High-precision in vivo therapeutic technologies that establish three-dimensional (3D), multimodal neural interfaces with targeted biotissues offer significant clinical potential for the timely treatments of localized peripheral nerve injury (PNI). Current approaches for this purpose such as implantable devices face challenges in terms of percutaneous wires and/or nondegradable designs, and support only single-mode operation that lack microscale spatial resolution. Here, we develop a miniaturized, self-wrapping system that yields wireless, multimodal neural interfaces with 3D adaptation across localized peripheral nerves at scales ranging from tens of micrometers (15 μm) to millimeters. Such platform integrates multilayer architectures that include SiN x layers as the mechanically triggered substrate for 3D wrapping, with multimodal treatments via MXene and drug-loaded layers for photothermal stimulation and pharmacological release. Experimental and computational studies establish operational principle as the basis for the combination of long-term photothermal therapy and transient drug delivery at high spatiotemporal resolution. In vivo tests on living rat models demonstrate that the implantable neural interface can roll up across the localized, dynamic surface of injured nerves, providing sustained treatments over 1 mo in a fully bioresorbable design after the healing process. These findings create future opportunities of such wireless, multimodal system with 3D self-wrapping techniques for precise PNI therapeutic strategies.

Exact analytical benchmarks of structural stochastic responses and reliability are desirable but have intractable issues. To avoid calculations of inverse mappings and its Jacobian in a change-of-variable formula, this study introduces a rigorous framework of the probability density integral equation (PDIE). The new derivation of PDIE is established based on the probability conservation without the calculation of Jacobian of inverse mappings, exhibiting a wider scope than the change-of-variable formula, especially for the mappings of multiple inputs and a single output. The closed-form probability density functions (PDFs), joint PDFs, high-order moments, correlation coefficients, and failure probabilities are achieved by analytically solving the PDIE whatever the existence of inverse mappings and Jacobian. The proposed analytical method is applicable to nonlinear, nonmonotonic, and unequal-dimensional input-output random vectors. The results are demonstrated by several examples, i.e., cantilever beams, rectangular plates, and frame buildings, which show that the obtained analytical solutions for response statistics and rare-event failure probabilities are superior to those of existing studies and Monte Carlo simulation. It is indicated that the obtained analytical solutions can be utilized to not only verify the accuracy of numerical algorithms but also reveal the effects of load variability and material and geometric parameters on system response and reliability.

Functionally graded plates with cutouts are common load-bearing structures in engineering,making the study of their dynamic behavior crucial.For plates with regularly shaped cutouts,the symplectic superposition method combined with subdomain decomposition technique can be used to establish a comprehensive analytical solution framework.However,when the research object is extended to plates with arbitrarily shaped cutouts,which have broader applications,the analytical solution faces significant challenges due to the increased complexity of the bound-ary conditions.While approximate or numerical methods exist,they may suffer from time-consuming computations and strong mesh dependency,often leading to insufficient accuracy in results.A novel solution framework that inte-grates the symplectic superposition method with the transfer learning technique is established.It leverages the analyti-cally solvable natural frequencies of functionally graded rectangular plates with rectangular cutouts for knowledge trans-fer,thereby achieving efficient and highly accurate solutions for the free vibration problems of functionally graded plates with arbitrary quadrilateral cutouts.First,a multi-layer perceptron neural network is pre-trained on large-scale analytical solution dataset to extract the complex mapping relationships of geometric parameters between different shapes.Sec-ond,the pre-trained model is transferred based on few-shot finite element simulation data,effectively transferring knowledge from the natural frequency dataset of the rectangular plates with rectangular cutouts to the free vibration of plates with arbitrary quadrilateral cutouts.Finally,the accuracy and applicability of the proposed solution framework for predicting the natural frequencies of functionally graded plates with arbitrary quadrilateral cutouts are validated,using metrics such as mean squared error and coefficient of determination.The transfer learning technique is used to lever-age small-sample data and existing analytical solutions to efficiently and accurately solve free vibration problems of functionally graded with arbitrary quadrilateral plates cutouts.The proposed framework,adaptable to various working conditions through model parameter adjustments,offers a novel strategy for the mechanical analysis of complex-shaped plates.

As one of the fundamental physical parameters characterizing sensor performance, the refractive index (RI) plays a significant role in the field of fiber optic sensing. This paper proposes a Fabry–Perot interferometer (FPI) RI sensor based upon an open cavity fabricated in a polymethyl methacrylate (PMMA) sheet. The sensing unit, designated FPI1, is constructed by etching a microgroove on the surface of a PMMA sheet using a CO2 laser, into which a single-mode fiber is embedded, forming an optical interference cavity open to the external environment and enabling high-sensitivity response to RI changes. To further enhance sensitivity, a Vernier effect is introduced to construct a compound sensor S1. The reference interferometer FPI2 in S1 is made by fusion splicing a single mode fiber (SMF)—capillary—SMF structure, and its free spectral range is comparable to FPI1, while remaining insensitive to RI variations. Experimental results demonstrate that the RI sensitivity of FPI1 is −1306.59 nm/RIU, whereas that of S1 reaches −12511.18 nm/RIU, corresponding to an amplification factor of ∼9.6.

Two air pressure sensors based upon the enhanced vernier effect (EVE) and enhance harmonic vernier effect (EHVE) generated by parallel Fabry-Perot interferometer (FPI) were developed. The sensors were prepared to use polydimethylsiloxane (PDMS) film and femtosecond laser microfabrication technology. FPI1 is composed of the single-mode fiber (SMF) spliced with the 75 mu m quartz capillary, and then coated with the PDMS film on the end face of the quartz capillary. FPI2 and FPI3 consist of SMF, 100 mu m quartz capillary, and thin-core fiber. Drill a through-hole in the capillary wall of FPI2 and FPI3 using femtosecond laser to facilitate air entry and exit. Due to the different sensing mechanisms of FPI1 and FPI2 (or FPI3) for air pressure, the spectral blue-shift of FPI1 and the spectral red-shift of FPI2 (or FPI3) occur during the pressurization process. Therefore, their sensitivity synbols to air pressure are opposite. Compared with the traditional vernier effect (VE), the EVE has a greater amplification effect on sensitivity. FPI1 and FPI2 form the EVE sensor S1. The experimental outcomes indicate that S1 has the air pressure sensitivity of 289.52 nm/MPa, which is much higher than the traditional VE sensors. Additionally, compared with the harmonic vernier effect (HVE), the EHVE has a greater amplification effect on sensitivity. FPI1 and FPI3 form the EHVE sensor S2. The experimental findings indicate that S2 has the air pressure sensitivity of 407.84 nm/MPa, which is much higher than the HVE sensors. The sensors have the advantages of simple preparation, easy reproducibility, stable structure, and low cost. The proposed design provides a new solution for ultra sensitive air pressure sensors.

This study addresses the challenging issue of analytical modeling of forced vibration of rectangular plates in thermal environments, which involves mathematical difficulties in treating complex boundary value problems in higher-order partial differential equations. An effective symplectic superposition method is extended for the present issue, focusing on non-L & eacute;vy-type boundary conditions that were not accurately analyzed by conventional analytical methods. To be specific, an original problem is decomposed into three subproblems, which are solved rigorously through separation of variables followed by symplectic eigen expansion, and the original problem's solution is determined by superposing the subproblems' solutions. Various forced vibration results under different thermal environments and different harmonic load scenarios are presented, showing good agreement with finite element numerical simulation results. Furthermore, the effects of temperature variation, harmonic frequency, simple harmonic load amplitude, and boundary conditions, among others, on the thermal vibration characteristics are explored. The findings delve into the significant impact of thermal environments on the forced vibration performance of rectangular plates, offering a theoretical basis for related structural designs.

High-power near-infrared photonics requires dielectric coatings that combine low optical loss with strong and reliable third-order nonlinearity. We present a Ta2O5 thin-film process based on ion-gun-assisted (IGA) electron-beam evaporation followed by oxygen annealing, benchmarked against conventional deposition without ion assistance. Films (similar to 700 nm) were deposited on thermally oxidized Si and characterized at 800 nm using open-/closed-aperture (OA/CA) Z-scan with femtosecond pulses over 0.45-82.92 GW/mm2, with recovery tests extended to 124.38 GW/mm2. The IGA process in O2/Ar ambient yields a denser microstructure, smoother morphology, and reduced oxygen vacancies. OA Z-scan results demonstrate strongly suppressed intensity-dependent loss in the IGA film: the maximum transmittance decrease remains similar to 0.02% at 82.92 GW/mm2, compared with similar to 0.10% for the non-IGA film with earlier onset (similar to 0.02% at 17.77 GW/mm2). After OA normalization, CA analysis gives Kerr coefficients of n 2 = (1.62-4.08) x 10-14 cm2/W for the IGA film, higher than the non-IGA counterpart (2.25 x 10-15 to 1.41 x 10-14 cm2/W). The damage-onset window (DOW) is significantly extended, from 11.84 GW/mm2 in the non-IGA film to 124.38 GW/mm2 with IGA, representing an approximate to 10.5-fold enhancement. Spatial mapping at 82.92 GW/mm2 further confirms excellent uniformity in the IGA film, while the non-IGA sample exhibits large site-to-site variations. Recovery measurements reveal predominantly reversible nonlinear response in the IGA film, in contrast to persistent absorption and scattering in the non-IGA case. These findings establish IGA-assisted deposition with oxygen annealing as a robust route to Ta2O5 coatings with reduced nonlinear loss, enhanced Kerr response, improved uniformity, and higher optical damage resistance, enabling their deployment in high-power photonic systems.

Triboelectric nanogenerators (TENGs) are promising energy sources and self-powered sensors for the Internet of Things, yet the output current strongly depends on mechanical stimulation speed, severely limiting performance under ultra-low-speed conditions. Although various strategies have been explored to convert relatively low-speed mechanical inputs into high-speed motions, achieving enough current enhancement at ultra-low stimulation speeds remains a significant challenge. Here, we present an arc-based triboelectric nanogenerator (A-TENG) that overcomes this limitation by converting ultra-low-speed inputs into high-speed motions through elastic energy storage and release enabled by an arc structure. The A-TENG achieves a current enhancement exceeding 2000 fold compared with a conventional vertical contact-separation TENG with planar structures at a stimulation speed of 0.1 mm s-1. To demonstrate its practical utility, the A-TENG is implemented as a self-powered telegraph key for Morse code input and identity recognition. This design strategy provides an effective route for enabling TENGs in ultra-low-frequency mechanical energy harvesting and sensing scenarios.

Point set registration is essential for computer vision, pattern recognition and intelligent robotics. Existing registration methods exhibit limited robustness against non-Gaussian noise, outliers and incomplete point clouds in complex engineering scenarios. This paper proposes a robust rigid point set registration method based on the maximum correntropy criterion (MCC). The method integrates the point-to-plane distance metric into correntropy measurement to construct a novel iterative optimization framework. In each iteration, point correspondences are established via nearest neighbor search, and rigid transformation parameters are optimized under the MCC criterion. An adaptive kernel width updating strategy is adopted to balance global convergence and local alignment accuracy. Experimental results on synthetic and real-world point sets verify the effectiveness and robustness of the proposed method. Relevant codes and data are published to https://github.com/ygq0000/mcc.

Investigating the buckling behaviors of cracked plates carries substantial significance, since crack existence induces remarkable modifications to plate mechanical properties, potentially leading to significant degradation of structural load-carrying capability. This study develops a novel analytic solution framework that integrates the finite integral transform (FIT) method with an elementary domain decomposition strategy for solving buckling problems of single-edge-cracked rectangular thin plates. The through-thickness edge crack is modeled as an internal free boundary. The proposed framework exhibits universal applicability to plates with arbitrary combinations of simply supported, clamped, and free edges, and requires no assumptions regarding the form of the solutions throughout the derivation. The framework briefly comprises four key steps: decomposition of a single-edge-cracked plate into four elementary domains, followed by the application of a double cosine FIT to the governing equation of each domain; enforcement of all boundary and continuity conditions pertaining to Kirchhoff shear forces and rotations to eliminate a subset of the unknowns; substitution of inverse transforms into unapplied bending moment and deflection conditions to formulate the complete system of linear algebraic equations; determination of analytic solutions by solving the equations. Comprehensive buckling load/mode solutions of representative single-edge-cracked plates are presented as new benchmarks. A comparison of the solutions with other methods is conducted to validate the effectiveness of the FIT-based new solution framework. Utilizing the derived analytic solutions, a parametric study is conducted to quantitatively investigate the influences of boundary conditions, crack length ratio, crack location, and aspect ratio on the buckling behaviors.

In order to meet the demand for current measurement in industrial production, this study presents a novel high-sensitivity fiber-optic current sensor and conducts experimental verification. The current sensing measurement is achieved using a Fabry-Perot interferometer (FPI) manufactured directly on a thin copper rod. Two single-mode fibers, observed and aligned by a charge coupled device imaging system, are glued onto the surface of the thin copper rod to form a FPI. When the copper rod is powered on, abundant heat is generated and then the copper rod expands, directly changing the length of the FPI cavity. This variation changes the optical path length of the FPI, enabling the indirect measurement of current. The experiment shows that the current square sensitivity of a single FPI can reach 568 ± 10 pm/A2. To further enhance the sensitivity, we used the FPI as a sensing interferometer to fabricate the Vernier effect sensor S1. The experiments found that the current square sensitivity of S1 is 4.7 ± 0.1 nm/A2, which is 8.5 times higher than the sensitivity of a single sensing FPI. Owing to the direct fabrication of the F-P cavity on a copper rod with excellent electrical and thermal conductivity, the sensor is particularly easy to fabricate, robust, and highly sensitive, offering an extremely simple solution for measuring current.

The demand for effective vibration suppression in mechanical and engineering structures continues to grow, motivating the development of vibration-isolation composite metamaterials filled with viscoelastic damping materials. When properly designed, such viscoelastic-filled composite metamaterials can simultaneously deliver enhanced vibration isolation and high load-bearing capacity. However, existing studies remain limited, and the coupled optimization of vibration isolation performance and load capacity has not been fully addressed. In this work, a positive Poisson's ratio honeycomb composite structure (PHCS) filled with a viscoelastic material is proposed and evaluated using finite element analysis (FEA). A surrogate-assisted multi-objective optimization design (MOD) framework, combined with a genetic algorithm, is developed to efficiently achieve global optimization. The geometric parameters of the PHCS are selected as design variables, and a design of experiments (DOE) strategy is used to generate datasets for surrogate-model training and testing. Before surrogate-model construction, geometric and material uncertainty propagation analyses are conducted for the baseline PHCS to quantify the effects of prescribed manufacturing and material-property variations on Tmax, fn, and Fmax, indicating limited response dispersion within the considered uncertainty ranges. The Pareto-optimal solution set is then obtained using the Non-dominated sorting genetic algorithm-II (NSGA-II), and a linear multi-criterion decision making (MCDM) method is subsequently applied to select a representative trade-off design that outperforms the baseline configuration, demonstrating the effectiveness and robustness of the proposed MOD procedure. Finally, quasi-static compression and swept-sine experiments are conducted to validate the numerical predictions and confirm the accuracy of the FEA model. Overall, this study provides an efficient and reliable methodology for improving both vibration isolation performance and load-bearing capacity of viscoelastic-filled PHCS metamaterials with high computational efficiency.

To meet the multi-directional load-bearing and vibration isolation requirements in aerospace environments, this study proposes a composite cellular design paradigm embedding hyperelastic elastomer cores within rigid thin-walled frameworks. The dynamic mechanics of 15 configurations are systematically investigated, establishing a comprehensive dataset of natural frequency, peak transmissibility, loss factor, and multi-axial capacity. Results demonstrate that viscoelastic infilling simultaneously modulates stiffness and damping, effectively suppressing resonance peaks. This isolation performance exhibits strong topology dependence; specifically, the cross-shaped re-entrant configuration (S-7) maximizes local shear deformation in the elastomer, achieving the lowest peak transmissibility. Under increased static pre-loads, S-7 exhibits concurrent reductions in resonant frequency and amplitude due to an intrinsic geometric softening effect, whereas reinforced architectures trigger a volumetric locking effect that rebounds transmissibility. Notably, the composites sustain high damping (loss factor > 0.1) across a broadband frequency range. Finally, a TOPSIS-based multi-criteria framework quantifies the trade-off between load-bearing and isolation, categorizing the topologies into vibration-isolation-dominant, load-bearing-dominant, and synergistic regimes. Moreover, a systematic experimental validation and rigorous performance benchmarking against existing solutions are conducted to evaluate the performance enhancement of the proposed methodology. This methodology provides a foundation for the tailored development of multi-functional composite structures.

This work introduces novel analytical solutions for the buckling of non-Levy-type plate assemblies with line hinges and line supports, overcoming the constraints of current methods that concentrate primarily on Levy-type cases. By utilizing the domain partitioning, we effectively divide plate assemblies into subplates free of internal discontinuities, facilitating the application of the symplectic superposition to derive analytical solutions with satisfactory convergence. Comparisons with the finite element method and the Ritz method confirm the reliability of the obtained buckling solutions. Comprehensive parametric studies reveal the significant effects of the hinge/support positions and the aspect ratios on the critical buckling loads. Moreover, the analytical framework developed in this paper is versatile enough to accommodate mixed boundary conditions and can be extended to thermal buckling. This research not only fills a gap in the existing literature but also deepens the understanding of buckling phenomena in line-hinged and line-supported plate assemblies.

To fill the gap in analytical solutions for free vibration problems of functionally graded (FG) moderately thick plates under non-Lévy-type boundary conditions in thermal environments, a new symplectic analytical solution is developed in the present study. In this paper, the analytical solutions for vibration of rectangular FG plates subjected to uniform, linear, and nonlinear temperature fields are investigated. The formulation is developed in the Hamiltonian system framework by extending the symplectic superposition method, where the physical neutral surface is introduced to eliminate tensile-bending coupling, which enables a systematic treatment of complex boundary conditions without assuming any trial functions. The original problem is decomposed into two subproblems, which are solved analytically via symplectic eigen-expansion together with the method of separation of variables, and the final solution is constructed by superposition. Convergence studies demonstrate that 30 series terms are sufficient to achieve four-decimal accuracy for the first several modes. Extensive benchmarks are reported for SUS304/Si3N4 FG plates, and the analytical results show close agreement with finite element simulations in both frequencies and mode shapes. Parametric results quantify the influences of the aspect ratio, volume fraction exponent, thickness-to-width ratio, shear correction factor, temperature-dependent material property, and temperature variation. The frequency-temperature relation is governed by material softening and thermally induced negative geometric stiffness, leading to vanishing frequencies near the thermal buckling limit; uniform heating produces the most pronounced reduction, while linear and nonlinear temperature fields yield similar trends.

Fiber-optic sensing has emerged as a promising technology for hydrogen (H2) detection by leveraging the interactions between guided light and H2-sensitive materials. However, the light field of conventional interferometric structures is non-localized and exhibits limited enhancement, consequently leading to a weak light-materials interaction. These fundamental limitations impede further improvements in sensitivity. Herein, we propose a 2.5-dimensional (2.5D) plasmonic metafiber consisting of spatially misaligned palladium (Pd) nano-disk and nanohole arrays, engineered to enhance light-materials interaction by localized light field enhancement. In contrast to conventional single-layer nanoarrays, the spatially misaligned gap length of the double-layer nanoarray introduces an additional out-of-plane degree of freedom, enabling flexible manipulation of the interaction between plasmonic field and materials. The hybrid plasmon mode in the 2.5D metafiber exhibits an exceptional response to Pd phase transitions, outperforming the sum of responses of two single-layer nanoarrays. The 2.5D metafiber is further fabricated using a UV-curable adhesive transfer technique, overcoming the challenges of direct patterning on small-area fiber tips. The metafiber exhibits a maximum wavelength response of 72.5 nm and a sensitivity of 9.3 nm/1 % when the carrier gas is N2, nearly 1-2 orders of magnitude higher than that of conventional fiber-optic interferometric H2-sensitive structures. Notably, the metafiber also exhibits a significant wavelength response at higher H2 concentrations using air as the carrier gas, despite interference from background gases. These results demonstrate that the novel structural design and sensing mechanism fundamentally enhance the light-material interaction, offering new design paradigms and theoretical insights for highly sensitive fiber-optic H2 sensing strategies.

Conical-cylindrical assembled shells are typical structural designs of launch vehicles. In addition to thermal stresses from the high-temperature environment, these structures are subjected to external aerodynamic loads during service, leading to a nonlinear stress state in the shells. However, current studies on the vibration behaviors of shells under coupled thermal-aerodynamic loads primarily rely on the linear solution framework, and they are predominantly limited to single-shell structures. To tackle the limitation, a novel theoretical scheme for the vibration of conical-cylindrical assembled shells under thermal-aerodynamic loads, considering geometric nonlinearity, is developed for this study. The original nonlinear governing equation is transformed by applying the perturbation method and the quasi-linearization method, and the obtained nonhomogeneous and homogeneous equations are solved with the precise integration method with and without dimensional expanding, respectively. Additionally, the flutter, thermal buckling, and free vibration analyses are also achieved by adjusting the involved aerodynamic, thermal, and vibration terms in the present scheme. Through extensive solution comparisons across different design parameters involving material properties, geometric parameters, and boundary and loading conditions, the developed scheme demonstrates excellent accuracy. Furthermore, the effects of key parameters on the vibration behaviors are quantitatively investigated. The summarized findings may help facilitate the structural designs of conical-cylindrical assembled shells.

Wool fibers undergo significant structural changes during industrial stretching, which directly impact their mechanical properties and textile performance, making monitoring of the stretching process essential for optimizing wool products. In this study, we demonstrate the effective use of polarized second harmonic generation (P-SHG) imaging for monitoring the wool fiber stretching process. P-SHG is highly sensitive to non-centrosymmetric structures, enabling clear observation of changes in α-keratin alignment and the reconstruction of cortical interfaces during stretching. Quantitative P-SHG analysis revealed a significant decrease in the effective pitch angle (θe) from 54° ± 1° to 33° ± 3° after stretching, confirming the dipole orientation changes in keratin molecules. These findings were further validated through additional characterization techniques, including scanning electron microscopy (SEM), polarizing optical microscopy (POM), X-ray diffraction (XRD), and Raman spectroscopy (RS). The results show that the industrial stretching process of wool alters the morphology at the surface scale, enhances the alignment of macroscopic fibers, and induces a transition from α-helix to β-sheet. Our technique is simple, effective, and capable of in situ monitoring of the structural changes in wool fibers, making it highly promising for applications in the wool industry.

To address the issues of high friction loss and insufficient load-carrying capacity in journal bearings, this study proposes a texture interval design method based on the oil film rupture point and maximum film pressure point, thus systematically investigating the effects of texture depth, axial length, circumferential quantity, and texture interval on bearing performance and the underlying mechanism. The results showed that the optimal bearing load-carrying capacity and minimum friction coefficient occurred within the 40%-80% pressure texture interval, rather than the traditional half-texture interval. Specifically, under low eccentricity conditions, texture depth optimization was prioritized, while high eccentricity necessitated the regulation of texture interval. An appropriate texture length further enhances bearing performance when combined with the pressure texture interval. Mechanistic analysis reveals that the texture depth ratio dominated the pressure distribution of the lubricant medium and boundary layer separation, whereas the number of textures influences bearing performance by inducing a secondary dynamic pressure effect. This study provides an engineering-oriented multi-parameter co-optimization strategy for the structural optimization of plain bearings.