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Based on integrating microscopic statistical mechanical theories for structure and ideal kinetic arrest at the naive mode coupling level, we study dynamic localization, the linear elastic shear modulus, applied stress induced modulus softening, and the absolute yielding of simple biphasic binary mixtures composed of equal diameter hard and attractive spheres. The kinetic arrest map is a rich function of total packing fraction, strength of attraction, and mixture composition. The gel to attractive ideal glass transition, the degree of glass melting re-entrancy, and the crossover boundary separating repulsive glasses from attractive glasses vary with the mixture composition. Exponential and/or apparent (high) power law dependences of the elastic shear modulus on the total packing fraction are predicted with effective exponents or exponential prefactors that are sensitive to mixture composition and location in the kinetic arrest map. An analysis of the effective mean square force on a tagged particle that induces dynamic localization reveals a compensation effect between structural correlations and degree of particle localization, resulting in the emergence of a weaker dependence of the shear modulus on mixture composition at very high attraction strengths. Based on a microrheologically inspired formulation of how external stress weakens particle localization and the shear modulus, we analyze mechanical-induced modulus softening and absolute yielding, defined as a discontinuous solid-to-fluid stress-induced transition that can occur in either one or two steps. Estimates of the corresponding yield strains predict that the binary mixture becomes more brittle with increasing sticky particle composition and/or attraction strength.
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A living cell is an active environment where the organization and dynamics of chromatin are affected by different forms of activity. Optical experiments report that loci show subdiffusive dynamics and the chromatin fiber is seen to be coherent over micrometer-scale regions. Using a bead-spring polymer chain with dipolar active forces, we study how the subdiffusive motion of the loci generate large-scale coherent motion of the chromatin. We show that in the presence of extensile (contractile) activity, the dynamics of the loci grows faster (slower) and the spatial correlation length increases (decreases) compared to the case with no dipolar forces. Hence, both the dipolar active forces modify the elasticity of the chain. Interestingly in our model, the dynamics and organization of such dipolar active chains largely differ from the passive chain with renormalized elasticity.
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To understand the dynamical and conformational properties of deformable active agents in porous media, we computationally investigate the dynamics of linear chains and rings made of active Brownian monomers. In porous media, flexible linear chains and rings always migrate smoothly and undergo activity-induced swelling. However, semiflexible linear chains though navigate smoothly, shrink at lower activities, followed by swelling at higher activities, while semiflexible rings exhibit a contrasting behavior. Semiflexible rings shrink, get trapped at lower activities, and escape at higher activities. This demonstrates how activity and topology interplay and control the structure and dynamics of linear chains and rings in porous media. We envision that our study will shed light on understanding the mode of transport of shape-changing active agents in porous media.
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Spontaneous persistent motions driven by active processes play a central role in maintaining living cells far from equilibrium. In the majority of research studies, the steady state dynamics of an active system has been described in terms of an effective temperature. By contrast, we have examined a prototype model for diffusion in an activity-induced rugged energy landscape to describe the slow dynamics of a tagged particle in a dense active environment. The expression for the mean escape time from the activity-induced rugged energy landscape holds only in the limit of low activity and the mean escape time from the rugged energy landscape increases with activity. The precise form of the active correlation will determine whether the mean escape time will depend on the persistence time or not. The activity-induced rugged energy landscape approach also allows an estimate of the non-equilibrium effective diffusivity characterizing the slow diffusive motion of the tagged particle due to activity. On the other hand, in a dilute environment, high activity augments the diffusion of the tagged particle. The enhanced diffusion can be attributed to an effective temperature higher than the ambient temperature and this is used to calculate the Kramers' mean escape time, which decreases with activity. Our results have direct relevance to recent experiments on tagged particle diffusion in condensed phases.
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We computationally investigate the dynamics of a self-propelled Janus probe in crowded environments. The crowding is caused by the presence of viscoelastic polymers or non-viscoelastic disconnected monomers. Our simulations show that the translational as well as rotational mean square displacements have a distinctive three-step growth for fixed values of self-propulsion force, and steadily increase with self-propulsion, irrespective of the nature of the crowder. On the other hand, in the absence of crowders, the rotational dynamics of the Janus probe is independent of self-propulsion force. On replacing the repulsive polymers with sticky ones, translational and rotational mean square displacements of the Janus probe show a sharp drop. Since different faces of a Janus particle interact differently with the environment, we show that the direction of self-propulsion also affects its dynamics. The ratio of long-time translational and rotational diffusivities of the self-propelled probe with a fixed self-propulsion, when plotted against the area fraction of the crowders, passes through a minimum and at higher area fraction merges to its value in the absence of the crowder. This points towards the decoupling of the translational and rotational dynamics of the self-propelled probe at an intermediate area fraction of the crowders. However, such translational-rotational decoupling is absent for passive probes.
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Fundamental understanding of the effect of microscopic parameters on the dynamics of probe particles in different complex environments has wide implications. Examples include diffusion of proteins in biological hydrogels, porous media, polymer matrix, etc. Here, we use extensive molecular dynamics simulations to investigate the dynamics of the probe particle in a polymer network on a diamond lattice, which provides substantial crowding to mimic the cellular environment. Our simulations show that the dynamics of the probe increasingly becomes restricted, non-Gaussian and subdiffusive on increasing the network rigidity, binding affinity and probe size. In addition, the velocity autocorrelation functions show negative dips owing to the viscoelasticity and caging due to the surrounding network. These observations go with the general experimental findings. Importantly, for a probe particle of size comparable to the mesh size, unrestricted motion engulfing large length scales has been observed. This happens with a more flexible polymer network, which is easily pushed by the bigger probe. On increasing the rigidity of the network, the bigger probe can not efficiently push the network and as a result the long tail disappears. Our study gives a general qualitative picture of the transport of probes in a gel-like medium, as encountered in different contexts.
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A prime example of a non-equilibrium or active environment is a biological cell. In order to understand in vivo functioning of biomolecules such as proteins and chromatins, a description beyond equilibrium is absolutely necessary. In this context, biomolecules have been modeled as Rouse chains in a Gaussian active bath. However, these non-equilibrium fluctuations in biological cells are non-Gaussian. This motivates us to take a Rouse chain subjected to a series of pulses of force with a finite duration, mimicking the run and tumble motion of a class of microorganisms. Thus by construction, this active force is non-Gaussian. Our analytical calculations show that the mean square displacement (MSD) of the center of mass grows faster and even shows superdiffusive behavior at higher activity. The MSD of a tagged monomer in an active bath also shows superdiffusion at an intermediate time unlike a monomer of a Rouse chain. In the case of a short chain length, reconfiguration is slower and the reconfiguration time of a chain with N monomers scales as Nσ, with σ ≈ 1.6 - 2. In addition, the chain swells. We compare this activity-induced swelling with that of a Rouse chain in a Gaussian active bath. In principle, our predictions can be verified by future single molecule experiments.
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Inspired by how the shape deformations in active organisms help them to migrate through disordered porous environments, we simulate active ring polymers in two-dimensional random porous media. Flexible and inextensible active ring polymers navigate smoothly through the disordered media. In contrast, semiflexible rings undergo transient trapping inside the pore space; the degree of trapping is inversely correlated with the increase in activity. We discover that flexible rings swell while inextensible and semiflexible rings monotonically shrink upon increasing the activity. Together, our findings identify the optimal migration of active ring polymers through porous media.