|Miri, Massoud - ROCHESTER INSTITUTE OF TECHNOLOGY|
Submitted to: American Chemical Society Symposium Series
Publication Type: Book / Chapter
Publication Acceptance Date: 8/23/2011
Publication Date: 10/24/2011
Citation: Cheng, H.N., Miri, M.J. 2011. Statistical models and NMR analysis of polymer microstructure. In: Cheng, H.N., Asakura, T., English, A.D., editors. NMR Spectroscopy of Polymers: Innovative Strategies for Complex Macromolecules. ACS Symposium Series 1077. Washington, DC: American Chemical Society. p. 372-382.
Interpretive Summary: Nuclear magnetic resonance (NMR) spectroscopy is being used extensively in polymer chemistry as a premiere technique for the determination of polymer structure. In liquid-state NMR analysis, a given polymer is first dissolved in a suitable solvent, and the NMR spectra (1H and/or 13C) are obtained on a NMR instrument. The spectra then need to be interpreted and analyzed in an appropriate manner in order to produce structural information such as polymer composition, sequence distribution, tacticity, regiochemistry, branching, and defect structures. A method that can facilitate analysis, improve accuracy, and provide information even on polymerization mechanisms is the use of statistical models. In this paper, a review is made of the common statistical models that have been used for different types of polymerizations. In addition to the models, new or improved methodologies are needed to match the statistical models to the NMR data in order to ensure accuracy of interpretation and to yield the maximum amount of information possible. These methodologies are often conducted with the help of computer calculations and simulations. These include “analytical”, “simulation”, and “integrated” approaches, including several devised previously by the authors. These approaches are applicable not only to synthetic polymers but also to many natural polymers, such as pectin, guar, and alginates. As an example of a recent development, this paper describes a computer program written in Excel that can be used for the simulation of homopolymer tacticity. Although this program is targeted specifically for polyolefins made with metallocene catalysts, it can also be used for the simulation of tacticity of many other polymeric systems as well.
Technical Abstract: Statistical models can be used in conjunction with NMR spectroscopy to study polymer microstructure and polymerization mechanisms. Thus, Bernoullian, Markovian, and enantiomorphic-site models are well known. Many additional models have been formulated over the years for additional situations. Typically spectral interpretation and data treatment can be done through either “analytical” or “simulation” approaches. These can be combined into “integrated” approaches for specific situations. An alternative (and more general) approach considers the kinetics of the polymerization process and carries out predictions of polymer microstructures and NMR spectra. These various methodologies are briefly reviewed here. Also reviewed is a recent effort in the simulation category involving a user-friendly Excel program (“Polytact”) that can simulate the tacticities of a large number of statistical models, particularly those that pertain to polyolefins made with single-site catalysts.