Electrochemically Regenerable SERS Substrates for in situ Detection of Pesticides

• Grant number: 25/10906-4
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: October 06, 2025
• End date: October 05, 2026
• Field of knowledge: Engineering - Materials and Metallurgical Engineering
• Principal Investigator: Priscila Alessio Constantino
• Grantee: Henry Seitiro Kavazoi
• Supervisor: Jeremy John Baumberg
• Host Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil
• Institution abroad: University of Cambridge, England
• Associated to the scholarship: 23/04196-9 - Development of SERS and GERS substrates to optimize in situ detection of mixed pesticides, BP.DR

Abstract

Surface-enhanced Raman scattering (SERS) is a powerful technique capable of detecting molecules at ultra-low concentrations due to the intense signal amplification generated at electromagnetic hotspots. However, challenges such as poor substrate reproducibility, limited reusability, and variability in hotspots distribution continue to limit its practical applications, particularly in quantitative and in situ analyses. In this project, we propose the application of regenerable SERS substrates based on multilayer aggregates (MLaggs) for the detection of the herbicides paraquat and diquat in standard and environmental water samples. Developed by Professor Jeremy Baumberg's group, MLagg substrates feature nanogaps precisely defined by molecular spacers, providing high spectral reproducibility and compatibility with electrochemical systems. The substrates can be cleaned and regenerated electrochemically, allowing multiple analytical cycles with the same device. The work plan involves the preparation and characterization of MLagg substrates, integration with an electrochemical-SERS flow cell, investigation of the electrochemical-SERS behavior of the target pesticides, and application of the developed method to spiked environmental samples. This approach aims to improve sensitivity, selectivity, and reproducibility, while reducing waste and operational costs, contributing to the development of more sustainable and reliable analytical tools for in situ environmental monitoring.