Automatic Identification of Individual Nanoplastics by Raman Spectroscopy Based on Machine Learning.

The increasing prevalence of nanoplastics in the environment underscores the need for effective detection and monitoring techniques. Current methods mainly focus on microplastics, while accurate identification of nanoplastics is challenging due to their small size and complex composition. In this work, we combined highly reflective substrates and machine learning to accurately identify nanoplastics using Raman spectroscopy. Our approach established Raman spectroscopy data sets of nanoplastics, incorporated peak extraction and retention data processing, and constructed a random forest model that achieved an average accuracy of 98.8% in identifying nanoplastics. We validated our method with tap water spiked samples, achieving over 97% identification accuracy, and demonstrated the applicability of our algorithm to real-world environmental samples through experiments on rainwater, detecting nanoscale polystyrene (PS) and polyvinyl chloride (PVC). Despite the challenges of processing low-quality nanoplastic Raman spectra and complex environmental samples, our study demonstrated the potential of using random forests to identify and distinguish nanoplastics from other environmental particles. Our results suggest that the combination of Raman spectroscopy and machine learning holds promise for developing effective nanoplastic particle detection and monitoring strategies.

Revealing Trace Nanoplastics in Food Packages─An Electrochemical Approach Facilitated by Synergistic Attraction of Electrostatics and Hydrophobicity.

Most food packages are made of plastics, nanoplastics released from which can be directly ingested and induce serious damage to organisms. Therefore, it is urgent to develop an effective and convenient method for nanoplastic determinations in food packages. In this work, we present a sandwich-based electrochemical strategy for nanoplastic determination. Positively charged Au nanoparticles were coated onto a Au electrode to selectively capture negatively charged nanoplastics in an aqueous environment. Subsequently, the nanoplastics were recognized by the signal molecule ferrocene via the hydrophobic interaction and determined by differential pulse voltammetry. Our sandwich-type detection depends on both electronegativity and hydrophobicity of nanoplastics, which make the method applicable for the assays of packages made of widely commercialized polystyrene (PS), polypropylene (PP), polyethylene (PE), and polyamide (PA). The method displays different sensitivities to above four nanoplastics but the same dynamic range from 1 to 100 µg·L-1. Based on it, the nanoplastics released from several typical food packages were assayed. Teabags were revealed with significant nanoplastic release, while instant noodle boxes, paper cups, and take-out boxes release slightly. The good recoveries in nanoplastic-spiked samples confirm the accuracy and applicability of this method. This work provides a sensitive, low-cost, and simple method without complicated instruments and pretreatment, which is of great significance for the determination of nanoplastics released from food packages.

Surface-enhanced Raman spectroscopy using gold-core platinum-shell nanoparticle film electrodes: toward a versatile vibrational strategy for electrochemical interfaces.

The aim of this work is to further improve the molecular generality and substrate generality of SERS (i.e., to fully optimize the SERS activity of transition-metal electrodes). We utilized a strategy of borrowing high SERS activity from the Au core based on Au-core Pt-shell (Au@Pt) nanoparticle film electrodes, which can be simply and routinely prepared. The shell thickness from about one to five monolayers of Pt atoms can be well controlled by adjusting the ratio of the number of Au seeds to Pt(IV) ions in the solution. The SERS experimental results of carbon monoxide adsorption indicate that the enhancement factor for the Au@Pt nanoparticle film electrodes is more than 2 orders of magnitude larger than that of electrochemically roughened Pt electrodes. The practical virtues of the present film electrodes for obtaining rich and high-quality vibrational information for diverse adsorbates on transition metals are pointed out and briefly illustrated with systems of CO, hydrogen, and benzene adsorbed on Pt. We believe that the electrochemical applications of SERS will be broadened with this strategy, in particular, for extracting detailed vibrational information for adsorbates at transition-metal electrode interfaces.