Combining Dense Au Nanoparticle Layers and 2D Surface-Enhanced Raman Scattering Arrays for the Identification of Mutant Cyanobacteria Using Machine Learning

• DOI: 10.1021/acs.jpcc.2c00584
• Publication Date: 2022-05-27T16:01:22Z
• Authors: Kai Gao; Hu Zhu; Benjamin Charron; Takahiko Mochizuki; Chunxia Dong; Hongrui Ding; Ying Cui; Mengdi Lu; Wei Peng; Shenggeng Zhu; Long Hong; Jean-Francois Masson
• Keywords: Silver nanoparticle

We report the crowding of Au nanoparticles (Au NPs) on a surface-enhanced Raman scattering (SERS) 2D array substrate with high nanoparticle surface coverage in combined approach for identification cyanobacteria machine learning. By simply using screening effect NaCl, PEG to overcome repulsion between nanoparticles, and different dithiol chain lengths during deposition process NPs substrate, we provide general increase density films over nanodisk-array SERS substrates. The optimized was subsequently utilized discrimination wild-type (WT) mutant learning methods (principal component analysis, logistic model, Gaussian naïve Bayes K-nearest-neighbor support vector classifier model radial basis function). best performance discriminate WT achieved by (SVC) positive rate as 97% five repeat tests congeneric cells. These results indicate that highly sensitive substrates, combination efficient data can be employed SERS, enabling high-throughput current biological research.