Modeling and analysis of nanoscale surface patterns produced by broad beam ion bombardment
Date
2020
Authors
Loew, Kevin M., author
Bradley, R. Mark, advisor
Gelfand, Martin, committee member
Shipman, Patrick, committee member
Wu, Mingzhong, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
When a solid surface is exposed to broad beam ion bombardment, nanoscale patterns may spontaneously form. This physical phenomenon is of interest to both the academic and nanofabrication communities. Ion bombardment has the potential to provide a cost-efficient method of producing nanoscale patterns over a large area. As such, it has gathered substantial interest and has been the focus of numerous studies, both experimental and theoretical. However, despite more than half a century of study, there are still many unknowns which limit the application of this method to fabrication. In this dissertation, I present contributions to the field of ion bombarded surfaces (IBS). The first is the development of a Python module which facilitates the rapid production and analysis of simulations. This module provides a well-documented tool to allow collaborators to numerically integrate a user-defined partial differential equation, specifically with IBS in mind. Second is a study of dispersive effects on IBS. Dispersion can lead to the formation of raised and depressed triangular regions traversed by parallel-mode ripples, highly ordered parallel-mode ripples, protrusions and depressions that are elongated along the projected beam direction even when there is no transverse instability, and needle-like protrusions that are visually similar to structures observed in experimental studies. Finally, we applied deep learning techniques to estimate the parameters in the underlying equation of motion from an image of a surface exposed to broad beam ion bombardment at a particular fluence. Our trained neural network will allow experimentalists to quickly ascertain the parameters for a given sputtering experiment.