Skip to main content
Powered by ShareScore

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.

5

datasets available to search

ShareScore release 0.7.1

Reset

Dataset results

5 results for “Kikuchi pattern”

Learn how ShareScore rates datasets ↗
zenodo40/100

Supplementary Data: Mapping of local lattice parameter ratios by projective Kikuchi pattern matching

<p>This is the experimental dataset which was analyzed in:</p> <p>&quot;Mapping of local lattice parameter ratios by projective Kikuchi pattern matching&quot;<br> Aimo Winkelmann, Gert Nolze, Grzegorz Cios, and Tomasz Tokarski<br> Phys. Rev. Materials&nbsp;<strong>2</strong>&nbsp;(2018) 123803<br> https://doi.org/10.1103/PhysRevMaterials.2.123803</p> <p>We describe a lattice-based crystallographic approximation for the analysis of distorted crystal structures via electron backscatter diffraction (EBSD) in the scanning electron microscope. EBSD patterns are closely linked to local lattice parameter ratios via Kikuchi bands that indicate geometrical lattice plane projections. Based on the transformation properties of points and lines in the real projective plane, we can obtain continuous estimations of the local lattice distortion based on projectively transformed Kikuchi diffraction simulations for a reference structure. By quantitative image matching to a projective transformation model of the lattice distortion in the full solid angle of possible scattering directions, we enforce a crystallographically consistent approximation in the fitting procedure of distorted simulations to the experimentally observed diffraction patterns. As an application example, we map the locally varying tetragonality in martensite grains of steel.</p>

opencc-by-4.0Dec 2018View details →
zenodo36/100

Kikuchi patterns for cNMF analysis.

<p><strong>Employing constrained non-negative matrix factorization for microstructure segmentation</strong></p> <p>Materials characterization using electron backscatter diffraction (EBSD) requires indexing the orientation of the measured region from Kikuchi patterns. The quality of Kikuchi patterns can degrade due to pattern overlaps arising from two or more orientations, in the presence of defects or grain boundaries. In this work we employ constrained non-negative matrix factorization to segment a microstructure with small grain misorientations,~\mbox{($&lt;1\degree$)}, and predict the amount of pattern overlap. First we implement the method on mixed simulated patterns - that replicates a pattern overlap scenario, and demonstrate the resolution limit of pattern mixing or factorization resolution using a weight metric. Subsequently, we segment a single-crystal dendritic microstructure and compare the results with high resolution EBSD. By utilizing weight metrics across a low angle grain boundary we demonstrate how very small misorientations/low-angle grain boundaries can be resolved at a pixel level. Our approach constitutes a versatile and robust tool, complementing other fast indexing methods for microstructure characterization.</p>

opencc-by-4.0Feb 2024View details →
zenodo36/100

EBSD Kikuchi Pattern Analysis, Silicon 15kV

<p>Supplementary Data and Images for Si EBSD pattern analysis as presented in</p> <p>A. Winkelmann, T.B. Britton, G. Nolze &quot;Constraints on the effective electron energy spectrum in backscatter Kikuchi diffraction&quot;, Physical Review B (2019)</p>

opencc-by-4.0Feb 2019View details →
dryad36/100

Kikuchi pattern dataset from wrought and as-built additively manufactured superalloys

Open the record for dataset details and reuse information.

publicSep 2025View details →
zenodo32/100

EBSD Kikuchi Patterns from Identification, classification and characterisation of hydrides in Zr alloys

<p>Data from paper <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.scriptamat.2023.115768" target="_blank" rel="noreferrer noopener"><span><span>https://doi.org/10.1016/j.scriptamat.2023.115768</span></span></a></p>

opencc-by-4.0Oct 2024View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record