Mitigating Scattering in QCL-IR Microscopy for Microplastic Identification

Micro- and nanoplastics (MNP) have emerged as a pressing concern due to their widespread presence in environmental and biological systems, yet their detection and characterization remain challenging. Their small particle size introduces strong scattering and optical artifacts that distort infrared (IR) spectra, complicating accurate chemical identification. In this work, we employ quantum cascade laser-infrared (QCL-IR) microscopy to address these limitations and establish a systematic framework for detecting and characterizing MNP across different media. We acquired the IR images and spectra of MNP samples, such as polypropylene (PP), polyethylene terephthalate (PET) particles, and high-density polyethylene (HDPE) fibers.
Our strategy is to mitigate scattering effects by matching the refractive index of MNP with that of the surrounding medium and, thus, to improve particle identification and measurement assurance across samples. We compared the IR spectral images between air-dried MNP and MNP dispersed in water or other organic solvents. These results indicate that a proper sample medium and an appropriate analysis strategy can make IR microscopy more reliable for quantitatively analyzing MNP across various environmental and experimental settings.