Emma Vargo was awarded the 2022-2023 Kavli Thesis Prize. Nominations were reviewed based on the quality of the work, publication status, strength of supporting letters, and relevance of the thesis to the Kavli ENSI mission. The award provides a $2,000 stipend.
Emma received her BS in Materials Science and Engineering from MIT in 2018, and her PhD from UC Berkeley in May 2023, under the guidance of Professor Ting Xu. Her graduate research focused on self-assembly of polymers, small molecules, and nanoparticles for applications in packaging, optical devices, and energy storage. Currently, Emma is a postdoc at the Center for High Precision Patterning Science. As a postdoc, she’s exploring polymer self-assembly as a way to correct errors in microelectronic device fabrication. Emma was originally drawn to research self-assembly because of its many parallels to biology, where amazingly complicated structures are encoded into relatively simple building blocks. Outside of the lab, Emma enjoys knitting, sewing, baking, and watching her plants self-assemble new leaves.
A short summary of her thesis is below:
Translating the Advantages of Biology to Synthetic Self-Assembled Nanocomposites
Ordered structures spanning multiple length scales can produce exceptional mechanics, as found in spider silk, and beautiful optics, as seen in the photonic wings of many birds and insects. While human-engineered materials will likely never match the diversity and complexity of natural materials, similar hierarchies of hard and soft domains have been achieved using a self-assembling polymer nanocomposite system. The system is a blend of block copolymer-based supramolecules, organic small molecules, and inorganic nanoparticles. In this dissertation, different compositions and processing conditions are used to produce a variety of functional nanocomposites: barrier coatings, dielectric breakdown materials, and optical devices. More broadly, this work describes the complexity and self-regulation that emerge from blends of dissimilar building blocks. The key insight of this dissertation is a new hierarchical self-assembly approach. Unlike traditional methods, which rely on condensation or precipitation, the system forms a coarse microscopic framework at low concentrations. This allows for fast diffusion and negligible enthalpy, enabling supramolecules, small molecules, and nanoparticles to be organized into stacks of parallel layers with thicknesses of 127 nm. The self-assembly mechanism is explored using neutron scattering, X-ray photon correlation spectroscopy, and computational image analysis of electron micrographs. The multilayer coatings exhibited excellent mechanical stability, structural color, dielectric breakdown strengths, and vapor barrier properties for water and volatile organic compounds. Performance analyses revealed a convoluted relationship between blend formulation, processing, morphology, and properties. Overall, this approach offers a promising strategy for producing functional materials through entropy-driven assembly.