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ShareScore release 0.9.0
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6 results for “Laser Texturing”
Polygon Laser Texturing Process
<p>Polygon Laser Texturing Process</p>
Laser Texturing Process
<p>Laser Texturing Process</p>
Data from: Making soil particle size analysis by laser diffraction compatible with standard soil texture determination methods
The standard sieving, pipette and hydrometer methods for soil particle size analysis (PSA) have three main drawbacks: procedures are tedious, time-consuming, and the results are protocol-dependent. Laser diffraction PSA delivers rapid results using standardized procedures, but so far it has been difficult to reconcile results with those from standard sedimentation methods. The objective of this study was to develop a protocol that would permit direct usage of laser diffraction PSA and render results compatible with current methods. The protocol was developed using standard soil samples from different textural classes. Regression of the laser diffraction PSA against the hydrometer/pipette method yielded coefficients of determination of 0.92/0.9, 0.92/0.94 and 0.99/0.99, and root mean square errors of 0.04/0.05, 0.07/0.06 and 0.05/0.03 for clay, silt and sand, respectively. These statistics are comparable to those obtained by regressing results of the hydrometer against the sieve and pipette methods. A key factor in securing accurate and precise results was limiting the particle size range of the samples by wet sieving the sand fraction. This created representative samples and stable soil dispersed suspensions, allowing accurate estimations of particle size distribution for clay and silt fractions without empirical transformations. Results obtained with the proposed protocol matched those of standard sedimentation analyses for a wide range of soils, encouraging further adoption of laser diffraction for soil PSA.
Data from: Making soil particle size analysis by laser diffraction compatible with standard soil texture determination methods
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Tailored deformation behavior of 304L stainless steel through control of the crystallographic texture with Laser-Powder Bed Fusion
<p>Laser-powder bed fusion (L-PBF) has gained significant research interest, not only for its profound advantage of producing near-net shape complex geometries of metallic parts, but also for the possibility of producing tailored microstructures. Recent observations have shown that by adjusting the process parameters it is possible to manipulate the crystallographic texture, through the control of the geometrical features of the melt pool. It is also known that the deformation behavior, namely the transformation induced plasticity or twinning induced plasticity effects, of austenitic stainless steels are dependent on the crystallographic texture. Based on the aforementioned observations, the deformation behavior of austenitic stainless steels processed by L-PBF can be tailored. By adjusting the laser power and the laser scanning speed, tailored crystallographic textures were obtained, along the uniaxial loading direction in 304L stainless steel samples produced by L-PBF. The possibility to engineer the crystallographic textures and thus the deformation behavior, in metastable stainless steels, is demonstrated by performing in situ neutron diffraction and uniaxial tension and compression tests. The influence of the initial and the evolving crystallographic texture on the deformation behavior is demonstrated and elaborated accordingly. The observed asymmetry in the deformation behavior between tension and compression is also discussed in detail.</p>
Data from: Making soil particle size analysis by laser diffraction compatible with standard soil texture determination methods
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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.