Enhancement of the Au/ZnO-NA Plasmonic SERS Signal Using Principal Component Analysis as a Machine Learning Approach

Enhancement of the Au/ZnO-NA Plasmonic SERS Signal Using Principal Component Analysis as a Machine Learning Approach

In this work, we modeled a novel approach to enhance surface-enhanced Raman scattering (SERS) signals using principal component analysis (PCA) as a machine learning approach. Zinc oxide nanoarrays (ZnO-NAs) were synthesized using a hydrothermal method followed by zinc oxide nucleation on ITO glass s...

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Bibliographic Details
Main Authors: Akhilesh Kumar Gupta, Chih-Hsien Hsu, Chao-Sung Lai
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Photonics Journal
Subjects:
Plasmonic model
SERS
signal enhancement
PCA analysis
machine learning approach
Online Access:https://ieeexplore.ieee.org/document/9165082/
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