Multisensor characterization of WEEE polymers: spectral fingerprints for the recycling industry

Abstract

Waste from electronic equipment (WEEE) is a fast-growing complex waste stream, and plastics represent around 25% of its total. The proper recycling of plastics from WEEE depends on the identification of polymers prior to entering the recycling chain. Technologies aiming for this identification must be compatible with conveyor belt operations and fast data acquisition. Therefore, we selected three promising sensor types to investigate the potential of optical spectroscopy-based methods for identification of plastic constituents in WEEE. Reflectance information is obtained using Hyperspectral cameras (HSI) in the short-wave infrared (SWIR) and mid-wave infrared (MWIR). Raman point acquisitions are well-suited for specific plastic identification (532 nm excitation). Integration times varied according to the capabilities of each sensor, never exceeding 2 seconds. We have selected 23 polymers commonly found in WEEE (PE, PP, PVC ABS, PC, PS, PTFE, PMMA), recognising spectral fingerprints for each material according to literature reports. Spectral fingerprint identification was possible for 60% of the samples using SWIR-HSI; however, it failed to produce positive results for black plastics. Additional information from MWIR-HSI was used to identify two black samples (70% identified using SWIR + MWIR). Fingerprint assignment in shorttime Raman acquisition (1 -2 seconds) was successful for all samples. Combined with the efficient mapping capabilities of HSI at time scales of milliseconds, further developments promise great potential for fast-paced recycling environments. Furthermore, integrated solutions enable increased accuracy (cross-validations) and hence, we recommend a combination of at least 2 sensors (SWIR + Raman or MWIR + Raman) for recycling activities.