UCLA

Fluctuation-induced interactions are an important organizing principle in a variety of soft matter systems. In this dissertation, I explore the role of both thermal and active fluctuations within cross-linked polymer networks. The systems I study are in large part inspired by the amazing physics found within the cytoskeleton of eukaryotic cells. I first predict and verify the existence of a thermal Casimir force between cross-linkers bound to a semi-flexible polymer. The calculation is complicated by the appearance of second order derivatives in the bending Hamiltonian for such polymers, which requires a careful evaluation of the the path integral formulation of the partition function in order to arrive at the physically correct continuum limit and properly address ultraviolet divergences. I find that cross linkers interact along a filament with an attractive logarithmic potential proportional to thermal energy. The proportionality constant depends on whether and how the cross linkers constrain the relative angle between the two filaments to which they are bound.

The interaction has important implications for the synthesis of biopolymer bundles within cells. I model the cross-linkers as existing in two phases: bound to the bundle and free in solution. When the cross-linkers are bound, they behave as a one-dimensional gas of particles interacting with the Casimir force, while the free phase is a simple ideal gas. Demanding equilibrium between the two phases, I find a discontinuous transition between a sparsely and a densely bound bundle. This discontinuous condensation transition induced by the long-ranged nature of the Casimir interaction allows for a similarly abrupt structural transition in semiflexible filament networks between a low cross linker density isotropic phase and a higher cross link density bundle network. This work is supported by the results of finite element Brownian dynamics simulations of semiflexible filaments and transient cross-linkers. I speculate that cells take advantage of this equilibrium effect by tuning near the transition point, where small changes in free cross-linker density will affect large structural rearrangements between free filament networks and networks of bundles.

Cells are naturally found far from equilibrium, where the active influx of energy from ATP consumption controls the dynamics. Motor proteins actively generate forces within biopolymer networks, and one may ask how these differ from the random stresses characteristic of equilibrium fluctuations. Besides the trivial observation that the magnitude is independent of temperature, I find that the processive nature of the motors creates a temporally correlated, or colored, noise spectrum. I model the network with a nonlinear scalar elastic theory in the presence of active driving, and study the long distance and large scale properties of the system with renormalization group techniques. I find that there is a new critical point associated with diverging correlation time, and that the colored noise produces novel frequency dependence in the renormalized transport coefficients.

Finally, I study marginally elastic solids which have vanishing shear modulus due to the presence of soft modes, modes with zero deformation cost. Although network coordination is a useful metric for determining the mechanical response of random spring networks in mechanical equilibrium, it is insufficient for describing networks under external stress. In particular, under-constrained networks which are fluid-like at zero load will dynamically stiffen at a critical strain, as observed in numerical simulations and experimentally in many biopolymer networks. Drawing upon analogies to the stress induced unjamming of emulsions, I develop a kinetic theory to explain the rigidity transition in spring and filament networks. Describing the dynamic evolution of non-affine deformation via a simple mechanistic picture, I recover the emergent nonlinear strain-stiffening behavior and compare this behavior to the yield stress flow seen in soft glassy fluids. I extend this theory to account for coordination number inhomogeneities and predict a breakdown of universal scaling near the critical point at sufficiently high disorder, and discuss the utility for this type of model in describing biopolymer networks.