Publication details
Optical Microscopy and Deep Learning for Absolute Quantification of Nanoparticles on a Macroscopic Scale and Estimating Their Number Concentration
| Authors | |
|---|---|
| Year of publication | 2025 |
| Type | Article in Periodical |
| Magazine / Source | Analytical chemistry |
| MU Faculty or unit | |
| Citation | |
| web | elektronická verze článku |
| Doi | https://doi.org/10.1021/acs.analchem.4c05555 |
| Keywords | nanoparticle number concentration; evaporated volume analysis (EVA); nanoparticle counting; optical microscopy |
| 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. |