|Keywords:||STEM; perovskite oxides|
|Full text PDF:||http://hdl.handle.net/1813/41170|
Perovskite oxides have received a significant amount of attention in research within recent years, due to their wide range of electronic and magnetic properties, and for their enormous potential for new and innovative device applications. The growth of perovskite oxides on silicon would be a tremendous advantage; considering that silicon has been the most successful material used in major global industries during the past century. The incorporation of perovskite oxides in a silicon-based industry will make it readily adaptable for new devices that utilize the properties of perovskite oxides, which are not widely accessible at the present time. To reach this goal, serious scientific efforts have been made in the controlled growth of perovskite oxides on silicon. Key to success is a better understanding of how perovskite oxides grow on silicon which could ultimately lead to high quality perovskite growth and potentially to successful commercialization of such for industrial applications. In this study, scanning transmission electron microscopy (STEM) is used to obtain atomic resolution images of perovskite oxides directly grown on silicon; to assist us in understanding and evaluating its precise structural details. A LaAlO3 /SrTiO3 /Si sample and several SrTiO3 /Si samples were used in these experiments. The specimens were prepared by wedge mechanical polishing, followed by ion milling for further thinning and to reduce polishing damage. Several milling tests were performed using Si and SiO2 /Si samples to optimize the milling conditions. An Atomic Force Microscope was utilized to measure the surface roughness of the samples before and after ion milling, so as to ex- amine and record the milling damage by measuring surface roughness. X-ray photoelectron spectroscopy was used to analyze the composition before and after milling. Some troubleshooting of a newer model ion mill was also performed and possible damage from polishing and ion milling during the STEM specimen preparation is discussed. In STEM data is collected by detectors as binary numbers, which need to be collated and processed before direct viewing and further analysis. Therefore, software applications have been developed for STEM image processing, which converts data into images and supports advanced editing, such as adjusting contrast or techniques to enhanced image clarity. In our research, ImageJ was used to precisely analyze STEM images of perovskite oxides grown on silicon. To customize image processing, we developed a python based software, 'STEM SmartPro'. This software displays binary images directly for ease of viewing and basic editing, while also saving edited images as tiff or jpeg files. Some other features include convenient viewing of images in a slide-show format, providing quick access to all supporting files stored in the same folder, and performing cross-correlation for image registration with a single click. The software design, both the UI layer and the system structure, is reviewed in detail. STEM images were recorded for the LaAlO3… Advisors/Committee Members: Muller,David Anthony (committeeMember).