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Metal-free AAO membranes function as both filters and Raman enhancers for the analysis of nanoplastics
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Scientists developed a simple, metal-free aluminum oxide membrane that works as both a filter and a signal-enhancing surface for detecting nanoplastics using Raman spectroscopy. The approach successfully identified plastic particles as small as 200 nanometers across six common polymer types, without complex sample preparation. This dual-function tool could offer a cost-effective and practical way to analyze nanoplastic contamination in environmental samples.
Nanoplastics (NPs) are growing concerns for health and the environment, being widely distributed across marine, freshwater, air, and biological systems. Analyzing NPs in real environmental samples requires pretreatment, which has traditionally been complex and often leads to underestimation in actual samples, creating a gap between real-world conditions and research findings. In this study, we propose using anodic aluminum oxide (AAO) membrane as a direct Raman substrate for particles on a filter, achieving complete recovery during separation and concentration while simplifying the pretreatment stages. Moreover, our study introduces AAO itself, without any metal coating, as a normal Raman spectroscopy substrate with strong Raman signal enhancement for NPs and an ultra-flat surface for rapid analysis. By using AAO with nanometer-sized pores, we effectively detected standard polystyrene spherical particles on the AAO membrane down to 200 nm. Our investigation extended to irregular NPs containing PP, PE, PET, PS, PMMA, and PLA, confirming the reliability of this approach. Our results suggest that employing an AAO membrane with dual functionality as both a filter and a Raman substrate effectively serves as a cost-effective, rapid, simple, and accurate tool for NP analysis in complex environments.
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Researchers developed Pre_seg, a data-driven Raman spectral processing algorithm integrated with regenerable anodic aluminum oxide membrane sensors, achieving ultrasensitive detection and quantification of nanoplastics in complex natural water matrices by addressing spectral interference challenges.
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