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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.
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Contributor : Jean-Pierre GOBEAU Connect in order to contact the contributor
Submitted on : Friday, January 28, 2022 - 1:16:14 PM
Last modification on : Friday, January 28, 2022 - 2:41:27 PM
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Y. Mansour, Y. Battie, A. En Naciri, N. Chaoui. Artificial neural network for the classification of nanoparticles shape distributions. Optics Letters, Optical Society of America - OSA Publishing, 2019, 44 (13), pp.3390-3393. ⟨10.1364/OL.44.003390⟩. ⟨hal-02167692⟩



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