High-speed detection of additives in technical polymers with laser-induced breakdown spectrometry

Technical polymers are used to manufacture components and housings for electrical appliances such as telephones, computer keyboards or household appliances. Various polymer matrices, e.g. ABS (acrylonitrile-butadiene-styrene), PC (polycarbonate), SB (styrene butadiene) and SAN (styrene acrylonitrile), are doped with additives to improve their mechanical, electrical and chemical properties. Common additives are flame retardants, antioxidants, light stabilisers, fillers, dyes and pigments. Their concentration varies from traces to several percent. During the recycling process of end-of-life waste electric and electronic equipment (EOL-WEEE), downgrading of valuable technical polymers has to be avoided by separating the collected material in fractions of high purity. Waste pieces containing brominated flame retardants (BFR) and heavy metals have to be automatically identified and removed from the waste stream to be recycled due to the significant environmental problems during the waste management phase caused by these substances. To establish an economically feasible recycling process which meets these requirements, high speed automatic sorting systems performing the identification of both the polymer and the critical additives at a rate of several parts per second are required. In the scope of the European project "Sure-Plast" (BRPR-CT98-0783) a prototype automatic identification and sorting line has been set-up for material specific sorting of EOL-WEEE pieces. As the detection unit of this automatic sorting line, a multi-sensor system for a rapid identification of the polymer matrix and the contained additives has been developed comprising three spectroscopic modules based on LIBS (= laser induced breakdown spectroscopy), NIR (= near infrared spectroscopy) and MIR (= mid-infrared spectroscopy). The goal is to combine the spectroscopic information measured in the infrared region with the element specific LIBS signals to identify the polymer type, the heavy metals and the flame retardants. This report focuses on the automated LIBS analyser of the multi-sensor system