Optical Microscopy and Deep Learning for Absolute Quantification of Nanoparticles on a Macroscopic Scale and Estimating Their Number Concentration

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081715%3A_____%2F25%3A00617156" target="_blank" >RIV/68081715:_____/25:00617156 - isvavai.cz</a>
Alternative codes found
RIV/68081723:_____/25:00617156
Result on the web
<a href="https://pubs.acs.org/doi/epdf/10.1021/acs.analchem.4c05555?ref=article_openPDF" target="_blank" >https://pubs.acs.org/doi/epdf/10.1021/acs.analchem.4c05555?ref=article_openPDF</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.analchem.4c05555" target="_blank" >10.1021/acs.analchem.4c05555</a>

Result language
angličtina
Original language name
Optical Microscopy and Deep Learning for Absolute Quantification of Nanoparticles on a Macroscopic Scale and Estimating Their Number Concentration
Original language description
We present a simplistic and absolute method for estimating the number concentration of nanoparticles. Macroscopic volumes of a nanoparticle dispersion (several μL) are dropped on a glass surface and the solvent is evaporated. The optical microscope scans the entire surface of the dried droplet (several mm2), micrographs are stitched together (several tens), and all nanoparticles are counted (several thousand per droplet) by using an artificial neural network. We call this method evaporated volume analysis (EVA) because nanoparticles are counted after droplet volume evaporation. As a model, the concentration of ∼60 nm Tm3+-doped photon-upconversion nanoparticles coated in carboxylated silica shells is estimated with a combined relative standard uncertainty of 2.7%. Two reference methods provided comparable concentration values. A wider applicability is tested by imaging ∼80 nm Nile red-doped polystyrene and ∼90 nm silver nanoparticles. Theoretical limits of EVA such as the limit of detection, limit of quantification, and optimal working range are discussed.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10406 - Analytical chemistry

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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