This study, inspired by the impact resistance of the pistol shrimp’s predatory claw, investigates the design and optimization of bionic energy absorption structures. Four types of bionic hierarchical porous metamaterial lattice structures with a negative Poisson’s ratio were developed based on the microstructure of the pistol shrimp’s fixed claw. These structures were validated through finite element models and quasi-static compression tests. Results showed that each structure exhibited distinct advantages and shortcomings in specific evaluation indices. To address these limitations, four new bionic structures were designed by coupling the characteristics of the original structures. The coupled structures demonstrated a superior balance across various performance indicators, with the EOS (Eight pillars Orthogonal with Side connectors on square frame) structure showing the most promising results. To further enhance the EOS structure, a parametric study was conducted on the distance d from the edge line to the curve vertex and the length-to-width ratio y of the negative Poisson’s ratio structure beam. A fifth-order polynomial surrogate model was constructed to predict the Specific Energy Absorption (SEA), Crush Force Efficiency (CFE), and Undulation of Load-Carrying fluctuation (ULC) of the EOS structure. A multi-objective genetic algorithm was employed to optimize these three key performance indicators, achieving improvements of 1.98% in SEA, 2.42% in CFE, and 2.05% in ULC. This study provides a theoretical basis for the development of high-performance biomimetic energy absorption structures and demonstrates the effectiveness of coupling design with optimization algorithms to enhance structural performance.

Icing on power lines and wings can cause serious economic damage and safety hazards. While superhydrophobic materials show promise for anti-icing applications, their passive anti-icing mechanisms require external energy activation, highlighting the need for the development of active de-icing materials with energy-to-heat conversion capabilities. Here, we developed three photothermal superhydrophobic shape-memory polymers with anti-icing performance (PSSPs), with 3%, 5%, and 7% CNT doping ratios, through a two-step process: resin preparation and laser-processing modification. The results showed that all samples presented good superhydrophobic properties. In addition, the tested materials demonstrated good shape-memory performance (recovery rates were close to 100%). They also showed excellent de-icing performance. Owing to the simplicity of the fabrication process, the material is suitable for mass production. The synergistic interplay between superhydrophobicity and photothermal activation endows the material with dual-functional icephobic performance, demonstrating practical applicability in industrial cryogenic environments.

With the continuous increase in human demand to improve aircraft performance, intelligent aircraft technologies have become a popular research field in recent years. Among them, the deformable skin structure has become one of the key technologies to achieve excellent and reliable performance. However, during the service, deformable skin structures may encounter problems such as surface impact and adhesion of droplets in rainy weather or surface icing in low-temperature environments, which can seriously affect the flight safety of the aircraft. One way to overcome these issues is to use superhydrophobic shape memory materials in the structure. In this regard, first, shape memory composites were prepared with shape memory epoxy resin as the matrix and carbon fiber orthogonal woven fabric as the reinforcement material. Superhydrophobic shape memory composites (SSMCs) were then obtained by casting the kirigami composite with superhydrophobic carbon nanotube–polydimethylsiloxane (CNT@PDMS) mixture, and the surface was processed by laser micromachining. Shape memory performance and surface wetting performance were determined by material testing methods. The results showed that the shape memory recovery rate can reach 85.11%, the surface is superhydrophobic, the average water contact angle is 156.9 ± 4.4°, and the average rolling angle is 3 ± 0.5°. The three-point bending test of the specimens with different kirigami cell configurations showed that the shape memory composite based on the rectangular structure has the best deformability with an aspect ratio of 0.4. From the droplet impact test, it was found that the impact speed of water droplets and the curvature of the surface can greatly affect the dynamic performance of water. This work is expected to be of significant research value and importance for developing functional deformable skin materials.

Webbed-foot gliding water entry is a characteristic water-landing strategy employed by swans and other large waterfowls, demonstrating exceptional low-impact loading and remarkable motion stability. These distinctive biomechanical features offer significant potential for informing the design of cross-medium vehicles’ (CMVs’) water-entry systems. To analyze the hydrodynamic mechanisms and flow characteristics during swan webbed-foot gliding entry, the three-dimensional bionic webbed-foot water-entry process was investigated through a computational fluid dynamics (CFD) method coupled with global motion mesh (GMM) technology, with a particular emphasis on elucidating the regulatory effects of entry parameters on dynamic performance. The results demonstrated that the gliding water-entry process can be divided into two distinct phases: stable skipping and surface gliding. During the stable skipping phase, the motion trajectory exhibits quasi-sinusoidal periodic fluctuations, accompanied by multiple water-impact events and significant load variations. In the surface-gliding phase, the kinetic energy of the bionic webbed foot progressively decreases while maintaining relatively stable load characteristics. Increasing the water-entry velocity will enhance impact loads while simultaneously increasing the skipping frequency and distance. Increasing the water-entry angle will primarily intensify the impact load magnitude while slightly reducing the skipping frequency and distance. An optimal pitch angle of 20° provides maximum glide-skip stability for the bio-inspired webbed foot, with angles exceeding 25° or below 15° leading to motion instability. This study on webbed-foot gliding entry behavior provided insights for developing novel bio-inspired entry strategies for cross-medium vehicles, while simultaneously advancing the optimization of impact-mitigation designs in gliding water-entry systems.

A hybrid aquatic–aerial vehicle (HAAV) is a novel type of aircraft capable of both aerial flight and underwater navigation. Inspired by the swan’s gliding and landing motion on water surfaces, this study investigates the dynamic modeling and integrated optimization design of an HAAV equipped with a biomimetic skipping plate. By comprehensively accounting for the aerodynamic, impact, hydrodynamic, and frictional forces during the water entry process, a dynamic model for the HAAV’s gliding water entry is established. The reliability of the model is verified through comparisons between numerical simulations and theoretical predictions. Parametric modeling of the skipping plate’s configuration and layout is performed to analyze the influence of different parameters on the water entry dynamics. With the objectives of minimizing the overload and pitch angle variation, a hybrid infilling strategy based on a radial basis function neural network (RBFNN) surrogate model is constructed to improve optimization efficiency. This is combined with a quantum-behaved particle swarm optimization (QPSO) algorithm to conduct the multi-objective optimization of the biomimetic plate, thereby obtaining its optimal configuration and layout parameters. The results demonstrate that the established dynamic model is effective and can accurately capture the kinematic characteristics of the gliding water entry process. The error between the peak load and the pitch angle variation is less than 5%. Compared with the direct QPSO algorithm, the proposed method reduces the number of model evaluations by 66.7%, the computational time by 52.1%, and the optimal solution response value by 12.01%, demonstrating strong potential for engineering applications.