Novel Hybrid plasmonic materials aided with machine learning techniques for SERS based trace detection

Abstract

This chapter provides a comprehensive overview of the motivation behind the work newlineperformed and the results presented in the thesis. It is set to focus on the basics and theory newlineof physics involved in this thesis methods. It begins with focusing on the significance of newlineplasmonic materials and their recent applications, including the preparation methods. newlineVarious trace detection techniques in vogue for the detection of different molecules like newlineexplosives, pesticides, dyes are examined, particularly emphasising the advantages of newlinesurface-enhanced Raman spectroscopy (SERS) over other techniques. The chapter then newlinedelves into the theoretical underpinnings of the Raman scattering and SERS enhancement, newlineexploring the influence of materials (Ag, Au, and Ag-Au alloys), nanoparticle size, newlinematerial, shape, and interparticle distance using COMSOL simulations. The challenges newlinecurrently facing SERS and their origins are also discussed. State-of-the-art in the SERS newlinetechniques in substrate fabrication, applications, and implementation of machine learning newlinetechniques is also detailed. An introduction to machine learning techniques and their newlineapplications in SERS is presented, along with an overview of the different molecules newlinestudied in the thesis, including explosives and biomolecules. newline newline