UC Irvine

In situ transmission electron microscopy enables the study of nanoscale solution state events such as battery electrode deposition and molecular self-assembly. Recent improvements in electron microscope detectors have vastly improved the spatial resolution (pixel count) and temporal resolution (frame rate) of microscopy videos, which has resulted in large, information-rich datasets. The central mission of my PhD has been to use image analysis techniques and algorithms to translate improvements in microscopy signal collection to improvements in materials insight. Towards this, I have developed several novel image analysis algorithms built on deterministic image science methods which extract quantitative information from raw microscopy datasets. I developed an algorithm to quantify materials dynamics captured with in situ microscopy videos and applied this algorithm to quantify the spatiotemporal dynamics of dissipative self-assembly processes (Chapters 1-2). I applied image science to track the presence of an unstable phase captured in time-resolved cryogenic transmission electron microscopy (Chapter 3). And finally, I applied a variety of custom image analysis algorithms to quantify amphiphilic block copolymer morphological transitions such as vesical-to-bilayer transitions, droplet-to-bilayer transitions, and droplet dissolution dynamics (Chapters 4-5). In each case, I demonstrate the power of deterministic image analysis methods for converting raw microscopy datasets into interpretable materials science results.