Abstract:

I will discuss my group’s recent progress on adapting a suite of electron microscopy methods (e.g., liquid-phase TEM, electron tomography, 4D-STEM) and machine-learning based data-mining to synthetic soft, biological, and energy related systems. In the first direction, we focus on the phase behaviors of nano-sized building units as they are dispersed in solution. As a proof-of-concept, we directly image the crystallization pathways of nanosized colloids into superlattices, where the discreteness and multi-scale coupling effects complicate the free energy landscape. Single particle tracking and simulations combined unravel a series of interesting pathways at this length scale, such as non-classical crystallization, size-dependent crystal growth habits of superlattices, and moiré patterning, enabling advanced crystal engineering. In the second direction, we study membrane proteins in their native lipid and liquid environment at the nanometer resolution. The proteins exhibit real-time “fingering” fluctuations, which we attribute to dynamic rearrangement of lipid molecules wrapping the proteins. The conformational coordinates of protein transformation obtained from the movies are used as inputs in our molecular dynamics simulations, to verify the driving force underpinning the function-relevant fluctuation. In the third direction, we further push direct imaging to separation membranes and multivalent ion batteries, where the strain embedded heterogeneously within leads to morphogenesis and distinct charge transport properties. We foresee our suite of “electron videography” tools to provide crucial and complementary insights in various materials systems, with the common theme of imaging and manipulating materials in space and time at the nanoscale.