Advancing microplastic characterization in environmental samples using optical photothermal infrared (O-PTIR)...

Microplastics have emerged as a widespread contaminant with potential impacts on ecological and human health. However, their detection and identification in environmental samples remain challenging due to the lack of standardized methodologies, hindering comparability across studies. Various techniques, including spectroscopy- and microscopy-based methods, have been employed for microplastic characterization; however, each has limitations in sensitivity, specificity, affordability, and ease of application. Optical Photothermal Infrared (O-PTIR) spectroscopy is a novel technique that provides high-resolution, non-contact infrared (IR) measurements with simultaneous Raman spectra acquisition. While O-PTIR has shown promise, its operational parameters for complex environmental samples require optimization. This study explored and refined O-PTIR workflows for microplastics identification. Specifically, the study examined the effects of Nile Red dye pretreatment, benchmarked detector configurations (standard vs. avalanche photodiode) to define power thresholds, and investigated cryogenic cooling as a mitigation strategy for thermal damage. Results showed that Nile Red staining impacted IR and Raman band intensities but maintained functional group absorptions. While cryogenic cooling successfully reduced thermal damage, maintaining a reduced but sufficient laser power remained necessary. Crucially, O-PTIR demonstrated high spectral concordance with ATR-FTIR while eliminating physical contact constraints, proving superior for analyzing irregular, micron-scale environmental particles. The optimized workflow was applied to identify 113 particles from complex environmental matrices. These findings provide practical recommendations for minimizing thermal damage, retaining diagnostic bands, and integrating O-PTIR with conventional methods in environmental microplastic research. By addressing key methodological considerations and performance metrics, this study advances microplastic analysis and supports improved data quality, thereby providing a stronger foundation for understanding microplastics environmental behavior.