Dubay Group

Research in the DuBay Group is organized around one central question: How do complex environments and collective behaviors influence self-organization at the nanoscale? This question is key to understanding phenomena as varied as mitotic spindle formation in the cell, polymer microphase separations, snowflake variability, and flocking patterns among active nanomaterials. Using advanced tools of computational modeling, we seek to understand the interplay between entropy, enthalpy, and kinetics within such complex, often non-equilibrium, systems.

Recent Publications

Niblo, J. K.; Swartley, J. R.; Zhang, Z.; DuBay, K. H. 2D capsid formation within an oscillatory energy landscape: orderly self-assembly depends on the interplay between a dynamic potential and intrinsic relaxation times. Soft Matter 2024.

Cover Feature

Multiple dissipative self-assembly protocols designed to create novel structures or to reduce kinetic traps have recently emerged. Specifically, temporal oscillations of particle interactions have been shown effective at both aims, but investigations thus far have focused on systems of simple colloids or their binary mixtures. In this work, we expand our understanding of the effect of temporally oscillating interactions to a two-dimensional coarse-grained viral capsid-like model that undergoes a self-limited assembly. This model includes multiple intrinsic relaxation times due to the internal structure of the capsid subunits and, under certain interaction regimes, proceeds via a two-step nucleation mechanism. We find that oscillations much faster than the local intrinsic relaxation times can be described via a time averaged inter-particle potential across a wide range of interaction strengths, while oscillations much slower than these relaxation times result in structures that adapt to the attraction strength of the current half-cycle. Interestingly, oscillation periods similar to these relaxation times shift the interaction window over which orderly assembly occurs by enabling error correction during the half-cycles with weaker attractions. Our results provide fundamental insights to non-equilibrium self-assembly on temporally variant energy landscapes.

Github Repository, DOI: 10.1039
Hamblin, R. L.; Zhang, Z.; DuBay, K. H. Characteristic System Timescales Can Influence the Collective Sequence Development of Nematically Ordered Copolymers.. Macromolecules 2024.

Publisher's Version

The sequence of copolymers is of significant importance to their material properties, yet controlling copolymer sequence remains a challenge. Previously, we have shown that polymer chains with sufficient stiffness and intermolecular attractions can undergo an emergent, polymerization-driven nematic alignment of nascent oligomers during a step-growth polymerization process. Both the extent of alignment and the point in the reaction at which it occurs impacts the kinetics and the sequence development of the growing polymer. Of particular interest is the emergence of a characteristic block length in the ensemble of sequences, resulting in unusually peaked block length distributions. Here we explore the emergence of this characteristic block length in time and investigate how changes in activation energy, solution viscosity, and monomer density influence the sequence and block length distributions of stiff copolymers undergoing step-growth polymerization. We find that emergent aggregation and nematic ordering restricts the availability of longer chains to form bonds, thereby altering the propensity of chains to react in a length dependent fashion, which changes as the reaction progresses, and promoting the formation of chains and blocks of a characteristic length. Further, we demonstrate that the characteristic length scale which emerges is sensitive to the relative timescales of reaction kinetics and reactant diffusion, shifting in response to changes in the activation energy of the reaction and the viscosity of the solvent. Our observations suggest the potential for biasing characteristic lengths of sequence repeats in stiff and semi-flexible copolymer systems by targeting specific non-bonded interactions and reaction kinetics through the informed adjustment of reaction conditions and the selection or chemical modification of monomer species.

Github Repository, DOI: 10.26434
Bowman, G. R.; Cox, S. J.; Dellago, C.; DuBay, K. H.; Eaves, J. D.; Fletcher, D. A.; Frechette, L. B.; unwald, M. G.; Klymko, K.; Ku, J.; et al. Remembering the Work of Phillip L. Geissler: A Coda to His Scientific Trajectory. Annual Review of Physical Chemistry 2023, 74, 1-27.

Phillip L. Geissler made important contributions to the statistical mechanics of biological polymers, heterogeneous materials, and chemical dynamics in aqueous environments. He devised analytical and computational methods that revealed the underlying organization of complex systems at the frontiers of biology, chemistry, and materials science. In this retrospective we celebrate his work at these frontiers.

DuBay Group

Department of Chemistry

University of Virginia