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

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.