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3,206 results for “property (T)”
Properties of recovered polyols by glycolysis of polyurethane waste foams
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Thermal and mechanical properties of PBSA and BIOCHAR blends
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Evolution of thermal and mechanical properties of PP-based composites subjected to mechanical recycling
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Effect of glycerol trilevulinate plasticizer on thermal and mechanical properties of PHB, PHBV, PLA, PVC and PCL polymers
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Engineering properties of Seawater-mixed LWAC
<p>The following files consists of data from the original article "Seawater-Mixed Lightweight Aggregate Concretes with Dune Sand, Waste Glass and Nanosilica: Experimental and Life Cycle Analysis" published in International Journal of Concrete Structures and Materials. The files are sequenced in the order of appearance of data from the article. <br>The worksheets in the uploaded file consists of data from the tests consistency, oven-dry density, thermal conductivity, open porosity, water absorption coefficient, and strength (2, 7, and 28 days) conducted on seawater-mixed light weight concretes. Also, the particle size distribution data of the raw materials used in this study is also included. The values are presented with units mentioned in appropriate locations. </p><p>Sheet 1: Particle size distribution of raw materials</p><p>Sheet 2: Slump flow data (Fresh state)</p><p>Sheet 3: Compressive strength data (@ 2, 7, and 28 days)</p><p>Sheet 4: Oven dry density data (@ 28 days)</p><p>Sheet 5: Open porosity data (@ 28 days)</p><p>Sheet 6: Thermal conductivity data (@ 28 days)</p><p>Sheet 7: Water absorption coefficient data (@ 28 days)</p><p>Link to access the published article at the source: https://link.springer.com/article/10.1186/s40069-023-00613-4</p><p>Specimen ID description: </p><p>QTW0 - CEM III with quartz sand (Tap water mixing)</p><p>QTW3 - CEM III + 3% nano-Silica with quartz sand (Tap water mixing)</p><p>QSW0 - CEM III with quart sand (Seawater mixing)</p><p>QSW3 - CEM III + 3% nano-Silica with quartz sand (Seawater mixing)</p><p>GTW0 - CEM III with crushed glass aggregate (Tap water mixing)</p><p>GTW3 - CEM III + 3% nano-Silica with crushed glass aggregate (Tap water mixing)</p><p>GSW0 - CEM III with crushed glass aggregate (Seawater mixing)</p><p>GSW3 - CEM III + 3% nano-Silica with crushed glass aggregate (Seawater mixing)</p><p>DTW0 - CEM III with dune sand (Tap water mixing)</p><p>DTW3 - CEM III + 3% nano-Silica with dune sand (Tap water mixing)</p><p>DSW0 - CEM III with dune sand (Seawater mixing)</p><p>DSW3 - CEM III + 3% nano-Silica with dune sand (Seawater mixing)</p><p> </p><p>PS - The attached file could be opened only with ORIGIN 2021b or any other compatible versions of the same software</p>
Dataset: Electromagnetic Properties of Indium Isotopes Elucidate the Doubly Magic Character of 100Sn
<p>Dataset for the article "Electromagnetic Properties of Indium Isotopes Elucidate the Doubly Magic Character of 100Sn."</p><p>Preprint at <a href="https://doi.org/10.48550/arXiv.2310.15093">arXiv.2310.15093.</a></p>
Sequence/simulation data for Direct Prediction of Intrinsically Disordered Protein Conformational Properties From Sequence
<p>This is a DOI-linked deposition of sequence/biophysical properties pairs used in the associated paper by Lotthammer et al:</p><p>Lotthammer, J. M.<strong>*</strong>, Ginell, G. M.<strong>*</strong>, Griffith, D.<strong>*</strong>, Emenecker, R. J. & Holehouse, A. S. <br>Direct Prediction of Intrinsically Disordered Protein Conformational Properties From Sequence.<br><i><strong>Nature Methods</strong></i> (<i>in press</i>), (2023).</p><p> </p>
StreetEasy Manhattan Properties September 2023
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Supporting data for 'Mechanical properties of the rocky interiors of icy moons' [DATASET]
<p>Supporting data for '<i>Mechanical properties of the rocky interiors of icy moons'</i>. </p><p>mechdata_6tests contains all data used for mechanical and elastic characteristics (Figure 1). </p><p>AEdata_7tests contains all data used for determining power from acoustic emissions released during deformation (Figure 2). pdata fields correspond to mechanical data - pstress, pstrain. </p><p>wavespeeddata_chondrite contains all data used for elastic wavespeeds during pressurization and depressurization (Figure 3). The AE_CAT_stack variable contains mechanical data, corresponding to columns in header variable. R_stack has stacked, smoothed waveforms. arrtime_afterpulse contains picked arrival times. </p>
DrugMol3D: An Expanded Collection of Molecular Data for Optimized Drug Structures and Descriptive Properties
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Electronic properties of MoSe2 nanowrinkles
<p>Dataset associated with a manuscript of the same name.</p>
Metadata - Direct C−H Arylation of Dithiophene-Tetrathiafulvalene: Tuneable Electronic Properties and 2D Self-Assembled Molecular Networks at the Solid/Liquid Interface
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Property-Based Testing in Practice: Codebook
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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>
Influence of ion irradiation on the nanomechanical properties of thin alumina coatings deposited on 316L SS by PLD
<p>Set consists three folders named after the methods used to obtained the data i.e. Nanoindentation, XRD and SEM.</p> <p><strong>→ SEM </strong></p> <p>In SEM folder there are 4 original image files that make up Figure 2 in the paper. Below please find the description:</p> <p><em>Fig. 2. SEM images of: (a) etched 316L SS surface; as-deposited PLD-grown Al2O3 coating on 316L SS: (b) cross-section, (c) surface; (d) surface of PLD-grown Al2O3 coating after ion irradiation (50 dpa).</em></p> <p><strong>→ XRD</strong></p> <p>In XRD folder there are two .txt files that makes up the Fig. 3 in the paper. In each of them there are two columns, where 1<sup>st</sup> is 2θ (°) and 2<sup>nd</sup> is Intensity (counts per second). Based on the filenames, they are clearly identifiable.</p> <p><strong>→ Nanoindentation</strong></p> <p>In Nanoindentation folder there are two folders dedicated to two different materials (coating and substrate steel). In each of these folders there are subfolders indicating data for the particular material state (level of dpa). To each unique combination of the material, state and nanoindentation force there are two .txt files assigned. First is named ‘LD [material] [dpa][force].txt’ and contains Load-displacement data. In such a file there are two columns, where 1<sup>st</sup> is force (mN) and 2<sup>nd</sup> is displacement (nm). Single curves are arranged one under another (separated with two empty rows). Second file is named ‘AR [material] [dpa][force].txt’ and contains aggregate data. For reproducing the calculations given in the paper, first seven columns from the file are needed:</p> <p>1<sup>st</sup> – measurement No</p> <p>3<sup>rd</sup> - Maximum indentation depth h(max) (nm)</p> <p>4<sup>th</sup> - Indenter contact depth at F(max) h(c) (nm)</p> <p>5<sup>th</sup> – Maximum force (mN)</p> <p>6<sup>th</sup> - Indentation hardness H(IT) (GPa)</p> <p>7<sup>th</sup> – Reduced modulus E (GPa)</p>
High versus low energy ion irradiation impact on functional properties of PLD-grown alumina coatings
<p>Set consists two folders named after the methods used to obtained the data i.e. Nanoindentation and SEM.</p> <p><strong>→ SEM </strong></p> <p>In SEM folder there are 3 original image files that make up Figure 3 in the paper. Based on the filenames, they are clearly identifiable.</p> <p><strong>→ Nanoindentation</strong></p> <p>To each material state (dpa level) and energy (high – HE or low - LE) there is one .txt file assigned. Each file is named ‘[HE/LE] [dpa level] L-D.txt’ and contains Load-displacement data. In such a file there are two columns, where 1<sup>st</sup> is displacement (nm) and 2<sup>nd</sup> is force (mN). Single curves are arranged one under another (separated with two empty rows). The curves where used to make up Figure 5.</p>
Microstructure and mechanical properties of mechanically-alloyed CoCrFeNi high-entropy alloys using low ball-to-powder ratio
<p>The main issue of this work was to analyse the microstructural evolution and mechanical properties of FCC high entropy alloy (HEA) when BPR (ball-to-powder ratio) was limited to 5:1. The motivation of our work is to increase the amount of milled fraction without losing efficiency of the milling process. Nowadays many papers describe HEAs by using powder metallurgy processes, but higher BPR is used. In consequence less amount of powder is milled in one period and the process is not effective enough from the industrial point of view.</p> <p>In this work four equiatomic CoCrFeNi samples were made by Mechanical Alloying plus Spark Plasma Sintering using different milling times: 10, 20, 30, 40 hours. We used 200 Φ5 mm WC balls and milled with intervals 15:15 minutes. Milling speed was 250 rpm. After the mechanical alloying has been finished samples were sintered by using Spark Plasma Sintering technique. We chose 950 °C as a process temperature with heating rate 100 °C/min. Sintering pressure was 50 MPa. Samples were then homogenise in 1050 °C for 12 hours. Then samples were water quenched.</p> <p>The densification of samples during sintering was in satisfied level, what was confirmed by relative densities of samples (>90 %) The microstructure observation of sintered samples revealed Cr-rich particles evenly distributed in samples volume. The number of particles decreases with increasing the milling time. Elements are randomly distributed in the matrix phase except a small Cr-depletion. XRD technique shows multiple FCC structure. As the milling time exceeds, the main FCC structure is promoted. Microhardness increased as a function of milling time. After annealing microstructures were almost out of Cr-rich phase. Only the biggest particles remained. EBSD revealed the grain size decrement as a function of milling time. Also X-ray diffractograms presented significant homogenisation of manufactured samples. Despite the microhardness decrease after heat treatment, the longest milled sample still possess very promising properties. Moreover hardness of samples is not indent’s size dependent (micro- and nanohardness).</p> <p>During milling time the particles are joining and fracturing many times. As a consequence elements are mixing and promoting the new phase(s) growing. We deduced that Hall-Petch effect is the most important factor determining better mechanical properties in longer milled samples. However the milling process need to be improvement. Cr-rich phase observed in sintered samples is the effect of low efficiency of the process, which might be improved by either smaller fraction of Cr at the beginning (premilling process) or increase the other process parameters (milling speed, sintering time).</p>
Psychometric properties of Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE®) in breast cancer patients: the prospective observational multicenter VIP study.
<p>Dataset for the proposed manuscript Psychometric properties of Patient-Reported Outcomes Common Terminology Criteria for Adverse Events (PRO-CTCAE®) in breast cancer patients: the prospective observational multicenter VIP study. </p>
A new method for eliminating dust effects when quantifying the light absorption properties of brown carbon
<p>Accurate quantification of the absorption properties of brown carbon (BrC) aerosols is crucial to assess the Earth-atmosphere radiative impacts of BrC. However, the BrC absorption properties were often misestimated in field observations, due to neglecting the contribution of dust absorption. This study solved this problem by coupling a method for calculating the dust concentration into the traditional model for quantifying BrC absorption. The results show that dust absorption was up to 16.8% of the sum of BrC and dust absorption in northwestern China. The potential contribution of dust to the sum of BrC and dust absorption was significantly higher in the Asia-located studies (0.4−16.8%) than in the Americas-located (<1.2%) and Europe-located (<2.3%) studies. This work underscores the necessity of eliminating the negative effect of dust in BrC quantitative model. It prompts us to revisit the BrC absorption properties resolved by previous studies, especially in dust-influenced areas such as Asia.</p> <p>The data file contains data from the AE31 aethalometer, aerodynamic particle sizer spectrometer (APS), tapered element oscillating microbalance machine (TEOM), and high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) used in this study, as well as data from each figure in this study.</p>
Data from: Evaluating the influence of novel charge transport materials on the photovoltaic properties of MASnI3 solar cells
<p>In recent decades, substantial advancements have been made in photovoltaic technologies, leading to impressive power conversion efficiencies exceeding 25% in perovskite solar cells (PSCs). Tin-based perovskite materials, characterized by their low band gap (1.3 eV), exceptional optical absorption, and high carrier mobility, have emerged as promising absorber layers in PSCs. Achieving high performance and stability in PSCs critically depends on the careful selection of suitable charge transport layers (CTLs). This research investigates the effects of five copper-based hole transport materials and two carbon-based electron transport materials in combination with methyl ammonium tin iodide (MASnI<sub>3</sub>). The carbon-based CTLs exhibit excellent thermal conductivity and mechanical strength, while the copper-based CTLs demonstrate high electrical conductivity. The study comprehensively analyzes the influence of these CTLs on PSC performance, including band alignment, quantum efficiency, thickness, doping concentration, defects, and thermal stability. Furthermore, a comparative analysis is conducted on PSC structures employing both p-i-n and n-i-p configurations. The highest-performing PSCs are observed in the inverted structures of CuSCN/MASnI3/C60 and CuAlO<sub>2</sub>/MASnI<sub>3</sub>/C<sub>60</sub>, achieving power conversion efficiencies (PCE) of 23.48% and 25.18%, respectively. Notably, the planar structures of Cu<sub>2</sub>O/MASnI<sub>3</sub>/C<sub>60</sub> and CuSbS<sub>2</sub>/MASnI<sub>3</sub>/C<sub>60</sub> also exhibit substantial PCE, reaching 20.67% and 20.70%, respectively.</p>
ScienceDex guides
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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.