Prof Ramin Golestanian

Abstract:

Interactions between active particles may be non-reciprocal, breaking action-reaction symmetry and leading to novel physics not observed in equilibrium systems. The non-reciprocal Cahn–Hilliard (NRCH) model is a phenomenological model that captures the large-scale effects of non-reciprocity in conserved, phase-separating systems. In this work, we explore the consequences of different variations of this model corresponding to different symmetries, inspired by the importance of symmetry in equilibrium universality classes. In particular, we contrast two models, one with a continuous SO(2) symmetry and one with a discrete C4 symmetry. We analyze the corresponding models by constructing three-dimensional linear stability diagrams. With this, we connect the models with their equilibrium limits, highlight the role of mean composition, and classify qualitatively different instabilities. We further demonstrate how non-reciprocity gives rise to out-of-equilibrium steady states with non-zero currents and present representative closed-form solutions that help us understand characteristic features of the models in different parts of the parameter space.

Abstract:

The study of active solids offers a window into the mechanics and thermodynamics of dense living matter. A key aspect of the nonequilibrium dynamics of such active systems is a mechanistic description of how the underlying mechanochemical couplings arise, which cannot be resolved in models that are phenomenologically constructed. Here, we follow a bottom-up theoretical approach to develop a thermodynamically consistent active solid model and uncover a nontrivial crosstalk that naturally ensues between mechanical response and dissipation. In particular, we show that dissipation reaches a maximum at finite stresses, while it is inhibited under large stresses, effectively reverting the system to a passive state. Our findings establish a generic mechanism plausibly responsible for the nonmonotonic behavior observed in recent experimental measurements of entropy production rate in an actomyosin material and enzymatic activity in crowded condensates.

Abstract:

We derive effective equations of motion governing the dynamics of sharp interfaces in phase-separated binary mixtures driven by spatio-temporal modulations of their material properties. We demonstrate, in particular, that spatial heterogeneities in the surface tension induce an effective capillary force that drives the motion of interfaces, even in the absence of hydrodynamics. Applying our sharp interface model to quantify the dynamics of thermophoretic droplets, we find that their deformation and transport properties are controlled by a combination of bulk and capillary forces, whose relative strength depends on droplet size. Strikingly, we show that small thermophobic droplets - composed of a material with a positive Soret coefficient - can spontaneously migrate towards high-temperature regions as a result of capillary forces.

Abstract:

Most living things on Earth - from bacteria to humans - must migrate in some way to find favourable conditions. Therefore, they nearly all use chemotaxis, in which their movement is steered by a gradient of chemicals. Chemotaxis is fundamental to many processes that control our well-being, including inflammation, neuronal patterning, wound healing, tumour spread in cancer, even embryogenesis. Understanding it is a key goal for biologists. Despite the fact that many basic principles appear to have been conserved throughout evolution, most research has focused on understanding the molecular mechanisms that control signal processing and locomotion. Cell signaling - cells responding to time-varying external signals - underlies almost all biological processes at the cellular scale. Chemotaxis of single cells provides particularly amenable model systems for quantitative cell signaling studies, even in the presence of noise and fluctuations, because the output, the cell's motility response, is directly observable. However, the different scientific disciplines involved in chemotaxis research rarely overlap, so biologists, physicists and mathematicians interact far too infrequently, methodologies and models differ and commonalities are often overlooked, such as the possible influence of physical or environmental conditions, which has been largely neglected.

Abstract:

Multifarious assembly models consider multiple structures assembled from a shared set of components, reflecting the efficient usage of components in biological self-assembly. These models are subject to a high-dimensional parameter space, with only a finite region of parameter space giving reliable self-assembly. Here, we use a continuous-time Gillespie simulation method to study multifarious self-assembly and find that the region of parameter space in which reliable self-assembly can be achieved is smaller than what was obtained previously using a discrete-time Monte Carlo simulation method. We explain this discrepancy through a detailed analysis of the stability of assembled structures against chimera formation. We find that our continuous-time simulations of multifarious self-assembly can expose this instability in large systems even at moderate simulation times. In contrast, discrete-time simulations are slow to show this instability, particularly for large system sizes. For the remaining state space, we find good agreement between the predictions of continuous- and discrete-time simulations. We present physical arguments that can help us predict the state boundaries in the parameter space and gain a deeper understanding of multifarious self-assembly.