Identification of plastic waste using spectroscopy and neural networks.: An article from: Polymer Engineering and Science

This digital document is an article from Polymer Engineering and Science, published by Society of Plastics Engineers, Inc. on June 1, 1995. The length of the article is 3412 words. The page length shown above is based on a typical 300-word page. The article is delivered in HTML format and is available in your Amazon.com Digital Locker immediately after purchase. You can view it with any web browser.

From the author: In this paper we investigate a new approach for the automated sorting of post-consumer plastic waste. We show that rapid and reliable identification of polymers can be achieved using a combination of fixed-filter near-infrared spectroscopy and neural network data analysis, and we demonstrate the effectiveness of the proposed method for sorting polyethylene terephthalate, high density polyethylene, and poly(vinyl chloride). Finally, we discuss a proposed compact, rugged instrument based on the new sorting method. Owing to the flexibility gained by incorporating neural networks in our system, this method can easily be extended to include additional polymers.

Citation Details
Title: Identification of plastic waste using spectroscopy and neural networks.
Author: D.M. Scott
Publication:Polymer Engineering and Science (Refereed)
Date: June 1, 1995
Publisher: Society of Plastics Engineers, Inc.
Volume: v35 Issue: n12 Page: p1011(5)

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