Discrete frequency infrared-guided image for microplastic analysis: Performance and limitations

Abstract

Applying a quantum cascade laser as a light source in a benchtop infrared spectrometer has enabled a new strategy for microplastic analysis. This strategy uses discrete frequency infrared images to recognize particles from a reflecting substrate prior to chemical identification, thereby improving analysis throughput.This research work established the performance of the approach using an Agilent Laser Direct Infrared chemical imaging system (LDIR). Over 90 % of fluorescently labelled polyethylene particles (> 20 µm) spiked in the environmental matrix were correctly identified at scanning wavenumbers and sensitivity settings. When the high-throughput setting was used, the discrete frequency infrared image-guided microplastic analysis demonstrated good selectivity. With around 30 % of particles in the sample scanned, the technique could recognize around 86 % percent of fluorescently labelled polyethylene particles introduced.The MirrIR low-e slide and gold-coated filter are suitable reflecting substrates for this particle analysis strategy. When detecting small microplastic particles with sizes between 5 and 20 µm, around 94 % spiked polymethyl methacrylate particles could be found on the MirrIR low-e slide. The analysis also showed good accuracy and precision in a three-day test. The texture on the gold-coated filter surface could interfere with the small particle analysis.Overall, this novel discrete frequency infrared image-guided particle analysis shows good accuracy, high precision, and respectable selectivity, which are all critical characteristics for microplastic analysis.