Noise and impact protection are essential for safeguarding human health and ensuring the safe operation of advanced equipment. However, the low-frequency and broadband nature of noise in real-world application environments, combined with the requirement to maintain mechanical performance under stringent lightweight constraints, presents significant challenges for the design of such structures. To address this issue, an acoustic-mechanical multifunctional hybrid lattice metamaterial (HLM) is proposed by combining spherical shell lattices with truss lattices. Integrating theoretical derivation, finite element simulation and experimental validation, this study clarifies the resonant sound absorption mechanism and acoustic-mechanical functional decoupling characteristics of the proposed HLM. By optimizing the configuration of the internal truss lattice, the specific energy absorption of the structure is improved by approximately 113 %, reaching about 6.1 J/g. Meanwhile, the parallel-arrayed configuration enables the HLM to deliver an average sound absorption coefficient of similar to 0.95 over the frequency range of 500-1300 Hz. Furthermore, it can be integrated with porous materials, allowing the effective absorption bandwidth to be further extended into an ultra-broad frequency range. This work establishes a novel framework for the compact integration of acoustic and mechanical functionalities, thereby expanding the potential applications of metamaterials in practical fields such as aerospace, construction, and defense.

Abstract Multifunctional metamaterials that manage stress, electromagnetic wave (EMW), and sound are essential for lightweight protection and stealth. However, compact integration of these functions remains challenging due to inherent design incompatibilities and functional trade-offs. Inspired by the unique optical and acoustic stealth mechanisms of lepidopteran insect, we propose a multifunctional hierarchical lattice (MHL). Through the coupling of photonic crystals and perforated resonant structures in a multi-scale hierarchical design, the MHL achieves stress regulation while simultaneously promoting enhanced wave manipulation via multiple electromagnetic reflections and dual-porosity acoustic resonance. This design effectively circumvents the conventional incompatibility between mechanical functionality and wave-manipulation performance, while demonstrating significant array-level design potential within an on-demand framework based on Kolmogorov–Arnold networks. Hence, the MHL simultaneously enhances mechanical (~21.9-fold enhancement in in-plane specific energy absorption), electromagnetic (EMW absorption bandwidth covering ~93.5% across 2–40 GHz), and acoustic performance (average sound absorption coefficient of ~0.9 over 600–900 Hz), while the total thickness of 24 mm is 36.9% of that of traditional functional stacking designs. This work establishes a general design paradigm for multifunctional metamaterials, offering new routes toward lightweight, mechanically robust structures for noise control and EM shielding in high-end engineering systems.

Lithium penetration through solid electrolytes is inherently associated with fracture, yet the crack-driving force in solid-state batteries remains incompletely quantified because conventional fracture formulations neglect the electrical contribution associated with the internal electric field and the crack-face loading generated during electrochemical plating. Here, we develop an extended energy release rate formulation within a power conservation-based framework and combine it with coupled calculations of electrochemical transport, lithium creep flow, and elastic deformation of the solid electrolyte. The resulting formulation predicts substantially larger crack-driving forces than classical mechanical contour integrals and is numerically path-independent over the contours examined. The calculated energy release rate decreases with increasing ionic conductivity and approaches a plateau at high conductivity, but increases with stack pressure because of enhanced mechanical confinement of deposited lithium. Sharper defects further amplify both electric-field localization and crack-tip confinement, while the electrical contribution becomes increasingly important at high current density, particularly in low-conductivity electrolytes. These findings show that fracture in solid electrolytes must be evaluated through coupled transport, electric-field, crack-face loading, and stress effects, and provide a basis for optimizing ionic conductivity, stack pressure, and defect geometry to mitigate dendrite-induced failure.

Microscale wall-climbing robots hold transformative potential for biomedical applications, however, their further miniaturization is hampered by the inability to achieve efficient surface adhesion at the microscale. Here, we present a rotating magnetic field-driven strategy for a magnetic microwheel to achieve gravity-resisting directional climbing on vertical walls, including biological tissue surfaces. By modulating the rotating magnetic field strength, orientation, wedge angle between the microwheel and the vertical wall, stable hydrodynamic interactions are induced, generating controllable wet friction force to counteract gravity. Experiments demonstrate that the climbing direction of microwheels can be dynamically adjusted on demand by regulating the magnetic field strength, wedge angle, and the angle between the magnetic field plane and the z-axis, enabling precise locomotion on vertical, overhanging, and biological tissue surfaces. Reversing the magnetic field and symmetrically adjusting the wedge angle along the z-axis further allows programmable directional switching. This approach circumvents the limitations of traditional negative-pressure adhesion mechanisms at microscales, offering a novel paradigm for integrating actuation and motion control in miniature wall-climbing robots. The strategy significantly expands the application scope of wall-climbing robots in biomedical scenarios, such as targeted drug delivery and minimally invasive surgery, while providing insights for designing multifunctional microrobots with adaptive locomotion capabilities.

ABSTRACT Conventional metasurface designs face fundamental trade‐offs among geometric freedom, fabrication fidelity, and optical functionality. Here, we transcend these limitations through Non‐Uniform Rational B‐Splines (NURBS)‐enabled computational co‐design, establishing a paradigm in which freeform curvature control, deep learning optimization, and nanoscale lithography act synergistically. Unlike topology‐constrained meta‐atoms requiring iterative electromagnetic simulations, our framework deploys a Transformer‐based differentiable surrogate to harness the parametric continuity of NURBS for arbitrary wavefront sculpting. Crucially, we introduce dose curvature proximity compensated lithography, which restores symmetry between design intent and fabricated structure through geometry dependent electron beam modulation. Experimental validation demonstrates achromatic wavelength scale focusing across 405–633 nm, with refined focal plane line profile analysis yielding full‐width‐at‐half‐maximum (FWHM) values of 1.15 λ ± 0.02 λ and limited focal shift across the measured wavelength range. The fabricated 200 μm diameter metalens resolves approximately 2.19 μm features in resolution target imaging and enables biological cell image analysis with sensitivity to subcellular refractive index variations (Δ n ≈ 0.02). This co‐design platform opens avenues for implantable photonics, microscopy, and quantum manipulation requiring precise freeform architectures.

Improving the mechanical performance of material-extrusion-based additive manufacturing has long been recognized as a major challenge in the field. The introduction of continuous fibers substantially improves the in-plane strength of printed parts; however, the inherently weak interlayer bonding remains a critical bottleneck that restricts their practical application. Inspired by three-dimensional woven composites, this study proposes a woven-like toolpath strategy for continuous fiber reinforced polymer additive manufacturing (CFRP-AM), in which continuous fibers periodically interlace across adjacent layers to construct a global translaminar interlocking architecture and thereby enhance interlayer strength. Compared with planar toolpaths, the woven-like toolpath achieves substantial interlaminar performance enhancement without compromising in-plane strength, increasing interlayer tensile strength by 97.37% and interlayer shear strength by 126.96%. Fracture analyses using optical microstructural characterization techniques reveal that woven-like toolpaths fundamentally alter crack propagation, from flat interlayer delamination in planar specimens to multi-layer crack deflection and extensive fiber breakage in woven-like toolpath specimens, and significantly increase fracture energy. This woven-like toolpath strategy provides a simple yet effective route to enhancing interlayer performance of CFRP-AM, achieving substantial strengthening without requiring any auxiliary heat source, external field, or hardware modification. At the same time, the method is fully compatible with existing thermal, material, or field-assisted enhancement techniques, enabling synergistic improvements and offering broad potential for high-performance additive manufacturing.

Micro-continuous liquid interface production (mu CLIP) enables high-speed and high-precision fabrication of magnetic microstructures by reducing resin residence time and suppressing particle settling. However, achieving large and reliable deformation remains challenging due to the high stiffness of conventional single-material prints and poor interfacial bonding between soft hydrogel and magnetic components. Here we present a multi-material mu CLIP process with in situ vat exchange, utilising a homogeneously doped Fe3O4/HEMA photopolymer to improve interfacial chemical continuity. The HEMA hydrogel showed a modulus drop from 1154.9 MPa (dry) to 0.21 MPa (swollen), enabling large reversible deformation while maintaining printing precision. Among five Fe3O4/HEMA formulations (0-10 wt%), 7.5 wt% HEMA in the Fe3O4/HEMA magnetic resin achieved optimal interfacial bonding, increasing tensile strength by 2.3 times and elongation by 3.1 times compared with the undoped resin. A cantilever and a compact magnetic aperture of 6.5 mm in diameter were fabricated to validate the approach. The aperture achieved a 69.4% increase in opening diameter (from 1.60 to 2.71 mm) under a 120 mT magnetic field, confirming reliable multi-material coupling and controllable actuation. This strategy provides an effective pathway toward multi-material magnetic devices with reliable interfacial integration and accurate motion control in optical and soft robotic systems.

Maskless lithography centered on digital micromirror devices (DMDs) is widely used for high precision fabrication of complex structures due to its advantages of high speed and low cost. However, the widespread adoption of DMD-based digital lithography remains hindered by its limited capability in fabricating high-precision submicron patterns-a challenge stemming from inherent optical aberrations, stray light interference during projection, and inconsistent focal plane control. Here we present a sub-micron digital lithography technology based on a dual-telecentric optical system. Using resin as the lithographic medium, this technology significantly suppresses optical aberrations through the dual-telecentric optical design, reduces the influence of stray light with Monte Carlo ray tracing, and employs an intelligent autofocus algorithm to achieve precise focal plane control. This enables the fabrication of patterns with feature sizes below 0.5 mu m over a manufacturing format exceeding 0.5 mm in a single-step planar projection process. This study demonstrates that resin materials can be used for high-precision digital lithography, offering high processing speed and good process controllability, and provides an alternative material and technological approach for submicron-scale fabrication.

With the escalating severity of noise and electromagnetic pollution, the demand for high-efficiency integrated sound and electromagnetic wave absorption structures has become increasingly prominent. However, under the stringent requirement of lightweight design, the compact integration of these two functionalities into a single structure remains a key challenge. To address this issue, based on the structure-material-function integrated design concept, this study proposes a multifunctional labyrinth metamaterial (MLM) through the ingenious combination of labyrinth structures and wave-absorbing lattices. This design achieves the synergistic enhancement of acoustic and electromagnetic performances: the cover plate required for acoustic functionality serves as a wave-transparent structure, which significantly improves the electromagnetic impedance matching characteristics; meanwhile, the lattice needed for electromagnetic functionality provides an additional energy dissipation for acoustic absorption. Ultimately, with an ultrathin thickness of 16 mm, MLM successfully realizes broadband electromagnetic wave absorption in the frequency band of 2.72-18 GHz and broadband acoustic absorption in the frequency band of 380-460 Hz. This research provides a novel solution for noise and electromagnetic protection in high-end fields such as transportation, aerospace, and national defense, exhibiting significant application prospects.

Plastic ball grid array (PBGA) packages are widely used in modern electronic systems, yet their non-hermetic encapsulation makes them highly vulnerable to electrochemical migration (ECM) and interfacial delamination under humidity-thermal-electrical loading. In this work, the failure mechanisms of PBGA-related interconnect structures were systematically investigated through ECM experiments, hygrothermal aging tests, reflow reliability evaluation, and multi-physics finite element simulation. ECM tests revealed that bare Cu conductors exhibited rapid dendritic bridging under high humidity and electrical bias. Under a 10 V bias, dendrite initiation occurred at 29 s and electrical short-circuit bridging was achieved at 52 s. In contrast, SAC305/OSP/Cu electrodes showed more complex ECM behavior due to multi-metal dissolution and precipitation. At 10 V, dendritic growth was observed at 384 s and short-circuit failure occurred at 392 s. Hygrothermal aging results demonstrated that PBGA packages primarily failed by delamination, initiating at die corners and propagating inward. Under 60 °C/85% RH, severe delamination appeared after 192 h and expanded to nearly the entire die-molding compound interface after 1000 h. Baking treatment effectively mitigated moisture-induced damage and reduced delamination after reflowing. Multi-physics simulations indicated that Joule heating accelerated moisture diffusion by increasing package temperature. Under moisture-thermal-electrical coupling, maximum stresses reached 134.9 MPa in the interconnect region and 83.8 MPa in the die region, indicating thermal stress dominance and non-linear coupling between thermal expansion and hygroscopic swelling.

This study presents a general toolpath planning framework integrated with multiple path generation strategies for continuous fiber-reinforced polymer additive manufacturing (CFRP-AM). Built upon the concept of offset weighting, the proposed method achieves strong adaptability to complex geometries and enables flexible fiber placement while providing tunable mechanical performance with excellent properties. To further enhance manufacturability and quality, a path filtering process and a novel optimization approach are introduced to mitigate potential fiber damage during deposition. Finite element analysis and mechanical testing of specimens fabricated with different strategies reveal that structural stiffness increases with the offset weight of the shape contour, while a balanced distribution of offset weights between shape and hole contours yields a higher load-bearing capacity. Moreover, varying offset weighting strategies cause migration of resin-rich regions, influencing local stress distributions and failure modes. A hybridization of different offset weighting strategies can further improve mechanical strength. Specifically, the hybrid-strategy specimen demonstrates a 22.26% increase compared with the strongest single-strategy specimen. This work establishes a novel toolpath planning framework for CFRP-AM, providing a solid foundation for future hybrid strategies while enabling enhanced control over fiber layout and improved structural performance in complex composite parts.

Soft growing robots, as highly mobile pneumatic membrane robots, are limited in control performance due to their soft structure and nonlinear mechanical properties, especially under dynamic conditions. Therefore, developing reliable control strategies for the robot is essential. This study proposes a dual-thread, goal-oriented control strategy for soft growing robot that combines planning and control. By integrating graph convolutional networks with deep reinforcement learning, the global path planning method is better suited to the self-growing behaviors of soft robots, leading to improvements in both computational efficiency and accuracy compared to inverse kinematics planning methods. Motion control reduces the adverse effects of deformation errors caused by its own low stiffness or by disturbances in the external environment. This strategy effectively combines reinforcement learning-based global planning with a multiple closed-loop motion control system, addressing the issues of low precision and reliability under dynamic conditions. Experimental results demonstrate that the robot achieves a tracking accuracy of 11.83 mm within a 5-meter range and successfully tracks and approaches a non-cooperative dynamic target. These results highlight the significant potential of the proposed approach in applications such as target capture and dynamic manipulation.

Colorectal cancer is a major global health burden and a leading cause of cancer-related mortality. Magnetically driven micro/nanorobots have been widely explored for cancer-related biomedical applications. However, translating these systems into precise physical interventions remains challenging due to undesirable side effects. Here, we report a magnetic-field-controlled wheel-like microswarm system for targeted mechanical grinding of cancer cells. The microswarms consist of a nickel-diamond composite structure, providing magnetic responsiveness and mechanical cutting capability. Their motion can be precisely controlled under external magnetic fields, enabling accurate localization and controlled locomotion. We validated the grinding capability through nanocopper layer removal experiments and further demonstrated its performance in in vitro HeLa cell experiments. We evaluated biosafety through hemolysis, coagulation, and cytotoxicity assays, which indicate acceptable biocompatibility under appropriate conditions. Overall, the wheel-like microswarms provide a physical paradigm for localized cancer cell elimination and may expand the application of micro/nanorobotic systems in precision oncology and biomedical engineering.

Tailoring the angular distribution of thermal emission is crucial for applications in space thermal management, infrared stealth, and energy systems. The inverse design of nonlocal metasurfaces remains challenging due to the high-dimensional parameter space and computationally expensive full wave simulations. This work presents and experimentally validates an efficient, deep learning driven inverse design platform for nonlocal thermal photonic metasurfaces with customized directional emissivity. First, by applying particle swarm optimization (PSO) to introduce perturbations to a bound state in the continuum (BIC) metasurface, we demonstrate precise control over the angular emissivity profile within a +/- 60 degrees range. Fourier-transform infrared spectroscopy and long wave infrared thermal imaging confirm the intended asymmetric emission, showing excellent agreement between experiments and simulations. To overcome the limited design freedom of perturbation-based strategies, we further develop a global optimization framework. It employs Non-Uniform Rational B-Splines (NURBS) for highdegree-of-freedom meta-atom parameterization, accelerated by an end-to-end deep learning surrogate model linked to spatiotemporal coupled-mode theory (STCMT). This differentiable surrogate bypasses repetitive fullwave simulations and enables efficient gradient based optimization without adjoint methods. Metasurfaces fabricated using this workflow exhibit thermal emissivity profiles at 150 degrees C in excellent agreement with predictions, achieving a normalized root mean square error below 0.15. This work demonstrates a robust and scalable platform for the inverse design of high performance nonlocal thermal metasurfaces with complex spectral-angular responses.

High-precision three-dimensional (3D) printing has enabled the fabrication of architected microlattices with complex geometries and tunable functionalities, offering new opportunities for electrochemical energy storage devices. In particular, 3D polymer octet-truss lattice frameworks exhibit exceptional mechanical robustness, structural regularity, and customizable porosity, making them promising candidates for electrode applications. However, current fabrication techniques often face challenges in achieving the required precision and structural integrity for advanced applications. In this study, projection micro stereolithography (P mu SL) was utilized to fabricate high-resolution 3D electrode substrates based on octet-truss microlattices. The printed structures were systematically optimized for both mechanical stability and printing accuracy. Electrochemical plating and magnetron sputtering were employed as surface modification techniques to improve the physicochemical characteristics of the lattices and introduce lithium-affinitive functionality. The resulting 3D microlattice electrodes demonstrate high structural precision and enhanced electrochemical performance, highlighting their strong potential for integration into advanced lithium metal batteries and related energy storage systems.

Despite the immense potential of metamaterials in acoustics and mechanics research, effectively integrating their advantages to meet specific application requirements remains a formidable challenge. In this study, we present a novel approach to designing a multifunctional metamaterial by combining Helmholtz resonant sound absorbers with lattice structures, successfully achieving integration of sound absorption and impact resistance capabilities. To accelerate the design process, we propose a neural network-driven impedance calculation model that can be flexibly applied to parallel structures with varying numbers of units. By integrating this with an optimization algorithm, our parallel array structure achieves an average sound absorption coefficient of approximately 0.87 within 300-600 Hz and on-demand sound absorption design based on the noise spectrum, while achieving a roughly 39% increase in specific energy absorption performance compared to traditional Helmholtz resonators. Overall, our study provides an innovative paradigm for designing combined acoustic/mechanical metamaterials and accelerates optimal design of metamaterial parallel arrays for noise control.

Three-dimensional packaging technology is constantly advancing, and more and more functional devices are being integrated into micrometer-scale spaces. This compresses overall temperature range that the system can withstand into an extremely small range, which raises higher demands for quick heat evaluation in the early stages of structural design. This paper proposes a method for modeling the thermal resistance network based on the chip layered structure, which describes the transient temperature variation during the bonding process. The method involves detailed modeling of the chip packaging structure, dividing nodes according to material differences and dimensional parameters of each layer. It analyzes the heat transfer paths and constructs the network accordingly. Additionally, the thermal performance of the packaging structure is abstracted into thermal resistance and thermal capacitance, with the RC circuit characteristics being used to simulate the temperature variation when the structure is subjected to heat. Through this thermal resistance model, the influence of structural dimensions and materials on heat transfer characteristics is studied. The findings indicate that while changing the substrate thickness can control the temperature difference, it also carries the risk of bonding failure. In contrast, changing the distance from the chip to the bonding surface proves to be a more effective and reliable approach. Additionally, the model accuracy was verified using ANSYS finite element simulation. The results show that, compared to the finite element solution, the temperature analysis error at the target points is at most 4.17%, demonstrating that the thermal resistance network model accurately reflects the transient temperature variation of the structure under heating. The research presented in this paper provides a fast and precise method for node temperature analysis, which is of significant importance for improving the efficiency of early-stage dimensional parameter design of microsystem packaging structures.

The practical implementation of aqueous zinc-ion batteries (AZIBs) is limited by uncontrolled zinc (Zn) dendrite growth during anode plating, compromising both safety and cycle life. Typically, Zn plating proceeds via 2D growth along the six equivalent prismatic [ 10 1 ¯ 0 ] $10\bar 10]$ directions of the hexagonal close-packed (HCP) Zn lattice, forming hexagonal platelets that promote dendrite formation. Here, an effective electrolyte engineering strategy is presented using rare-earth ions to regulate Zn plating. Combined multiscale experimental analyses and computational modeling reveal that these ions preferentially adsorb onto the prismatic { 10 1 ¯ 0 $10\bar 10$ } facets, suppressing lateral epitaxial growth of the basal (0002) planes. This redirects Zn plating toward an apparent screw dislocation-driven growth along the [0001] axis. The resulting growth pathway, together with randomly oriented Zn nucleation, yields dense, uniform, and dendrite-free Zn layers with markedly improved cycling stability and high depth-of-discharge operation, thereby challenging the prevailing assumption that dendrite suppression requires (0002)-oriented growth parallel to the substrate. This work provides new mechanistic insights into Zn plating dynamics and establishes a scalable strategy for stable, dendrite-free Zn anodes in next-generation AZIBs.

A three-dimensional(3D) package using a micro bump is a key technique to achieving high-density integration, fine spacing and smaller size. However, duo to the increase of bump density and chip layer, monitoring internal defects within the bump has become increasingly challenging. In this paper, the active thermography is used for in-situ monitoring of inside defects during the bonding process of a 3D package. The two-dimensional heat resistance thermal resistance network is constructed and heat conduction of different defects in the bonding process is analyzed. An experimental investigation is carried out to inspect the inside defect, such as bump missing and bridge at the top, intermediate, and bottom, respectively. The temperature curve of the bump is acquired, and results show that the maximum temperature of the missing bottom bump is 18.05 degrees C lower than the normal. The maximum temperature of the bottom bumps bridge is 16.61 degrees C higher than the normal. The void of top is lower than that of the normal, and the temperature difference is 3.325 degrees C. The support vector machines (SVM) is used to defect classification of bumps. The Computed Tomography (CT) is used to verify the method. This work introduces a new method for the inside defect in-situ monitoring of bumps while providing valuable inspiration for future research on 3D package online repair.