Multi-sensor characterization for an improved identification of polymers in WEEE recycling.

Polymers represent around 25% of total waste from electronic and electric equipment. Any successful recycling process must ensure that polymer-specific functionalities are preserved, to avoid downcycling. This requires a precise characterization of particle compounds moving at high speeds on conveyor belts in processing plants. We present an investigation using imaging and point measurement spectral sensors on 23 polymers including ABS, PS, PC, PE-types, PP, PVC, PET-types, PMMA, and PTFE to assess their potential to perform under the operational conditions found in recycling facilities. The techniques applied include hyperspectral imaging sensors (HSI) to map reflectance in the visible to near infrared (VNIR), short-wave (SWIR) and mid-wave infrared (MWIR) as well as point Raman, FTIR and spectroradiometer instruments. We show that none of the sensors alone can identify all the compounds while meeting the industry operational requirements. HSI sensors successfully acquired simultaneous spatial and spectral information for certain polymer types. HSI, particularly the range between (1600-1900) nm, is suitable for specific identification of transparent and light-coloured (non-black) PC, PE-types, PP, PVC and PET-types plastics; HSI in the MWIR is able to resolve specific spectral features for certain PE-types, including black HDPE, and light-coloured ABS. Fast-acquisition Raman spectroscopy (down to 500 ms) enabled the identification of all polymers regardless their composition and presence of black pigments, however, it exhibited limited capacities in mapping applications. We therefore suggest a combination of both imaging and point measurements in a sequential design for enhanced robustness on industrial polymer identification.