Application of multi-technique correlation and multivariate analysis to heterogeneous polymer systems

The goal of this project is the creation of new methods for the non-destructive, three-dimensional characterization of heterogeneous organic materials. Data are acquired from polymer blend samples using a variety of analytical techniques, including x-ray photoelectron spectroscopy (XPS) and Fourier transform infra-red spectroscopy (FTIR). Multivariate statistical analysis (MVA) and classification methods are used to enhance interpretation of the resulting multi-dimensional data sets.; Heterogeneous polymer blends of poly (vinyl chloride), PVC and poly(methyl methacrylate), PMMA were chosen for these correlative studies.; Recent improvements in the spatial resolution and data acquisition times for a variety of analytical instrumentation allow for new approaches to the chemical characterization of complex heterogeneous materials. This project takes advantage of recent advances in XPS and FTIR. Commercially available FTIR and XPS instruments offer rapid, real-time imaging with comparable lateral resolution and, critically, comparable image fields. This is the first study that has demonstrated that XPS and FTIR images and spectra can be acquired from the same areas on heterogenous polymer films. The techniques sample different properties of the films, but the good correlation between the XPS and FTIR images demonstrates that qualitative and quantitative comparisons are possible. The technique combination provides a more complete method for characterizing complex polymer films containing differing surface and bulk compositions. Analysis of the blends using either technique alone would result in less complete, and potentially misleading, conclusions regarding the structure of these complex films.; This study has evaluated a number of different MVA algorithms that can be applied to XPS spectra and images to enumerate the species existing in a multicomponent system and resolve chemically meaningful components. The degradation of PVC under X-ray exposure serves as a means to create multi-dimensional spectral and imaging data sets for algorithm evaluation. The performance of multivariate methods in the resolution of chemically meaningful pure components was tested by comparing the extracted information to the chemical information obtained from direct interpretation of the XPS data.; The PVC/PMMA blend was chosen as a test system for the evaluation of various algorithms since it was considered to be a well-studied system. Attempts to correct for degradation in quantification and multivariate analysis techniques applied to the XPS spectra and images indicate that the degradation behavior of PVC within the blend is more complex than was expected. This study thus also demonstrated that the appropriate application of surface chemometrics can extract “hidden” information from complex data.