MACHINE LEARNING APPLIED TO MODELING SURFACE PLASMON-BASED SENSORS

• Grant number: 22/11722-6
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: December 01, 2022
• End date: November 30, 2023
• Field of knowledge: Engineering - Electrical Engineering - Telecommunications
• Principal Investigator: Hugo Enrique Hernández Figueroa
• Grantee: Henrique Stumm Rocha
• Host Institution: Faculdade de Engenharia Elétrica e de Computação (FEEC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
• Associated research grant: 21/11380-5 - CPTEn - São Paulo Center for the Study of Energy Transition, AP.CCD

Abstract

This project aims to introduce the candidate in the study of electromagnetic sensors based on theexcitation of the resonance modes of a metallic surface when it is illuminated by an optical beam,these modes are called Surface Plasmons Polaritons (SPP). Sensors based on this phenomenon arecalled Surface Plasmon Resonators (SPR) and use two interrogation modes: angular and spectral.A modification of the Kretschmann configuration will be used, whose basic automated setup forthe angular interrogation mode is already implemented and operating at the Laboratory ofApplied and Computational Electromagnetism (LEMAC). In this project, an interrogation setup based on the use of a Spatial Light Modulator (SLM) will be implemented, which permits to keep the setup fixed, and the post processing of images captured with a Charged-Coupled Device (CCD) camera based on machine learning algorithms, aiming at a decrease in the mechanical noise level and greater sensitivity. The interrogation schemes implemented will be tested adopting as a case study the verification of the identification of adulteration of Ethanol or high-quality alcoholic beverages, when mixed with water.