High Throughput Plastic Sorting Technique Based on Molecular Vibrational Signatures

Plastic pollution is an enormous environmental problem that has been increasing exponentially in the last few decades. Despite the huge public awareness, overall recycling rate remains only at 8.7%. Overall recycling of post-consumer plastic can be recovered only with improved separation efficiency at the Material Recovery Facilities (MRF). Therefore, the success of plastic recycling critically depends on developing cost-effective techniques that automate the entire process of sorting plastics based on their chemical composition in a high throughput fashion. At present, the most effective methods like NIR, LIBS Raman spectroscopy or AI robotic arms have poor sensitivity, subpar selectivity, increased risk of false identification and inability to detect black plastics. Here we report a novel, simple and cost-effective technique that can increase the sensitivity, molecular selectivity, and speed of plastic sorting. This approach relies on resonant excitation of molecular bonds with pulses of mid-infrared radiation that are unique to the selected resin. Non-radiative relaxation of resonantly excitation of vibrational states increases the local temperature of the irradiated area. The increased local temperature is then imaged with a highly sensitive infrared camera. Superimposition of the thermal and visible images provide identification each plastic enables high throughput sorting. This technique has the potential to sort black plastics rapidly, which is a major challenge for any other currently used technique.