Abstract
The average composition and detailed microstructure of copolymers of ethylene and propylene have been studied by pyrolysis–gas chromatography (Py–GC), using a statistical modeling approach to analyze the data. The trimer distribution obtained from Py–GC is used to infer monomer arrangement information, which is quantified in terms of a number-average sequence length for each monomer. These values are used to define the microstructure and to calculate the average composition. Compared with other available techniques, Py–GC provides a simple, quick and reliable approach to study the microstructure and composition of polyolefin copolymers. Details of this Py–GC method are discussed, including an examination of its advantages and disadvantages, and a summary of the qualitative and quantitative analysis aspects of this approach is presented. The combination of a statistical modeling approach with Py–GC to study copolymer composition and microstructure allows one to investigate the complex problem of monomer arrangement in copolymers using a widely available analytical technique. We expect that with further advances in separation technology, especially two-dimensional gas chromatography (GC × GC), research of this type will be become increasingly accurate and reproducible in the near future.
Published Version
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