Surface plasmon resonance sensor based on a novel prism for the detection of a broad range of polymers

TL;DR

This paper introduces a novel prism design for surface plasmon resonance (SPR) sensors that can simultaneously detect multiple parameters of microplastics, including polymer type, size, and quantity, with high accuracy and broad polymer detection range.

Contribution

A new prism design for SPR sensors that enables simultaneous detection of microplastic parameters and broad polymer identification, overcoming limitations of existing SPR methods.

Findings

98.47% agreement between experimental and theoretical refractive index measurements

Successful identification of ten different polymer types including pigmented variants

Demonstrated potential for microplastics imaging and comprehensive particle analysis

Abstract

Microplastics are pervasive pollutants that pose threats to the environment and human health. Detecting them reliably represents a crucial step toward finding solutions. While traditional techniques like vibrational and mass spectroscopies are time-consuming and have limitations in analysing polymers with pigment additives, surface plasmon resonance (SPR) shows promise due to its high sensitivity and rapid detection capabilities.However, existing SPR methods rely on one output variable and fail to determine various microplastic parameters simultaneously. To address this uncertainty between size and polymer type, we propose a prism design that enables SPR resonance in a refractive index range of 1.402-1.56 RIU (Refractive Index Units) for polymer detection. Experimental verification of the prism's dynamic range using refractive index oils presented an agreement of 98.47% with theoretical analysis. Furthermore, we acquired SPR curves from ten different polymer types, including Nitrile, Viton and Tyre rubber. These results demonstrate SPR's potential to identify polymers and its ability to detect even pigmented materials, often challenging for other techniques. The imaging capabilities of the novel prism are presented, indicating its potential for future imaging of microplastics. Our approach holds promise for advancing microplastics analysis by enabling comprehensive assessment of particle parameters, such as polymer type, size, quantity and shape, and expanding the range of detectable polymer types.