Catch bond kinetics are instrumental to cohesion of fire ant rafts under load.

Dynamic networks composed of constituents that break and reform bonds reversibly are ubiquitous in nature owing to their modular architectures that enable functions like energy dissipation, self-healing, and even activity. While bond breaking depends only on the current configuration of attachment in these networks, reattachment depends also on the proximity of constituents. Therefore, dynamic networks composed of macroscale constituents (not benefited by the secondary interactions cohering analogous networks composed of molecular-scale constituents) must rely on primary bonds for cohesion and self-repair. Toward understanding how such macroscale networks might adaptively achieve this, we explore the uniaxial tensile response of 2D rafts composed of interlinked fire ants (S. invicta). Through experiments and discrete numerical modeling, we find that ant rafts adaptively stabilize their bonded ant-to-ant interactions in response to tensile strains, indicating catch bond dynamics. Consequently, low-strain rates that should theoretically induce creep mechanics of these rafts instead induce elastic-like response. Our results suggest that this force-stabilization delays dissolution of the rafts and improves toughness. Nevertheless, above 35[Formula: see text] strain low cohesion and stress localization cause nucleation and growth of voids whose coalescence patterns result from force-stabilization. These voids mitigate structural repair until initial raft densities are restored and ants can reconnect across defects. However mechanical recovery of ant rafts during cyclic loading suggests that-even upon reinstatement of initial densities-ants exhibit slower repair kinetics if they were recently loaded at faster strain rates. These results exemplify fire ants' status as active agents capable of memory-driven, stimuli-response for potential inspiration of adaptive structural materials.

Programming Motion into Materials Using Electricity-Driven Liquid Crystal Elastomer Actuators.

As thermally driven smart materials capable of large reversible deformations, liquid crystal elastomers (LCEs) have great potential for applications in bionic soft robots, artificial muscles, controllable actuators, and flexible sensors due to their ability to program controllable motion into materials. In this article, we introduce conductive LCE actuators using a liquid metal electrothermal layer and a polyethylene terephthalate substrate. Our LCE actuators can be stimulated at low currents from 2 to 4 A and produce a maximum work density of 9.4 kJ∕m3. We illustrate the potential applications of this system by designing a palm-activated artificial muscle gripper, which can be used to grasp soft objects ranging from 5 to 55 mm in size, and even ring-shaped workpieces with precise external or internal support. Furthermore, inspired by the movement of fruit fly larvae, we designed a new soft robot capable of bioinspired crawling and turning by inducing anisotropic friction with an asymmetric design. Finally, we illustrate advanced motional control by designing an autonomously rotating wheel based on the asymmetric contraction of its spokes. To assist in the production of autonomously moving robots, we provide a thorough characterization of its motion dynamics.

Micromechanics and damage in slide-ring networks.

We explore the mechanics and damage of slide-ring gels by developing a discrete model for the mechanics of chain-ring polymer systems that accounts for both crosslink motion and internal chain sliding. The proposed framework utilizes an extendable Langevin chain model to describe the constitutive behavior of polymer chains undergoing large deformation and includes a rupture criterion to innately capture damage. Similarly, crosslinked rings are described as large molecules that also store enthalpic energy during deformation and thus have their own rupture criterion. Using this formalism, we show that the realized mode of damage in a slide-ring unit is a function of the loading rate, distribution of segments, and inclusion ratio (number of rings per chain). After analyzing an ensemble of representative units under different loading conditions, we find that failure is driven by damage to crosslinked rings at slow loading rates, but polymer chain scission at fast loading rates. Our results indicate that increasing the strength of the crosslinked rings may improve the toughness of the material.

Nonlinear Viscoelasticity and Toughening Mechanisms in Nanoclay-PNIPAAm Double Network Hydrogels.

We investigate the mechanical properties of a magnetic temperature-sensitive hydrogel at varying concentrations of covalent and physical cross-linking. The hydrogel consists of covalently cross-linked poly(N-isopropylacrylamide) (PNIPAAm), physically interacting nanoclay particles, and magnetic ferric oxide nanoparticles. The physical nanoclay network exhibits strong viscoplastic behavior, and we find that increasing nanoclay content improves both strength and toughness in the double network materials. We investigate the behavior of the gels using a nonlinear viscoplasticity model with a modified rule of mixtures approach and attribute the observed trends to two factors: (a) the yield-stress behavior of the nanoclay network and (b) load-sharing interactions between the PNIPAAm and the nanoclay. Our findings indicate a strong correlation between the mass ratio of covalent cross-linker used and fractional percolation of the PNIPAAm network.

Profiling oocytes with neural networks from images and mechanical data.

The success rate of assisted reproductive technologies could be greatly improved by selectively choosing egg cells (oocytes) with the greatest chance of fertilization. The goal of mechanical profiling is, thus, to improve predictive oocyte selection by isolating the mechanical properties of oocytes and correlating them to their reproductive potential. The restrictions on experimental platforms, however - including minimal invasiveness and practicality in laboratory implementation - greatly limits the data that can be acquired from a single oocyte. In this study, we perform indentation studies on human oocytes and characterize the mechanical properties of the zona pellucida, the outer layer of the oocyte. We obtain excellent fitting with our physical model when indenting with a flat surface and clearly illustrate localized shear-thinning behavior of the zona pellucida, which has not been previously reported. We conclude by outlining a promising methodology for isolating the mechanical properties of the cytoplasm using neural networks and optical images taken during indentation.