# Online Coupling of Field-Flow Fractionation with Raman Microspectroscopy Enables the Advanced Study of Nanoplastics Directly in Food

## TL;DR

A new method combines field-flow fractionation and Raman microspectroscopy to detect and study nanoplastics in food without pretreatment.

## Contribution

This is the first application of AF4-MD-RM for detecting nanoplastics in unprocessed food matrices.

## Key findings

- The AF4-MD-RM platform successfully separated and detected polystyrene nanoplastics in milk.
- The method achieved detection thresholds comparable to existing quantification techniques.
- The approach enables multiparametric characterization of nanoplastics and matrix interactions.

## Abstract

The detection and understanding of the behavior of nanoplastics
(NPLs) in complex (in)­organic systems is a growing concern and one
of the major challenges in analytical chemistry today. Current analytical
methods are limited in terms of sample flexibility and automation,
often require laborious pretreatment, and usually only provide limited
information about the presence of NPLs without assessing the behavior
of the plastics in the matrix. Coupling an asymmetrical flow field-flow
fractionation multidetector (AF4-MD) platform with Raman microspectroscopy
(RM) represents a significant advancement in the field, offering a
novel approach that combines the advantages of a highly flexible,
automatable, and informative analytical system (AF4-MD) with a detector
able to chemically identify NPLs (RM). Up to now, this pioneering
technique has only been used to study different nanoparticles in an
aqueous environment. Here, for the first time, we report the application
of an AF4-MD-RM platform to detect NPLs in a real unprocessed matrix.
The developed approach allowed for the separation, selective detection,
and multiparametric characterization of milk components and NPLs (polystyrene,
PS beads, 100–500 nm) in a short analytical time without sample
pretreatment, while providing PS detection threshold values compatible
with those of the currently exploited quantification approaches. These
beyond the state-of-the-art results were proved with orthogonal techniques
and highlight the game-changing potential of AF4-MD-RM for a straightforward
detection of NPLs in complex matrices and the characterization of
NPL-matrix interactions.