Highly Robust Conductive Organo-Hydrogels with Powerful Sensing Capabilities Under Large Mechanical Stress

The low mechanical strength of conductive hydrogels (<1 MPa) has been a significant hurdle in their practical application, as they are prone to fracturing under complex conditions, limiting their effectiveness. Here, this work fabricates a strong and tough conductive hierarchical poly(vinyl alcohol) (PEDOT:PSS/PVA) organo-hydrogel (PPS organo-hydrogel) via a facile combining strategy of self-assembly and stretch training. With PVA/PEDOT:PSS microlayers and aligned PVA/PEDOT:PSS nanofibers, PVA and PEDOT:PSS nanocrystalline domains, and semi-interpenetrating polymer networks, PPS organo-hydrogels display outstanding mechanical performances (strength: 54.8 MPa, toughness: 153.97 MJ m-3 ). Additionally, PPS organo-hydrogels also exhibit powerful sensing capabilities (gauge factor (GF): 983) due to the aligned hierarchical structures and organic liquid phase of DMSO. Notably, with the synergy of such mechanical and sensing properties, organo-hydrogels can even detect objects as light as 1 gram, despite bearing a tensile strength of ≈23 MPa. By incorporating these materials into human-machine interfaces, such as controlling artificial arms for grabbing objects and monitoring sport behaviors in soccer training, this work has unlocked a new realm of possibilities for these high-performance hierarchical organo-hydrogels. This approach to designing hierarchical structures has the potential to lead to even more high-performance hydrogels in the future.

Repurposed Leather with Sensing Capabilities for Multifunctional Electronic Skin

Electronic skin (e-skin), an important part toward the realization of artificial intelligence, has been developing through comprehending, mimicking, and eventually outperforming skin in some aspects. Most of the e-skin substrates are flexible polymers, such as polydimethylsiloxane (PDMS). Although PDMS was found to be biocompatible, it is not suitable for long-time wearing due to its air impermeability. This study reports a simple and designable leather based e-skin by merging the natural sophisticated structure and wearing comfort of leather with the multifunctional properties of nanomaterials. The leather based e-skin could make leather, "the dead skin," repurposed for its sensing capabilities. This e-skin can be applied in flexible pressure sensors, displays, user-interactive devices, etc. It provides a new class of materials for the development of multifunctional e-skin to mimic or even outshine the functions of real skin.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham’s Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm.