Search Results (218)

Electrode-level compressibility may not imply transferable hardware redundancy in biomimetic myoelectric interfaces. This study tested whether sensor-count sufficiency discovered by trial-level analysis survives participant-grouped evaluation. Dataset A comprised 398 archived Myo Armband trials from eight gestures. Dataset B contained 864 one-second trials from 36 participants and six gestures. A timestamp audit identified extensive repeated channel values; Dataset B was therefore analyzed on a conservative 100 Hz grid with 20–45 Hz filtering. Sensor subsets and RBF-SVM parameters were selected exclusively within grouped training data using repeated nested validation. Electrode-level NMF, all 28 fixed six-sensor layouts, cyclic re-indexing, channel-block ablation, participant-cluster bootstrap, PCA, and time-domain-only sensitivity analyses were evaluated. Dataset A yielded 97.74% accuracy with six sensors and 97.93% with eight. In Dataset B, accuracy was 75.96% ± 7.47% with six sensors and 77.93% ± 6.49% with eight; the paired difference was −1.97 percentage points (corrected 95% CI, −5.50 to 1.56). The participant-cluster bootstrap interval was −3.70 to −0.31 points. Active-gesture accuracy was 71.67% and 74.35%, respectively. All fixed six-sensor layouts averaged 74.59%. Three NMF components reconstructed 89.95% ± 1.78% of held-out-participant normalized RMS patterns, with no nonconverged folds. One-position cyclic re-indexing reduced accuracy to 40.28%; channel-block ablation caused losses of 0.62–6.71 points. Low-dimensional electrode-level RMS structure did not establish removable sensors across unseen users. Compact biomimetic interfaces require registration, adaptation, or equivariant processing before physical sensor reduction. Full article

Flexible and stretchable electronics inevitably undergo stretching, compression, bending and torsion when conformally attached to skin, soft tissues and dynamic organs. While deformation-induced electrical variations act as target signals for motion sensors, they cause resistance/impedance drift, baseline shift and sensitivity degradation in physiological electrodes, temperature/chemical sensors, interconnects and stimulation devices, leading to motion artifacts and reduced long-term reliability. Hydrogels are pivotal materials for soft bioelectronic interfaces owing to their high water content, low modulus, tissue compatibility and ionic conductivity. However, their conductive networks are susceptible to structural reconstruction under deformation, dehydration, swelling and cyclic fatigue, meaning that stretchability is by no means equivalent to strain insensitivity. This review focuses on stable resistance/impedance and functional output within a specified strain window, this paper reviews three representative material systems, liquid metal (LM)-based composite hydrogels, conductive polymer/elastic network composite hydrogels, and hydrogen-bonded isotropic architectures. It further summarizes three design strategies—geometric and functional compensation, mechanical decoupling and strain isolation, and interfacial engineering for conductive network stabilization—and discusses their applications in wearable epidermal and implantable bioelectronics. Finally, unified evaluation metrics for strain insensitivity are proposed, with future directions covering high-conductivity–low-modulus synergy, long-term water/ionic stability, robust soft-hard interfaces, multiaxial deformation tolerance and scalable manufacturability. Full article

Honey–gelatin–water composite membranes containing silver microparticles (SmPs) are investigated as soft pressure-responsive materials with potential applications in low-pressure sensing, including biomedical monitoring, and in tunable capacitive components. Three compositions, with nominal volumes of loose SmP powder of up to $3{\mathrm{cm}}^3$, are prepared to determine how silver loading affects their electrical and apparent compressive response. The membranes are characterized by optical microscopy, XRD, and SEM and are placed between electrodes in a parallel-plate configuration. Capacitance and parallel resistance are measured at $1\mathrm{kHz}$ under applied pressures up to $2.25\mathrm{kPa}$, and the corresponding admittance components and apparent compressive parameters are calculated from these measurements. It is shown that SmP loading increases the capacitance and reduces the resistance. Between the SmP-free and most highly loaded membranes, the zero-pressure capacitance increases by more than four orders of magnitude, whereas the resistance decreases by approximately a factor of 40. Applied pressure further increases the capacitance and decreases the parallel resistance of all membranes. The apparent strain increases approximately linearly with pressure and is greater in the SmP-loaded membranes, whereas the apparent modulus decreases as the SmP content is increased. The structural and electrical results show that SmP content and the associated heterogeneous microstructure influence both the electrical and apparent compressive response. Full article

Knowledge of the time-dependent behavior of polyvinyl alcohol (PVA) gel polymer electrolytes (GPEs) is essential for their application in structural supercapacitors (SSCs) at lower degrees of integration (DoI). Due to the soft, viscoelastic nature of GPEs, their mechanical response under compressive and transient loading is critical for maintaining necessary long-term electrode contact. To enable reliable structural design configurations, a tailored PVA GPE, prepared via a freeze–thaw method, was examined using compressive stress-relaxation testing. The mechanical response was modeled using a novel, non-linear viscoelastic constitutive framework, which couples a time-dependent elastic modulus for the non-linear loading phase with a Prony series for accurate relaxation prediction. The parameters for this practical framework were successfully derived from one single stress-relaxation experiment. Experimental results confirmed pronounced viscoelastic relaxation and up to 10% cyclic hardening. Implemented via finite-element method (FEM) analysis, the non-linear model achieved high accuracy (0.8% average relative deviation), significantly outperforming a linearized model (1.36% deviation). This validated framework is crucial for optimizing the mechanical stability of SSC assemblies and predicting the GPE’s short-time response under transient loading events. Full article

Flexible pressure sensors serve as core sensing components for wearable health monitoring systems, electronic skins for soft robots, and flexible human–machine interaction devices. Benefiting from the interfacial electric double-layer polarization effect, iontronic sensing delivers far higher pressure response sensitivity than conventional parallel-plate capacitive sensors, endowing it with distinctive advantages in the detection of weak physiological signals. Nevertheless, current dense ionic thin-film dielectric layers suffer from limited deformation space under compression and poor low-pressure sensing capability. Mainstream high-precision micropillar arrays are fabricated via photolithography, 3D printing, and metal etching molds, which require costly equipment and complicated fabrication procedures, making large-area mass production unfeasible. Random frosted concave-convex microstructures feature disordered dimensions, leading to severe device hysteresis and narrow linear ranges, which fail to achieve ultrahigh sensitivity alongside a wide pressure detection range simultaneously. To address the aforementioned multiple bottlenecks, this paper proposes a low-cost resin template replication process to fabricate TPU-based ionic thin-film dielectric layers with ordered micropillar array microstructures. Combined with inkjet-printed silver conductive PI flexible electrodes, an iontronic flexible pressure sensor with a sandwich layered structure is constructed. Multi-dimensional investigations including microscopic morphology characterization, electromechanical sensing performance calibration, and human wearable application tests are systematically implemented to thoroughly elucidate the synergistic enhancement mechanism of the arrayed micropillars. Test results demonstrate that the effective pressure detection range of the sensor spans 0–1038 kPa, accommodating ultra-low pressures such as pulse signals as well as medium-to-high-pressure loads including joint bending. The sensitivity reaches 23.27 kPa⁻¹ within the low-pressure range of 0–200 kPa and remains stable at 3.52 kPa⁻¹ in the high-pressure range of 200–1038 kPa, with piecewise linear fitting correlation coefficients of 0.93 and 0.96 respectively. Both the response time and recovery time of the device are 40 ms, and the hysteresis error throughout the loading-unloading cycle is merely 2.62%. After 20,000 consecutive cyclic loading-unloading tests, the peak capacitance output only decays by 5.1%, verifying outstanding mechanical fatigue resistance and electrical stability. Validations in multi-scenario applications prove that the sensor can accurately capture human physiological and motion signals including radial artery pulses, laryngeal deformation induced by multi-syllable vocalization, and multi-angle bending of fingers and elbow joints, suitable for home-based health monitoring, quantitative rehabilitation training, flexible tactile interaction and other scenarios. The entire fabrication process eliminates high-precision micro-nano processing equipment such as photolithography systems, plasma etchers and 3D printers; only general chemical raw materials and conventional laboratory instruments are adopted. The reusable templates enable low manufacturing costs and large-area coating forming, offering a novel low-cost technical solution for the engineering implementation and industrialization of high-performance iontronic flexible pressure sensors. Full article

Flexible pressure sensors featuring high sensitivity, a broad detection range, and excellent stability are pivotal components for high-precision electronic skins and human health monitoring. To circumvent the limitations of existing sensors in maintaining high responsiveness across extensive pressure ranges, herein, a novel flexible capacitive pressure sensor is developed based on a 3D porous ionogel foam composite (IL/EG/PVA@MF) coupled with a planar electrode array. This device leverages the synergistic structural engineering of the 3D hyperelastic melamine foam (MF) skeleton and the pressure-regulated fringe-field distribution and iontronic interfacial polarization of the porous ionogel. Experimental evaluations demonstrate that the sensor achieves a high normalized sensitivity of 62.45 kPa⁻¹ (2–10 kPa) and maintains reliable piecewise linear sensing performance across a broad working range of 0–50 kPa, accompanied by a rapid response time of within 8 ms. Furthermore, the sensor exhibits outstanding performance consistency after 6000 compression-release cycles at 50 kPa, verifying its good mechanical durability. In practical applications, the device can monitor diverse physiological signals with high fidelity, ranging from subtle radial artery pulses to large-scale joint movements and specific coughing patterns, underscoring its broad potential for integrated wearable systems and intelligent healthcare. Full article

In multilayer ceramic capacitors, the internal electrodes are fabricated by printing thin layers of nickel paste, which contains a dispersant to prevent the agglomeration of nickel powder particles within the paste. We used molecular dynamics simulations and cryogenic focused ion beam-scanning electron microscopy to investigate the effects of microscopic structures in the adsorbed dispersant layer on the steric stabilization of nickel powder particles. Three dispersants were considered with different molecular structures. The simulation results indicated that stearic acid (SA) resulted in the highest steric stabilization efficiency, followed by lauric acid (LA) and oleic acid (OA). The high crystallinity of the SA and LA layers resulted in compressed molecular chains that induced strong repulsion between nickel powder particles, and the high effective thickness of the SA layer induced a stronger repulsion. The OA layer offered less steric stabilization because the molecular chains exhibited interpenetration rather than compression. The experimental results confirmed that the steric stabilization of nickel paste samples qualitatively aligned with the simulation results. Thus, multicomponent nickel pastes containing a polar solvent require a dispersant that forms a thick and highly crystalline adsorbed layer on nickel powder particles for effective steric stabilization. Full article

The performance of a Proton Exchange Membrane Fuel Cell (PEMFC) stack is largely determined during assembly, where component materials, sealant selection, and clamping force jointly influence both sealing effectiveness and interfacial losses. These factors interact through coupled mechanical, thermal, and electrical phenomena. Although detailed multiphysics models can accurately capture these effects, their high computational cost limits their application in parametric analyses and optimisation studies. The Equivalent Stiffness Model (ESM) provides an efficient alternative, representing each stack component as a simplified stiffness formulation. Starting from an earlier ESM that reproduces the nonlinear compression of the Membrane Electrode Assembly (MEA) and sealants, this work adds the calculation of the electrical contact resistance at the Gas Diffusion Layer (GDL)–Bipolar Plate (BPP) interface and the resulting GDL porosity. Given the large number of input parameters, a Design of Experiments (DoE) approach systematically explores a wide range of stack configurations and operating conditions. The analysis shows that GDL type, sealant properties, and clamping force are the main drivers of assembly-related performance, whereas BPP material and thermo-hygrometric conditions become more influential during operation. These results provide quantitative guidance on which design and operating choices most strongly affect stack behaviour and under which conditions. Full article

Oxygen bubbles, not catalysis, limit the anode of zero-gap alkaline water electrolysis (AWE) at industrial current densities. Here we compare stainless-steel (SS) mesh (M), felt (F), and a bonded felt–mesh bilayer mounted with the felt facing the Zirfon separator (FM) or reversed (MF) in a zero-gap cell (6 M KOH, 80 °C), bare and Ni-plated. On bare SS, architecture dominates: the felt generates fine bubbles (54 μm) and the mesh coarse ones (109 μm), and the correctly oriented bilayer exploits this contrast—fine generation at the separator, coarse evacuation (95 μm) through the mesh—to deliver 1.85 V at 1.0 A cm⁻², whereas the reversed stack is the worst electrode tested, showing voltage fluctuations symptomatic of interfacial gas blanketing. Ni plating improves every architecture (bilayer: 391 → 325 mV OER overpotential; 1.85 → 1.80 V) yet compresses the differences between them. Voltammetry and X-ray photoelectron spectroscopy show why: OER cycling converts the plated Ni into an Fe-incorporated NiFe (oxy)hydroxide—Fe appearing despite a nominally Fe-free bath—whose hydrophilicity shrinks bubbles on every architecture. Architecture and surface chemistry are thus complementary attacks on the same gas-management problem, and stacking orientation is a free design variable that no catalyst can replace. Operando impedance at 1.8 V and an overpotential decomposition price the penalty: flipping the electrode nearly triples the gas-transport overpotential at 1.0 A cm⁻², from ≈140 to ≈402 mV, while ohmic and kinetic terms remain nearly untouched. Full article

Redundant channels, sparse electrode topology, and insufficient cross-layer feature fusion limit electroencephalography (EEG)-based emotion recognition. This study proposes the Topology-Aware Dual-Bridge Fusion Network (TDBF-Net), a compact framework that integrates adaptive channel selection, topology-aware sparse convolution, and bidirectional bridge fusion. First, sample entropy, dispersion entropy, and fuzzy entropy are fused to estimate channel importance, while particle swarm optimization (PSO) learns the entropy weights and an elbow-based criterion determines the retained channel subset. Second, differential entropy (DE) features from the $\theta$, $\alpha$, $\beta$, and $\gamma$ bands are mapped to an $8\times 9$ sparse topological tensor according to electrode locations. A fixed spatial validity mask is applied before and after convolution to suppress invalid responses from zero-padded regions and preserve real electrode topology. Third, a dual-bridge fusion module recalibrates shallow and deep features in both directions through channel attention and gated fusion, and a bidirectional long short-term memory network (BiLSTM) further captures short-term temporal dependencies. Subject-dependent experiments on the SJTU Emotion EEG Dataset (SEED) and the Database for Emotion Analysis using Physiological Signals (DEAP) show that TDBF-Net achieves $97.62\%$ ± $1.59\%$ accuracy on SEED and $98.46\%$ ± $0.94\%$ and $98.14\%$ ± $0.77\%$ on DEAP valence and arousal, respectively. Paired DEAP ablations support topology and bridge contributions for valence, whereas the corresponding arousal differences are not significant. Selector controls, robustness tests, computational profiling, and held-out visualizations further characterize the method’s compression, cost, and interpretability. The evidence supports TDBF-Net as an effective subject-dependent framework while leaving subject-independent and cross-dataset generalization for future validation. Full article

To address prevalent industrial challenges, including the high cost of fabricating microstructures via photolithography and 3D printing, impurity residues easily generated by conventional physical/chemical pore-forming techniques, and the limited sensitivity of regular capacitive sensors, this paper innovatively proposes an integrated low-temperature in situ gas foaming strategy using ammonium bicarbonate for the fabrication of porous TPU-based ionic gels. Relying on the complete gaseous decomposition property of ammonium bicarbonate upon heating, a three-dimensionally interconnected continuous porous network is spontaneously constructed inside the polymer matrix. Thermoplastic polyurethane (TPU) is selected as the continuous polymer phase, and [EMIM][TFSI] imidazolium ionic liquid is blended as the ion source to synthesize composite ionic gel substrates. A PDMS composite slurry filled with graphene is employed to prepare flexible substrates, followed by low-temperature oxygen plasma surface modification to introduce polar functional groups such as hydroxyl and carboxyl onto electrode surfaces. A standard sandwich-structured ionic pressure sensor with the configuration of “top modified electrode—porous ionic gel dielectric layer—bottom modified electrode” is finally assembled. The porous framework and modified electrodes constitute a dual synergistic enhancement system: the porous structure markedly reduces the equivalent elastic modulus of the gel and improves its compressive deformation capacity; polar-modified electrodes optimize the interfacial compatibility between electrodes and gels, shorten ion migration paths and lower interfacial contact resistance. Systematic calibration of multiple batches of parallel samples reveals that the as-fabricated sensor achieves a high sensitivity of 25.3 kPa⁻¹ across the full measuring range from 0 to 1000 kPa with a linear fitting coefficient R² = 0.992. The loading response time and unloading recovery time of the device are 60 ms and 80 ms respectively, with a performance degradation of less than 3% after 1000 consecutive loading–unloading cycles, featuring low hysteresis error and excellent signal repeatability. Multi-scenario in vivo wearable tests on human subjects verify that the device can precisely capture subtle fluctuations of radial artery pulse and periodic laryngeal deformation during swallowing, distinguish characteristic waveform patterns of various English words according to differences in vocal cord vibration, and accurately detect bending motions when attached to finger joints. The entire fabrication process adopts common chemical raw materials and standard laboratory equipment without expensive micro-nano processing facilities, featuring convenient raw material procurement and high process fault tolerance, which enables large-area coating-based mass production. This work delivers a novel technical route for the low-cost large-scale production of high-performance ionic flexible sensors and bears significant industrialization reference value for applications in wearable medical monitoring, bionic robotic electronic skin, flexible human–machine interactive touch panels and other related fields. Full article

As the global automotive industry is transitioning toward sustainable development, new energy vehicles (NEVs) have experienced rapid global growth due to their environmental friendliness and high efficiency. Global sales of NEVs are projected to reach 50 million units by 2030. Nevertheless, safety incidents caused by impacts on traction batteries remain a major factor restricting the development of NEVs. Prismatic batteries, which account for over 90% of the traction battery market owing to their high energy density and structural robustness, nevertheless continue to face significant safety challenges under mechanical loading conditions. Typical failure modes involve structural damage induced by external compressive forces during severe vehicular collisions, which can subsequently result in the tearing of internal electrode layers and rupture of the separator, thereby initiating internal short circuits and leading to severe incidents. Accordingly, this research focuses on the mechanism of structural damage transmission for prismatic lithium-ion batteries under compression conditions. By integrating a refined mechanical model, it further elucidates the structural failure mechanisms and conducts a microscopic analysis of the damaged battery structure to investigate the effects of varying damage levels on battery safety performance, providing significant guidance for the safety and reliability of new energy vehicles. Full article

Ionic liquid-based localized high-concentration electrolytes, leveraging their intrinsically nonflammable safety characteristics and wide electrochemical windows, have emerged as strong contenders for next-generation lithium metal battery electrolytes. However, because such systems are anion-rich, the electrolyte bulk phase tends to form solvation structures dominated by bulky anionic clusters along with an excess of free anions, which triggers persistent and uncontrollable anion decomposition at the interphase. To address this issue, we adopt a strategy of constructing a compressed solvation structure by introducing a weakly interacting chlorinated diluent (TeCA), which helps form a compact solvation environment and alleviates excessive anion decomposition at electrode interphases. In this work, 1,1,2,2-tetrachloroethyl acetate (TeCA) was introduced as a weakly coordinating chlorinated diluent into an ionic-liquid localized high-concentration electrolyte (LHCE) to regulate the Li⁺-FSI⁻ solvation environment. By combining Raman spectroscopy, molecular dynamics simulations, and electrochemical characterization, the TeCA-LHCE system was found to exhibit altered ion-cluster configurations, improved oxidation tolerance, and enhanced interfacial stability under high-voltage conditions. The as-prepared TeCA-LHCE electrolyte presents improved electrochemical performance in comparison with TTE-LHCE and the baseline electrolyte (BE). The Li||Cu half-cell employing TeCA-LHCE achieved a high Coulombic efficiency above 99% over 500 cycles and formed a uniform and dense lithium deposition layer without obvious dendritic growth. When paired with a high-loading NCM811 cathode (10 mg cm⁻²), the TeCA-LHCE-based Li||NCM811 full cell delivered significantly improved cycling stability and rate capability under a high cutoff voltage of 4.3 V. Full article

Currently, dual-functional composites that simultaneously provide structural support and energy storage capabilities have garnered significant attention. However, the challenge of balancing mechanical strength and energy storage performance remains a limiting factor for their application. Herein, a novel N-doped reduced graphene oxide/nano-sulfur@porous SiC (N-rGO/S@porous SiC) composite material was successfully prepared by in situ embedding N-rGO supported with nano-sulfur into a 3D-printed porous SiC scaffold via a hydrothermal synthesis approach. The hierarchical porous structure composed of SiC and N-rGO facilitates mass transport of the liquid electrolyte. Benefiting from the high strength of SiC, the novel material achieves a compressive strength of 93.5 MPa. Benefiting from the synergistic effect of the N-rGO/S composite and the high ionic conductivity of the liquid electrolyte, the electrode material delivers superior electrochemical energy storage performance, achieving a specific capacitance of 800.7 mF/cm² at a current density of 1 mA/cm², together with remarkable rate capability and good cycling stability. To our knowledge, this composite exhibits a high level of integrated properties. More importantly, the strategy of integrating porous, high-strength supports with high-performance electrode materials opens new avenues for the synthesis of structure-energy-storage dual-functional composites. Full article

3D concrete printing (3DP) enables automated construction with reduced material waste and enhanced geometric flexibility. However, its structural performance remains sensitive to anisotropy, mix design, and printing parameters, thereby complicating quality control. Self-sensing cementitious materials provide a promising approach by enabling intrinsic strain monitoring during fabrication and service. In this study, a hybrid multi-material printing strategy was developed using a conductive cement-based mix incorporating graphite (G), milled carbon microfibers (MCMF), and chopped carbon microfibers (CCMF), alongside a plain cement-based matrix. Based on percolation analysis, an optimal composition of 2 wt.% G, 0.25 wt.% MCMF, and 0.0625 wt.% CCMF was selected. Reinforced beam specimens were fabricated with the conductive material embedded in either the tensile (bottom) or compressive (top) region, combined with two internal architectures: diagonal infill and solid-base configuration. Four configurations were defined: Pattern 1 (bottom/diagonal), Pattern 2 (bottom/solid-base), Pattern 3 (top/diagonal), and Pattern 4 (top/solid-base). Cyclic three-point bending tests with spatially distributed electrical measurements were conducted to evaluate the electromechanical response in the elastic range. Specimens with the conductive layer located in the tensile region (Patterns 1 and 2) consistently exhibited higher gauge factors than those in the compressive region (Patterns 3 and 4). Pattern 2 exhibited the best sensing performance, with an average gauge factor of 556 and SNR of 31. Across all configurations, SNR decreased with increasing electrode spacing, with reductions of up to 31.0%, demonstrating the effect of current path length on sensing performance. Full article