Search Results (350)

This study introduces a novel hybrid model for an electromembrane stack, unifying an equivalent electrical circuit model incorporating specific resistance ($R_M,R_s$) and capacitance ($C_{gs},C_{dl}$) parameters with an empirical fouling model in a single framework. The model simplifies the traditional approach by serially connecting N ($N=10$) ion exchange membranes (anionic PC-SA and cationic PC-SK) and is validated using $NaCl$ and $N{a}_{2}S{O}_4$ solutions in comparison with laboratory tests using various voltage signals, including direct current and electrically pulsed reversal operations at frequencies of 2000 and 4000 Hz. The model specifically accounts for the chemical stratification of the cell unit into bulk solution, diffusion, and Stern layers. We also included a calibration method using correction factors (${\alpha }_i$) to fine-tune the electrical current signals induced by voltage stimulation. The empirical component of the model uses experimental data to simulate membrane fouling, ensuring consistency with laboratory-scale desalination processes performed under pulsed reversal operations and achieving a prediction error of less than 10%. In addition, a comparative analysis was used to assess the increase in electrical resistance due to fouling. By integrating electronic and empirical electrochemical data, this hybrid model opens the way to the construction of simple, practical, and reliable models that complement theoretical approaches, signifying an advance for a variety of electromembrane-based technologies. Full article

In this work, a substrate-integrated waveguide (SIW) filtering power divider with a modified complementary split-ring resonator (CSRR) is reported. Firstly, by integrating the meander-shaped slots with the conventional CSRR, the proposed inner-meander-slot CSRR (IMSCSRR) can enlarge the total length of the defected slot and increase the width of the split, thus enhancing the equivalent capacitance and inductance. In this way, the fundamental resonant frequency of the IMSCSRR can be effectively decreased without enlarging the circuit size, which can generally help to reduce the physical size by over 35%. Subsequently, to further reduce the circuit size, two IMSCSRRs are separately loaded on the top and bottom metal covers to constitute a broadside-coupled IMSCSRR, which is combined with the SIW. To verify the efficacy of the proposed SIW-IMSCSRR unit cell, a two-way filtering power divider is implemented. It combines the band-selection function of a filter and the power-distribution property of a power divider, thereby enhancing system integration and realizing size compactness. Experimental results show that the proposed filtering power divider achieves a center frequency of 3.53 GHz, a bandwidth of about 320 MHz, an in-band insertion loss of (3 + 1.3) dB, an in-band isolation of over 21 dB, and a size reduction of about 30% compared with the design without broadside-coupling, as well as good magnitude and phase variations. All the results indicate that the proposed filtering power divider achieves a good balance between low loss, high isolation, and compact size, which is suitable for system integration applications in microwave scenarios. Full article

Accurate estimation of internal temperature is essential for safe operation and state estimation of lithium-ion batteries, yet it usually cannot be measured directly and requires physically grounded electro-thermal models. High fidelity 3D simulations capture geometry-dependent heat transfer behavior but are too computationally intensive for real-time use, whereas common lumped models cannot represent internal gradients. This work presents an integrated geometry-resolved workflow that combines detailed 3D finite volume thermal modeling with systematic reduction to a compact multi-node thermal network and its coupling with an equivalent circuit electrical model. A realistic 3D model of the Panasonic NCR18650B cell was reconstructed from computed tomography data and literature parameters and validated against published axial and radial thermal conductivity measurements. The automated reduction yields a five-node thermal network preserving radial temperature distribution, which was coupled with five parallel Battery Table-Based blocks in MATLAB/Simulink R2024b to capture spatially distributed heat generation. Experimental validation under dynamic loading is performed using measured surface temperature and terminal voltage, showing strong agreement (surface temperature MAE ≈ 0.43 °C, terminal voltage MAE ≈ 16 mV). The resulting model enables physically informed estimation of internal thermal behavior, is interpretable, computationally efficient, and suitable for digital twin development. Full article

The surface morphology of lithium metal electrodes evolves markedly during cycling, modulating interfacial kinetics and increasing the risk of dendrite-driven internal short circuits. Here, we infer this morphological evolution from direct-current (DC) signals by analyzing open-circuit voltage (OCV) transients after constant current interruptions. The OCV exhibits a rapid initial decay followed by a transition to a slower long-time decay. With repeated plating, this transition shifts to earlier times, thereby increasing the contribution of long-term relaxation. We quantitatively analyze this behavior using an equivalent circuit with a transmission-line model (TLM) representing the electrolyte-accessible interfacial region of the electrode, discretized into ten depth-direction segments. Tracking segment-wise changes in resistances and capacitances with cycling enables morphology estimation. Repeated plating strongly increases the double-layer area near the current collector, while the charge-transfer-active surface shifts toward the separator side, showing progressively smaller and eventually negative changes toward the current-collector side. Together with the segment-resolved time constants, these trends indicate that lithium deposition becomes increasingly localized near the separator-facing surface, while the interior becomes more tortuous, consistent with post-mortem observations. Overall, the results demonstrate that DC voltage-relaxation analysis combined with a TLM framework provides a practical route to track lithium metal electrode surface evolution in Li-metal-based cells. Full article

This study proposes an indirect approach that estimates roll force from motor current signals in a rolling mill. Motor current is first converted to motor torque using an induction-motor equivalent-circuit model, then to roll torque via the gear ratio, and finally to roll force through a torque-arm relationship. A laboratory-scale rolling mill was designed and fabricated to experimentally validate the approach. Two torque-conversion schemes were examined: Method A, which determines the slip of the induction motor from measured rpm and recalculated motor parameters, and Method B, which estimates slip from measured motor current and applies a finite element (FE)–based response surface function to calibrate the converted torque. The converted roll torques were validated against FE analysis, and the resulting roll forces were compared with load cell measurements under various rolling conditions. Deviation, defined as the average difference between the FE-predicted torque and the converted torques, ranged from −11.9% to 28.8% for Method A and −7.2% to 13.8% for Method B. Roll force deviations from measurements ranged from −14.1% to 14.9% for Method A and −3.7% to 14.2% for Method B. Method A provided a straightforward and computationally light conversion route but was more sensitive to rpm-measurement noise, whereas Method B yielded smoother temporal behavior at the cost of FE-based calibration. The results demonstrate that both methods can reproduce the overall evolution of roll torque and roll force using only motor-side measurements, offering a practical foundation for real-time monitoring in rolling mills where stand-by-stand load cells are unavailable. Full article

Previous studies on reconfigurable intelligent metasurface (RIS) design have primarily relied on full-wave electromagnetic simulation software, which often incurs high computational costs and lacks clear design direction. The design of multi-bit RIS remains challenging and there is currently no suitable systematic method for selecting the corresponding tuning devices. To overcome these limitations, this article proposes a novel equivalent circuit-based approach to RIS design. In contrast to the conventional approach, where the equivalent circuit model is derived from post-design evaluation of the scattering properties of RIS, our work is entirely driven by the equivalent circuit model from the outset to accomplish the unit cell design. A complete workflow as well as details of each constituent step are presented for the topology design of RIS based on equivalent circuit topology. Building on this circuit topology, a 3-bit reflective phase reconfigurable unit cell is developed based on a tunable band-stop filter circuit. We conducted adjustable phase verification experiments and beam deflection experiments. The consistency between the experimental results and circuit theory demonstrates the feasibility and practicality of the equivalent circuit method of RIS design. This circuit-to-structure methodology provides a physically interpretable and systematic framework for designing RIS with arbitrary electromagnetic responses, offering new insights into RIS design. Full article

This study presents a comparative analysis of the performance and modeling differences among lithium titanate oxide (LTO) batteries with three different cathode materials. An evaluation was conducted by performing performance tests over −20 °C to 25 °C at various current rates. Differences in open-circuit voltage curves, as well as charge and discharge capacities under different temperatures and C-rates, were systematically compared. At 25 °C, the NCM cathode enabled superior rate capability, retaining over 90% of its capacity at 8 C discharge, whereas the LCO-based cells exhibited significant capacity fade. Conversely, at −20 °C, the LCO cathode demonstrated better low-temperature performance, delivering almost 80% of its room-temperature capacity at 4 C, compared to less than 5% for the NCM cathode. The batteries were modeled using a second-order equivalent circuit model, and variations in model parameters were analyzed from the perspectives of internal resistance and electrode kinetics. The second-order equivalent circuit model revealed that the NCM-based cells had lower ohmic resistance and faster electrode kinetics. By correlating battery performance with cathode materials, this study evaluates the suitability of LTO batteries with different cathodes for various application scenarios, providing valuable insights for battery application and management. Full article

Improving the interfacial stability of graphite anodes remains a major challenge for extending the lifetime of lithium-ion batteries. In this study, ultrananocrystalline diamond (UNCD) and nitrogen-incorporated UNCD (N-UNCD) coatings were employed as protective layers to enhance the electrochemical and mechanical robustness of graphite electrodes. Half-cells were cycled for 60 charge–discharge cycles, and their behavior was examined through electrochemical impedance spectroscopy (EIS), Distribution of Relaxation Times (DRT), and Equivalent Circuit Modeling (ECM) to disentangle the characteristic relaxation processes. The potential–capacity profiles exhibited the typical LiC₁₂–LiC₆ transition plateaus without any additional features for the coated electrodes, confirming that the UNCD and N-UNCD films do not participate in lithium storage but serve as chemically inert and electrically stable interlayers. In contrast, the uncoated reference graphite anodes showed greater capacity fluctuations and increasing interfacial impedance. DRT and ECM analyses revealed four consistent relaxation processes—electronic transport (τ₁), ionic transport through the electrolyte (τ₂), Solid Electrolyte Interface (SEI) response (τ₃), and lithium intercalation (τ₄). The τ₂ process remained invariant, whereas τ₃ and τ₄ were markedly stabilized by the UNCD and N-UNCD coatings. UNCD exhibited the lowest SEI-related resistance and the most stable charge-transfer kinetics, while N-UNCD displayed an initially higher τ₃ resistance followed by progressive self-stabilization after 20 charge/discharge cycles, linked to reorganization of nitrogen-rich grain boundaries. Overall, polycrystalline diamond coatings—particularly UNCD—proved to be highly effective in suppressing SEI layer growth, minimizing impedance rise, and preserving lithium intercalation efficiency, leading to enhanced long-term electrochemical performance. These findings highlight the potential of diamond-based protective layers as a durable and scalable strategy for next-generation graphite anodes. Full article

The phase-pure cubic pyrochlore of the Bi₂Cr_0.5Co_0.5Nb₂O_9+Δ composition can be successfully synthesized by a modified sol–gel method (Pecini method-PM) and a traditional solid-phase method (SPM). A feature of the solid-phase synthesis method is the formation of bismuth(VI) chromates as intermediate synthesis products, which is confirmed by X-ray spectroscopy data (NEXAFS). During the sol–gel synthesis method, bismuth chromates are not formed due to the formation of the Bi₂₈O₃₂(SO₄)₁₀ salt, which is thermally stable up to 880 °C, preventing the interaction of bismuth(III) and chromium(III) oxides. The temperature of the final pyrochlore calcination during sol–gel synthesis is reduced by 100 °C (950 °C) compared to the solid-phase method. The crystal structure of pyrochlore (sp. gr. Fd-3m, PM, a = 10.49360(5) Å, Z = 4) was refined by the Rietveld method based on X-ray powder diffraction (XRD) data. NEXAFS Cr2p and Co2p spectra of ceramics synthesized at 1050 °C correspond to the charge states of Cr(III), Co(II) and Co(III) ions. The thermal expansion coefficient of the cell was calculated from high-temperature X-ray diffraction measurements in the range of 20–1200 °C. The thermal expansion coefficient (TEC) monotonically increases from 3.92 × 10⁻⁶ °C⁻¹ (20 °C) to 9.89 × 10⁻⁶ °C⁻¹ (1020 °C). Above 1110 °C, TEC decreases due to thermal dissociation of Bi₂Cr_0.5Co_0.5Nb₂O_9+Δ with the formation of CoNb₂O₆, Bi₂O₃. The mixed pyrochlore (PM) exhibits a moderately high permittivity of ∼97, and low dielectric losses of ∼2 × 10⁻³ at 1 MHz and ∼30 °C. The activation energy of conductivity of the high-temperature region is 0.89 eV. The electrical properties of pyrochlore were synthesized by the ceramic (SPM) and Pechini methods (PM) were analyzed. The electrical properties of the samples up to 400 °C were modeled using equivalent electrical circuits Full article

Eosinophilic granulomatosis with polyangiitis (EGPA) is a rare systemic vasculitis characterized by asthma, eosinophilia, and necrotizing inflammation of small- to medium-sized vessels. Accumulating evidence indicates that EGPA is a polygenic and heterogeneous disorder comprising distinct antineutrophil cytoplasmic antibody (ANCA)–defined endotypes with divergent genetic backgrounds, immune pathways, and clinical phenotypes. Its pathogenesis reflects the convergence of epithelial–alarmin signaling, type 2 inflammation, eosinophil effector mechanisms, and B-cell/autoantibody responses, with myeloperoxidase (MPO)-ANCA serving as a hallmark of the vasculitic subset. Recent advances in genomics, immunology, and multi-omics profiling have uncovered biomarkers and molecular circuits sustaining disease activity and guiding therapeutic stratification. The identification of the interleukin (IL)-5–eosinophil axis, epithelial-derived alarmins, and B-cell/IgG4 networks as central pathogenic nodes has enabled the development of targeted biologic therapies that are redefining treatment paradigms. Benralizumab (anti-IL-5Rα) has recently been approved for EGPA following the phase 3 head-to-head MANDARA trial, which demonstrated non-inferiority to mepolizumab in achieving remission (BVAS = 0 with ≤4 mg/day prednisone equivalent) at weeks 36 and 48. These results, together with the established efficacy of mepolizumab, inform practical selection between IL-5 and IL-5Rα blockade and support glucocorticoid-sparing approaches. A structured literature search (2015–2025) was conducted in PubMed, Scopus, and Web of Science to identify recent advances in epidemiology, genetics, biomarkers, and targeted therapies for EGPA. This updated review integrates molecular insights, clinical endotypes, and therapeutic innovations to outline current evidence and future precision-medicine strategies aimed at improving long-term patient outcomes. Full article

The low recovery of fine chalcopyrite particles and the limited Cu/Fe selectivity with conventional thiol collectors prompted the evaluation of a Polystyrene–Divinylbenzene–Cetyltrimethylammonium Bromide–Potassium Amyl Xanthate (PS-DVB-CTAB-PAX) polymeric nanocollector. The copolymer was synthesized by emulsion polymerization and characterized using Total Organic Carbon (TOC) analysis, Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), Particle Size Analysis, and contact angle measurement. Its performance was tested in a Hallimond cell (150 mL) using a synthetic industrial water solution (0.010 mol/L NaCl + 0.005 mol/L CaCl₂) at a natural pH range of 6.0 to 8.0. PAX concentrations ranged from 0 to 16.19 mg L⁻¹, and nanocollector doses equivalent to 0 to 45 mg g⁻¹ of solid were tested. The nanocollector increased chalcopyrite recovery to 98 ± 1% for the −53 + 38 µm size fraction and maintained values greater than 95% in the coarse fractions, outperforming PAX across the entire dosage range. The PAX + nanocollector combination achieved the same recovery by reducing the total xanthate dosage by one-third, demonstrating a synergistic effect. TOC assays showed preferential adsorption of 96.6% on chalcopyrite versus 86.4% on pyrite, a difference that explains the observed Cu/Fe selectivity (pyrite floatability < 70%). The contact angle of chalcopyrite increased from 56.4° (water) to 86.5° in the presence of the nanocollector, demonstrating the generation of localized superhydrophobicity that reduces interfacial free energy and favors bubble–particle adhesion, whereas pyrite showed lower values of 51.1°, 58.3°, and 75.1°, confirming its more hydrophilic nature. These findings indicate that PS-DVB-CTAB-PAX enables optimized copper sulfide recovery, reduced thiol collector consumption, and improved metallurgical selectivity, making it a promising alternative for flotation circuits with high ionic strength water and for scaling up to pilot tests. Full article

Swelling in pouch batteries poses reliability issues and safety hazards, resulting in product damage, fires, and explosions. This study examines swelling based on the impact of C-rate and temperature during charge–discharge tests, and upper voltage limit and temperature during constant voltage/float charging tests. Internal cell dynamics related to swelling are analyzed using equivalent circuit model parameters from electrochemical impedance spectroscopy tests, and correlations with thickness are established. Constant voltage charging experiments show that swelling follows an initial increase, a plateau, and then a rapid escalation. The onset of rapid swelling accelerated with temperature and voltage, thereby reducing the time to the knee point. A double-exponent swelling model is developed to predict the evolution of thickness under various stress conditions. The results demonstrate that monitoring swelling rate and magnitude can serve as an effective diagnostic for identifying abnormal cell behavior. Full article

We present a time-domain direct current (DC) approach to differentiate positive- (PE) and negative-electrode (NE) contributions from two-electrode full-cell signals in lithium-ion batteries, enabling electrode-resolved diagnostics without specialized instrumentation. The responses of a LiNi_0.8Co_0.1Mn_0.1O₂ (PE)/graphite (NE) cell were recorded across −20 to 20 °C during galvanostatic pulses and subsequent open-circuit relaxations, alongside electrochemical impedance spectroscopy (EIS) measurements. These responses were analyzed using an equivalent-circuit-based model to decompose them into terms with characteristic times. Their distinct temperature dependences enabled attribution of the dominant terms to PE or NE, especially at low temperatures where temporal separation is substantial. The electrode attribution and activation energies were cross-validated against three-electrode measurements and were consistent with EIS-derived time constants. Reconstructing full-cell voltage transients from the identified terms reproduced the measured electrode-specific behavior, and quantitative comparisons showed that the DC time-domain separation aligned closely with directly measured PE/NE overpotentials during the current pulse. These results demonstrate a practical pathway to extract electrode-resolved information from cell voltage alone, offering new methodological possibilities for battery diagnostics and management while complementing three-electrode and alternating current (AC) techniques that are often constrained in field applications. Full article

The accurate estimation of the state of charge (SOC) and state of health (SOH) is essential for the safety and reliability of electric vehicle batteries. Conventional single-state Kalman filters are prone to parameter drift caused by cell aging, which leads to persistent SOC estimation errors. This study compares two dual-estimator methods, the Dual Extended Kalman Filter (DEKF) and the Dual Unscented Kalman Filter (DUKF), for simultaneous SOC and SOH estimation using a second-order equivalent-circuit model. The process and measurement covariance matrices were tuned through a structured optimization procedure to ensure consistent performance under different drive cycles and initialization errors. To mitigate the weak voltage sensitivity to capacity, synthetic SOC–capacity coupling was introduced to enhance SOH observability and accelerate convergence. Simulations conducted under the Urban Dynamometer Driving Schedule (UDDS) and a real-world CLUST7 profile demonstrated SOC root-mean-square errors near 2% for both filters. The DUKF achieved faster and smoother convergence than the DEKF but required roughly fivefold higher computational cost. These findings provide quantitative evidence supporting dual Kalman filtering as an effective framework for accurate and robust SOC/SOH estimation in production battery management systems. Full article

Accurate estimation of the state of health (SOH) of lithium-ion batteries is essential for the safe and efficient operation of electric vehicles (EVs). Conventional approaches, including Coulomb counting, electrochemical impedance spectroscopy, and equivalent circuit models, provide useful insights but face practical limitations such as error accumulation, high equipment requirements, and limited applicability across different conditions. These challenges have encouraged the use of machine learning (ML) methods, which can model nonlinear relationships and temporal degradation patterns directly from cycling data. This paper reviews four machine learning algorithms that are widely applied in SOH estimation: support vector regression (SVR), random forest (RF), convolutional neural networks (CNNs), and long short-term memory networks (LSTMs). Their methodologies, advantages, limitations, and recent extensions are discussed with reference to the existing literature. To complement the review, MATLAB-based simulations were carried out using the NASA Prognostics Center of Excellence (PCoE) dataset. Training was performed on three cells (B0006, B0007, B0018), and testing was conducted on an unseen cell (B0005) to evaluate cross-battery generalisation. The results show that the LSTM model achieved the highest accuracy (RMSE = 0.0146, MAE = 0.0118, R² = 0.980), followed by CNN and RF, both of which provided acceptable accuracy with errors below 2% SOH. SVR performed less effectively (RMSE = 0.0457, MAPE = 4.80%), reflecting its difficulty in capturing sequential dependencies. These outcomes are consistent with findings in the literature, indicating that deep learning models are better suited for modelling long-term battery degradation, while ensemble approaches such as RF remain competitive when supported by carefully engineered features. This review also identifies ongoing and future research directions, including the use of optimisation algorithms for hyperparameter tuning, transfer learning for adaptation across battery chemistries, and explainable AI to improve interpretability. Overall, LSTM and hybrid models that combine complementary methods (e.g., CNN-LSTM) show strong potential for deployment in battery management systems, where reliable SOH prediction is important for safety, cost reduction, and extending battery lifetime. Full article