Nano-Patterning by Ion Bombardment
This event is part of the Preliminary Oral Exam.
Examining Committee: Karl Ludwig, Ophelia Tsui, Anatoli Polkovnikov, Lee Roberts
Abstract: The bombardment of surfaces by ions can lead to the spontaneous formation of nano-structures. Depending on the irradiation conditions, smoothening or roughening mechanisms can be the leading order in pattern formation which can result in the creation of dots, ripples or ultra-smoothening effects. The fundamental processes governing surface pattern formation are not well understood; therefore, understanding the physical mechanisms of surface evolution during ion bombardment is one of our research goals. Our recent grazing incidence small angle x-ray scattering (GISAXS) measurements of the structure factor of Si surfaces undergoing 1 keV Ar+ ion-bombardment indicate an important role for ion-induced stress as a competing mechanism along with the more recognized impact-induced redistribution and erosion processes for pattern formation. Therefore, stress measurement techniques were also designed and performed in our lab in order to measure the stress in Si surfaces irradiated as a function of ion energy, flux and angle. Moreover, using new x-ray photon correlation spectroscopy (XPCS) techniques in a coherent GISAXS scattering geometry offers extensive new opportunities to investigate surface dynamical processes and fluctuations in much greater detail than was previously possible. We have taken advantage of this new capability to perform XPCS studies of silicon surfaces under various ion-beam irradiation conditions. The early time as well as the steady state regime of the surface evolution provide us valuable information that can lead to better understanding the mechanisms of pattern formation. In addition, I will present the results of simulations of growth models such as linear Kuramoto- Sivashinsky (KS) and Kardar-Parisi-Zhang (KPZ) that have been carried out for comparing the temporal correlation functions of the scattered intensity with the new Co-GISAXS experiments.