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19 results for “Microstructure analysis”
Automated Segmentation of Large Image Datasets using Artificial Intelligence for Microstructure Characterisation and Damage Analysis
<p>Many properties of commonly used materials are driven by their microstructure, which can be influenced<br>by the composition and manufacturing processes. To optimise future materials, understanding the<br>microstructure is critically important. Here, we present two novel approaches based on artificial intelligence<br>that allow the segmentation of the phases of a microstructure for which simple numerical approaches, such<br>as thresholding, are not applicable: One is based on the nnU-Net neural network, and the other on generative<br>adversarial networks (GAN).<br>Using scanning electron microscopy images collected from large areas (~1 mm²) of dual-phase steels as a<br>case study, we demonstrate how both methods effectively segment intricate microstructural details,<br>including martensite, ferrite, and damage sites, for subsequent analysis.<br>Either method shows substantial generalizability across a range of image sizes and conditions, including<br>heat-treated microstructures with different phase configurations. The nnU-Net excels in mapping large<br>image areas. Conversely, the GAN-based method performs reliably on smaller images, providing greater<br>step-by-step control and flexibility over the segmentation process.<br>This study highlights the benefits of segmented microstructural data for various purposes, such as<br>calculating phase fractions, modelling material behaviour through finite element simulation, and<br>conducting geometrical analyses of damage sites and the local properties of their surrounding<br>microstructure.</p> <p>https://doi.org/10.1016/j.matdes.2024.113031</p>
Tractography Templates for White Matter Microstructure Analysis in Aging and Alzheimer's Disease
<p>This dataset contains tractography templates derived from several studies focused on white matter microstructure and its associations with neurodegenerative diseases, particularly Alzheimer's disease and Parkinsonism. These templates span key tracts relevant to both cognitive decline and motor function, including but not limited to the medial temporal lobe white matter, transcallosal fibers, sensorimotor tracts, and the fornix. The templates were developed and validated using advanced diffusion MRI techniques across various populations, including aging individuals, dementia patients, and those at risk of neurodegenerative conditions. This resource serves as a valuable tool for researchers investigating the structural integrity of white matter in both health and disease, allowing for cross-study comparability and enhancing the understanding of neurodegenerative processes.</p>
Thermal and percolative analysis of 3D diffuse-interface composite microstructure
<p>This dataset contains supplementary data and utilities of the publication "Data-driven thermal and percolative analysis of 3D diffuse-interface composite microstructure" (<a href="https://doi.org/10.1016/j.matdes.2023.111746">Fathidoost, 2023</a>).</p> <p>This dataset documents homogenized anisotropic thermal conductivity of the corresponding microstructure (identified by volume fraction (Vf) and aspect ratio (Ar)) as a tensor with normalized interface thermal resistance (see Table 1). Voxelized digital microstructures and utilities are also attached for visualizing the overall thermal anisotropy.</p> <p><em>Table 1: The geometrical and thermal parameters employed in the generated microstructures.</em></p> <table> <thead> <tr> <th>Parameters</th> <th>Value (Unit)</th> <th>Type</th> <th>Increment</th> </tr> </thead> <tbody> <tr> <td>Minor principal axes length</td> <td>5 (nm)</td> <td>Constant</td> <td>-</td> </tr> <tr> <td>Aspect ratio, <span class="math-tex">\(A_\mathrm{r}\)</span></td> <td>[1 ,6]</td> <td>Linear</td> <td>1</td> </tr> <tr> <td>Inclusion volume fraction, <span class="math-tex">\(V_\mathrm{f}\)</span></td> <td>[5, 60]</td> <td>Linear</td> <td>5</td> </tr> <tr> <td>Thermal conductivity ratio, <span class="math-tex">\(K_\mathrm{r}\)</span></td> <td>[15, 100]</td> <td>Linear</td> <td>15</td> </tr> <tr> <td>Normalized interface resistance, <span class="math-tex">\(\tilde{R}_\mathrm{s} \)</span></td> <td>[1e-6, 1e10]</td> <td>Logarithmic</td> <td>1e2</td> </tr> </tbody> </table> <p><strong>Notice:</strong> The digital microstructure has been voxelized and stored in the ExodusII format, which can be loaded and visualized by the post-processing software, such as ParaView. In order to perform the homogenization, interface smoothening is required, i.e., to generate diffuse interfaces. In this work, we smoothened the interface by operating transient Allen-Cahn calculation with finite timesteps. Sec. 2.1 of the publication for more information).</p>
Microstructural geometry revealed by NMR lineshape analysis
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Thermometry and microstructural analysis imply protracted extensional exhumation of the Tso Morari UHP nappe, northwestern Himalaya: implications for models of UHP exhumation
<p>Documenting the processes that facilitate exhumation of ultra-high pressure (UHP) rocks at convergent margins is critical for understanding orogen dynamics. Here, we present structural and temperature data from the Himalayan UHP Tso Morari nappe (TMN) and overlying nappes, which we integrate with published pressure-temperature-time constraints to refine interpretations for their structural evolution and exhumation history. Our data indicate that the 5.5 km-thick TMN is the upper portion of a penetratively deformed ductile slab, which was extruded via distributed, pure shear-dominated, top-down-to-east shearing. Strain in the TMN is recorded by high-strength quartz fabrics (density norms between 1.74-2.86) and finite strain data that define 63% transport-parallel lengthening and 46% transport-normal shortening. The TMN attained peak temperatures of ~500-600°C, which decrease in the overlying Tetraogal and Mata nappes to ~150-300°C, defining a field gradient as steep as 67°C/km. Within the overlying nappes, quartz fabric strength decreases (density norms between 1.14-1.21) and transport-parallel lengthening and transport-normal shortening decrease to 14% and 18%, respectively. When combined with published 40Ar/39Ar thermochronometry, quartz fabric deformation temperatures as low as ~330°C indicate that the top-to-east shearing that exhumed the TMN continued until ~30 Ma. Peak temperatures constrain the maximum depth of the overlying Mata nappe to 12.5-17.5 km; when combined with published fission-track thermochronometry, this provides further support that the TMN was not underplated at upper-crustal levels until ~30 Ma. The long-duration, convergence-subnormal shearing that exhumed the TMN outlasted rapid India-Asia convergence by ~15 Myr and may be the consequence of strain partitioning during oblique convergence.</p>
FIG. 3 in Otolith Microstructure Analysis Elucidates Spawning and Early Life Histories of Federally Endangered Fishes in the San Juan River
FIG. 3. Razorback Sucker age as a function of length (SL). Colored dots indicate otolith ages, and black squares are predicted ages produced from the linear growth function.
FIG. 1. Colorado Pikeminnow and Razorback Sucker larvae for this study were selected from 2009 in Otolith Microstructure Analysis Elucidates Spawning and Early Life Histories of Federally Endangered Fishes in the San Juan River
FIG. 1. Colorado Pikeminnow and Razorback Sucker larvae for this study were selected from 2009 to 2017 larval fish collections made in the San Juan River between reach 6, near Farmington, NM, and reach 1, near the terminus of the San Juan River in Lake Powell.
FIG. 4 in Otolith Microstructure Analysis Elucidates Spawning and Early Life Histories of Federally Endangered Fishes in the San Juan River
FIG. 4. Back-calculated spawn dates of Colorado Pikeminnows produced from otolith ages (Plot B: Actual), from the transformed linear equations (Plot A: Best-fit), and from the published function (Nesler et al., 1988; Plot C: Published). Data are from larvae collected from 2010 to 2017 in the San Juan River. Dashed gray vertical bars denote weekly intervals.
Unsupervised Machine Learning and Cepstral Analysis with 4D-STEM for Characterizing Complex Microstructures of Metallic Alloys
<p>Raw 4D-STEM data of Ni50Ti26Hf20Al4 used for analysis in the publication "Unsupervised Machine Learning and Cepstral Analysis with 4D-STEM for Characterizing Complex Microstructures of Metallic Alloys". Datasets were collected using the electron microscope pixel array detector (EMPAD) with a Themis Z STEM. Custom python scripts used for data analysis are available upon request to one of the corresponding authors.</p>
Dataset for Foundation Model for Composite Materials and Microstructural Analysis
<p>This repository contains datasets generated for the publication <strong>"Foundation Model for Composite Materials and Microstructural Analysis". </strong></p> <p>The datasets are provided to facilitate replication of results, further research, and development in the field of composite materials and machine learning.</p> <h1>Contents:</h1> <ol> <li><strong>downstream_circular_inclusion.zip</strong> <ul> <li> <p>Description: This dataset consists of microstructure images and associated properties for circular inclusion composites used in the downstream tasks of the study.</p> </li> <li> <p>Structure:</p> <ul> <li> <p>train/: Contains training data directories and files.</p> </li> <li>valid/: Contains training data directories and files.</li> <li> <p>descriptors.csv: A CSV file with descriptors and homogenized stiffness components for validation data.</p> </li> </ul> </li> </ul> </li> <li><strong>downstream_short_fiber.zip</strong> <ul> <li> <p>Description: This dataset consists of microstructure images and associated properties for short-fiber composites used in the downstream tasks of the study.</p> </li> <li> <p>Structure:</p> <ul> <li> <p>train/: Contains training data directories and files.</p> </li> <li>valid/: Contains training data directories and files.</li> <li> <p>descriptors.csv: A CSV file with descriptors and homogenized stiffness components for validation data.</p> </li> </ul> </li> </ul> </li> <li><strong>inclusion_train_100k.zip</strong> <ul> <li>Description: This dataset contains 100,000 microstructure images of short-fiber composites used for self-supervised pre-training of the Masked Material Autoencoder (MMAE).</li> <li> <p>Structure:</p> <ul> <li> <p>mesh0dir/, mesh1dir/, ... mesh99999dir/: : Folders containing microstructure images used for pre-training.</p> </li> <li>descriptors.csv: A CSV file with descriptors related to the microstructures.</li> </ul> </li> </ul> </li> </ol>
Microstructural Analysis of Ingestive Behavior After Roux-en-Y Gastric Bypass - Pilot
ClinicalTrials.gov study NCT03747445. IPD Sharing: NO. Countries: 1. Publications: 6.
Otolith microstructures analysis of juveniles sole (Solea solea L.) in the Southern North Sea
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Degradation of Ni-YSZ and Ni-GDC fuel cells after 1000 h operation: Analysis of different overpotential contributions according to electrochemical and microstructural characterization
<p>Datasets from the paper:</p> <p>"Degradation of Ni-YSZ and Ni-GDC fuel cells after 1000 h operation: Analysis of different overpotential contributions according to electrochemical and microstructural characterization". E3S Web of Conferences <strong>334</strong>, 04011 (2022).</p> <p>The activity was carried out within the framework of the European Project AD ASTRA. This project has received funding from the Fuel Cells and Hydrogen 2 Joint Undertaking under <strong>Grant Agreement No 825027</strong>. This Joint Undertaking receives support from the European Union's Horizon 2020 research and innovation programme and Hydrogen Europe.</p>
Thermophysical and kinetics properties up to 1100 °C of a selected Fe-C-O-Cr-Ni alloy by means of DTA, DSC measurements, and microstructural analysis
<p>Data from DTA, DSC, P-DSC. Heat capacity, enthalpy, austenite fractions.</p>
Data from: Electron backscatter diffraction (EBSD) analysis of maniraptoran eggshells with important implications for microstructural and taphonomic interpretations
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Voxel-wise co-analysis of macro- and microstructural brain alteration in Mild Cognitive Impairment and Alzheimer's disease using anatomical and diffusion MRI
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Data from: Microstructure and cerebral blood flow within white matter of the human brain: a TBSS analysis
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FIG. 2 in Otolith Microstructure Analysis Elucidates Spawning and Early Life Histories of Federally Endangered Fishes in the San Juan River
FIG. 2. Colorado Pikeminnow age as a function of length (SL). Colored dots indicate otolith ages, and black squares are predicted ages produced from the transformed linear function.
Data of "Fully automated pipeline for the fiber tractography of the anterior optic pathway in patients with sellar and parasellar tumors and analysis of the microstructural alterations"
<p>This dataset contains the numerical data used for the analysis described in the paper "<strong><span>Fully automated pipeline for the fiber tractography of the anterior optic pathway in patients with sellar and parasellar tumors and analysis of the microstructural alterations</span></strong>", Gramegna LL et al.</p> <p>chiasma_displacement.xlsx contains the value in mm of the vertical displacement of the chiasm for each subject (see the paper for the methodological procedure of the evaluation).</p> <p>parameters_along_tract.xlsx contains for each subject (Exam): the condition (Cond, 0=healthy control, 1=patient), whether they experienced complete or partial resolution of symptoms after surgical treatment (Responder), the corresponding area along the anterior optic pathway (Zone), the sampling point among the 45 that the anterior optic pathway was divided into (Bin), the microstructural parameter considered (Measure) and its corresponding value (Value).</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.