Hydrodynamic imaging using the lateral line plays a critical role in fish behavior. To engineer such a biologically inspired sensing system, we developed an artificial lateral line using MEMS (microelectromechanical system) technology and explored its localization capability. Arrays of biomimetic neuromasts constituted an artificial lateral line wrapped around a cylinder. A beamforming algorithm further enabled the artificial lateral line to image real-world hydrodynamic events in a 3D domain. We demonstrate that the artificial lateral line system can accurately localize an artificial dipole source and a natural tail-flicking crayfish under various conditions. The artificial lateral line provides a new sense to man-made underwater vehicles and marine robots so that they can sense like fish.

The exfoliation of graphene has opened a new frontier in material science with a focus on 2D materials. The unique thermal, physical and chemical properties of these materials have made them one of the choicest candidates in novel mechanical and nano-electronic devices. Notably, 2D materials such as graphene, MoS₂, WS₂, h-BN and black phosphorus have shown outstanding lowest frictional coefficients and wear rates, making them attractive materials for high-performance nano-lubricants and lubricating applications. The objective of this work is to provide a comprehensive overview of the most recent developments in the tribological potentials of 2D materials. At first, the essential physical, wear and frictional characteristics of the 2D materials including their production techniques are discussed. Subsequently, the experimental explorations and theoretical simulations of the most common 2D materials are reviewed in regards to their tribological applications such as their use as solid lubricants and surface lubricant nano-additives. The effects of micro/nano textures on friction behavior are also reviewed. Finally, the current challenges in tribological applications of 2D materials and their prospects are discussed.

We demonstrate a label-free biosensor imaging approach that utilizes a photonic crystal surface to detect surface attachment of individual dielectric and metal nanoparticles.

Using a precision drop-casting method, a bioinspired hydrogel-capped hair sensory system was created, which enhanced the performance of flow detection by about two orders of magnitude and endowed the sensors with threshold sensitivities that rival those of fish.

Significance: Deterministic lateral displacement (DLD) is a technique for size fractionation of particles in continuous flow that has shown great potential for biological and clinical applications. Several theoretical models have been proposed to explain the trajectories of different-sized particles in relation to the geometry of the pillar array, but experimental evidence has demonstrated that a rich class of intermediate migration behavior exists, which is not predicted by models. In this work, we present a unified theoretical framework to infer the trajectory of particles in the whole array on the basis of trajectories in the unit cell. This framework explains many of the unexpected particle trajectories reported in literature and can be used to design arrays for the fractionation of particles, even at the smallest scales reaching the molecular realm. We also performed experiments that verified our predictions, even at the nanoscales. Using our model as a set of design rules, we developed a condenser structure that achieves full particle separation with a single fluidic input.