Analyzing Colored Microplastics with the Agilent 8700 Laser Direct Infrared (LDIR) Chemical Imaging System

Significance of the Topic

Plastic pollution has become a critical environmental concern, with microplastics entering ecosystems and the food chain. Accurately identifying microplastics—including those dyed or pigmented—is essential for assessing their distribution and ecological impact. Conventional Raman microscopy often struggles with colored particles due to interference from dyes, leading to misidentification and prolonged analysis times.

Objectives and Study Overview

This study evaluates the performance of the Agilent 8700 Laser Direct Infrared (LDIR) Chemical Imaging System for identifying colored polyethylene terephthalate (PET) microplastics. Three PET bottle colors (brown, white, and blue) were ground, suspended in ethanol, and analyzed to determine whether added pigments affect automated microplastic characterization.

Methodology

Samples of brown, white, and cobalt-blue PET bottles were mechanically ground and dispersed in absolute ethanol. Aliquots of the suspension were deposited onto a low-e infrared reflective glass slide and air-dried. The LDIR system scanned each sample area at 1,442 cm–1 to generate an infrared image, locating particles by contrast in carbon–hydrogen absorption. Each particle was then automatically moved under the IR beam to acquire a full spectrum, which was compared to a reference library for identification.

Used Instrumentation

• Agilent 8700 LDIR Chemical Imaging System
• Agilent Clarity software with Microplastics Starter 2.0 spectral library
• Low-e infrared reflective MirrIR glass slides
• Absolute ethanol (CAS 64-17-5)

Main Results and Discussion

The system detected and correctly identified over 95% of colored PET particles in each test (brown: 96.0%; white: 97.4%; blue: 97.2%). High-confidence matches (hit quality index ≥0.80) accounted for 76.6% of brown, 89.7% of white, and 84.9% of blue particles. Spectral overlays of brown, white, and blue PET showed nearly identical absorbance profiles, indicating that dyes and pigments do not interfere with infrared-based identification. In contrast, Raman methods often suffer from pigment fluorescence and extra peaks, complicating polymer detection.

Benefits and Practical Applications

• Color-independent microplastic identification without custom pigment libraries
• Fully automated workflow for particle detection, sizing, and spectral analysis
• Reduced analysis time and operator involvement compared to manual Raman methods
• High-throughput capability for routine environmental and QA/QC monitoring

Future Trends and Potential Applications

Advancements may include expanding spectral libraries to cover more polymer types and environmental matrices, integrating machine learning for enhanced classification, and coupling LDIR with automated sample preparation and microfluidic extraction. These developments could enable real-time monitoring of microplastics in water, soil, and biological samples.

Conclusion

The Agilent 8700 LDIR Chemical Imaging System provides robust, color-independent identification of PET microplastics with high confidence and minimal sample preparation. This infrared-based approach overcomes the limitations of Raman spectroscopy when analyzing dyed or pigmented particles, offering a rapid, automated solution for environmental microplastics research.

References

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