Search Results (255)

Silicon oxide/graphite (SiO_x/Gr) anodes are promising candidates for high energy-density lithium-ion batteries. However, their complex multiphysics degradation mechanisms pose challenges for accurately interpreting and predicting capacity fade behavior. In particular, existing multiphysics models typically treat gas generation and solid electrolyte interphase (SEI) growth as independent or unidirectionally coupled processes, neglecting their bidirectional interactions. Here, we develop an electro–thermal–mechanical–gaseous coupled model to capture the dominant degradation processes in SiO_x/Gr anodes, including SEI growth, gas generation, SEI formation on cracks, and particle fracture. Model validation shows that the proposed framework can accurately reproduce voltage responses under various currents and temperatures, as well as capacity fade under different thermal and mechanical conditions. Based on this validated model, a mechanistic analysis reveals two key findings: (1) Gas generation and SEI growth are bidirectionally coupled. SEI growth induces gas release, while accumulated gas in turn regulates subsequent SEI evolution by promoting SEI formation through hindered mass transfer and suppressing it through reduced active surface area. (2) Crack propagation within particles is jointly governed by the magnitude and duration of stress. High-rate discharges produce large but transient stresses that restrict crack growth, while prolonged stresses at low rates promote crack propagation and more severe structural degradation. This study provides new insights into the coupled degradation mechanisms of SiO_x/Gr anodes, offering guidance for performance optimization and structural design to extend battery cycle life. Full article

Pulse current-assisted flexible granular medium forming is a promising approach for manufacturing complex thin-walled components from difficult-to-deform Ti₂AlNb-based alloys. In this study, the electro-thermo-mechanical deformation behavior of Ti₂AlNb sheets is investigated through pulse current-assisted uniaxial tensile tests, microstructural characterization, and finite element simulations. The influences of pulse current intensity and strain rate on flow behavior, fracture characteristics, and phase evolution are clarified, and an effective forming window is identified. Numerical simulations are employed to analyze the role of granular medium friction in material flow and wall thickness distribution, providing guidance for forming box-shaped components. The results demonstrate that forming at approximately 950 °C with a strain rate of 0.001 s⁻¹ reduces deformation resistance, while enhanced tangential interaction between the granular medium and the sheet improves wall thickness uniformity. This study provides a feasible processing route and practical guidelines for the fabrication of complex Ti₂AlNb sheet components. Full article

The performance of cement adhesive in large-tonnage insulators is crucial for determining their structural stability and service life when subjected to long-term electromechanical loading and complex environmental interactions. This work addresses the issue of late-stage strength reduction in alumina cement by employing a rapid steam curing process. The influence of curing temperature on the phase composition and microstructure of the hydration products is investigated, along with the evolution over time of the mechanical properties, dry shrinkage rate and elastic modulus. These findings are further validated through thermal–mechanical performance testing of bonded insulators. The results demonstrate that: (1) The hydration products of the adhesive are significantly influenced by steam curing temperature: the metastable phase CAH₁₀ forms at 20 °C; it transforms into the metastable phase C₂AH₈ at 50–60 °C; it changes to the stable phase C₃AH₆ at 70 °C; and microcracks appear and porosity increases at 80–90 °C, although the stable phase C₃AH₆ remains the dominant phase. (2) Alumina cement adhesive prepared via 2 h steam curing at 70 °C exhibited superior properties, with flexural and compressive strengths reaching 14.2 MPa and 112.7 MPa, respectively. After 360 days, flexural strength remained above 12 MPa and compressive strength exceeded 110 MPa. Dry shrinkage was below 0.04%, with an elastic modulus of approximately 49.6 GPa. (3) Microstructural analysis revealed that the hydration products of the cured adhesive were predominantly C₃AH₆ and AH₃, exhibiting stable structures. After 90 days, porosity decreased to 3.56%, with the C₃AH₆ and AH₃ gels tightly enveloping the aggregates and forming a dense, three-dimensional network structure. (4) All bonded insulators successfully passed thermomechanical performance tests. Therefore, this work can provide a good way to prepare a high-performance cement adhesive for insulators. Full article

Bond wire degradation represents the predominant failure mechanism in IGBT modules, accounting for approximately 70% of power converter failures and posing significant reliability challenges in modern power electronic systems. Existing monitoring techniques face inherent trade-offs between measurement accuracy, implementation complexity, and electromagnetic compatibility. This paper proposes a physics-constrained ensemble learning framework for non-intrusive bond wire health assessment via V_ce-on prediction. The methodological innovation lies in the synergistic integration of multidimensional feature engineering, adaptive ensemble fusion, and domain-informed regularization. A comprehensive 16-dimensional feature vector is constructed from multi-physical measurements, including electrical, thermal, and aging parameters, with novel interaction terms explicitly modeling electro-thermal stress coupling. A dynamic weighting mechanism then adaptively fuses three specialized gradient boosting models (CatBoost for high-current, LightGBM for thermal-stress, and XGBoost for late-life conditions) based on context-aware performance assessment. Finally, the meta-learner incorporates a physics-based regularization term that enforces fundamental semiconductor properties, ensuring thermodynamic consistency. Experimental validation demonstrates that the proposed framework achieves a mean absolute error of 0.0066 V and R² of 0.9998 in predicting V_ce-on, representing a 48.4% improvement over individual base models while maintaining 99.1% physical constraint compliance. These results establish a paradigm-shifting approach that harmonizes data-driven learning with physical principles, enabling accurate, robust, and practical health monitoring for next-generation power electronic systems. Full article

Tissue engineering is entering a new era, one defined not by passive scaffolds but by smart, adaptive biomaterials that can sense, think, and respond to their surroundings. These next-generation materials go beyond simply providing structure; they interact with cells and tissues in real time. Recent advances in mechanically responsive hydrogels and dynamic crosslinking have demonstrated how materials can adjust their stiffness, repair themselves, and transmit mechanical cues that directly influence cell behavior and tissue growth. Meanwhile, in vivo studies are demonstrating how engineered materials can harness the body’s own mechanical forces to activate natural repair programs without relying on growth factors or additional ligands, paving the way for minimally invasive, force-based therapies. The emergence of electroactive and conductive biomaterials has further expanded these capabilities, enabling two-way electrical communication with excitable tissues such as the heart and nerves, supporting more coordinated and mature tissue growth. Meanwhile, programmable bioinks and advanced bioprinting technologies now allow for precise spatial patterning of multiple materials and living cells. These printed constructs can adapt and regenerate after implantation, combining architectural stability with flexibility to respond to biological changes. This review brings together these cross-cutting advances, dynamic chemical design, mechanobiology-guided engineering, bioelectronic integration, and precision bio-fabrication to provide a comprehensive view of the path forward in this field. We discuss key challenges, including scalability, safety compliance, and real-time sensing validation, alongside emerging opportunities such as in situ stimulation, personalized electromechanical sites, and closed loop “living” implants. Taken together, these adaptive biomaterials represent a transformative step toward information-rich, self-aware scaffolds capable of guiding regeneration in patient-specific pathways, blurring the boundary between living tissue and engineered material. Full article

Irregular wheel wear can significantly degrade wheel–rail interaction performance and, in severe cases, compromise the safety of high-speed trains. Accurate and timely monitoring of wheel wear is crucial for maintaining operational reliability. Existing monitoring methods often rely on high-end sensors or are sensitive to environmental disturbances, limiting their practical deployment. This study proposes a novel method for monitoring irregular wheel wear by analyzing the stator current spectrum of traction motors. Firstly, an electromechanical coupled model is developed by integrating the electric drive system with the vehicle–track dynamic model to capture the propagation of wear-induced excitation. The effect of polygonal wear on the stator current is investigated, revealing the presence of harmonic components coupled with the wear excitation frequency. To extract these features, a comb filter based on Variational Mode Decomposition (VMD) is introduced. The method effectively isolates wheel wear-related harmonics from existing electrical harmonics in the stator current signal. Simulation results demonstrate that the proposed approach can accurately detect harmonic features caused by polygonal wear, validating its applicability. This method provides a feasible and non-intrusive solution for wheel wear monitoring, offering theoretical support for condition-based maintenance of high-speed rail systems. Full article

This paper presents a comparative assessment of interaction analysis methods applied to a multi-variant offshore power system model. Complementary analytical techniques—eigenvalue analysis, frequency–response characteristics, RGA, DRGA, and GDRG—are used to quantify interactions across electromechanical and electromagnetic frequency ranges. The main novelty of this study is a modified DRGA approach that incorporates a hybrid FIR/IIR digital filtering stage, significantly improving the accuracy of interaction evaluations. The results show that no single method provides complete data and that the enhanced DRGA and GDRG techniques are essential for interaction analysis. The proposed framework offers practical guidelines for analyzing and coordinating control loops in offshore grids. Full article

Waste stone powder is a major solid waste byproduct of stone operations. This study developed a novel “alkali activation-calcination” process that efficiently converts waste stone powder into high-value-added silicon-based materials (SSM). This study elucidated the morphological evolution of silicon during the conversion process and revealed the formation mechanism of active silicon. Through further integration of batch adsorption experiments and multi-technique characterization analysis, the immobilization efficacy of this material for heavy metals cadmium/lead was elucidated, revealing both direct and indirect interfacial reaction mechanisms. The results demonstrate that in-creasing the calcination temperature, alkali activator concentration, and calcination duration enhances the reactive silica content in SSM. NaOH as activator, the calcination process significantly reduces both the thermal decomposition temperature of raw materials and the initial temperature required for silicon conversion. Under optimized conditions (WG:MD:activator = 1:0.8:0.32, temperature = 800 °C, time = 1 h), the reactive silica content reached 24.30%. The generation rate of reactive silica is governed by the combined effects of interfacial chemical reactions and solid-phase product layer diffusion. Under idealized laboratory conditions, the maximum adsorption capacities (Qm) of SSM were determined to be 57.40 mg/g for cadmium and 496 mg/g for lead, which are significantly higher than those of many other adsorbents. Continuous desorption experiments and characterization analyses confirm that Cd and Pb adsorption by SSM is primarily driven by electro-static interactions, complexation, precipitation, and coordination, while ion ex-change plays a secondary role. Highly reactive silica facilitates interactions between Cd/Pb and oxygen-containing functional groups (e.g., -OH, ≡Si-OH, Si-O-Si), promoting precipitate formation for effective heavy metal removal. This work offers theoretical guidance for valorizing silica-rich waste rock powder. It is important to note, however, that while the adsorption capacity of SSM is encouraging, its practical implementation requires resolving key issues identified during the lab-to-application transition. Full article

Biocompatible electroactive hydrogels with bidirectional pH-responsive bending are important for the creation of biomedical actuators. This study developed chitosan/carboxymethylcellulose (CS/CMC) semi-interpenetrating networks (SIPNs) with different volume ratios, which were crosslinked with glutaraldehyde. The swelling and bending behaviors of SPINs were systematically characterized as a function of the pH of the solution and the magnitude of the applied electric field. The hydrogels exhibited pH-dependent bidirectional actuation, with the maximum swelling of 4.67–6.00 at pH ≈ 3.9 and minimum swelling of 1.58–2.53 at pH ≈ 5.7. The SPINs with CS/CMC = 1:1 composition achieved the highest bending angle of 77° at pH ≈ 5.7, while cathodic bending up to an angle of −13.7° was observed in basic conditions. The electromechanical response was significantly enhanced by decreasing the electrode distance and increasing the applied voltage. The observed correlation between the composition, swelling behavior, and bending performance was explained in terms of the electrostatic interactions between NH₃⁺ and COO⁻ groups present in the CS/CMC mixtures. These findings provided novel insight into the ongoing efforts for the development of non-toxic electroactive hydrogels with tailored electromechanical bending behavior necessary for use as artificial muscles and biomedical actuators. Full article

The increasing adoption of electric bicycles (e-bikes) has led to a growing need for advanced active safety systems, such as anti-lock braking systems (ABSs), to enhance rider safety. In recent years, both hydraulic and electromechanical ABSs were researched. To support the development and validation of these systems, this paper presents a longitudinal vehicle dynamics model of an electric bicycle. The model captures key physical interactions, including drivetrain, transmission, braking, and tire–road contact, to accurately simulate longitudinal motion. By leveraging this model, future studies can perform virtual validation of active safety components in a controlled and repeatable environment, reducing the dependency on costly and time-intensive physical testing. The proposed model lays the foundation for a model-based design approach, enabling early-stage performance assessment and optimization of safety-critical functions in electric bicycles. Full article

Ruggedized computers are the core of modern communication, guidance, control, and data-processing systems, and typically operate under extreme environmental conditions. However, under extreme service conditions such as temperature cycling, vibration, and mechanical shock, thermo–electro–mechanical (TME) multi-physics coupling in ball grid array (BGA) solder joints is particularly significant, severely affecting system reliability and signal integrity. To comprehensively elucidate the effects of thermal, electrical, and mechanical fields on solder joints and signal transmission, this study proposes a multiscale multi-physics modeling and analysis framework for BGA solder joints in microelectronic systems of ruggedized computers, covering the computer system level, motherboard level, solder joint level, and solder interconnect level. A model correlation study under ten thermal cycling conditions demonstrated an accuracy of 88.89%, confirming the validity and applicability of the proposed model. Based on this validated framework and model, the temperature distribution, stress–strain response, and signal integrity characteristics were further analyzed under combined conditions of thermal cycling, random vibration, and mechanical shock. The results indicate that a rise in temperature in solder joints induces thermal stresses and deformations, while variations in electrical conductivity under thermal loading trigger electromigration and concentration evolution, which further couple with stress gradients to form TME multi-physics interactions. Under such coupling, critical solder balls exhibit stress concentration at the metallurgical interfaces, with a maximum von Mises stress of 191.51 MPa accompanied by plastic strain accumulation. In addition, the PCIe high-speed interconnect experienced a maximum deformation of 16.104 μm and a voltage amplitude reduction of approximately 18.51% after 928 thermal cycles, exceeding the normal operating range. This research provides a theoretical basis and engineering reference for reliability assessment and optimization design of microelectronic systems in ruggedized computers in complex service environments. Full article

This study investigates the combined resonance phenomenon in magneto-electro-elastic (MEE) cylindrical shells under longitudinal and lateral excitations with thermal factors, addressing the complex interaction between mechanical, electrical, and magnetic fields in smart structures. The research aims to establish a theoretical framework for predicting resonance behaviors in energy harvesting and sensing applications. Using Maxwell’s equations and Hamilton’s principle, the governing equations for combined resonance are derived. The method of varying amplitude (MVA) is employed to acquire the combined resonance response across varying parameters. Furthermore, the Runge–Kutta method is applied to investigate the bifurcation and chaotic motion characteristics under different longitudinal and lateral excitation conditions. Key findings reveal the coupling effects of multi-physical fields on resonance frequencies, demonstrating quantitative agreement with prior studies. The results provide fundamental insights into the dynamic characteristics of MEE materials, offering theoretical support for optimizing their performance in adaptive engineering systems. Full article

Background and Objectives: Postoperative atrial fibrillation (POAF) remains one of the most frequent complications after cardiac surgery, increasing the risk of morbidity, prolonged hospitalization, and adverse long-term outcomes. Although several clinical and echocardiographic factors have been associated with POAF, the integrated contribution of atrial conduction delay, biatrial mechanics, and atrioventricular coupling to arrhythmogenesis remains unclear. Materials and Methods: This retrospective study included 131 adult patients undergoing coronary artery bypass grafting and/or aortic valve replacement. Preoperative echocardiography within one week before surgery provided detailed assessment of atrial phasic function, valvular motion, and total atrial conduction time (TACT). Univariate analysis was followed by multivariable modeling using penalized logistic regression (Elastic Net) to identify the most robust predictors of POAF. Discriminative performance and calibration were evaluated via receiver operating characteristic (ROC) and calibration analysis. An exploratory Extreme Gradient Boosting (XGBoost) model with SHapley Additive exPlanations (SHAP) analysis was used to confirm the stability and directionality of nonlinear feature interactions. Results: POAF occurred in 47 (36%) patients. The Elastic Net model identified prolonged TACT, reduced right atrial active emptying fraction (RAAEF), increased indexed minimal left atrial volume (MIN LA/BSA), and lower tricuspid annular plane systolic excursion (TAPSE) as the most informative predictors. The model demonstrated excellent internal discrimination (AUC = 0.95; 95% CI 0.91–0.99) and satisfactory calibration (Hosmer–Lemeshow p = 0.41). Exploratory XGBoost analysis yielded concordant feature hierarchies, confirming the physiological consistency of the results. Conclusions: POAF arises from an identifiable electromechanical substrate characterized by atrial conduction delay, biatrial mechanical impairment, and reduced atrioventricular coupling. A parsimonious, regularized statistical model accurately delineated this profile, while complementary machine-learning analysis supported its internal validity. These findings underscore the potential of echocardiographic electromechanical parameters for refined preoperative risk stratification, pending prospective multicenter validation. Full article

As a favorable hydrophilic additive for antifouling modification of polyvinylidene fluoride (PVDF) membrane, titanium dioxide (TiO₂) nanoparticles have been applied for years. Sodium dodecyl sulfonate (SDS), a representative anionic surfactant, has been proven to benefit the dispersion of nano-TiO₂ via an electro-spatial stabilizing mechanism. In this study, various proportionally SDS-functionalized TiO₂ nanoparticles were adopted to modify PVDF membrane. Dispersion and stability of SDS-functionalized TiO₂ nanoparticles in casting solutions were evaluated by multiple light scattering technology. The properties and antifouling performance of PVDF/SDS-TiO₂ composite membranes were assessed. The uniformity of surface pores as well as structures on cross-section morphologies was modified. The finger-like structure of PVDF/SDS-TiO₂ composite membrane was adequately developed at the SDS/TiO₂ mass ratio of 1:1. The improved antifouling performance was corroborated by the increasing free energy of cohesion and adhesion as well as the interaction energy barrier between membrane surfaces and approaching foulants assessed by classic extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) theory, the low flux decline during bovine serum albumin (BSA) solution filtration process, and the high critical flux (38 L/(m²·h·kPa)) in membrane bioreactor. This study exploits a promising way to modify PVDF membrane applicable to the wastewater treatment field. Full article

This paper presents a dynamic modeling approach for a 3-phase BLDC motor used in a differential-drive serving robot using bond graph (BG) methodology. Designed for structured indoor environments, the serving robot incorporates mechanical, electrical, and control components that require an integrated modeling strategy. Traditional methods often fall short in handling the multi-domain nature of such systems. Bond graphs, with their energy-based modeling capability, offer a unified framework for capturing electromechanical dynamics and physical interactions. This work develops a complete bond graph model of a three-phase BLDC motor-driven robot, simulates its performance under typical operating conditions, and validates the model through current, torque, EMF, and velocity responses. The results demonstrate the model’s effectiveness in reflecting real-world robot behavior, supporting future design optimization and control development. Full article