L. Brunnbauer, S. Larisegger, J. Lohninger, M. Nelhiebel, A. Limbeck:
"Spatially resolved polymer classification using laser induced breakdown spectroscopy (LIBS) and multivariate statistics";
Synthetic polymers and plastics have become one of the most important materials in our modern world and everyday life with all kinds of applications mainly due to their wide range of excellent and tuneable properties. Several novel materials consisting of multiple different synthetic polymers or composite materials like natural-fiber-reinforced polymer composites have already been reported in literature. Additionally, materials consisting of multiple synthetic polymers already found their way in our daily lives (e.g. double-sided adhesive tape). With emerging materials consisting of different structured synthetic polymers, the need for analytical methods characterizing these kinds of sample also arises. Conventionally, analytical techniques such as FT-IR or Raman spectroscopy are used for polymer classi-fication. Although, these techniques offer laterally resolved investigations they lack the possibility of analyzing depth profiles. In this work, we present laser induced breakdown spectroscopy (LIBS) as a novel and powerful analytical method for spatially resolved polymer classification. As a feasibility study, two exemplary structured synthetic polymer samples (2D structured and multilayer system) have been analyzed using LIBS and the spatial distribution of 5 different synthetic polymers, namely acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), polyethylene (PE), polyacrylate (PAK) and polyvinylchloride (PVC) have been suc-cessfully classified using multivariate statistical approaches (principal component analysis (PCA) and k-means clustering). Spatially resolved classification results were validated by comparing the obtained distribution of the 2D structured sample to the elemental distribution of a contamination present in one of the synthetic polymers. Classification of the polymeric multilayer system was validated by comparing the obtained results to a microscopic cross-section. It was shown that LIBS cannot only be used to investigate 2D structured polymer samples but also for direct analysis of depth profiles. Besides synthetic polymer classification, LIBS provides simultaneous analysis of the elemental composition of the sample, which increases the total amount of information accessible with only one measurement.
LIBS, polymer classification, spatially resolved analysis
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