Nanoparticle Mapping
Nanoparticle Mapping - Related Videos
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Energy Dispersive X-ray Tomography for 3D Elemental Mapping of Individual Nanoparticles
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Cited by 11 •
2016
The use of energy dispersive X-ray tomography in the scanning transmission electron microscope to characterize elemental distributions within single nanoparticles in three dimensions is described.
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Laser-induced Breakdown Spectroscopy: A New Approach for Nanoparticle's Mapping and Quantification in Organ Tissue
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Cited by 18 •
2014
Laser-induced breakdown spectroscopy performed on thin organ and tumor tissue successfully detected natural elements and artificially injected gadolinium (Gd), issued from Gd-based nanoparticles. Images of chemical elements reached a resolution of 100 μm and quantitative sub-mM sensitivity. The compatibility of the setup with standard optical microscopy emphasizes its potential to provide multiple images of a same biological tissue.
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Identification of Metal Oxide Nanoparticles in Histological Samples by Enhanced Darkfield Microscopy and Hyperspectral Mapping
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Cited by 37 •
2015
Enhanced darkfield microscopy and hyperspectral imaging with spectral mapping enable screening, localization, and identification of nanoscale materials in histological samples with improved speed and accuracy over traditional methods. The goal of this paper is to provide methods for darkfield imaging and hyperspectral mapping of metal oxide nanoparticles in histological samples.
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Fate Mapping
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2023
Fate mapping is a technique used to understand how embryonic cells divide, differentiate, and migrate during development. In classic fate mapping experiments, cells in different areas of an embryo are labeled with a chemical dye and then tracked to determine which tissues or structures they form. Technological improvements now allow for individual cells to be marked and traced throughout embryonic development and adulthood. This video reviews the concepts behind fate mapping, and then details a...
11:03
Motor Maps
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2023
Source: Laboratories of Jonas T. Kaplan and Sarah I. Gimbel—University of Southern California One principle of brain organization is the topographic mapping of information. Especially in sensory and motor cortices, adjacent regions of the brain tend to represent information from adjacent parts of the body, resulting in maps of the body expressed on the surface of the brain. The primary sensory and motor maps in the brain surround a prominent sulcus known as the central sulcus. The cortex...
FAQs
A nanoparticle map describes a sample under defined measurement conditions, so its results should be interpreted within that experimental setting. Imaging or spectroscopy may reveal particle positions, size, composition, or aggregation only when the selected method can resolve those features. Keeping conditions consistent allows researchers to compare regions, materials, or processing outcomes without confusing measurement differences with changes in the sample.
Spatial patterns provide different engineering clues. A relatively even distribution indicates dispersion, concentrated groups indicate clustering, and changes in particle location near boundaries can reveal interfaces or transport pathways. Image analysis converts these patterns into interpretable spatial information, helping researchers determine whether nanoparticles remain distributed through a material or accumulate in particular regions.
Imaging primarily supplies spatial information, while spectroscopy can add information about characteristics such as composition when the technique permits. Combining them helps connect where nanoparticles occur with what they are or how they differ across a sample. This is especially useful when similar-looking regions may have different material properties or when aggregation must be evaluated alongside particle identity.
Particle position and organization can influence how a nanostructured material behaves. Maps expose distributions, clusters, and interfaces that may help explain differences in electrical, optical, mechanical, or catalytic behavior. Rather than relying only on an average measurement, engineers can relate local structure to observed performance and use that relationship to guide more predictable material design.
A typical workflow begins by selecting the surface, material, or biological sample and defining the measurement conditions. Researchers then collect spatially resolved images or spectra, analyze the resulting data to identify particle locations and permitted characteristics, and compare patterns across regions or samples. This sequence turns raw measurements into evidence about dispersion, clustering, transport, or interfaces.
Engineers can apply the method when nanoparticle location or organization may affect a product or material outcome. In coatings and composites, it can reveal dispersion and aggregation; in devices, it can clarify distributions and interfaces. These observations support process optimization, performance evaluation, and quality control by showing whether the nanoscale structure matches the intended design.
Spatial maps allow engineers to compare nanoparticle distributions between production conditions, material regions, or completed samples. Differences in clustering, dispersion, or interfacial location can identify changes associated with processing and indicate whether a structure is consistent with design goals. The results provide a more localized basis for evaluating quality than measurements that do not preserve spatial information.
The method can produce spatially resolved evidence about particle positions and, when supported by the measurement approach, properties such as size or composition. Researchers use these outcomes to evaluate transport, aggregation, interfaces, and material uniformity. In engineering studies, such evidence helps connect nanostructure to electrical, optical, mechanical, or catalytic behavior and informs future material designs.