Highly efficient, low-frequency (<2 Hz) high-impedance generators convert ambient mechanical energy to electrical energy; however, their high internal impedance causes most of the voltage to drop internally, limiting energy delivery to low-impedance loads. Herein, we propose a theoretical framework for a novel single-input, multi-output (SIMO) switched-capacitor circuit designed to overcome this impedance mismatch and achieve a high output energy at low impedance. When integrated with an alternating-current dielectric generator (AC-DEG), the system attains an ultra-low optimal matching impedance of 280 Omega, delivering an energy output of 3.37 mJ (1685 mJ/m(2)) per cycle and a short-circuit charge output of 1.21 mC (605 mC/m(2)) per cycle. Through reconfiguring output paths, the energy transfer efficiency can exceed 50%-far outperforming other energy management strategies. We demonstrate that this energy management strategy enables practical applications in powering low-impedance electronic devices such as motors and batteries, paving the way for advanced self-powered systems.

Precise 3D point cloud registration is crucial for quality control in advanced manufacturing, as it enables the reliable comparison of as-built components with their digital design models. However, current registration algorithms often produce significant measurement errors in real-world settings due to process-induced deformations and structured defects. This paper proposes NDT-EH, a novel measurement framework that advances measurement science through three key innovations: physics-informed compensation, adaptive optimization, and robust pre-alignment. Comprehensive validation on both synthetic and real-world manufacturing datasets demonstrates superior performance. NDT-EH achieves a 100% success rate and up to an 80-fold precision improvement over state-of-the-art methods, establishing a new benchmark in manufacturing metrology.

Achieving both a low startup wind speed and high output power remains a key challenge for wind energy harvesters in self-powered systems. Therefore, a galloping-driven dielectric elastomer generator (G-DEG) is proposed by integrating a mechanical energy extraction component (MEEC) with dual DEG units. A trapezoidal-section cylinder combined with low-stiffness springs enables self-excited galloping at 1.2 m/s, generating large-amplitude (11 cm) and low-frequency (0.9 Hz) oscillations, which are efficiently converted into electricity via a fully passive AC-mode DEG. Experimental results show that the device initiates power generation at 1.4 m/s and achieves a peak output of 23 mW at 2.0 m/s, significantly outperforming existing low-speed wind energy harvesters. When integrated with a power management circuit, the system can reliably power a wireless environmental monitoring module, demonstrating strong potential for distributed self-powered systems.

Porous foams have been identified as having broad application prospects in a number of fields. However, the existing foams have problems e.g., poor sound absorption performance, low structural strength, and bad degradability. Herein, a lightweight but high-strength biomass foam was reported by drying at ambient pressure, which was composed of cellulose nanofibrils (CNFs) immersed in ethanol/Fe3+ bath. By adjusting the solid contents of CNFs, the compressive strength of the foam was improved, allowing it to support forces up to 4500 times its weight. The macroporous-doped gradient structure was demonstrated to enhance the foam's ability to absorb sound waves. For a 10 mm sample, the average sound absorption coefficient reached 93.4% above 2000 Hz. The macroporous structure inside the foam was conducive to acoustic coupling, while the small pores were effective in the obstruction of sound wave propagation. Moreover, an increase in the solid contents of CNFs was associated with an enhancement in thermal insulation performance of the foam. This work will provide a feasible strategy for promoting the advancement of nanocellulose foams as sophisticated acoustic building materials.

A fundamental challenge in additive manufacturing (AM) metrology is separating actionable defect signals from complex measurement data. This work advances measurement science by introducing a new methodology for AM quality control centered on dual-constrained signal decoupling and cross-modal verification. We formulate the analysis of cloud-to-model (C2M) deviations as a signal processing problem. Our Dual-Constrained Outlier Clustering (DCOC) method uses joint geometric and topological constraints to decouple systematic artifacts (e.g., warping) from stochastic defects, establishing a new theoretical basis for robust signal extraction. A lightweight 3D-2D cross-modal verification module enhances measurement confidence by enforcing spatial consistency between geometric and visual evidence. This transforms raw measurement data into structured, objectified quality assessments with minimal computational overhead (O(n log n)). On representative AM parts, our framework achieves 96.2 % measurement accuracy with a 3.8 % false positive rate and a 100 % cross-modal verification rate, with <1.5 % computational overhead relative to baseline methods. The method reduces measurement parameter sensitivity by 73 % and improves the measurement robustness index from 0.45 to 0.92. The framework outputs structured measurement objects with quantified uncertainty metrics, directly enabling traceable, automated quality control workflows and providing actionable feedback for process optimization.

To explore the coupling effect of the bidirectional bistable nonlinear energy sink (BBNES), this study examines the dynamics of both BBNES and dual bistable nonlinear energy sinks (BNESs), with their application in monopile offshore wind turbines (OWTs). The research methodology involves: (1) establishing physical models of both absorbers with corresponding force and potential energy analyses; (2) developing separate dynamic analysis models for host structure (HS)-mounted and nacelle-mounted absorber configurations; (3) comparing harmonic forced vibration responses between the BBNES and dual BNESs installed on the HS to preliminarily reveal the BBNES’s coupling effect. This study culminates in evaluating both absorbers’ performance under wind-wave loads, paying attention to the emergency shutdown scenario characterized by significant tower vibrations. Under harmonic excitation, the BBNES demonstrates superior vibration mitigation with the strongly modulated response when excitations are equal in both directions, but shows complex coupling effects under asymmetric excitations. During emergency shutdown conditions with wind-wave loads, the BBNES matches the performance of the dual BNESs in the fore-aft direction but exhibits inferior side-to-side damping performance due to its bidirectional energy coupling and limited adaptability to amplitude variations. Notably, the BBNES reduces nacelle space requirements by 1.24 m, and its performance is highly sensitive to slight changes in the proportionality factors but robust against variations in the mass ratio, frequency ratio, damping ratio, and pre-compressed spring’s original length. The research reveals that while the BBNES has greater application potential than the dual BNESs, its coupling effect suggests optimization opportunities through bidirectional decoupling as well as bidirectional stiffness and damping inequality designs. This work not only provides deep insights into the dynamics of the BBNES but also lays the foundation for its future optimization design.

Replicating core-shell architectures with cross-scale structural precision spanning from macroscopic geometry to microscopic pore alignment remains a formidable manufacturing challenge. Here, we report a robust cryogenic 3D printing strategy to fabricate bio-inspired aerogel fibers with customized structural attributes. We quantitatively elucidate the non-equilibrium solidification regimes, specifically the spatiotemporal competition between rheological ink spreading and synchronous ice-crystal propagation along orthogonal axes within both filaments and interconnected junctions. Crucially, this mechanistic insight enables the simultaneous regulation of the macroscopic shape, internal pore dimensions, and the interfacial integrity of fiber networks. The resulting fibers exhibit decoupled porosity and mechanical robustness (1.6 MPa), while their unique structural asymmetry effectively reconciles the intrinsic paradox between high sensitivity and broad detection range. The assembled flexible sensors demonstrate ultra-fast response (20 ms), wide detection window (0.02-200 g), and high gauge factor (16.665 at 1% strain). This work establishes a versatile paradigm for the cross-scale structural customization of aerogel fibers for intelligent wearable systems.

This paper proposes an asymmetric arc-tube type vibro-impact dielectric elastomer oscillator (AAVI DEO) aimed at improving the energy harvesting (EH) performance of vibro-impact DEGs and enabling energy harvesting from vibrations in arbitrary directions. Built upon the existing AVI DEO, the proposed design introduces asymmetric impact angles, offering a potential approach to enhance EH performance and broaden the effective operating frequency range under both unidirectional and arbitrary-direction excitations. The study first presents the physical model of the AAVI DEO system and establishes its dynamic model under vibration excitation in an arbitrary direction (i.e., resultant excitation in three orthogonal directions). The dynamic model is then validated through experiments. Subsequently, numerical simulations are conducted to investigate the effects of the impact angle and tilt angle parameters on the dynamic behavior and EH performance of the system under unidirectional excitation. Finally, the EH performance under resultant three-directional excitation is examined, considering the joint effects of the impact angle and tilt angle parameters. The results show that under unidirectional excitation, the asymmetric impact angle design can effectively broaden the system effective operating frequency range and increases the output power. Under resultant three-directional excitation, an appropriate impact angle can also achieve high output power and a wider effective operating frequency range; however, the optimal impact angle must be determined by jointly considering the tilt angle of the system and the excitation amplitude (phase angles) and frequency. This work provides new insights and a theoretical basis for the secondary design and optimization of the existing (i.e., completed) AVI DEO.

Soft robotic grippers, with their intrinsic compliance and dexterity, provide safer manipulation of soft and fragile items compared to traditional rigid ones. However, achieving high functional integration within a single soft gripper, particularly for cross-scale, multi-particle, and high-load manipulation, remains a major challenge. Here, a monolithically 3D-printed, rapeseed-flower-inspired self-reconfigurable soft gripper (SRSG) is presented, which can rapidly reconfigure its finger arrangement within ∼130 ms and achieves precise, reversible switching between diagonal and parallel configurations. The SRSG can be readily incorporated with detachable petal modules to alter the grasping workspace. Leveraging these capabilities enables a range of functions: rotating bulbs of varying diameters, picking fruits, grasping cross-scale objects ranging from 0.07 to 270 mm (grasping range ratio of ∼3857 times), lifting payloads up to 5.6 kg (∼106 times its own weight), and adaptively enveloping numerous fine particles, multiple live aquatic organisms, and fragile underwater targets. The fully soft, electronics-free SRSG establishes a self-reconfigurable grasping paradigm for robust operation in unstructured environments, and opens up new directions for soft robotic end-effectors.

End fire antennas in planar technology which suits for THz and mm-wave antenna design are studied. A 5-element end-fire antenna at 24 GHz is designed, fabricated and tested in Rogers 4350 PCB technology. A 5-element end-fire antenna based on dipole units at 24 GHz using Rogers 4350 PCB is given in this work. Gain of the end-fire antenna is 9.6 dBi. S11 bandwidth is 0.9 GHz. In X-Y plane and X-Z plane, half power width are 35° and 38° respectively. This antenna boasts of simplicity in design and high gain. And it is compact in size as well. Its area is merely 2.4×1.3 cm2. This end fire antenna architecture may be used in planar PCB antenna design, and it could also be used for on-chip mm-wave or THz antenna design in various applications.

Dielectric polymers for electrostatic energy storage suffer from low energy density and reduced efficiency at elevated temperatures, limiting their practical application. Here, we introduce an electret-enhancement strategy that suppresses conduction losses and enhances energy density under high-temperature conditions. By exploiting intrinsic electret behavior to form an internal negative charge layer via corona-discharge charging, electrostatic assembly, and thermal aging, our approach impedes electron injection and transport. As a result, at 200°C, the discharged energy density of aged polyetherimide (PEI) (at >90% efficiency) increases by 394%—from 0.32 J/cm3 (pristine PEI) to 1.58 J/cm3—and reaches a maximum of 1.90 J/cm3. Demonstrating its universality, this strategy boosts the maximum energy densities of biaxially oriented polypropylene (BOPP) and polyethylene terephthalate (PET) by over 51% relative to their pristine counterparts. Finally, we demonstrate scalable fabrication of large-area (>1 m2) electret-enhanced BOPP films, underscoring their potential for high-temperature energy storage and power-electronics applications.

This paper presents results of experimental study of flow structure and heat transfer in the accelerating swirling flow insight the subsonic conical nozzle. Three different nozzles with inlet angle (24 degrees, 32 degrees, 40 degrees) and module (0.25, 0.4, 0.56) was tested in this work. The swirl flow generator with variable blade width (phi(w) = 45 degrees, n = 3) was installed in front of the nozzle, the short cylindrical pipe (L-0/D = 2.33) was between swirl generator and nozzle inlet aimed to avoid the flow angular unevenness. The experimental program was established for incompressible swirling flow (M < 0.30), the inlet Reynolds number Re-D (in) was ranged from 5.3 10(4) to 1.1 10(5), the inlet flow temperature in heat transfer experiments was 110-120 degrees C. The new results obtained include the axial and rotational flow speed, turbulence distribution, and local heat transfer development. The tangential flow dominates in the nozzle axial zone with maximum speed value, gradually shifting to the nozzle central area. Since the axial speed grows faster, the swirl flow angle drops down throughout the nozzle space. The nozzle module affects greatly the radial turbulent fluctuations both inside the nozzle and in front of it, making them almost even across the nozzle radius due to acceleration. At a high flow acceleration (m = 0.25) the turbulent fluctuations fall down up to 3-5 % both in the central nozzle area and near its surface. The novel experimental correlations were obtained, including the angular momentum flux and swirl flow number decay, link between local and total swirl flow parameters, radius of zero static pressure excess, local heat transfer growth, and some others. The Nu(d)/Nu(d0) ratio is maximal at the nozzle entrance, but drops down inside the nozzle. As for the axial flow the maximal heat transfer occurs in the nozzle minimum cross section.

This study investigates the effects of carbon fiber (CF) content on the rheological, mechanical, and thermal properties of Fused Granular Fabrication (FGF) polyphenylene sulfide (PPS) composites. PPS composites with various CF loadings (0-25 wt%) were prepared, and their rheological behavior, mechanical properties, thermal properties, and micro-morphology were analyzed. Results indicate that increasing CF content significantly enhances the rheological characteristics of the composites, with the storage modulus increasing to the order of 10(4)-10(5) Pa. The tensile strength, flexural strength, and Young's modulus of the 3D-printed specimens improved with higher CF content, reaching optimal values at 25 wt% CF (tensile strength: 109.96 MPa, flexural modulus: 7.08 GPa), representing 367% and 325% increase over neat PPS, respectively. While the Z-direction tensile strength achieved 33.37 MPa. However, these values remained slightly inferior to those of injection-molded counterparts. Due to pore existence furthermore, CF incorporation markedly improved the thermal resistance, with the 25 wt% PPS-CF composite exhibiting a heat deflection temperature of 246.8 degrees C, a 136 degrees C enhancement over neat PPS (110 degrees C). This work provides theoretical insights for optimizing processing parameters and tailoring properties of high-heat-resistant PPS-CF composites in 3D printing applications.

Abstract To address the difficulties in observing surface cracks during fretting fatigue of tenon structures and the irregular geometry of the friction contact zone in the pad, this study developed a novel fretting fatigue test fixture. Utilizing this fixture, fretting fatigue experiments were systematically conducted, and a corresponding finite element simulation model was established. Through fretting fatigue tests on typical dovetail tenon specimens combined with digital image correlation (DIC) technology, we found that fatigue cracks predominantly initiated at the edge of the contact surface. The contact interface remained intact but exhibited accumulated wear debris, demonstrating a distinct fretting fatigue failure mechanism. The experimental results confirmed that the proposed testing apparatus fully meets the evaluation requirements for fretting fatigue in dovetail tenon structures. This study provides high-precision experimental data, offering valuable insights into fretting damage mechanisms and supporting the development of fatigue life prediction models.

In this paper, installing a pair of vibro-impact dielectric elastomer generators (VI DEGs) inside the nacelle of a wind turbine subjected to random wind-wave loads is proposed to harvest lateral ultra-low frequency vibration energy. First, the dynamic model of the dual VI DEGs in the nacelle is developed, followed by a concise introduction of the studied offshore wind turbine (OWT) model, along with the computational methodology for the dynamic responses of the energy harvesters. Subsequently, four representative load cases considered in this study are outlined. Next, the dynamic behavior and energy harvesting (EH) performance of the dual VI DEGs are examined under the load cases, along with the nacelle dynamics. Finally, the parametric analysis of the energy harvesters is conducted to explore approaches for further enhancing their EH performance. The research results show that the EH performance can be enhanced by increasing the ball mass and pre-stretched ratio within their limited value ranges or by appropriately selecting the impact distance. This work not only provides a new insight into the dynamic behavior of the dual VI DEGs in a wind turbine under random wind-wave loads, but also offers methodological guidance for their structural design and optimization to enhance the EH performance.

In this work, a novel deep learning algorithm is proposed within the framework of the physics-informed neural network (PINN) architecture. Physical constraints are incorporated through the Navier–Stokes and continuity equations, which are commonly used in fluid mechanics applications. The proposed approach addresses the challenge posed by the multicomponent nature of the PINN's loss function. This challenge arises from the need to determine an optimal weight configuration for the various components of the loss function. The issue is resolved by dynamically updating the weight configuration to balance the influence of different data types during training. The procedure, known as GradNorm, originally developed for deep multitask networks in computer vision, is adapted and integrated into the PINN framework. GradNorm adjusts the weight configuration to equalize the gradients of the loss function components. The new algorithm achieves a 50% improvement in accuracy compared to the conventional PINN in reconstructing the back-facing step flow. For the Taylor–Couette flow (Taylor vortex mode) test case, where the conventional PINN fails to capture the flow structure, the proposed approach demonstrates high accuracy even with sparse training datasets. Additionally, it does not require known flow parameter values in close proximity to walls to achieve accurate near-wall resolution. The application of the new algorithm shows great potential for processing sparse experimental datasets to reconstruct detailed flow fields and for providing a continuous representation of discrete solutions.

This study investigates the damage effects and residual structural strength of Carbon Fiber Reinforced Polymer (CFRP) laminates under multi-factor coupled lightning strikes, combining numerical simulations and experimental methods. An electro-thermal-chemical coupling model was developed to simulate lightning damage under varying layup angles, lightning current peaks (7.6–100 kA), different thickness and grounding conditions. Experimental validation was conducted via a lightning current A-component generator and residual tensile strength tests. The results show that the damage area is directly proportional to the current size, showing rapid expansion at the peak value. When the current peak reaches 46 kA, the damage area reaches 2738.4 mm². The single ground will lead to the asymmetric damage of carbon fiber laminates, and the damage on the grounding side will increase by 53.5

Real-time driving monitoring systems can use self-powered sensors based on artificial intelligence (AI) and triboelectric nanogenerators (TENGs). Here, we created a TENG-based self-powered intelligent steering wheel that can detect hand gripping. The TENG serves as the steering wheel’s smart surface. In addition to monitoring the steering wheel in real time, the intelligent steering wheel reacts quickly. The TENG sensor can detect hazardous conditions and lower processing demands while retaining excellent identification accuracy when used in conjunction with machine learning. Additionally, the TENG sensor may now offer an accurate and affordable monitoring solution for smart driving thanks to the integration of AI.

To investigate the influence of varying concentrations and types of carbon fiber (CF) on the mechanical properties of polyamide 6 (PA6) composites, this study explores the mechanical properties of PA6 composites with various CF types and quantities. The micro-morphology of the composites and the CF length distribution were characterized. The results indicate that the inclusion of carbon fibers significantly enhances the tensile, flexural, and notched impact strengths of PA6. Specifically, when about 30 wt% of CF T300 was added, the tensile and flexural strength of the composite reached a maximum of 166 MPa and 224 MPa, respectively, representing increases of 236.6% and 229.6%, respectively, compared to pure PA6. The maximum flexural modulus achieved 14.6 GPa, which was six times as large as that of pure PA6. Moreover, the CF length in the PA6 matrix follows a near-Gaussian distribution. A proper CF length and orientation, along with strong interfacial bonding between CF and the PA6 matrix, contribute to improved mechanical properties. The overall performance of T700-reinforced composites is better than that of T300-reinforced ones due to T700’s higher precursor strength and better fiber-length retention. This study provides guidance for fabricating high-performance PA6 composites.

This work examines the joining performance of metal-polymer composite single-lap joints (SLJs) enhanced with 316 L stainless steel Z-pins manufactured through fused filament fabrication (FFF). The Z-pin arrays and steel substrates were co-printed using FFF, and then subjected to debinding and sintering processes. The resulting structure was subsequently combined with polyphenylene sulfide (PPS) through an injection molding direct joining (IMDJ) process to create durable 316 L-PPS composite SLJs. The results show that incorporating FFF-fabricated Z-pins significantly enhance the joining performance of metal-polymer SLJs. A detailed investigation into the effects of pinning density and Z-pin alignment on polymer melt behavior and joint performance revealed that higher pinning densities and vertically aligned Z-pins (90° angle) resulted in superior joint strength. This configuration enhanced PPS melt flow, minimized interfacial defects, and achieved the highest shear strength—improving by up to 113.1