Publications

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.

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.

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, oscillations 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.

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.

The phase behavior and material properties of copolymers are intrinsically dependent on their primary comonomer sequences. Achieving precise control over monomer sequence in synthetic copolymerizations is challenging, as sequence determination is influenced not only by the reaction conditions and the properties of the reactants but also by the statistical nature of the copolymerization process itself. Mayo–Lewis reactivity ratios are often used to predict copolymer composition and sequence and are based on ratios of static reactivity constants. However, prior results have demonstrated that in a generic, solution-based step-growth A,B-copolymerization, relatively weak non-bonded attractions between certain monomer pairs induce emergent microphase separations. Such polymerization-driven separations lead to deviations from standard kinetics due to the emergent heterogeneities in reactant concentrations, which can also cause significant shifts in the resulting copolymer sequences. Previously, these effects were observed in systems where the activation energies were equal for all reaction pathways, that is, between all monomer pair combinations. In this work, we explore the combined effects on copolymerization kinetics of differences in both activation energies and non-bonded attractions between monomers and examine the sequences produced within this same step-growth copolymerization model. Our results indicate that altering activation energies influences the kinetics and sequences in a manner that also depends on the non-bonded attractions, showing that these effects may work in concert or in opposition to one another to bias the sequences formed. Non-standard kinetic behaviors and long-range sequence biasing are observed under certain conditions, and the extent of each clearly shifts as the reaction proceeds. These findings provide insight into the complex interplay between sequence and nascent oligomer phase behavior, highlighting the potential for exploiting emergent phase properties in the informed design of advanced sequence-biased materials.

Advanced carbon microelectrodes, including many carbon-nanotube (CNT)-based electrodes, are being developed for the in vivo detection of neurotransmitters such as dopamine (DA). Our prior simulations of DA and dopamine-o-quinone (DOQ) on pristine, flat graphene showed rapid surface diffusion for all adsorbed species, but it is not known how CNT surfaces affect dopamine adsorption and surface diffusivity. In this work, we use molecular dynamics simulations to investigate the adsorbed structures and surface diffusion dynamics of DA and DOQ on CNTs of varying curvature and helicity. In addition, we study DA dynamics in a groove between two aligned CNTs to model the spatial constraints at the junctions within CNT assemblies. We find that the adsorbate diffusion on a solvated CNT surface depends upon curvature. However, this effect cannot be attributed to changes in the surface energy roughness because the lateral distributions of the molecular adsorbates are similar across curvatures, diffusivities on zigzag and armchair CNTs are indistinguishable, and the curvature dependence disappears in the absence of solvent. Instead, adsorbate diffusivities correlate with the vertical placement of the adsorbate’s moieties, its tilt angle, its orientation along the CNT axis, and the number of waters in its first hydration shell, all of which will influence its effective hydrodynamic radius. Finally, DA diffuses into and remains in the groove between a pair of aligned and solvated CNTs, enhancing diffusivity along the CNT axis. These first studies of surface diffusion on a CNT electrode surface are important for understanding the changes in diffusion dynamics of dopamine on nanostructured carbon electrode surfaces.

Carbon microelectrodes enable in vivo detection of neurotransmitters, and new electrodes aim to optimize the carbon surface. However, atomistic detail on the diffusion and orientation of neurotransmitters near these surfaces is lacking. Here, we employ molecular dynamics simulations to investigate the surface diffusion of dopamine (DA), its oxidation product dopamine-o-quinone (DOQ), and their protonated forms on the pristine basal plane of flat graphene. We find that all DA species rapidly adsorb to the surface and remain adsorbed, even without a holding potential or graphene surface defects. We also find that the diffusivities of the adsorbed and the fully solvated DA are similar and that the protonated species diffuse more slowly on the surface than their corresponding neutral forms, while the oxidized species diffuse more rapidly. Structurally, we find that the underlying graphene lattice has little influence over the molecular adsorbate's lateral position, and the vertical placement of the amine group on dopamine is highly dependent upon its charge. Finally, we find that solvation has a large effect on surface diffusivities. These first results from molecular dynamics simulations of dopamine at the aqueous-graphene interface show that dopamine diffuses rapidly on the surface, even without an applied potential, and provide a basis for future simulations of neurotransmitter structure and dynamics on advanced carbon materials electrodes.

Sequence control in synthetic copolymers remains a tantalizing objective in polymer science due to the influence of sequence on material properties and self-organization. A greater understanding of sequence development throughout the polymerization process will aid the design of simple, generalizable methods to control sequence and tune supramolecular assembly. In previous simulations of solution-based step-growth copolymerizations, we have shown that weak, non-bonding attractions between monomers of the same type can produce a microphase separation among the lengthening nascent oligomers and thereby alter sequence. This work explores the phenomenon further, examining how effective attractive interactions, mediated by a solvent selective for one of the reacting species, impact the development of sequence and the supramolecular assembly in a simple A–B copolymerization. We find that as the effective attractions between monomers increase, an emergent self-organization of the reactants causes a shift in reaction kinetics and sequence development. When the solvent-mediated interactions are selective enough, the simple mixture of A and B monomers oligomerize and self-assemble into structures characteristic of amphiphilic copolymers. The composition and morphology of these structures and the sequences of their chains are sensitive to the relative balance of affinities between the comonomer species. Our results demonstrate the impact of differing A–B monomer–solvent affinities on sequence development in solution-based copolymerizations and are of consequence to the informed design of synthetic methods for sequence controlled amphiphilic copolymers and their aggregates.

Synthetic copolymer sequences remain challenging to control, and there are features of even simple one-pot, solution-based copolymerizations that are not yet fully understood. In previous simulations on step-growth copolymerizations in solution, we demonstrated that modest variations in the attractions between type A and B monomers could significantly influence copolymer sequence through an emergent aggregation and phase separation initiated by the lengthening of nascent oligomers. Here we investigate how one aspect of a copolymer’s geometry─its flexibility─can modulate those effects. Our simulations show the onset of strand alignment within the polymerization-induced aggregates as chain stiffness increases and demonstrate that this alignment can influence the resulting copolymer sequences. For less flexible copolymers, with persistence lengths ≥10 monomers, modest nonbonded attractions of ∼k_BT between monomers of the same type yield A and B blocks of a characteristic length and result in a polydispersity index that grows rapidly, peaks, and then diminishes as the reaction proceeds. These results demonstrate that for copolymer systems with modest variations in intermonomer attractions and physically realistic flexibilities a nascent copolymer’s persistence length can influence its own sequence.

In the outer membrane of Gram-negative bacteria, membrane proteins are thought to be organized into domains or islands that play a role in the segregation, movement, and turnover of membrane components. However, there is presently limited information on the structure of these domains or the molecular interactions that mediate domain formation. In the present work, the Escherichia coli outer membrane vitamin B₁₂ transporter, BtuB, was spin-labeled, and double electron–electron resonance was used to measure the distances between proteins in intact cells. These data together with Monte Carlo simulations provide evidence for the presence of specific intermolecular contacts between BtuB monomers that could drive the formation of string-like oligomers. Moreover, the EPR data provide evidence for the location of the interacting interfaces and indicate that lipopolysaccharide mediates the contacts between BtuB monomers.