Analyzing Microscopic Contaminants Embedded in Recycled Plastic

Importance of the Topic

Recycling of plastics is essential for sustainable materials management and achieving carbon neutrality. Ensuring the quality of recycled plastic products requires accurate detection and characterization of microscopic contaminants that can compromise mechanical properties and product performance.

Objectives and Overview of the Study/Article

This application note describes a streamlined workflow for rapid in situ analysis of microscopic contaminants embedded in recycled polyethylene and polypropylene films. The goal is to identify contaminant types, counts, shapes and sizes without extracting them from the polymer matrix.

Methodology

Samples of recycled plastic pellets were formed into approximately 100 µm thick films using a thermal press. High-speed mapping was performed by transmission spectroscopy: each mapping position received a single scan, and regions showing a target infrared peak underwent additional repeated scans. Exclusion ranges were set to suppress base polymer absorptions and focus on contaminant signals. Detected spectra were then processed in a particle analysis program to assess the morphology and number of particles in the area of interest.

Used Instrumentation

• Infrared spectrometer IRTracer-100 with AIMsight microscope
• Software: AMsolution with high-speed mapping and particle analysis modules
• Optical mode: transmission spectroscopy
• Mapping parameters: resolution 8 cm⁻¹, 50 scans per detected peak, step size and aperture 30 µm, mapping area 2370 × 1470 µm, detector T2SL
• High-speed mapping settings: noise threshold 0.01, detection threshold 0.15, exclusion ranges 3200–2000 cm⁻¹ and 1700–700 cm⁻¹

Main Results and Discussion

Infrared Spectral Analysis revealed two contaminant types in the films. Single-scan regions matched the background spectrum of PE/PP. Multiple scans in detected regions produced spectra identified as cellulose fibers and polybutyl methacrylate (PBMA) by searching outside the excluded polymer absorption ranges.
Particle Analysis detected 74 contaminants within the mapped area, with PBMA particles approximately twice as numerous as cellulose fibers. Histograms of short and long particle diameters showed that cellulose contaminants exhibited fiber-shaped geometries while PBMA particles were more isotropic, with both types appearing predominantly in the 20–30 µm size range. Selective multiple scanning reduced total analysis time to about one-fifteenth of a full 50-scan mapping run, improving throughput.

Benefits and Practical Applications

This method offers a rapid, non-destructive approach for quality control of recycled plastics. It enables automated contaminant detection, classification and quantification directly in film samples without chemical extraction, supporting efficient process monitoring and material certification in recycling operations.

Future Trends and Potential Applications

Future developments may include integration of machine learning for real-time spectral classification, extension to a broader range of polymer contaminants, deployment of inline process monitoring systems, and coupling with complementary microscopy techniques to enhance morphological insights.

Conclusion

The combination of high-speed infrared mapping with selective scanning and automated particle analysis provides a powerful, efficient solution for characterizing microscopic contaminants in recycled plastic films. This workflow accelerates analysis, reduces noise, and supports robust quality assurance in recycling processes.