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Optical Extraction of Single Microplastics Followed by Online Molecular and Elemental Characterization
Summary
A new three-part instrument was built that uses an optical laser trap to isolate individual microplastic particles from complex samples, then identifies the polymer type using Raman spectroscopy and measures the particle's carbon mass using mass spectrometry. This advance allows much smaller microplastics to be detected and identified in difficult environmental matrices like soil or high-carbon water, improving the precision of contamination assessments.
The accurate characterization of microplastics (MPs) in complex matrices remains a major analytical challenge and requires advanced methods, which decipher information on size and polymer identity at single particle resolution. Single particle (SP) inductively coupled plasma-mass spectrometry (ICP-MS) has emerged as an element-selective method to detect individual particles in a one-by-one fashion and can be used to detect and characterize MPs regarding carbon mass and particle sizes. However, this technique has two relevant shortcomings. First, its ability to pinpoint small MPs requires a low dissolved C-background. Second, SP ICP-MS neither distinguishes different MP polymer species from each other nor from other C-particulates (e.g., cells, black carbon). As such, the application of SP ICP-MS is significantly limited when targeting MPs in complex matrices without a priori knowledge. Here, we present a novel trimodal analytical platform that integrates optofluidic force induction (OF2i), single particle Raman spectroscopy (SP Raman), and SP ICP-MS for multimodal online MP characterization. The main objective was the development and demonstration of an optical extraction mechanism, in which an optical trap employing a weakly focused laser vortex beam was used to immobilize MPs from a sample suspension. This provided two analytical opportunities, which were demonstrated in conjunction with a SP Raman module and SP ICP-MS. First, the optical trapping enabled the investigation of inelastically scattered light of individual MPs via Raman spectroscopy and consequently, the identification of polymer type. Second, the trapping enabled a matrix exchange, reducing the background signal in SP ICP-MS. Both the polymer identification and the reduction of background signal resulted in improved detection and calibration capabilities in SP ICP-MS. Polymer type identification via SP Raman provided the C-mass fraction and polymer density in MPs, which are critical factors for size estimations in SP ICP-MS. However, the reduced background and improved size detection limit enabled the analysis of smaller MPs. In a proof-of-concept, 5 μm polystyrene particles were dispersed in a high carbon content matrix (1 g C/L) and analyzed via OF2i-SP Raman-SP ICP-MS using the optical extraction mechanism. The mass and size detection limits were improved by factors of 28 and 3.1, respectively, and were determined to be 1.0 μm and 0.6 pg of carbon per particle. In a second proof-of-concept, polyamide-6 (PA-6) MPs were spiked into soil to simulate a complex terrestrial environment at the lab-scale. Following the resuspension, PA-6 MPs were optically extracted and analyzed using SP Raman and SP ICP-MS. The optical extraction of MPs is a new concept, which enables isolation of specific polymer particles for molecular and elemental single particle characterization. However, the developed methods can also be expanded to characterize inorganic (non-polymeric) nano- and microstructures.
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