Recent investigation shows that chiral metamaterials consisting of freely rotatable units can generate twist buckling under large compression, simultaneously achieving high stiffness, high buckling strength, large recoverable strain, and high energy density. However, the torsional buckling behaviors in multilayer chiral structures and their intrinsic mechanisms are still unexplored. Here we develop chiral metamaterials composed of multilayer units, which are stacked with mirror-symmetric, translationally symmetric (i.e., co-directional), or gradient arrangements. We systematically investigate their compressive twist buckling behaviors based on simulations and experiments. Various interesting twist-buckling modes are found in these systems, and some modes appear randomly, depending on the number of layers and symmetry. Particularly, nearly all models exhibit the rebound behavior under large compression, where some layers recover from buckling but other layers undergo snap-through and thus buckle deeply, causing the energy tunnelling effect. These behaviors are dominated by bifurcations and instability of twist buckling. Furthermore, we demonstrate that the gradient design can robustly guide the buckling sequence, offering stepwise buckling curves. With non-optimized gradient parameters here, the multilayer models can improve the peak buckling loads by 2.4 times, and improve the specific energy absorption by 34% to 61% relative to the original bilayer units. This research broadens the understanding of chiral twist buckling and provides feasible methods for designing advanced structures and metamaterials.

Flexible structures, like slender rods, beams and pipelines suffer from dense modal distributions, making broadband vibration suppression highly challenging. Metamaterial bandgaps provide a viable solution, though traditional methods-using low-frequency locally resonant bandgap and high-frequency Bragg bandgap-are either narrowband or demand impractical mass ratios. This study introduces a reverse strategy using a slender pipeline as a flexible model. We synergistically couple a low-frequency Quasi-Bragg bandgap (0-129 Hz, zero-frequency bandgap) from periodic clamps with a high-frequency locally resonant bandgap using lightweight resonators (similar to 10% mass ratio). We analyze the origin of each bandgap and the edge frequencies, through waves, vibration, and mode shapes, then examine the influence of system parameters to analyze the modulation patterns of the bandgaps to widen the bandgaps. Specifically, we find that nonperiodic clamps can broaden the low-frequency bandwidth, and further superposing Bragg bandgap and locally resonant bandgap can broaden the desired high-frequency bandwidth. Experiments considering different additional resonators, lattice constant, bandgap coupling, and nonperiodic supports are established to validate the theory. By combining different effects in experiment, we achieve substantial (20-60 dB) and nearly full-band (0-800 Hz) vibration reduction. This work establishes a robust framework for designing flexible metamaterials, offering a highly effective vibration control strategy for critical infrastructure.

Motivated by the knowledge gap on nonlinear sound transmission of acoustically excited structures with large geometric deformations, this paper proposes the Spectral Chebyshev-Incremental Harmonic Balance (SC-IHB) method for analyzing the nonlinear sound transmission properties of a composite laminated plate. The plate generates large deformation vibration subjected to strong sound excitation, modeling in the frame of Von Karman theory and Rayleigh-Ritz principle. It reveals that nonlinearity entails the suppression of structural vibration and significantly increases the sound transmission loss (STL) within the resonance band, due to primary resonance condition. Two specific STL valleys are observed in non-resonance bands, in which vibration is suppressed but total transmitted sound is increased, attributing to the superharmonic resonances enhanced by geometric nonlinear during sound radiation process. The enhancement index just right equals to the superharmonic order. Moreover, geometry nonlinearity also slightly reduces STL in bifurcation band. These properties are confirmed by the time-domain integration method. Therefore, this paper reveals properties of nonlinear sound insulation, and elucidates their harmonic resonance mechanisms. The study deepens the understanding of nonlinear sound transmission of plates, and provides theoretical guidance on the design of high-performance sound proofing structures.

Nonlinear acoustic meta-materials/structures (NAMs) hold great promise for ultra-low and ultra-broadband vibration suppression through chaotic band mechanisms, but at the expense of compromising the original bandgap benefits. To concurrently harness the benefits arising from both bandgaps and chaotic passbands, we propose a dedicated design paradigm in which both linear and nonlinear oscillators are integrated in meta-plates. Harmonic balance method and time-domain integration are utilized to compute the system responses and evaluate the performances of two types of meta-plates. Type I design leverages the complementary benefits of linear acoustic meta-materials/structures (LAMs) and NAMs. The design entails the stability of the bandgap, in which additional 17 dB improvement is achieved over traditional NAMs, while maintaining a stable chaotic band. Type II extends the Type I design, elucidating the influence of nonlinearity location, linear stiffness and damping. Based on the insights gained, broadband vibration suppression has seen a significant extension into the lower frequency range, along with a notable improvement in vibration suppression effectiveness. Our concept is demonstrated experimentally on a meta-plate consisting of linear and vibro-impact nonlinear oscillators. The study alludes to a new route for designing high-performance meta-structures in views of structural vibration control.

Mitigating structural sound radiation is crucial for numerous engineering applications, which requires simultaneous handling of structural vibration and sound radiation. Nonlinear acoustic metamaterial (NAM) plates have demonstrated remarkable broadband vibration suppression abilities, yet their sound radiation characteristics and the corresponding underlying physical mechanisms have not been fully explored. This issue is investigated in this paper using a Rayleigh integral model and spatial-domain analysis. It is shown that the introduction of nonlinearity mainly leads to fluctuations in both sound radiation efficiency and sound power near the bandgap, whereas sound radiation reduction in other regions is primarily governed by vibration. Notably, the nonlinearity-induced third harmonics significantly enhance sound radiation, driven by energy pumping near the bandgap and the high radiation efficiency at mid-to-high frequencies. To mitigate this, linear-nonlinear band control strategies are proposed through eliminating harmonic interference near the bandgap, alongside a proper deployment of structural damping to suppress the third harmonic radiation in the mid-to-high frequency regime. By fine-tuning system parameters, we ultimately achieve broadband sound control, as evidenced by a systematic reduction of 8-30 dB at all resonant peaks below 600 Hz, as a result of optimized design with only a 10% mass penalty.

Dynamic vibration absorbers (DVAs) serve as critical passive control devices. However, their conventional designs are characterized by high directional sensitivity and large additional mass, failing to meet the rigorous demands of modern equipment for multi-directional coupled vibration suppression and lightweighting. To address these challenges, this study establishes an isotropic dynamic model of coupling spring and shell stiffnesses. This model shows that the isotropy degrades with the lightweight design due to a failure mode of shear deformation. Then, by constraining the shear stiffness, a collaborative design framework integrating topology optimization and parameter optimization is constructed to lighten the DVA. Using a 50 Hz DVA as a case study, prototype designs, simulations, and experiments are conducted. The results indicate that the isotropic natural frequencies agree well with the design targets. The shell mass is reduced by 79.8% compared to the conventional rigid shell design. Moreover, in vibration reduction simulations under the same total mass, the optimized absorber further reduces the vibration response by 7.4 dB compared to the rigid shell design.

Abstract To address the problems of high computational cost, poor generalization ability, and inadequate physical consistency associated with frequency response prediction and inverse parameter design for multi-degree-of-freedom (MDOF) vibration systems, we propose an intelligent design method integrating physics-informed and data-driven approaches. Taking a 10-degree-of-freedom lumped mass-spring system as the research object, we first construct a forward prediction model based on the one-dimensional Residual Network-Physics-Informed Neural Network (1D-ResNet-PINN), then design an inverse generation model of the Physics-Constrained Conditional Wasserstein Generative Adversarial Network (PC-cWGAN), and finally establish a closed-loop intelligent design framework integrating the aforementioned forward and inverse models to realize intelligent structural design. Experimental results demonstrate that the forward model exhibits remarkable advantages in prediction accuracy and generalization ability, the inverse model enables end-to-end generation from response requirements to structural parameters with a substantial improvement in computational efficiency, and the construction of the closed-loop framework provides effective technical support for the intelligent design of complex vibration systems.

Mechanical metamaterials with tunable bending stiffness are significant for realizing smart adaptable machines or structures composed of beams, shells and plates. However, different from tuning longitudinal stiffness, realizing broad-range, continuous, and in situ (without global shape morphing) tunability of bending properties remains a major challenge. Here, we report a deformation conversion principle for designing meta-beams/plates that offer such extraordinary tunability. The metamaterials incorporate planetary gear assemblies as tension-compression fibers within sandwich beams or plates, effectively transferring the localized tunable longitudinal stiffness of these geared units into the global tunable bending stiffness. This principle enables diverse tunable bending modes, including the static bending deformation, vibrational modal shapes and frequencies, and bending wave bandgaps. Their smoothly tunable properties and mechanisms are demonstrated based on analytical, numerical and experimental methods. This work offers a new pathway for developing structures with adaptively tunable bending properties that are free from the constraints of intrinsic material properties, elucidating innovations and applications of mechanical metamaterials and structures for intelligent systems.

Extreme climate events are becoming increasingly frequent, and flood disasters have been one of the most frequent and devastating forms of such events, threatening the lives and property of coastal residents. To reduce the potential costs to residential lives and property, fast and reasonable predictions and decisions should be made for quick emergency response based on timely flood routing analysis. This study proposes a hybrid model that aims to achieve real-time forecasting of time-varying flood routing and inundation maps by integrating hydrodynamic analysis and deep learning. A computational fluid dynamics (CFD) database of 125 simulated flood scenarios is established under varying flood frequency and runoff roughness of potential routing areas. Various deep learning networks, such as the long short-term memory (LSTM) network, convolutional neural network (CNN), and transpose convolutional neural network (TCNN), are used in this study to develop the proposed hybrid model for real-time and visual flood routing analysis. The results show that the model can quickly generate flood inundation maps with the input of real-time water level monitoring histories along the drainage basin, which provides valid support for emergency decision-making in various flood scenarios.

ABSTRACT Actively and smoothly tunable mechanical metamaterials are in high demand for adaptive, variable‐stiffness structures in smart machines. However, existing designs are largely restricted to tunable transverse deformation, reciprocal response, and linear dynamics. Here, we propose a novel gear‐based design paradigm—using Taiji planar gears and planetary gear assemblies as building blocks—that overcomes these limitations by enabling simultaneous control of translational and torsional stiffnesses, shear nonreciprocity, and programmable nonlinear dynamics. Our metamaterials achieve in situ, continuous tuning of shear stiffness by 30–100×, break reciprocity under positive versus negative loads, and allow the nonreciprocity ratio to be tuned by over 100×. Meta‐resonators constructed from these units showcase an application example exhibit broadly tunable transverse and torsional resonant frequencies. Furthermore, we demonstrate that static nonreciprocity serves as a precise control knob for dynamic nonlinearity—a property traditionally fixed and nearly impossible to tune in conventional materials. Analytical models and analyses elucidate the underlying mechanisms and extendable design freedoms. This work bridges the critical gaps in mechanical metamaterials and dynamics, offering a practical pathway to control both linear and nonlinear structural deformations, elastic waves, and vibrations.

Abstract Construction activities impose substantial cognitive demands on workers, making mental fatigue assessment critical for occupational health and safety (OHS) management. Portable wearable electroencephalography (EEG) devices offer practical advantages in mental fatigue identification. However, they are typically limited to a few channels, restricting the spatial coverage of brain activity and potentially limiting the ability to capture fatigue-related spatial patterns. To address this limitation, a sensor-level scalp EEG representation mapping framework was developed to enhance spatial information in fatigue assessment. First, a stacked long short-term memory (LSTM)-based regression model is developed to approximate multichannel scalp EEG representations from preprocessed single-channel in-ear EEG and electrocardiography (ECG) signals. Quantitative evaluation demonstrates stable predictive performance, with mean absolute error ( MAE ) and root mean square error ( RMSE ) both below 24 μV across fatigue states. Second, the predicted scalp EEG signals are transformed into EEG topographic maps to enhance spatial interpretability. The proposed framework enables portable yet spatially informative fatigue assessment and provides methodological support for future OHS-oriented monitoring systems.

Mechanical metamaterials with high recoverable elastic energy density, which we refer to as high-enthalpy elastic metamaterials, can offer many enhanced properties, including efficient mechanical energy storage1,2, load-bearing capability, impact resistance and motion agility. These qualities make them ideal for lightweight, miniaturized and multi-functional structures3–8. However, achieving high enthalpy is challenging, as it requires combining conflicting properties: high stiffness, high strength and large recoverable strain9–11. Here, to address this challenge, we construct high-enthalpy elastic metamaterials from freely rotatable chiral metacells. Compared with existing non-chiral lattices, the non-optimized chiral metamaterials simultaneously maintain high stiffness, sustain larger recoverable strain, offer a wider buckling plateau, improve the buckling strength by 5–10 times, enhance enthalpy by 2–160 times and increase energy per mass by 2–32 times. These improvements arise from torsional buckling deformation that is triggered by chirality and is absent in conventional metamaterials. This deformation mode stores considerable additional energy while having a minimal impact on peak stresses that define material failure. Our findings identify a mechanism and provide insight into the design of metamaterials and structures with high mechanical energy storage capacity, a fundamental and general problem of broad engineering interest. High-enthalpy elastic metamaterials constructed from freely rotatable chiral metacells have high stiffness, large recoverable strain and improved buckling strength.

Variable-stiffness materials/structures are poised to optimize system performance in complex environments. Mechanical metastructures hold significant potential for smoothly and broadly tuning both linear and nonlinear properties. However, current tunable metastructures often exhibit asymmetric tension-compression stiffness and underutilize nonlinear tunability. Here we propose novel programmable metastructures with symmetrically tunable linear and nonlinear behaviors. Inspired from planetary gear systems, the tunable metacell comprises a circular slide rail and rotatable bidirectional pivots, enabling balanced stiffness under tension and compression, with a 30× tunable linear stiffness. Incorporating a subtle clearance within the metacell, we uncover a robust “clearance-lever” mechanism that enables a remarkable 106× tunability of nonlinear stiffness, smoothly transitioning from linear to strongly nonlinear states. Beyond static properties, the metastructures present versatile tunability on both frequency and linear and nonlinear vibration response spectra. The dynamic metastructure designed based on this strategay offers tunable bandgap for elastic wave manipulation. Therefore, this work not only provides a new method for designing programmable metastructures, but also demonstrates its broad application sceneries for vibration isolation, absorption and wave manipulation.

The intrinsic coupling of torsion (shear) properties with the Poisson effect is typical of the chiral materials subjected to compressive loads. Pure torsion functionalities with suppressed Poisson effect are of great interest for innovative actuators capable of switching displacement modes in confined or specialized assembly spaces. However, both the torsion property and Poisson effect may be dependent on the strain, which makes it challenging to design the constant torsion functionality with zero Poisson effect under large deformation. This study develops an inverse design method of a compression-torsion mechanical metamaterial with a suppressed Poisson effect. In the method, a nonlinear representative volume element model is built to characterize the coupling deformation behavior under large compression strain. Then, a topology optimization model is formulated to provide a high-dimensional design space, and it maintains high computational efficiency via the representative volume element model. Freeform microstructure topologies with tailored torsion functions and near-zero Poisson's ratios are generated by this topology optimization formulation. The performance of the designed microstructures is validated at both the microscale and macroscale. Furthermore, experiments show the torsion angle of the metamaterial cylindrical shell is tunable via local confinement, overcoming the difficulty of reconstructing the metamaterial to change the torsion functionality.

Metallic metamaterials that combine superelasticity, high energy density (enthalpy), and heavy load-bearing capacity have been long sought for applications in energy absorption, impact protection, and vibration control. However, achieving this combination remains elusive due to limitations of material strength and design paradigm. Here, inspired by DNA supercoiling, we report all-metallic metamaterials composed of helices that undergo hierarchical twist-buckling under compression. This supercoiled geometry synergistically enhances load resistance and energy storage while mitigating stress concentrations, enabling recoverable strains up to 50%, tripling the buckling strength and quadrupling the enthalpy of densely packed prismatic lattices. An accurate deep-buckling theory clarifies how global twist elevates strength and energy density, while local curvature ensures superelasticity. Using steel assemblies, we demonstrate robust cyclic superelasticity and create quasi-zero-stiffness isolators that maintain ultralow resonance frequency (f0 ≤ 2 Hz) while supporting 100-1000× higher loads than existing designs, bridging the critical gap between high load capacity and low-frequency isolation, and breaking through the theoretical limit of conventional springs. Our work establishes a general, scalable and manufacturable principle for superelastic metallic metamaterials, opening new pathways for advanced applications in vibration mitigation, energy absorption, and protective structures.

Regular inspection of underground sewer networks is essential for the healthy operation of drainage systems and urban safety. This paper proposes a framework based on an enhanced Transformer for small-sample defect classification and localization. The framework includes data augmentation using Mixup, a novel Feature-aware Swin Transformer (FSwin_T), and class activation mapping (CAM) for weakly supervised localization. The proposed FSwin_T model combines the features of the residual module and the Transformer, increases the complexity of extracting feature information, and solves the poor training effects on small-sample datasets. We address the issue of poor classification accuracy in small-sample datasets by using Mixup and employ five CAM techniques to interpret the FSwin_T model, enabling defect localization and visualization. Our research demonstrates that the proposed enhanced Transformer framework has better defect classification results without relying on manual annotation, locates and visualizes key information in images, and provides certain explanations for inspectors to identify pipe defects.

High-speed aircraft generally endure complex and random vibration environments, thus mitigating random vibrations in the wing is critical to ensuring flight safety. Nonlinear acoustic metamaterials (NAM) provide efficient ways for structural vibration reduction. This paper investigates the random aeroelastic vibration of a supersonic NAM wing plate, which has never been studied. Based on a theoretical model combining mode superposition and modified third-order piston theory, extensive numerical simulations and statistical analyses are performed to show the aeroelastic properties of pure plate, linear and nonlinear metamaterial plates. The results indicate that, under broadband random excitation, the mean value, standard deviation, and maximum peak value of the timedomain displacement and velocity responses of the NAM plate are significantly reduced by >50 %, demonstrating superior vibration reduction capabilities compared to the linear metamaterial plate. The parameter analysis reveals the influence regularities of aerodynamic and structural parameters on the random vibration reduction properties of the NAM plate. Furthermore, we design the NAM plate composed of double frequency resonators, which exhibits superior reduction effects on broadband random vibration under low damping condition. This research provides valuable insight into the aeroelastic vibration control of supersonic wings in complex aerodynamic environments, and promotes the application of strongly nonlinear metamaterials.

Metamaterials can be engineered with tunable bandgaps to adapt to dynamic and complex environments, particularly for controlling elastic waves and vibration. However, achieving wide-range, seamless, reversible, in-situ and robust tunability remains challenging and often impractical due to limitations in bandgap mechanisms and design principles. Here, we introduce gear-based metamaterials with unprecedented bandgap tunability. Our approach leverages Taiji planetary gear systems as variable-frequency local resonators, which allows the metamaterial to seamlessly modulate its bandgap's center frequency by 3-7 times (e.g. shifting from 250-430 Hz to 1400-2000 Hz), surpassing existing methods. Notably, this is achieved without pre-deformation or major changes to its static stiffness in the wave propagation direction, ensuring robust in-situ tunability and smooth control even under heavy static loads. This enables adaptable wave manipulation for versatile smart platforms.

A fully multiplexed metasurface (FMMTS) is presented and exploited to engineer a low-profile, compact, and wideband metasurface antenna (MTA). The proposed FMMTS element is constructed by slotting and subdividing a conventional hexagonal radiating patch into three congruent diamond-shaped segments, with each one being shared by adjacent elements. This full-reusing configuration drastically enhances spatial efficiency. Additionally, the increased inter-unit gaps lead to supplementary edge capacitances, which effectively lower the resonance frequency of the FMMTS radiator, allowing for a more compact radiation aperture. Then, the FMMTS array is modified for miniaturization, and the characteristic mode analysis is adopted to explain its mechanism. As a proof of concept, the modified FMMTS array is coupled to a T-shaped feeding network through a rectangular aperture, forming a linearly polarized MTA and realizing an impressive impedance bandwidth of 57.83% and a peak gain of 6.93 dBi, all within an extremely compact overall size of 0.34 lambda(low) x 0.34 lambda(low) x 0.035 lambda(low) (lambda(low )is the lower operating wavelength in free space), which shows a size reduction of approximately 50% when compared to recently developed wideband MTAs.