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Reviewing the fundamentals and best practices to characterize microplastics using state–of–the-art quantum-cascade laser reflectance-absorbance spectroscopy

TrAC Trends in Analytical Chemistry 2025 6 citations

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Researchers reviewed best practices for using quantum cascade laser infrared imaging (a high-speed scanning technology) to reliably identify microplastic particles, addressing technical pitfalls like particle-size effects on spectral readings. Standardizing this method is important for generating consistent, comparable data as governments push for official microplastic monitoring programs.

Microplastic pollution studies depend on reliable identification of the suspicious particles. Out of the various analytical techniques available to characterize them, infrared transflectance using a tuneable mid-IR quantum cascade laser is a high-throughput state-of-the-art imaging option, specifically Agilent's QCL-LDIR (Quantum Cascade Laser Direct Infrared imaging). Its conceptual grounds are reviewed, instrumental developments are discussed, along with a review of applications and best practices to overcome obstacles/difficulties in routine measurements, namely: the spectral range, the variation of some peak intensities with the particles size, processing speed, and avoiding the use of measurement aliquots. Objective procedures to avoid too many false positives when identifying spectra and to distinguish fibers and fragments are given. These practices open a path to QCL-LDIR measurement standardization and potential use for microplastics monitoring, as requested by many governmental bodies in charge of setting environmental protection rules. • It is shown that the experimental setup can alter the final identification of suspicious particles. • Reducing number of particles and measurement area per project accelerate measurements. • Due to transflectance phenomena, measured spectra depend nonlinearly on the particle size. • A way to evaluate the length penetration of the laser beam is proposed for some polymers. • Three levels of reliability are proposed to report match of unknowns to spectral databases.

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