Sorting at industrial scale is required to perform mechanical recycling of plastics in order to obtain properties that could be competitive with virgin polymers. As a matter of fact, the most part of the various types of plastic waste are not miscible and even compatible. Mid-Infrared (MIR) HyperSpectral Imagery (HSI) is viewed as one of the solutions to the problem of black plastic sorting. Many Waste of Electrical and Electronic Equipment (WEEE) plastics are black. Nowadays, these materials are difficult to sort at an industrial scale because the main used pigment to produce this color, carbon black, masks the Near-Infrared (NIR) spectra of polymers, the currently most used technology for acute sorting in industrial conditions. In this study, laboratory Fourier-Transform Infrared (FTIR) in Attenuated Total Reflection mode (ATR) has been used as a theoretical toolbox based on physical chemistry to help building an automated HSI discrimination despite its limited conditions, especially shorter wavelengths ranges. Weaker resolution and very short acquisition times are other HSI limitations. Helping fast and exhaustive laboratory characterizations of polymeric waste stocks is the other goal of this study. This study focusses on polyolefins as they represent the second biggest fraction of WEEE plastics (WEEP) after styrenics and since little quantities mixed to styrenics during mechanical recycling can lead to important decrease in mechanical properties. Twelve references were thus evaluated and compared between each other and with real waste samples to highlight spectral elements, which can enable differentiation. Charts compiling the signals of discussed polymers were built aiming to the same objective.
Keywords: Identification; MIR; Polymer recycling; Polyolefins; Sorting; WEEE.
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