Artificial Intelligence-Assisted Multiparameter Size Discrimination of Silver Nanoparticles through Electrochemical Collision

Single particle collision is an important tool for size analysis at the individual particle level; however, due to complex dynamic behaviors of nanoparticles on the surface of an electrode, the accuracy of size discrimination is limited. A silver (Ag) nanoparticle (NP) was chosen as the research tar...

Full description

Saved in:
Bibliographic Details
Published in:Analytical chemistry (Washington) 2024-04, Vol.96 (16), p.6195-6201
Main Authors: Xu, Ying, Jiang, Wei-Jian, Bai, Yi-Yan, Yang, Yan-Ju, Zhang, Zhi-Ling
Format: Article
Language:English
Subjects:
Accuracy
Artificial intelligence
Charge transfer
Electrochemistry
Multidimensional data
Nanoparticles
Parameters
Particle collisions
Silver
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Single particle collision is an important tool for size analysis at the individual particle level; however, due to complex dynamic behaviors of nanoparticles on the surface of an electrode, the accuracy of size discrimination is limited. A silver (Ag) nanoparticle (NP) was chosen as the research target, and the dynamic behavior of Ag NPs was simplified by enhancing adsorption between Ag NP and Au ultramicroelectrode (UME) in alkaline media. Immediately after, accurate dynamic and thermodynamic information on single Ag NP was accurately extracted from collision events, including current intensity, transferred charge, and duration time. On the basis that there were differences between parameters of different-sized Ag NPs, multiparameter size discrimination was proposed, which improved the accuracy compared to single-parameter discrimination. More intriguingly, multiparameter analysis was combined with artificial intelligence, a tool adept at processing multidimensional data, for the first time. Finally, artificial intelligence-assisted multiparameter size discrimination was successfully used to intelligently distinguish mixed Ag NPs, with an optimal accuracy of more than 95%. To sum up, the artificial intelligence-assisted multiparameter method showed an excellent ability to quickly achieve the most accurate size discrimination of nanoparticles at the level of individual particle and provide an effective guidance for the application of nanoparticles.
ISSN:0003-2700
1520-6882
DOI:10.1021/acs.analchem.3c05115