2023/03/31 Chia-Hao Lee's PhD Defense @ UIUC Supercon 2008 Advisor: Prof. Pinshane Huang Committee: Prof. Pinshane Huang, Prof. Jian-Min Zuo, Prof. Andre Schleife, Prof. Vidya Madhavan Youtube recording: https://youtu.be/oJhY6ZOJabo Personal website: https://sites.google.com/view/chiahao-lee Research Summary: My research explores the use of advanced microscopy techniques and machine learning algorithms to understand the heterogeneities of two-dimensional (2D) materials. While 2D materials exhibit a wide range of unique properties that make them ideal candidates for various applications, including flexible electronics, energy conversion, and catalysis, their properties can vary significantly due to their heterogeneity, which arises from the presence of defects, grain boundaries, and other structural imperfections. I combined the class-averaging technique with deep learning models for defect identification to generate high signal-to-noise images of single-atom defects. These images provide the 1st direct observation of oscillating strain fields around a single atom vacancy with sub-pm precision. Additionally, I co-developed an AI-in-the-loop framework that combines a cycle generative adversarial network with automatic acquisition and image simulation. This framework generates high quality training data that greatly enhances the generalizability of machine learning applications. Furthermore, I explored the anisotropic phase transition kinetics of few-layer MoTe2, a promising phase-change material, using in situ heating, dark-field TEM, and aberration-corrected STEM. Most recently, I applied electron ptychography on 2D materials and obtained unprecedented details about their local lattice distortion and rippling with 0.4 Å resolution, greatly surpassing the conventional approaches. In summary, my research demonstrates a combination of new S/TEM techniques with machine learning, enabling atom-by-atom characterization of heterogeneities of 2D materials including phase boundaries, strain, point defects, and local rippling with high precision. Overall, these techniques pave the way for the development of reliable and efficient 2D electronics, making significant contributions to the field of nanotechnology.