Imaging studies and density functional analysis of surfaces and interfaces: comparison of theory and experiment

The ability to develop imaging technology over an appropriate range of energy and momentum transfer coupled with an ability to reason about and interpret such images is critical to the development of AI for process control. We present the results of imaging studies which have been directed towards developing surface and near-surface imaging technology for material and process control. The first was an experimental model system chosen to simulate the near surface region of a polymeric composite. Polymers were modeled as an homologous series of oligomeric alkane fragments deposited on the [0001] plane (basal) of highly-ordered pyrolytic graphite. Raman and scanning tunneling spectroscopy reveal that matter in the surface and near surface region takes on a qualitatively different structure from the bulk material. The alkanes form a self-assembled monolayer on the surface and adopt a characteristic rank and file structure on the surface. In the second system, Raman imaging and STM imaging studies were applied to the surface of thin superconducting films of yttrium barium copper oxide on the [111] face of a lanthanum oxide substrate. There is evidence that the performance of these films is influenced by the stoichiometric ratios and it is therefore of interest to determine if the surface material is homogeneous or whether there is evidence of speciation and/or aggregation. The underlying mechanisms for structure formation are discussed in terms of the symmetry of local fluctuations and the symmetry breaking role of the interface