Development of lateral flow device for detection of polystyrene nanoplastic

Abstract

This thesis focuses on the development of a lateral flow assay (LFA) for the rapid and instrument-free detection of polystyrene nanoplastics (PS NPs). The sensing principle is based on gold nanoparticles (AuNPs) functionalized with 11-mercaptoundecanoic acid (MUA) and goat anti-mouse IgG (GAM), forming a pH-responsive system capable of switching between aggregation and anti-aggregation states. Under acidic conditions, protonation of the MUA carboxyl groups reduces electrostatic repulsion and promotes nanoparticle aggregation into clusters larger than the 0.22 µm filter layer. These aggregates are unable to migrate to the test line, resulting in the absence of a visual signal. When PS NPs are present, hydrophobic interactions between PS and the MUA layer stabilize the nanoparticles and inhibit acid-induced aggregation. The dispersed conjugates can then migrate through the filter and bind to Protein A/G at the test line, producing a visible color band. All assay components were systematically optimized, including the nitrocellulose membrane type, the ratio of MUA and GAM on the nanoparticle surface, the quantity of conjugate applied to the pad, Protein A/G loading concentration, surfactant composition in the running buffer, and the acid concentration required to trigger aggregation. Under these optimized conditions, the developed LFA exhibited a linear response in the range of 100–400 ng/mL, with a calculated limit of detection of 77 ng/mL and a visual detection threshold of 100 ng/mL. The assay demonstrated good repeatability, yielding a relative standard deviation of 1.33% for ten replicates at 100 ng/mL. The performance of the device was further assessed using hot-water extracts from food-contact materials. The concentrations obtained were in agreement with transmission electron microscopy (TEM) observations, and spiked recovery values ranged from 95.20% to 111.68%, confirming the reliability of the analytical approach. In summary, this work establishes a practical LFA platform for detecting PS nanoplastics and provides a basis for further development toward simple, rapid, and user-friendly testing applications.