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Huth-Fehre, Th., Feldhoff, R., Kantimm, Th., Quick, L., Winter, F., Cammann, K., van den Broek, W., Wienke, D., Melssen, W. and Buydens L. (1995) NIR—Remote Sensing and Artificial Neural Networks for Rapid Identification of Post Consumer Plastics. Journal of Molecular Structure, 348, 143-146.
http://dx.doi.org/10.1016/0022-2860(95)08609-Y

has been cited by the following article:

• TITLE: Improved High Performance Recycling of Polymers by Means of Bi-Exponential Analysis of Their Fluorescence Lifetimes

  AUTHORS: Heinz Langhals, Dominik Zgela, Thorben Schlücker

  KEYWORDS: Recycling, Polymers, Fluorescence Decay, Fluorescence Spectroscopy, Gaussian

  JOURNAL NAME: Green and Sustainable Chemistry, Vol.5 No.2, May 14, 2015

  ABSTRACT: Technical polymers could be identified by means of their remarkably strong auto fluorescence. The mono-exponentially obtained time constants of fluorescence decay were applied for a rough assignment of the polymeric materials whereas bi-exponential analysis allowed a fine classification such as for special batches and for preceding contaminations. Chemically similar materials such as LDPE (low-density polyethylene), HDPE (high-density polyethylene) and UHDPE (ultrahigh-density polyethylene) could be as well identified as contaminations of mineral oil in PET (polyethylene terephthalate). Furthermore, the fluorescence spectra could be characterized by means of five Gaussian functions in the visible allowing a redundant assignment to the fluorescence lifetimes. Thus, efficient sorting of polymers was possible for high performance recycling.