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Hyperspectral TERS Imaging Reveals Strain Heterogeneity in Individual Nanoplastic Particles

Repository for Publications and Research Data (ETH Zurich) 2025 Score: 48 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Anushree Dutta, Anushree Dutta, Siiri Bienz, Naresh Kumar, Naresh Kumar, Renato Zenobi, Renato Zenobi

Summary

Using AFM-based tip-enhanced Raman spectroscopy (TERS) with hyperspectral imaging, researchers characterized the chemical heterogeneity of individual polystyrene nanoplastic particles at nanoscale resolution. The technique revealed unexpected strain and chemical variation within single particles—information inaccessible to bulk spectroscopy—demonstrating TERS as a powerful label-free tool for nanoplastic characterization.

Polymers

Nanoplastics pose growing environmental and health risks, yet their label-free, nondestructive detection and characterization, especially at the single-particle level, remain challenging. Here, we deploy AFM-based tip-enhanced Raman spectroscopy (AFM-TERS) to chemically characterize individual polystyrene (PS) nanoplastic particles via hyperspectral imaging under ambient conditions. TERS spectra from nanoparticles as small as 32 nm establish reliable single-particle sensitivity beyond the optical diffraction limit. Furthermore, hyperspectral TERS maps reveal pronounced intraparticle heterogeneity, reflected spatially as varying red-/blue-shifts of PS marker bands with broad frequency distributions, without any systematic dependence on particle size. Correlative AFM phase imaging exposes nanoscale variations in local stiffness indicating strain heterogeneity as the origin of the spectral shifts. These results demonstrate that AFM-TERS enables single-particle mapping of intraparticle heterogeneity in nanoplastics. This offers new possibilities to identify nanoplastics with molecular specificity and monitor chemical transformations at the single-particle level within complex biological and environmental matrices.

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