Aggregated polymer fillers, such as carbon black and silica, at concentrations above the percolation threshold form an emergent structure, the hierarchical filler network, in immiscible systems where dispersion is driven by accumulated strain. It is proposed that the hierarchical filler network is composed of a primary nanoscale network that locally percolates at ∼5 vol % of aggregates, associated with changes in the dynamic spectrum at low strain, and a secondary micrometer-scale network that globally percolates at ∼20 vol % associated with the Payne effect and electrical conductivity. A model is proposed with an elastomer dominated dynamic response described by Einstein–Smallwood behavior at high frequencies and small sizes and a filler network dominated response at low frequencies and large sizes. The nanoscale mesh size correlates with this transition in low strain dynamic response. The micrometer-scale network displays a gel-like dynamic response at very low frequencies and a corresponding gel-like structural scaling regime at large sizes. The hierarchical filler network is described by two crossover frequencies and associated relaxation times, τ* and τcc, and two related structural scaling regimes.

The dispersion of nanoparticles in viscous polymers is dictated by kinetics, interaction potentials between particles, and interfacial compatibility between the matrix and dispersed phases. It was previously proposed that an analogy can be made between thermally dispersed colloids and kinetically dispersed nanoparticles in viscous media when weak interactions exist between particles allowing for a mean-field description under the Ginzburg criterion such as for carbon black dispersed in polybutadiene elastomer. For these cases, the second virial coefficient can be used to quantify the quality of dispersion; additionally, the nanoscale network mesh size can be calculated, which is related to dynamic properties. However, this approach fails for nanoparticles with surface charges or other specific interactions that lead to correlations. Here, these correlated systems are investigated in the context of the mean-field systems in order to gain a comparative description of dispersion using the network mesh size and a derived virial coefficient. The physical origin of the structural parameters from the proposed model for these correlated systems is investigated.

No abstract

Advances in fabrication methods have positioned Janus micromotors (JMs) as candidates for use as autonomous devices in applications across diverse fields, spanning drug delivery to environmental remediation. While the design of most micromotors is straightforward, the non‐steady state active motion exhibited by these systems is complex and difficult to characterize. Traditionally, JM active motion is characterized using optical microscopy single particle tracking for systems confined in 2D. Dynamic light scattering (DLS) offers an alternative high‐throughput method for characterizing the 3D active motion in bulk JM dispersions with additional capabilities to quantify time‐dependent behavior for a broader range of JM sizes. Here, the active motion of spherical JMs is examined by DLS and it is demonstrated that the method enables decoupling of the translational and rotational diffusion. Systematic studies quantifying the time‐dependent diffusive properties as a function of fuel concentration, JM concentration, and time after fuel addition are presented. The analyses presented in this work position DLS to facilitate future advances of JM systems by serving as a fast‐screening characterization method for active motion.

No abstract