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.
182
datasets available to search
ShareScore release 0.7.1
Dataset results
182 results for “aluminum”
Dataset: Kaiser Aluminum Corporation (KALU) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Figure 9 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 9. Means number of deposited eggs by females of tested mites after 4 days post-exposure to α- and γ-Al2O3 NPs at tested concentrations. Different letters denote to significant differences in means at tested concentrations (Duncan test, P ≤ 0.05).
Figure 12 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 12. SEM visualization of α- and γ-Al2O3 NPs aggregation on ventral side of C. mycophagus mite. A = treated female by α-Al2O3 NPs, B = treated female by γ-Al2O3 NPs, C = untreated female.
Figure 7 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 7. Females, nymphal and larval mortality (means ± SE) of C. mycophagus mites, subjected to synthesized α- and γ- Al2O3 NPs at different concentrations and exposure time – A. α-Al2O3 NPs; B. γ-Al2O3 NPs. Different letters within the same exposure time are significantly different (Duncan test, P ≤ 0.05).
Figure 5 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 5. Females, nymphal and larval mortality (means ± SE) of M. fungivorus mites, subjected to synthesized α- and γ-Al2O3 NPs at different concentrations and exposure time – A. α-Al2O3 NPs; B. γ-Al2O3 NPs. Different letters within the same exposure time are significantly different (Duncan test, P ≤ 0.05).
Figure 14 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 14. Mean growth Inhibition (A) and corresponding percentage (B), of F. oxysporum in response to different concentrations of α and γ-Al2O3 NPs after 5 days of growth at 30 °C and 180 rpm in PDB growth medium (Where R2: the relation coefficient and y: the predicted fungal inhibition value at "X" nanoparticles concentration).
Figure 6 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 6. Mortality (means ± SE) of M. fungivorus females, nymphs and larvae, concerning α- and γ-Al2O3 NPs at tested concentrations and exposure time.
Figure 10 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 10. Females' mortality (means ± SE) of (A) M. fungivorus and (B) C. mycophagus mites subjected to synthesized α and γ-Al2O3 NPs at different concentrations and exposure time. different letters within the same concentrations are significantly different, Duncan test (P ≤ 0.05).
Figure 13 in Morphological, optical and thermal properties of α- and γ-aluminum nanoparticles: Assessment of their biological activities against storage mites and mycotoxin producing fungi
Figure 13. Mean growth Inhibition (A) and corresponding percentage (B) of Aspergillus flavus in response to different concentrations of α- and γ-AL2O3 NPs after five days of growth at 30 ℃ and 180 rpm in PDB growth medium. (Where R2: the relation coefficient and y: the predicted fungal inhibition value at "X" nanoparticles concentration).
Figure 8 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 8. AST levels in the serum of female rats orally exposed to Al2 O 3, TiO2, and CuO nanoparticles for 14 days. Details are given in Figure 1.
Figure 7 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 7. ALT levels in the serum of female rats orally exposed to Al2 O 3, TiO2, and CuO nanoparticles for 14 days. Details are given in Figure 1.given in Figure 1.
Figure 6 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 6. ALP levels in the serum of female rats orally exposed to Al2 O 3, TiO2, and CuO nanoparticles for 14 days. Details are given in Figure 1.
Figure 5 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 5. Total antioxidant levels in the serum of female rats orally exposed to Al2 O 3, TiO2, and CuO nanoparticles for 14 days. Details are given in Figure 1.
Figure 4 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 4. Total oxidant levels in the serum of female rats orally exposed to Al O, TiO, and CuO nanoparticles for 14 days. 2 3 2 Details are given in Figure 1.
Figure 3 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 3. The activity of Ca-ATPase in the erythrocytes of female rats orally exposed to Al O, TiO, and CuO nanoparticles for 14 2 3 2 days. Details are given in Figure 1.
Figure 1 in Effects of aluminum, copper, and titanium nanoparticles on some blood parameters in Wistar rats
Figure 1. The activity of Na,K-ATPase in the erythrocytes of female rats orally exposed to Al 2 O 3, TiO 2, and CuO nanoparticles for 14 days. Each point shows the mean of 6 rats and the standard errors. Statistical results and % alterations are given in the Table.
Accompanying dataset for the paper "An implicit staggered algorithm for CPFEM-based analysis of aluminum"
<h2>Contributions</h2> <ul> <li>Pedro Areias did contribute to general programming and theory</li> <li>Charles dos Santos did contribute to investigation, specific programming and validation</li> <li>Rui Melicio did contribute to the text and typesetting</li> <li>Nuno Silvestre did contribute to the Scientific validation</li> </ul> <h2>Funding sources</h2> <ul> <li>FCT Fundação para a Ciência e a Tecnologia project LAETA Base Funding (DOI: 10.54499/UIDB/50022/2020)</li> </ul> <h2>Data structure and information</h2> <ul> <li>data - <code>dataset directory</code><ul> <li>convertFig2Eps - <code>script to convert xfig sources to EPS</code></li> <li>driftfigures - <code>data to assess drifting in \xi and effective strain</code> <ul> <li>cuboid.gid - <code>directory for a single cube analysis, to assess drifting</code></li> </ul> </li> <li>epcfigures - <code>these are the sources for the cylinder test with localization</code><ul> <li>cylindersinglecrystalcoarse.gid - <code>cylinder with ( $\theta=0.25\pi,\phi=0$)</code></li> <li>cylindersinglecrystalcoarseotherangles.gid - <code>cylinder with ($\theta=0.304\pi,\phi=0.25\pi$")</code></li> </ul> </li> <li>errorlogstrain - <code>contains the mathematica sheet for the plots in the logstrain error analysis</code></li> <li>originalfigures - <code>these are the original figures in the paper</code></li> <li>padeerrorgraf - <code>mathematica sheet for the analysis of padé approximation error</code></li> <li>reactions - <code>reactions sources for the localization problem</code></li> </ul> </li> <li>workflows - <code>reproducibility of some of the computational results</code></li> </ul> <h2>Dataset Description</h2> <p>Contains:</p> <ul> <li>Data sources from SimPlas (txt and order)</li> <li>Gnuplot files (gp)</li> <li>Tikz files (tikz)</li> <li>XFig files (fig)</li> <li>Mathematica scripts (nb)</li> <li>Script to convert Xfig in Eps: figtex2eps.sh</li> </ul> <p><em>Original figures are also included.</em></p> <h2>Paper Description</h2> <p>In this paper, we propose an implicit staggered algorithm for crystal plasticity finite element method (CPFEM) which makes use of dynamic relaxation at the constitutive integration level. An uncoupled version of the constitutive system consists of a multi-surface flow law complemented by an evolution law for the hardening variables. Since a saturation law is adopted for hardening, a sequence of nonlinear iteration followed by a linear system is feasible. To tie the constitutive unknowns, the dynamic relaxation method is adopted. A Green-Nagdhi plasticity model is adopted based on the Hencky strain calculated using a [ 2/2 ] Padé approximation. For the incompressible case, the approximation error is calculated exactly. A enhanced-assumed strain (EAS) element technology is adopted, which was found to be especially suited to localization problems such as the ones resulting from crystal plasticity plane slipping. Analysis of the results shows significant reduction of drift and well defined localization without spurious modes or hourglassing.</p>
Supplementary Materials for: Intense alteration on early Mars revealed by high-aluminum rocks at Jezero crater
<p>Supplementary tables S3 and S4 for "Intense alteration on early Mars revealed by high-aluminum rocks at Jezero crater" published in Nature Communications Earth & Environment.</p>
Dataset for publication: "Magnesium and Aluminum in Contact with Liquid Battery Electrolytes: Ion Transport through Interphases and in the Bulk"
<div> </div> <div> <p>This is the experimental raw data set associated with the following publication: M. Löw, J. Grill, MM May, and J. Popovic-Neuber, Magnesium and Aluminium in Contact with Liquid Battery Electrolyte: Ion Transport through Interphases and in the Bulk, ACS Material Letters (2024). DOI:10.1021/acsmaterialslett.4c01589</p> <p>The data set is organized according to the publication's figures. </p> </div>
Data from: Temperature-dependent mechanical behavior of aluminum AM structures generated via multi-layer friction surfacing
<p>This dataset contains the data for the publication " Temperature-dependent mechanical behavior of aluminum AM structures generated via multi-layer friction surfacing "</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.