Dragonfly-Inspired Wing Design Enabled by Machine Learning and Maxwell's Reciprocal Diagrams.

This research is taking the first steps toward applying a 2D dragonfly wing skeleton in the design of an airplane wing using artificial intelligence. The work relates the 2D morphology of the structural network of dragonfly veins to a secondary graph that is topologically dual and geometrically perpendicular to the initial network. This secondary network is referred as the reciprocal diagram proposed by Maxwell that can represent the static equilibrium of forces in the initial graph. Surprisingly, the secondary graph shows a direct relationship between the thickness of the structural members of a dragonfly wing and their in-plane static equilibrium of forces that gives the location of the primary and secondary veins in the network. The initial and the reciprocal graph of the wing are used to train an integrated and comprehensive machine-learning model that can generate similar graphs with both primary and secondary veins for a given boundary geometry. The result shows that the proposed algorithm can generate similar vein networks for an arbitrary boundary geometry with no prior topological information or the primary veins' location. The structural performance of the dragonfly wing in nature also motivated the authors to test this research's real-world application for designing the cellular structures for the core of airplane wings as cantilever porous beams. The boundary geometry of various airplane wings is used as an input for the design proccedure. The internal structure is generated using the training model of the dragonfly veins and their reciprocal graphs. One application of this method is experimentally and numerically examined for designing the cellular core, 3D printed by fused deposition modeling, of the airfoil wing; the results suggest up to 25% improvements in the out-of-plane stiffness. The findings demonstrate that the proposed machine-learning-assisted approach can facilitate the generation of multiscale architectural patterns inspired by nature to form lightweight load-bearable elements with superior structural properties.

Electrochemical Healing of Fractured Metals.

Repairing fractured metals to extend their useful lifetimes advances sustainability and mitigates carbon emissions from metal mining and processing. While high-temperature techniques are being used to repair metals, the increasing ubiquity of digital manufacturing and "unweldable" alloys, as well as the integration of metals with polymers and electronics, call for radically different repair approaches. Herein, a framework for effective room-temperature repair of fractured metals using an area-selective nickel electrodeposition process refered to as electrochemical healing is presented. Based on a model that links geometric, mechanical, and electrochemical parameters to the recovery of tensile strength, this framework enables 100% recovery of tensile strength in nickel, low-carbon steel, two "unweldable" aluminum alloys, and a 3D-printed difficult-to-weld shellular structure using a single common electrolyte. Through a distinct energy-dissipation mechanism, this framework also enables up to 136% recovery of toughness in an aluminum alloy. To facilitate practical adoption, this work reveals scaling laws for the energetic, financial, and time costs of healing, and demonstrates the restoration of a functional level of strength in a fractured standard steel wrench. Empowered with this framework, room-temperature electrochemical healing can open exciting possibilities for the effective, scalable repair of metals in diverse applications.