Energy-efficient Systems for the Sensing and Separation of Mixed Polymers

Polymers are ubiquitous in modern manufactured products. The potential detrimental impacts of their end-of-life disposal have stimulated significant increases in recycling rates. Recyclate purity is paramount; however this must be achieved with a positive net energy balance. Existing technologies for identification and separation of polymers are often both expensive and energy intensive. This paper investigates Infrared (IR) imaging to extract information on thermal properties of various product polymers within a recycling line. An intelligent decision making support system is enabled using neural network based pattern recognition for automatic polymer identification and classification. Potential energy savings versus current technologies are discussed.