Label-Free Detection of Pathogenic Microorganism Using Ag Nps@Pdms Sponge Sers Substrate and Machine Learning

We develop an Ag NPs@PDMS SERS substrate for detection of microorgnisms on a micron scale. The detection limit was up to 1 CFU/mL and the differentiation ability of this SERS substrate was evaluated for six different microorganisms. The machine learning algorithms were used for achieving automatic classification of microorganisms, with PCA-SVC model presents superior performance. Different from labeled SERS, label-free SERS technique is conducive to the discovery of unknown microorganisms in water environment. Therefore, this substrate is expected to be used for microbial system assessment and microbial safety monitoring in water environment combined with handheld Raman spectrometer and artificial intelligence.