This paper presents the development of a novel line-camera device in the lower THz-domain which is capable of measuring minute differences in broadband spectral fingerprints of non-conducting materials. The primary focus is sorting black plastics in industrial recycling contexts, where large scale sorting of different types of black plastics remains a challenge. The system operates between 84 GHz and 96 GHz. As the relevant plastics exhibit no specific absorption lines in this frequency range, a broadband approach is necessary to accumulate slight differences in dielectric properties. Using this technique, enough entropy can be gathered that a machine learning algorithm can be trained to differentiate between different materials. This has to work even in the presence of contaminants such as flame retardants, color pigments and dirt. Preliminary results suggest that the THz sensor system is capable of achieving these goals.

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