Nanoparticle Identification
Nanoparticle Identification - Related Videos
12:19
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.
09:23
Harmonic Nanoparticles for Regenerative Research
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Cited by 1 •
2014
Protocol details are provided for in vitro labeling human embryonic stem cells with second harmonic generating nanoparticles. Methodologies for hESC investigation by multi-photon microscopy and their differentiation into cardiac clusters are also presented.
13:39
Optical Trapping of Nanoparticles
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Cited by 7 •
2013
The following setup approach details low power optical trapping of dielectric nanoparticles using a double-nanohole in metal film.
14:12
Rodent Identification II
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2015
Source: Kay Stewart, RVT, RLATG, CMAR; Valerie A. Schroeder, RVT, RLATG. University of Notre Dame, IN Animal records must be accurately maintained to ensure that data collection is correct. Records range from maintaining information on cage cards to having a detailed database with all of the relevant information on each animal. The primary component of recordkeeping is the individual identification of research animals. There are a variety of methods suitable for identifying mice and rats. This...
08:51
Evaluation of Polymeric Gene Delivery Nanoparticles by Nanoparticle Tracking Analysis and High-throughput Flow Cytometry
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Cited by 9 •
2013
A protocol for nanoparticle tracking analysis (NTA) and high-throughput flow cytometry to evaluate polymeric gene delivery nanoparticles is described. NTA is utilized to characterize the nanoparticle particle size distribution and the plasmid per particle distribution. High-throughput flow cytometry enables quantitative transfection efficacy evaluation for a library of gene delivery biomaterials.
FAQs
No single measurement captures every property relevant to a nanoparticle’s performance or safety. Electron microscopy, dynamic light scattering, spectroscopy, and surface-chemistry analysis provide complementary information about structure, size, composition, aggregation, and coatings. Comparing these results gives researchers a more complete characterization and helps distinguish genuine particle features from incomplete or misleading observations.
Aggregation changes the apparent state of a nanoparticle preparation and can influence measured size and behavior in biological fluids. Dynamic light scattering can help assess this aggregation state, while electron microscopy provides additional structural information. Recognizing whether particles remain individual or form aggregates is important when predicting cellular interactions, delivery behavior, or experimental reproducibility.
Surface-chemistry analysis reveals the composition and functional coatings associated with a nanoparticle. These surface features help differentiate materials that may have similar physical dimensions but different biological behavior. In bioengineering, examining coatings supports interpretation of how particles interact with cells and biological fluids, and it helps connect material design with intended delivery or biosensor functions.
A characterization workflow combines imaging, size analysis, spectroscopy, and surface-chemistry measurements instead of relying on a single result. Researchers can compare particle shape and size with composition, aggregation state, and functional coatings to build a consistent profile. This integrated profile supports classification, helps identify contaminants, and provides the evidence needed for reproducible nanomaterial design.
Nanoparticle identification is especially important when researchers are developing drug delivery systems, biosensors, tissue-engineering materials, or other biomedical nanomaterials. In each setting, physical and chemical properties can affect performance and safety. Characterization allows investigators to relate the material profile to biological interactions and to select particles whose measured properties match the intended research application.
Characterization supports quality control by documenting whether a nanoparticle preparation has the expected size, shape, composition, aggregation state, and surface coating. It can also help distinguish nanoparticles from contaminants. Repeating these measurements across preparations gives researchers a basis for comparing experiments, identifying inconsistencies, and designing nanomaterials with more reproducible properties for biomedical research.