample from a living body for classical tests. A series of pioneering tests of tensile/compression on the heel of ten volunteers are reported, with the reference of tests on mimic foot model made by silicon rubber, standard silicon rubber brick sample, and finite elementary analysis. In addition to demonstrating the effectiveness of the device and approach, interesting correlations between the results and clinic data were found, suggesting considerable potential for the invention in future research.</span></p>
Results of the mechanical characterization by tensile tests and the in vitro cell-biomaterial interaction analyses by WST-1 and Live/Dead of 3D-printed scaffolds generated by PLA, PCL, FF, FD and GelMA
<p>Dataset containing the quantitative results of the mechanical characterization, and the in vitro cell-biomaterial interaction analyses with neural cells after 72 hours and 7 days of cell culture of the following 3D printed scaffolds:</p> <ul> <li>Polylactic acid (PLA)</li> <li>Polycaprolactone (PCL)</li> <li>Conductive Filaflex (FF)</li> <li>Flexdym (FD)</li> <li>GelMA (G)</li> </ul> <p>The Live/Dead results were quantified using ImageJ software to determine area fractions corresponding to live (green) and dead (red) cells.</p>
Data supplement for "Wetting dynamics under periodic switching on different scales: Characterization and mechanisms"
<p>Data set and python code to recreate the figures of "Wetting dynamics under periodic switching on different scales: Characterization and mechanisms". Additionally, it includes the oomph-lib Code to reproduce the data for the simulations in the mesoscopic thin-film model.</p>
A novel technique to simulate and characterize a yarn's mechanical behavior based on a geometrical fiber model extracted from micro-CT imaging: geometry and simulation data
<p>This dataset contains the original µCT scan data, the scripts and intermediate results for the generation of the geometrical fiber model, as well as the structural simulation files and their experimental validation data described in the paper <a href="https://journals.sagepub.com/doi/10.1177/00405175221137009">"A novel technique to simulate and characterize a yarn's mechanical behavior based on a geometrical fiber model extracted from micro-CT imaging"</a>, published in Textile Research Journal.</p>
Data from: A pioneering experimental investigation of a novel in-situ dynamic characterization of the tensile/compression stress-strain mechanism on human plantar soft tissue
Open the record for dataset details and reuse information.
RAW Data - Mechanical characterization for the severely processed FSPed WE54 magnesium alloy
<p>The present data set present the raw data of the mechanical characterization of a WE54 magnesium alloy, processed by friction stir processing (FSP), using a refrigerated backing anvil. File names describe the kind and characteristics of each test as follows: </p> <ol> <li>All file names start by the initial temper of the WE54 magnesium alloy (T6 or TT) followed by the FSP processing conditions: first two digits are the rotation speed while the second two digits correspond to the advancing speed, both divided by a factor of 100.</li> <li>Files tagged at the end as _iUMI.opj correspond to the characterization by instrumented ultra-microindentation and provide a data matrix including prosition and hardness value (readable in Origin).</li> <li>Files tagged at the end as _CSRtt.opj correspond to the characterization by constant strain rate tensile test.</li> </ol>
Characterizing the molecular mechanisms for flipping charged peptide flanking loops across a lipid bilayer
<p>All simulation input data and analysis tools for regenerating results from the journal paper:</p> <p>S. J. Patel and R. C. Van Lehn. "Characterizing the Molecular Mechanisms for Flipping Charged Peptide Flanking Loops across a Lipid Bilayer." The Journal of Physical Chemistry B <strong>2018</strong> <em>122</em> (45), 10337-10348</p>
Characterization of Low Density Lipoprotein and Mechanism of the Pro Aggregant Effect Through Oxidant Stress and Lipid Exchange
ClinicalTrials.gov study NCT00932087. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Characterization of the Mechanisms of Resistance to Azacitidine
ClinicalTrials.gov study NCT01210274. IPD Sharing: NO. Countries: 2. Publications: 1.
Non-invasive Characterization of the Mechanisms of Atrial Fibrillation Maintenance
ClinicalTrials.gov study NCT02497248. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Characterization of Fungal Infections in COVID-19 Infected and Mechanically Ventilated Patients in ICU
ClinicalTrials.gov study NCT04368221. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Raw data for the article: Regional biomechanical characterization of human ascending aortic aneurysms: Microstructure and biaxial mechanical response
<p>The ascending thoracic aortic aneurysm (ATAA) is a permanent dilatation of the vessel with a high risk of adverse events, and shows heterogeneous properties. To investigate regional differences in the biomechanical properties of ATAAs, tissue samples were collected from 10 patients with tricuspid aortic valve phenotype and specimens from minor, anterior, major, and posterior regions were subjected to multi-ratio planar biaxial extension tests and second-harmonic generation (SHG) imaging. Using the data, parameters of a microstructure-motivated constitutive model were obtained considering fiber dispersion. SHG imaging showed disruptions in the organization of the layers. Structural and material parameters did not differ significantly between regions. The non-symmetric fiber dispersion model proposed by Holzapfel et al. [25] was used to fit the data. The mean angle of collagen fibers was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. The experimental data collected in this study contribute to the biomechanical data available in the literature on human ATAAs. Region-specific parameters for the constitutive models are fundamental to improve the current risk stratification strategies, which are mainly based on aortic size. Such investigations can facilitate the development of more advanced finite element models capable of capturing the regional heterogeneity of pathological tissues. STATEMENT OF SIGNIFICANCE: Tissue samples of human ascending thoracic aortic aneurysms (ATAA) were collected. Samples from four regions underwent multi-ratio planar biaxial extension tests and second-harmonic generation imaging. Region-specific parameters of a microstructure-motivated model considering fiber dispersion were obtained. Structural and material parameters did not differ significantly between regions, however, the mean fiber angle was negatively correlated between minor and anterior regions, and the parameter associated with collagen fiber stiffness was positively correlated between minor and major regions. Furthermore, correlations were found between the stiffness of the ground matrix and the mean fiber angle, and between the parameter associated with the collagen fiber stiffness and the out-of-plane dispersion parameter in the posterior and minor regions, respectively. This study provides a unique set of mechanical and structural data, supporting the microstructural influence on the tissue response. It may facilitate the development of better finite element models capable of capturing the regional tissue heterogeneity.</p>
Structuran and NMR Characterization of Hexamer and Octamer Foldamers in Chloroform and Water: A Molecular Dynamics and Quantum Mechanics Approach
Open the record for dataset details and reuse information.
Nanoscale structural and mechanical characterization of thin bicontinuous cubic phase lipid films
<p>In the manuscript, Atomic Force Microscopy (AFM) and AFM-Force Spectroscopy (AFM-FS) are employed for obtaining the first nanomechanical characterization of bicontinuous cubic phase lipid film, presenting a thickness of 150 nm. </p>
Mechanical and electrochemical characterization of 3D printed orthodontic metallic appliances after in vivo ageing
<p>Dataset for all analyses</p>
Characterization and Brain Mechanisms of Frustration in Youth With Severe Irritability or Attention Deficit Hyperactivity Disorder (ADHD)
ClinicalTrials.gov study NCT05357495. IPD Sharing: YES. Countries: 1. Publications: 0.
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.