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Development of Data Processing Scheme for Plastic Identification Instruments--Physical Sciences, Inc., 20 New England Business Center, Andover, MA  01810-1077; 978-689-0003

Dr. Thomai Panagiotou, Principal Investigator

Dr. B. David Green, Business Official

DOE Grant No. DE-FG02-00ER83076

Amount:  $99,982

 

Rapid and accurate identification of the type of plastic waste prior to recycling is essential for producing good quality products at competitive prices. Most plastic identification instruments rely on matching the spectrum of an unknown plastic with a spectrum in the library of the instrument. Even the most sophisticated of these instruments use crude and inefficient data processing methods, which limit their speed and accuracy and also their ability to sort between plastics with small variations in composition.  The overall objective of Phase I and Phase II is the development of data processing methods (identification algorithms) that will be used by existing plastic identification instruments.  The algorithms will enhance the speed and accuracy of identification and will provide the ability to sort between plastics with small variations in composition.  The proposed work will address the problem of sorting out waste plastics fast and accurately prior to recycling.  We will develop data processing methods for plastic identification instruments that will increase the speed and accuracy of such instruments.  In Phase I we will generate a spectral database of commonly used industrial plastics and we will determine the number and location of spectral bands necessary for the identification of each type of plastic.  Subsequently we will develop data processing strategies that will result in rapid and accurate identification.  Finally we will assess the identification algorithm using data provided to us by automotive manufacturers.

 

Commercial Applications and Other Benefits as described by the awardee:  The objective of this work is to develop data processing methods, which will increase the speed and accuracy of systems that identify waste plastics prior to recycling. Emphasis will be given in identification of industrial plastics such as automotive parts.  Excluding the tires and bumper, more than 8 million tons of plastic per year can be recycled from discarded automobiles, provided that reliable sorting systems exist.  Automotive companies have shown substantial interest in the proposed work and promised to help us validate our algorithm.