Artificial muscles are indispensable components for next-generation robotics capable of mimicking sophisticated movements of living systems. However, an optimal combination of actuation parameters, including strain, stress, energy density and high mechanical strength, is required for their practical applications. Here we report mammalian-skeletal-muscle-inspired single fibres and bundles with large and strong contractive actuation. The use of exfoliated graphene fillers within a uniaxial liquid crystalline matrix enables photothermal actuation with large work capacity and rapid response. Moreover, the reversible percolation of graphene fillers induced by the thermodynamic conformational transition of mesoscale structures can be in situ monitored by electrical switching. Such a dynamic percolation behaviour effectively strengthens the mechanical properties of the actuator fibres, particularly in the contracted actuation state, enabling mammalian-muscle-like reliable reversible actuation. Taking advantage of a mechanically compliant fibre structure, smart actuators are readily integrated into strong bundles as well as high-power soft robotics with light-driven remote control.

Mobile defects in solid-state materials play a significant role in memristive switching and energy-efficient neuromorphic computation. Techniques for confining and manipulating point defects may have great promise for low-dimensional memories. Here, we report the spontaneous gathering of oxygen vacancies at strain-relaxed crack walls in SrTiO 3 thin films grown on DyScO 3 substrates as a result of flexoelectricity. We found that electronic conductance at the crack walls was enhanced compared to the crack-free region, by a factor of 10 4 . A switchable asymmetric diode-like feature was also observed, and the mechanism is discussed, based on the electrical migration of oxygen vacancy donors in the background of Sr-deficient acceptors forming n + −n or n−n + junctions. By tracing the temporal relaxations of surface potential and lattice expansion of a formed region, we determine the diffusivity of mobile defects in crack walls to be 1.4 × 10 −16 cm 2 /s, which is consistent with oxygen vacancy kinetics.

Closing gaps in cellular monolayers is a fundamental aspect of both morphogenesis and wound healing. This closure can be achieved through leader cell crawling or actomyosin-based contraction, depending on the size of the gap. Here, we focus on wounds whose closure is driven by interfacial instabilities, featuring both leader cell-driven fingers and actin-mediated contraction. Our proposed model predicts a positive correlation between the frequency of fingering and the overall speed of boundary closure. This fingering frequency is precisely regulated through the orchestration of cell density-driven pressure, cell-cell repulsions, and the initial curvature of the wound boundary. Our findings demonstrate an inverse correlation between fingering frequency and boundary curvatures, indicating a "self-control" mechanism for closure rates independent of the initial curvatures of the wound periphery. Notably, changes in curvature caused by fingering formation generate force that aids in the healing process.

Significant attention has been paid to developing highly flexible and highly stretchable strain sensors due to the increasing demand for wearable devices such as motion-capturing devices and health-monitoring devices. Especially, carbon nanotube (CNT) network-based elastomeric sensors have been studied extensively for their unique strong piezoresistive response under large deformation. Despite its importance for the facile design of sensors, the effect of length and volume fraction of CNT on the piezoresistivity over a large strain range has not been fully uncovered. In this study, by combining coarse-grained molecular statics (CGMS) simulations and efficient percolation network analysis, we investigate the piezoresistive response of the CNT network for a wide range of the length and volume fraction and visualized the CNT network topology to understand the mechanism behind the piezoresistivity response. Based on the set of calculations, we obtain the design map of stretchability and sensitivity for the CNT-elastomer nanocomposite sensors over a wide range of design parameters of CNT, which can be used to fabricate the strain sensor with a desired performance.