Artificial neural network for the classification of nanoparticles shape distributions - Université de Lorraine Access content directly
Journal Articles Optics Letters Year : 2019

Artificial neural network for the classification of nanoparticles shape distributions

Abstract

A new methodology, to the best of our knowledge, is developed to determine the shape distribution profile of gold nanoparticles (NPs) from optical spectroscopic measurements. Indeed, an artificial neural network (ANN) approach was introduced to classify Au NP shape distributions from their normalized absorption spectra. This ANN quantitatively analyzes the absorption spectra and provides the posterior probability to have a bimodal or unimodal shape distribution. Several colloidal suspensions were considered to investigate the robustness of the ANN approach. The comparison between ANN classification and TEM analysis was also given and discussed. We demonstrate that ANN classification is a suitable tool to inspect rapidly Au colloidal suspensions after their synthesis.
Fichier principal
Vignette du fichier
opticsletters.pdf (1.35 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-02167692 , version 1 (28-01-2022)

Identifiers

Cite

Y. Mansour, Y. Battie, A. En Naciri, N. Chaoui. Artificial neural network for the classification of nanoparticles shape distributions. Optics Letters, 2019, 44 (13), pp.3390-3393. ⟨10.1364/OL.44.003390⟩. ⟨hal-02167692⟩
50 View
37 Download

Altmetric

Share

Gmail Facebook X LinkedIn More