Sequence distributions in polymers

Applications of Monte Carlo Methods to Sequence Distributions in Polymers... 

A general method has been developed for the estimation of model parameters from experimental observations when the model relating the parameters and input variables to the output responses is a Monte Carlo simulation. The method provides point estimates as well as joint probability regions of the parameters. In comparison to methods based on analytical models, this approach can prove to be more flexible and gives the investigator a more quantitative insight into the effects of parameter values on the model. The parameter estimation technique has been applied to three examples in polymer science, all of which concern sequence distributions in polymer chains. The first is the estimation of binary reactivity ratios for the terminal or Mayo-Lewis copolymerization model from both composition and sequence distribution data. Next a procedure for discriminating between the penultimate and the terminal copolymerization models on the basis of sequence distribution data is described. Finally, the estimation of a parameter required to model the epimerization of isotactic polystyrene is discussed. 

In the earlier two editions, a 5Va in. diskette was included at the end of the books with some computer programs in Pascal. These programs were there to offer the students experience in calculating results from size exclusion chromatograph or to determine sequence distribution in polymers from NMR spectra, and some others. These programs have been omitted, however, because there are now considerably better programs, written by professional computer scientists, now commercially available. 

Stochastic methods have been applied to compare observed and predicted sequence distribution in polymers prepared to high conversion. For example, the sequence distributions of a range of styrene/methyl methacrylate copolymers,... 

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