Micro/nanoplastic (MNPs) pollution in aquatic ecosystems, including drinking water, has become crucial for human and environmental health. MNP harm mitigation requires systems capable of performing rapid qualitative and quantitative MNPs detection and analysis. This project aims to develop gold nanotriangle (AuNTs) array substrates used in surface-enhanced Raman spectroscopy (SERS) for rapid, accurate, trace-level sensitivity detection of the most abundant polymers pollutants (PP, PS, PET, PVC, and PE) in water. The unique tunable AuNT array structures are known to enhance Raman signals and therefore make them effective in SERS applications. In line with the project aim, bow-tie and AuNT arrays will be prepared by using electron beam lithography and capillarity-assisted particle deposition (CAPA) methods by first determining their geometric patterns through FDTD and FEM simulation. Optical and morphological characterizations of AuNT arrays will be made and results will be compared with simulations. The limit of detection for the bow-tie and AuNT arrays will be calculated, providing vital data on the sensitivity. Then, fingerprint libraries of polymers will be prepared by obtaining SERS spectra at various concentrations and in different aqueous conditions. Spectral data will be used by machine learning models to enhance the detection sensitivity of SERS substrates and to detect multiple pollutants. Thus, the project results will be useful for MNP pollutant type and quantity determination in the aqueous samples with unprecedented sensitivity.
Project funding:
Research Council of Lithuania (RCL), Projects of Postdoctoral fellowships funded by the state budget of the Republic of Lithuania
Project results:
Based on the results, scientific publications will be prepared and the results will be presented at various conferences and to the general public.
Period of project implementation: 2024-11-04 - 2026-11-03
Project coordinator: Kaunas University of Technology
