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Multi-sensor characterization for an improved identification of polymers in WEEE recycling
Andréa de Lima Ribeiro1, Margret C Fuchs1, Sandra Lorenz1
1Helmholtz-Zentrum Dresden-Rossendorf, Helmholtz Institute Freiberg for Resource Technology, Freiberg, Chemnitzer Str. 40, 09599 Freiberg, Germany.
Waste Management (New York, N.Y.)
|February 28, 2024
Summary
Recycling electronic waste polymers requires precise identification. Combining hyperspectral imaging and Raman spectroscopy effectively identifies various plastics, even black ones, on conveyor belts for improved recycling processes.
Area of Science:
- Materials Science
- Environmental Science
- Analytical Chemistry
Background:
- Polymers constitute a significant portion (25%) of electronic waste, necessitating effective recycling to preserve material value and prevent downcycling.
- Accurate identification of polymer types on high-speed conveyor belts is crucial for successful recycling operations in processing plants.
Purpose of the Study:
- To evaluate the performance of various spectral sensors for identifying 23 different polymers under industrial recycling conditions.
- To determine the suitability of hyperspectral imaging (HSI) and point measurement techniques for real-time polymer characterization.
Main Methods:
- Utilized hyperspectral imaging sensors (HSI) across visible to near-infrared (VNIR), short-wave (SWIR), and mid-wave infrared (MWIR) ranges.
- Employed point measurement techniques including Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, and spectroradiometry.
- Tested sensors on 23 polymer types, including ABS, PS, PC, PE-types, PP, PVC, PET-types, PMMA, and PTFE.
Main Results:
- No single sensor could identify all polymers while meeting industrial operational requirements.
- HSI in the 1600-1900 nm range effectively identified transparent/light-colored PC, PE-types, PP, PVC, and PET-types.
- MWIR HSI resolved spectral features for specific PE-types (including black HDPE) and light-colored ABS.
- Fast-acquisition Raman spectroscopy (500 ms) identified all polymers, including those with black pigments, but had limited mapping capabilities.
Conclusions:
- A combined approach using both HSI and point measurement techniques in a sequential design offers enhanced robustness for industrial polymer identification.
- This integrated strategy addresses the limitations of individual sensor types, paving the way for more efficient and effective e-waste polymer recycling.
