| Abstract Scope |
This project examines growth kinetics during thin film deposition by pairing the analysis technique reflection high energy electron diffraction (RHEED) with machine learning. The first phase of this project underlines the necessary descriptors within RHEED videos to distinguish crystals of varying growth mode while the second phase utilizes this descriptor in order to understand how the kinetics of growth for several materials compare. RHEED videos were broken into frames so that the length, width, and intensity of the diffraction patterns could be analyzed over time via a self-made R program. In the first phase of the research a support vector machine model classified SrRuO3 samples by growth condition using the descriptor of RHEED spot length with time. In the second phase, materials LiLaTiO3, SrTiO3, LiNdTiO3, and LaAlO3 were added and compared via unsupervised learning to better understand the relationship between their growth modes. |