Extracting the Size Distribution of Gold Nanoparticles from UV-Visible Spectrum: an Artificial Neural Network Model 


Vol. 69,  No. 5, pp. 219-224, Oct.  2025
10.5012/jkcs.2025.69.5.219


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  Abstract

A nondestructive detection of the size distribution of nanoparticles (NPs) is desired in various applications. The conventional method utilizes the dynamic light scattering from which the sizes of NPs are drawn by using the Stokes-Ein-stein relation. We propose a novel method to draw the size distribution of NPs from the UV-visible spectrum. Our method uti-lizes an artificial neural network (ANN) model trained against an extensive dataset generated by Mie theory. The promising performance of the present ANN model is demonstrated.

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  Cite this article

[IEEE Style]

J. Kim, S. Choi, K. Kim, K. Byun, J. Jang, "Extracting the Size Distribution of Gold Nanoparticles from UV-Visible Spectrum: an Artificial Neural Network Model," Journal of the Korean Chemical Society, vol. 69, no. 5, pp. 219-224, 2025. DOI: 10.5012/jkcs.2025.69.5.219.

[ACM Style]

Jaeyoung Kim, Seyong Choi, Kiduk Kim, Kisang Byun, and Joonkyung Jang. 2025. Extracting the Size Distribution of Gold Nanoparticles from UV-Visible Spectrum: an Artificial Neural Network Model. Journal of the Korean Chemical Society, 69, 5, (2025), 219-224. DOI: 10.5012/jkcs.2025.69.5.219.

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ISSN(Print) 1017-2548
ISSN(Online) 2234-8530