Nanoscale morphologies of polystyrene and polyethylene ionomers

Ionomers are highly valued for their unique properties and therefore have long been studied to characterize, understand, and improve these properties. Many studies have focused on the bulk properties of ionomers with more recent efforts using X-ray scattering to characterize the nanometer scale structure especially the ionic aggregate. Scanning transmission electron microscopy (STEM) technology has developed to the point within the past decade that direct imaging of the ionic aggregate is possible. In this dissertation, STEM techniques are refined by accounting for extensive overlap in the projected image and STEM techniques along with X-ray scattering methods are used to study a unique group of poly(ethylene-co-acrylic acid) (P(E-AA)) copolymers and ionomers.;We examined poly(styrene-ran-7%-methacrylic acid) Cu (P(S-MAA0.07) Cu) ionomer with model dependant X-ray scattering and direct imaging through STEM. Using the liquid-like hard sphere X-ray scattering model proposed by Yarusso and Cooper with Fornet interference, the ionic aggregate number density indicate an extensively overlapped system for the STEM imaging. Thus, to properly interpret the STEM data, the extensive overlap must be corrected. By creating a computer model that is able to simulate STEM images from an X-ray model, the amount of overlap can be estimated and a proper number density can be calculated from the STEM images. The number density calculated from STEM agrees with the X-ray scattering. Also, despite the extensive overlap, the brightest, isolated features in the STEM are of the appropriate size and shape that would be expected from the projection of a single ionic aggregate. Therefore, the STEM and X-ray scattering are in agreement about the morphology of the ionic aggregates in these P(S-MAA0.07) Cu ionomers. These experiments are repeated for poly(styrene-ran-1.9%-sulfonated styrene) neutralized by Cu, Zn, Ba, or Cs and found that the liquid-like hard sphere X-ray model and the STEM agree on the size, shape, distribution, and number density of the ionic aggregates.;We generalize our simulation method to projection of overlapping spheres. A procedure is developed to create and analyze large numbers of simulated projections through computer algorithms. To analyze the data set, it is plotted on axes chosen to reduce the number of variables that influenced the number of features counted in the simulated image (N2D) as a function of simulation thickness (t). The dependant axis is N2D normalized by the area of the simulation in units of 4 times the square of the sphere radius. The independent axis is simply the thickness in units of the sphere radius. With these axes, the important variable is the volume fraction of spheres (&phis; R). In addition, there is a critical thickness, t c, where if t < tc, then the normalized N2D is proportional to talpha and if t > t c, the normalized N2D is independent of thickness at a value of beta. By knowing the thickness of the sample, the normalized N2D, the volume fraction can be estimated and thus the number of spheres in the volume can be calculated.;Finally, we study the morphology of linear P(E-AA) copolymers with precisely-sequenced and irregularly sequenced acid groups to establish the effect that the acid group sequence has on the crystal structure. The linear irregularly-sequenced P(E-AA) copolymers behave similarly to low density poly(ethylene-acrylic acid) forming an orthorhombic polyethylene crystal structure and excluding the acid groups to the amorphous regions. The linear precisely-sequenced P(E-AA) copolymers exhibit an unique structure with the acids forming large planar layers that are incorporated into the crystal structure. The precisely-sequence linear P(E-AA) ionomers exhibit both the new acid layer structures and the traditional ionic aggregates. With increasing neutralization, the crystallinity of the P(E-AA) and the new acid layer structure decrease as the acid groups necessary are co-opted to form the ionic aggregates in the amorphous regions.