Linearity and hysteresis are frequently overlooked critical parameters in the pursuit of ultrahigh sensitivity for flexible strain sensors. Significant nonlinearity and hysteresis can lead to poor measured accuracy as pre-strain often occurs and hard to be completely eliminated during installation. Here, inspired by the geometry and function of scorpions’ sensing organs, a surface wrinkle–cracks interaction engineering combined with a double conductive network is proposed and introduced into stretchable strain sensors, achieving an outstanding linearity of up to 0.9985 and a sufficient sensitivity of 22.8 over a working strain range of 30%, along with a low hysteresis of 1.91%. Wearable applications demonstrate the proposed strain sensor works reliably when installed on the measured surfaces, regardless of whether pre-strain is generated, achieving convenient and arbitrary conformal installation. This surface wrinkle–cracks interaction engineering provides a potential strategy for other stretchable strain sensors to achieve high sensing performance indexes and excellent functions simultaneously.

Modern ballistic protection equipment demands a critical balance between high impact resistance and lightweight, a challenge unresolved by conventional approaches. Biological systems achieve such synergy through evolutionarily optimized structures, offering promising biomimetic solutions, yet a limited understanding of impact-resistance mechanisms hinders their full potential. This study employed a multi-technique approach combining ultra-depth-of-field microscopy, SEM, EDS, FTIR, nanoindentation, and impact testing to investigate the convex hull of Lq (desert scorpion) tergum and the locally thickened regions at the hulls relative to the inter-hull gaps. Convex hulls deflect and disperse impact loads, while local thickening guides cracks and dissipates energy, balances impact resistance, and lightweighting. Hp tergum (rainforest scorpion) served as a control, confirming this convex hull-local thickening dual mechanism as a key adaptation of desert scorpions to particle impacts. Finite element models of the central (BM1) and lateral (BM2) convex hull arrangements were subjected to particle impacts. The lateral (BM2) configuration exhibited superior stress regulation and damage mitigation. Guided by this lateral prototype, bio-inspired ceramic-fiber protectors were designed and fabricated. Ballistic tests (7.62 mm armor-piercing incendiary projectiles, 800-815 m/s) showed a 24.9% reduction in BFS compared with conventional flat composites of equal areal density, lowering potential human impact. Its impact-resistance mechanism, which involves projectile deflection combined with stress homogenization and crack guidance, closely replicates the desert scorpion tergum's biological mechanism. This work provides a mechanism-driven design paradigm for lightweight composite armor.

Superelastic alloys for critical applications in extreme environments are required to combine a wide operating temperature range, low temperature sensitivity, and high strength. Achieving this combination is challenging. Drawing from high-entropy and superelastic alloy design principles, this study utilised laser-directed energy deposition (L-DED) to fabricate TiZrHfNiCu high-entropy superelastic alloys with excellent forming quality. The intricate composition and swift solidification conditions resulted in a uniform, fine, and isotropic dendritic microstructure within this high-entropy alloy, which comprises the B2 phase, B19' phase, and Zr2Cu-like phase. In comparison to the as-cast material, the LDED-TiZrHfNiCu material exhibits a reduced degree of component segregation and concurrently experiences strain glass transition alongside martensitic crystallisation behaviour. The alloy demonstrated recoverable superelastic strains exceeding 5%, a fracture strength over 2 GPa, and very low temperature sensitivity between 173 K and 473 K. Additionally, this method addresses the difficulties associated with machining superelastic alloys and the challenges associated with manufacturing complex geometries. This study illustrates the fabrication of TiZrHfNiCu alloy via L-DED, offering a new perspective on the preparation of high-strength, wide-temperature-range superelastic alloys and providing insights into phase-structure transformations and microstructural evolution in additively manufactured high-entropy superelastic alloys. This study demonstrates the feasibility of using L-DED technology to fabricate high-performance high-entropy shape memory alloys.Refined composite microstructures were achieved under non-equilibrium solidification conditions.The (TiZrHf)(5)(0)(NiCu)(5)(0) alloy fabricated by L-DED exhibits high strength and stable superelasticity over a wide temperature range.The interplay between compositional segregation and composite microstructure promotes the coordinated occurrence of reversible martensitic transformation and strain glass transition.This study established correlations between the manufacturing process, microstructure, and mechanical properties.

Tactile sensors are essential to human-machine interaction. However, current technologies still face key challenges, including energy supply, electrode redundancy, and signal crosstalk. This work proposes an all-in-one tactile sensor with event-driven operation and in-sensor modulation (ATS-EI). ATS-EI consists of frequency-division responsive materials, allowing it to use the alternating current (AC) signal generated by the coupling of the human body with the power frequency electric fields as the signal source. By modulating the AC signal within the sensor, ATS-EI senses continuous stimulation position with a single electrode interface. Notably, ATS-EI operates in an event-driven mechanism, triggered only when electromagnetic coupling occurs upon skin contact. It is demonstrated that ATS-EI can adapt to different environments, and exhibit an extremely low pressure detection limits (<0.015 N), fast response time (approximate to 20 ms), and excellent durability (>300 000 cycles). The all-in-one sensor, which is power free, uses single electrode and is crosstalk-free, paves a new path for tactile sensors.

Soft robots are constrained by the complexity of structural and drive systems, rendering implementation challenging and impeding flexible adaptation to diverse application scenarios. Smart materials with self-deforming properties offer promising solutions. Herein, this investigation develops an intelligent prediction model through machine learning for the training parameters and deformation angle of NiTi shape memory alloy. The properties of NiTi alloy wires after training under various conditions are clarified. Based on multiple biomimetic prototypes, multi-dimensional functional transformation soft robots driven by shape memory alloy wires are constructed. The results show intelligent training methods enhance both programming efficiency and design intelligence. The NiTi alloy wires can obtain the specific shape memory effect performance after programming training. The constructed soft robots perform functions corresponding to the biomimetic prototypes. This work extends training methods for shape memory alloys, providing technological innovation for soft robots in various scenarios.

Heterogeneous material 3D printing (HM3DP) represents a transformative approach in additive manufacturing, enabling precise spatial control over material composition, microstructure, and functionality. This technology transcends the limitations of homogeneous fabrication by integrating multi-material systems, dynamic process programming, and external field modulation, offering innovative solutions for biomimetic structures, flexible electronics, and smart devices. This review systematically examines the chemical foundations, process innovations, and applications of HM3DP and proposes a three-tier classification system—composition, structure, and functional–temporal heterogeneity—to standardize evaluation metrics. Key challenges, including dynamic interface compatibility, cross-scale heterogeneous mechanical integrity and fracture control, and functional–temporal synergy, are critically analyzed. Future directions emphasize multi-physics collaboration and intelligent optimization to achieve adaptive, high-performance heterogeneous systems. HM3DP is poised to bridge the gap between static manufacturing and dynamic, intelligent design, unlocking new frontiers in materials science and engineering.

Vibration sensors often face a trade-off between sensitivity and impact tolerance. Inspired by scorpion slit sensilla, we developed a biomimetic vibration sensor with high sensitivity and impact tolerance (BHIS), combining a spiral-slit resonator with a compliant-rigid-coupled base. The spiral-slit architecture provides geometry-tunable stiffness, and reduced-order modeling together with dispersion analysis reveals local resonance near a zero-effective-mass condition, which amplifies electromechanical transduction. At resonance, the optimized BHIS achieves a sensitivity of 0.118 V g-1 and resolves frequency differences of 0.1 Hz, corresponding to a 23.6-fold improvement over a commercial piezoelectric sensor. The compliant-rigid-coupled base mitigates transient loading, allowing the sensor to withstand 220 g impact while retaining stable electrical output. We further define a figure of merit as the product of sensitivity and the highest tested survivable acceleration to compare sensitivity with structural survival. Coupled with deep learning, the BHIS enables turbofan engine condition monitoring. Periodic BHIS arrays also attenuate propagating vibrations through a bandgap effect while producing electrical output. This work establishes a self-powered bioinspired platform for vibration monitoring and regulation in complex loading environments.

Flexible tactile sensors are essential for robotics and health monitoring, yet they often face challenges related the complexity of multi-electrode wiring and the inherent trade-off between sensing sensitivity and dynamic range. Inspired by the hierarchical porous architecture of the elephant trunk whisker, we propose a sophisticated tactile sensing fiber that enables distributed pressure perception along a single continuous filament via the integration of a bioinspired porous hierarchical structure and electrical time domain reflectometry (ETDR) electrodes. Pressure-induced deformation triggers localized impedance mismatches along the electrodes, which are accurately resolved and localized in the time domain. The engineered graded pores enable a sequential deformation mechanism: larger apertures maximize sensitivity to subtle tactile inputs, while smaller intervals ensure structural resilience under high loads. The sophisticated sensing fiber, consisting of a styrene-ethylene-butylene-styrene (SEBS) matrix with embedded graded pores and parallel copper wires, is fabricated through the multimaterial thermal drawing technique, which offers high-speed production and consistent structural uniformity. Experimental results demonstrate a remarkable sensitivity of 1.15×10-4N-1 in the low-pressure regime and a spatial resolution of 2.0cm. This synergy between bionic design and reflectometry offers a robust, scalable approach for electronic skins, balancing detection precision with mechanical durability. Ultimately, this strategy provides a low-complexity, high-performance solution for large-area tactile sensing systems.

Tactile sensors based on polymer optical fibers (POFs) possess high sensitivity, superior flexibility, and immunity to electromagnetic interference. Nevertheless, the scalable fabrication of sensor arrays capable of accurately resolving multiple contact points remains a challenge. Here, we propose an architecture combining mechanically tailored heterogeneous POFs with a warp-and-weft braided network to achieve high signal-to-noise ratio force measurement and precise localization. This heterogeneous POF architecture is realized by strategically embedding soft-fiber segments within a poly(methyl methacrylate-b-n-butyl acrylate-b-methyl methacrylate) (MAM) fiber backbone, thereby achieving localized mechanical tunability. The results show that the soft fluorinated ethylene propylene/polydimethylsiloxane (FEP/PDMS) POF segment exhibit a robust, material-dependent response to applied force, whereas the MAM fibers remain mechanically insensitive, serving exclusively as optical transmission lines. To construct the sensing network, multiple POFs featuring strategically integrated soft FEP/PDMS segments are interwoven in a warp-and-weft configuration. This architecture forms an array where the sensing nodes are defined by orthogonal soft-fiber intersections. The resulting network enables precise tactile quantification and localization, achieving a force resolution of 0.013 N. This design transforms continuous MAM optical fibers from passive waveguides into discrete, high-sensitivity perception pixels. This pixelation effectively eliminates signal crosstalk and ghosting artifacts, critical bottlenecks inherent in conventional flexible grid sensors. The tactile sensor presents a compelling pathway for advancing wearable sensing technologies in human–computer interaction, soft robotics, and health monitoring.

Efficient acquisition of spatial airflow information is vital for organisms to orient within complex environments and detect predators. For scorpions with degraded vision, specialized mechanosensory trichobothria provide a crucial vision-compensatory mechanism, enabling hypersensitive perception of subtle airflow fluctuations. Inspired by this evolutionary adaptation, we present a biomimetic neuromorphic airflow sensor (BNAS) integrating a bioinspired lever-amplification structure with a pressure-induced ionic enrichment mechanism. This synergistic design inherits the hypersensitive anemosensation and neural response features of scorpion. The BNAS demonstrates a superior sensitivity of 18.22% (m/s)-1 at low velocities and maintains high performance across a broad dynamic range (0.1 to 10.27 m/s), along with omnidirectional detection capability. The integration of this neuromorphic hardware with AlexNet deep-learning algorithm enables the efficient extraction of human respiratory patterns, achieving 95.56% accuracy in identifying individual "breathing fingerprints." Our work underscores the potential of bioinspired neuromorphic systems to bridge the gap between biological perception and artificial sensing, establishing a neuromorphic front-end design paradigm that advances next-generation brain-inspired computing.

The impact resistance of aluminum alloys critically influences the service reliability of key load-bearing components in aerospace and automotive industries. However, the unclear micro-failure mechanisms under high-velocity impact loads severely limit lifespan improvements. This study developed a compact desktop-level electromagnetic ejection-based high-velocity impact in-situ testing system through systematic optimization of excitation current parameters, coil geometry, and multi-stage configuration. The system integrates a nine-stage electromagnetic coil acceleration module achieving 62 m/s impact velocity and an in-situ monitoring unit combining infrared thermography, high-speed imaging, and acoustic emission signal. Multi-angle impact experiments enabled synchronized monitoring of dynamic mechanical responses, micro-damage evolution, and transient temperature fields. Experimental results demonstrate that increased impact angles reduce impact load, shift plastic flow from radial uniformity to shear dominance, expand transient thermal zones, and transition acoustic emission signatures from low-frequency plasticity to shear-induced frequencies.

Ceramic materials are valued in aerospace, automotive, and protective applications for their high-temperature stability, corrosion resistance, and hardness, but their inherent brittleness limits simultaneous improvement of strength and toughness. Inspired by natural architectures, a fabrication strategy integrating material extrusion, ultrasonic-vacuum-assisted cyclic metal infiltration, and stepwise vacuum heat treatment is proposed for ceramic-metal composites. Microstructural and phase analyses indicate that the metallic phase effectively infiltrates the porous ceramic scaffold and forms stable interfaces. Mechanical tests show that the composites with optimized heat treatment and about 4.6 wt

ABSTRACT Biological anti‐impact materials can effectively satisfy low‐to‐medium‐speed impact resistance (∼20 m/s) under natural conditions. However, extremely high‐speed impact scenarios (>100 m/s) represent the most demanding service environments in engineering practice, where dynamic embrittlement and catastrophic failure of structural materials remain long‐standing challenges. Herein, we propose a multi‐level, multi‐scale composite structure enabled by a dual bioinspired coupling design strategy, which yields exceptional impact fracture resistance and delamination tolerance. Low‐velocity impact tests demonstrate that the bioinspired structure realizes efficient energy dissipation through the synergy of multiple structural configurations, thus significantly enhancing damage tolerance. Meanwhile, the complementary combination of stiffness and toughness suppresses plastic deformation and preserves structural mechanical stability. Compared with conventional orthogonal composites, this bioinspired composite exhibits a 41.4% higher ballistic limit velocity, a 78.4% improvement in energy absorption per unit density, and reductions in delamination damage area of 45.6% and 11.5% in the sinusoidal and Bouligand regions, respectively. Under high‐speed impact loading, the cavity area, protrusion height, and backside damage area are reduced by 76.8%, 68.2%, and 80.9%, respectively. This integrated bioinspired design provides an important theoretical foundation and technical support for developing next‐generation lightweight, high‐strength, and tough composites toward critical engineering applications including aero‐engine blades.

The efficient absorption and dynamic regulation of impact energy represent core challenges in engineering protection, particularly in applications demanding lightweight solutions and stringent safety requirements such as aerospace, precision instruments, and biomedical devices. Traditional impact protection materials struggle to meet diverse needs due to their complex structures, non-adjustable properties, and poor adaptability. Inspired by the fact that during compression, the vascular bundles in bamboo are compressed, leading to localized densification of the structure and an increase in stiffness, and leveraging the temperature-sensitive properties of NiTi shape memory alloys, this study proposes a NiTi variable stiffness structures (NiTi VSSs) based on Laser Powder Bed Fusion (LPBF) technology. This material achieves dynamic optimization of stiffness and energy absorption efficiency through synergistic control of structure and temperature. Research demonstrates that NiTi VSSs exhibits markedly different mechanical responses at 25 degrees C (coexistence of martensite and austenite) and 100 degrees C (austenitic). At low temperatures, structures with larger thin walls contact areas (e.g., trapezoid variable stiffness structure unit, TVSSU) achieve higher energy absorption (8.33 J), while at high temperatures, structures with smaller thin walls contact areas (e.g. sandglass variable stiffness structure unit, SVSSU) demonstrate superior impact resistance due to the high stability of the austenitic phase. By adjusting thin walls geometric parameters (distance, thickness) and array design, precise balancing of load-bearing capacity and deformation is further achieved. Moreover, NiTi VSSs combines superelasticity (SE) and shape memory effects (SME), offering novel insights for reusable smart protective structures. This work not only establishes a bio-inspired, material-process co-optimization model for multi-condition adaptive metamaterial design but also paves new pathways for additive manufacturing of NiTi alloys in lightweight dampers, robotic actuators, and related fields.

The thermal history nonuniformity during metallic additive manufacturing induces heterogeneity in microstructures and mechanical properties, which remains a critical challenge to the component performance. In this work, a high-throughput parameter optimisation algorithm is developed to allocate laser power on each deposition track so as to reduce thermal history nonuniformity in directed energy deposition (DED). Firstly, a numerical surrogate model is developed to infer the multi-layer transient temperature fields efficiently. In the model, a matrix-wise computational workflow is introduced, which substantially accelerates computational speed and reduces inference time for optimisation evaluations. In addition, a heuristic optimisation algorithm is proposed to allocate laser power parameters on each deposition track, where the standard deviation of cross-track temperature integrals serves as the objective metric and is minimised to achieve a uniform thermal history. In the experiments, the optimised manufacturing strategy suppresses over 57% of the thermal history nonuniformity. The component fabricated with optimised parameters achieves an average improvement of 33% in mechanical property homogeneity and enhanced ductility without sacrificing tensile strength. It highlights the practical value of reducing thermal history nonuniformity to improve mechanical reliability and mitigate the strength-ductility trade-off in DED-fabricated components.

The paw pad is an outstanding cushioning structure, which demonstrates nonlinear mechanical characteristics when subjected to pressure. Nonlinear mechanical characteristics are generally considered to be related to the viscoelastic properties of the material. However, the relationship between its nonlinear mechanical properties and the morphological characteristics of the paw pad remains unknown. In this study, morphological data, mechanical data, and finite element simulation methods were integrated to explore how the unique shape of the paw pads enables them to exhibit excellent cushioning performance. The research findings indicate that the paw pad exhibits an irregular morphology. Nevertheless, its cross-sectional area increases in proportion to the increase in the paw pad height, presenting a linear gradient relationship (R2 = 0.99). Two comparison models with the same volume and height but different morphologies as the paw pad model, were designed for finite element simulation. The finite element static analysis shows that the influence of morphology is mainly reflected in the early deformation process, while the influence of viscoelastic material properties is reflected in the later load-bearing capacity. The finite element dynamic analysis shows that compared with the comparison models, the paw pad model has a more stable force during the impact process, without an instantaneous impact force at the initial contact moment. Moreover, the peak normal ground reaction force (GRF) component under different impact speeds is lower than that of the comparison models, demonstrating better buffering effects. The research results can provide inspiration and a biomechanical basis for the morphological design of buffering units.

Endowing intelligent robots with the ability to perceive and analyze complex liquid environments is essential for autonomous decision-making. However, conventional liquid-sensing technologies remain constrained by a fundamental trade-off between transient response and recognition accuracy, a limitation stemming from the sluggish kinetics of interfacial charge transfer and complex analytical procedures. Herein, we present a bionic liquid-sensing electronic skin (BLSE) inspired by the gating-controlled signal transduction mechanism of ion channels on the surface of biological sensory cells. By emulating the transient signal transduction of ion channels, BLSE achieves instantaneous reconstruction of electronic pathways triggered by the contact between low-impedance droplets and the high-impedance sensing array. This design enables an ultrafast response and recovery time of 1.8 ms. To ensure stability in complex liquid environments, a superhydrophobic coating with a contact angle of 159° is integrated, minimizing interfacial adhesion to allow instantaneous functional recovery and stable cyclic sensing. By coupling a multi-layer interlaced electrode network with deep learning algorithms for multi-channel feature extraction, BLSE demonstrates a liquid recognition accuracy of 99.58% and the ability to precisely detect droplet sliding. This gating-inspired sensing paradigm offers a versatile strategy for liquid recognition, paving the way for developing intelligent autonomous systems capable of human-like environmental awareness.

In this study, we develop a multistable tensegrity-inspired auxetic metamaterial to address the limited durability, restricted deformation modes, and poor self-recovery commonly observed in conventional negative Poisson’s ratio structures. The proposed design is based on a regular quadrilateral unit cell composed of rigid sliding rods, compression springs, and elastic tensile elements, forming a self-equilibrated configuration with a central rigid core and a surrounding tensile network. This architecture enables synchronized longitudinal contraction and transverse expansion, resulting in an equivalent Poisson’s ratio close to −1 and a highly isotropic deformation pattern. Quasi-static compression tests show a clear three-stage force–displacement response, with programmable stiffness and tunable energy absorption ranging from 93 mJ to 313 mJ. After 1000 loading–unloading cycles, the energy dissipation capacity decreases by only 9.03%, indicating stable fatigue performance. Assemblies consisting of 4, 6, and 9 unit cells preserve the essential mechanical characteristics of the single-cell structure. Moreover, impact tests demonstrate a reduction in peak force of 68.94%–78.49% and an approximately twofold increase in impact duration. These results suggest that the proposed metamaterial provides a practical and scalable solution for reusable impact-mitigation systems in aerospace, robotics, and protective engineering applications.

ABSTRACT Achieving synergistic strengthening and toughening in engineering materials remains a significant challenge. Although nacre‐inspired composites with brick‐and‐mortar structures exhibit high strength and toughness, the synergistic enhancement of these two properties is severely constrained by inadequately engineered interfaces. In this study, we innovatively integrate the sinusoidal interlocking interface found in chiton shells into brick‐and‐mortar architectures to overcome the inherent weakness of interfacial regions. Tensile test results reveal that the crossed sinusoidal interface morphology significantly enhances both strength and toughness of the bioinspired composites. Under the N 2‐ A 0.4 interface, the values of σ I , σ II , σ M , and toughness increased by 91.2%, 54.8%, 365.2%, and 170.9%, respectively. The integration of the sinusoidal interface from chiton shells eliminates low‐stress regions within brick‐and‐mortar structures, thereby enabling a synergistic enhancement of strength and toughness. Furthermore, the results indicate that the orientation of the sinusoidal interfaces plays a crucial role in determining the strength and toughness of composites. The underlying principle for the synergistic enhancement of strength and toughness in bioinspired composites lies in rationally optimizing the interlocking interfaces to balance load transfer and stress concentration. The unique bioinspired interface overcomes the weaknesses of brick‐and‐mortar architectures, offering a promising design strategy for the next‐generation ultra‐strong and tough composites.

Superamphiphobic surfaces, inspired by the springtail re-entrant microstructure array skin, have wide applications in environmental protection, chemical engineering and biomedicine. However, due to the complex geometry of re-entrant microstructures, it remains difficult to fabricate large-area re-entrant microstructure arrays on metal surfaces without expensive equipment and complex processing techniques. Here, by combining the nanosecond laser direct writing technology with the template-assisted transfer technology, we developed an efficient, low-cost, and large-area manufacturing technology for superamphiphobic surfaces on metal substrates. The prepared surfaces demonstrate a strong ability to repel low surface tension droplets, such as hexadecane (surface tension: gamma = 27.2 mN m- 1), and have excellent self-cleaning property. Furthermore, by adjusting the manufacturing process parameters, different superamphiphobic surfaces with adjustable droplet adhesion can be manufactured easily. Overall, this study provides a simple way for obtaining the superamphiphobic surfaces on metal substrates, and verified their potential application fields for self-cleaning, oil droplet manipulation and oilbased microreactor engineering.