Computational Investigations of Self-assembly Under Time-oscillatory Interaction Potentials.

In this project, Professor Kateri DuBay of the University of Virginia will lead a team to employ computational simulations in order to determine how nano-scale materials assemble themselves when the interactions between them are changing in time. The results will illuminate the physics underlying the assembly of ordered biological structures that form within the highly variable environments of living cells and tissues, while also providing new routes towards the synthetic manufacture of advanced materials. These novel assembly processes have the potential to improve the efficient manufacture of existing materials and to enable the fabrication of previously inaccessible ordered nanomaterials, two central aims of advanced manufacturing initiatives. The ability to better control assembly will provide the basis for countless applications in energy production and storage, water purification, drug delivery, as well as the construction of novel materials with quantum and photonic properties. This project will also train the next generation of research scientists in materials science, data science, and molecular and coarse-grained simulations, while emphasizing the importance of the responsible conduct of research. This project will generate new and essential insights into complex assembly pathways by investigating the effects of different time-dependent protocols on nano-scale assembly. Specifically, the team will investigate the self-organization of model viral-like capsids and polymeric materials under temporally and spatially varying interaction potentials. Using computational simulations coupled with analytical calculations, the team will determine the types of potential oscillations, fluctuations, and interaction gradients that are able to yield novel and currently inaccessible stable and steady-state nanoscale structures. Learning more about the roles played by energy dissipation, stochastic fluctuations, and topological and spatial features in determining dynamic assembling pathways will yield design rules to guide assembly protocols within systems containing both temporal and spatial variations, thereby enabling and improving the manufacture of advanced ordered materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.