Search Results (900)

Sodium-ion batteries (SIBs) present a sustainable alternative to lithium-ion systems due to the abundance and low environmental impact of sodium. However, their integration into multifunctional structural battery systems that combine electrochemical and mechanical properties remains unexplored. This work investigates the electrochemical performance of sodium-ion chemistry within a structural battery framework using unsized carbon fiber (UCF) as both a structural substrate and active electrode material. Ultrasonic spray coating was employed to deposit Mesocarbon Microbeads (MCMB) and NaNi${}_{1/3}$Fe${}_{1/3}$Mn${}_{1/3}$O${}_2$ (NFM) on UCF to form hybrid anode and cathode half-cells, respectively, with 1 M NaPF${}_6$ in diglyme electrolyte. The MCMB on UCF hybrid anode demonstrated dual graphitic and carbon fiber storage mechanisms, achieving 50 mAh g${}^{-1}$ capacity over 500 cycles at 1C with excellent Coulombic efficiency. The NFM–UCF cathode exhibited an initial capacity of 27.5 mAh g${}^{-1}$ and maintained over 80% capacity retention for 230 cycles, continuing to cycle stably beyond 400 cycles. Post-cycling SEM imaging revealed surface cracking, particle expansion, and gas-pocket formation in both electrodes. These results demonstrate the electrochemical viability of sodium-ion chemistry in a multifunctional structural configuration and establish ultrasonic coating as a scalable, precise method for fabricating carbon fiber electrodes toward future sodium-ion structural batteries. Full article

The rapid advancement of wearable technology has created an increasing demand for efficient, high-performance energy storage systems that also offer key characteristics such as flexibility, lightweight, and durability. Among the emerging materials, polymer hydrogels have garnered significant attention due to their unique combination of viscoelasticity, low density, and tunable porous nanostructures. These materials exhibit adaptable surface and structural properties, making them promising candidates for next-generation flexible and wearable energy storage devices. This work provides an overview of recent progress and innovations in the application of polymer hydrogels for the development of flexible energy storage systems. The intrinsic three-dimensional architecture and porous morphology of these hydrogels offer a versatile platform for constructing high-performance supercapacitors, rechargeable batteries, and personal thermal management devices. Various types of polymer hydrogels and their principal fabrication methods are discussed in detail, along with the structural factors that influence their electrochemical and mechanical performance. Furthermore, recent advancements in integrating polymer hydrogel materials into wearable and flexible technologies—such as energy storage devices, thermal regulation systems, and multifunctional energy platforms—are comprehensively reviewed and analyzed. Full article

Background: The Na⁺/K⁺-ATPase (NKA) maintains electrochemical gradients by exporting Na+ and importing K⁺ at the expense of ATP hydrolysis. Although NKA inhibition is a well-established strategy for increasing cardiac contractility, existing inhibitors such as cardiotonic steroids (CTS) are limited by serious adverse effects. N106 is a small molecule previously shown to enhance cardiac lusitropy by promoting SERCA2a SUMOylation and, intriguingly, also exerts positive inotropic effects, suggesting additional mechanisms of action. Methods: To test whether N106 directly modulates NKA, we combined ATPase activity assays with molecular docking and microsecond-scale molecular dynamics simulations. Results: Biochemical measurements showed that N106 partially inhibits NKA, achieving ~80% maximal inhibition with an IC50 of 7 ± 1 µM, while leaving the pump’s apparent affinity for Na⁺, K⁺, and ATP unchanged. Computational analyses suggest that N106 binds within the canonical CTS-binding pocket but undergoes intermittent unbinding events, consistent with the partial inhibition observed experimentally. Conclusions: These findings identify N106 as a first-in-class dual modulator of cardiac ion pumps, partially inhibiting NKA while previously shown to activate SERCA2a through enhanced SUMOylation. This combined mechanism likely underlies its positive inotropic and lusitropic effects and positions the N106 scaffold as a promising lead for developing next-generation dual-target therapeutics for heart failure. Full article

Real-time monitoring is essential for maintaining water quality and optimizing aquaculture productivity. Ion-selective electrodes (ISEs) are widely used to measure key parameters such as pH, nitrate, and dissolved oxygen in aquatic environments. However, these sensors are prone to fouling, the non-specific adsorption of organic, inorganic, and biological matter, which leads to potential drift (e.g., 1–10 mV/h), loss of sensitivity (e.g., ~40% in 20 days), and reduced lifespan (e.g., 3 months), depending on membrane formulation and environmental conditions. This review summarizes current research from mostly the last two decades with around 150 scientific studies on fouling phenomena affecting ISEs, as well as recent advances in fouling detection, cleaning, and antifouling strategies. Detection methods range from electrochemical approaches such as potentiometry and impedance spectroscopy to biochemical, chemical, and spectroscopic techniques. Regeneration and antifouling strategies combine mechanical, chemical, and material-based approaches to mitigate fouling and extend sensor longevity. Special emphasis is placed on environmentally safe antifouling coatings and material innovations applicable to long-term monitoring in aquaculture systems. The combination of complementary antifouling measures is key to achieving accurate, stable, and sustainable ISE performance in complex water matrices. Full article

Fractional-order models (FOMs) have been recognized as superior tools for capturing the complex electrochemical dynamics of lithium-ion batteries, outperforming integer-order models in accuracy, robustness, and adaptability. Parameter identification (PI) is essential for FOMs, as its accuracy directly affects the model’s ability to predict battery behavior and estimate critical states such as state of charge (SOC) and state of health (SOH). In this study, a hybrid deep learning approach has been introduced for FOM PI, representing the first application of deep learning in this domain. A simulation platform was developed to generate datasets using Sobol and Monte Carlo sampling methods. Five deep learning models were constructed: long short-term memory (LSTM), gated recurrent unit (GRU), one-dimensional convolutional neural network (1DCNN), and hybrid models combining 1DCNN with LSTM and GRU. Hyperparameters were optimized using Optuna, and enhancements such as Huber loss for robustness to outliers, stochastic weight averaging, and exponential moving average for training stability were incorporated. The primary contribution lies in the hybrid architectures, which integrate convolutional feature extraction with recurrent temporal modeling, outperforming standalone models. On a test set of 1000 samples, the improved 1DCNN + GRU model achieved an overall root mean square error (RMSE) of 0.2223 and a mean absolute percentage error (MAPE) of 0.27%, representing nearly a 50% reduction in RMSE compared to its baseline. This performance surpasses that of the improved LSTM model, which yielded a MAPE of 9.50%, as evidenced by tighter scatter plot alignments along the diagonal and reduced error dispersion in box plots. Terminal voltage prediction was validated with an average RMSE of 0.002059 and mean absolute error (MAE) of 0.001387, demonstrating high-fidelity dynamic reconstruction. By advancing data-driven PI, this framework is well-positioned to enable real-time integration into battery management systems. Full article

This scoping review evaluates the literature on options for planar solid oxide cell (SOC) performance optimization, with a focus on applied fabrication methods and design enhancements. Literature identification, selection, and charting followed PRISMA-ScR guidelines to ensure transparency, reproducibility, and comprehensive coverage, while also enabling the identification of research gaps beyond the scope of narrative reviews. We analyze the influence of fabrication methods on cell and component characteristics and evaluate optimization approaches identified in the literature. Subsequent discussion explores how design innovations intersect with fabrication choices. The surveyed literature reveals a broad spectrum of manufacturing methods, including conventional processes, thin-film deposition, infiltration, and additive manufacturing. Our critical assessment of scalability revealed that reduction in operating temperature, improving robustness, and electrochemical performance are the main optimization objectives for SOC designs. Regarding production cost, production scale-up, and process control, inkjet, electrophoretic deposition, and solution aerosol thermolysis appeared to be promising manufacturing methods for design enhancements. By combining the PRISMA-ScR evidence map with a synthesis focused on scalability and process control, this review provides practical insights and a strong foundation for future SOC research and scale-up, also for evolving the field of proton-conducting cells. Full article

This review presents a comprehensive overview of electrochemical-based technologies as emerging and sustainable methods for treating pesticide-contaminated wastewater. Core processes, including electro-Fenton, electrocoagulation, and electrochemical oxidation, as well as their hybrid combinations, have demonstrated high degradation efficiency, operational flexibility, and the ability to achieve complete mineralization of persistent pesticides. A bibliometric analysis covering 1997–2025 reveals growing global interest in these technologies, particularly in hybrid systems such as photoelectro-Fenton and solar-assisted electrochemical treatments, which offer improved degradation rates and reduced energy demand. Compared to conventional and biological approaches, electrochemical methods provide superior pollutant removal without generating excessive sludge or secondary contamination. Future advancements should focus not only on optimizing operational parameters but also on overcoming current methodological limitations through the development of durable and selective electrode materials and the integration of renewable energy sources, ultimately enhancing process efficiency and sustainability. Coupling electrochemical treatments with complementary physicochemical or biological methods may further improve mineralization and reduce costs. Overall, electrochemical technologies represent a promising pathway toward efficient, scalable, and environmentally friendly wastewater treatment systems capable of mitigating pesticide pollution and protecting aquatic ecosystems. Full article

Graphene nanoplatelets (GNPs) represent a promising class of carbon nanomaterials bridging the gap between graphite and monolayer graphene. Their unique combination of high electrical conductivity, large specific surface area, mechanical strength, and chemical stability makes them attractive for advanced energy storage applications. This review summarizes recent developments in the synthesis, functionalization, characterization, and application of GNPs in supercapacitors, batteries, and hybrid systems. The influence of key structural parameters—such as flake thickness, lateral size, surface chemistry, and defect density—on electrochemical performance is discussed, highlighting structure–property correlations. Particular emphasis is placed on scalable production methods, including mechanical, liquid-phase, and electrochemical exfoliation, as well as edge functionalization and heteroatom doping strategies. Comparative analyses show that GNP-based electrodes can significantly improve specific capacitance, conductivity, and cycling stability, especially when used in composites with polymers or metal oxides. The review also addresses current challenges related to aggregation, dispersion, standardization, and environmental impact. Finally, prospects for the development of sustainable, low-emission GNP production and its integration into next-generation energy storage systems are outlined. Full article

Lithium-ion batteries are widely used in electric vehicles (EVs) due to their high energy and power density. The accurate prediction of Remaining Useful Life (RUL) is critical for ensuring safety, reliability, and optimal battery utilization. However, RUL estimation remains challenging because battery degradation is influenced not only by electrochemical factors but also by real-world operating conditions, which often exhibit complex symmetric and asymmetric patterns. Existing RUL prediction models neglect the impact of micro-climatic conditions and road-induced vehicle vibrations, which leads to reduced prediction accuracy and limited application in practical driving environments. This paper proposes a Bayesian-optimized Gaussian process regression model (BO_GPR) for RUL prediction by integrating internal resistance data, battery degradation characteristics, micro-climatic parameters (temperature, humidity, wind speed), and vehicle vibration data under diverse driving scenarios. Vibration signals are preprocessed using the Discrete Wavelet Transform (DWT) and band-specific features are extracted using Tunable Q-factor Wavelet Transform (TQWT) to enhance feature sensitivity. The proposed BO-GPR model achieves an accuracy of 98.1%, outperforming conventional machine learning approaches. Experimental analysis shows that Z-axis vibrations, aggressive driving patterns, and urban terrain roads, in combination with micro-climatic variability, play a crucial role in accelerating RUL degradation. By explicitly modeling these factors, the proposed method provides a more realistic, data-driven framework for the health monitoring of electric vehicle batteries. These findings highlight the importance of incorporating environmental influences, vehicle dynamics, and degradation symmetry considerations in RUL prediction, supporting predictive maintenance, fleet management, and battery warranty optimization, improving the reliability and lifecycle cost-effectiveness of electric mobility systems. Full article

In recent years, porous carbon-based materials have demonstrated their potential as electrode materials, particularly as supercapacitors for energy storage. The specific capacitance of a carbon-based material is strongly influenced by its porosity. Herein, activated biochar (BCA) from millet was prepared using ZnCl₂ as an activator at temperatures of 400, 700, and 900 °C. Activation was achieved through wet and dry impregnation of millet bran powder particles. The porosity of BCAs was assessed by determining the iodine and methylene blue numbers (N_I and N_MB, respectively), which provide information on microporosity and mesoporosity, respectively. Characterization of the BCAs was carried out using Raman spectroscopy, X-ray diffraction, X-ray photoelectron spectroscopy, and cyclic voltammetry. The data show that the BCA prepared at 700 °C following dry impregnation, P700(p), has the highest N_I and the highest geometric mean value ($ñ=\sqrt{N_I\times N_{MB}}$), a descriptor we introduce to characterize the overall porosity of the biochars. P700(p) biochar exhibited remarkable electrochemical properties and a maximum specific capacitance of 440 F g⁻¹ at a current density of 0.5 A g⁻¹, in the three-electrode configuration. This value drops to 110 F g⁻¹, in the two-electrode configuration. The high specific capacitance is not due to ZnO, but essentially to the textural properties of the biochar (represented by ñ descriptor), and possibly but to a lesser extent to small amounts of Zn₂SiO₄ left over in the biochar. Moreover, the capacitance retention increases with cycling, up to 130%, thus suggesting electrochemical activation of the biochar during the galvanostatic charge-discharge process. To sum up, the combination of pyrolysis temperature and the method of impregnation permitted to obtaining of a porous biochar with excellent electrochemical properties, meeting the requirements of supercapacitors and batteries. Full article

In this study, a rough-surfaced LiFePO₄ (RS-LFP) cathode material with a well-defined porous architecture was successfully synthesized via a scalable, template-assisted spray drying method. The resulting RS-LFP exhibited a high specific surface area of 41.2 m² g⁻¹, significantly enhancing electrode–electrolyte contact. This tailored microstructure, combined with an in-situ-formed carbon network, reduced the charge-transfer resistance and facilitated efficient ion/electron transport. Consequently, the RS-LFP demonstrated outstanding electrochemical performance, including a high initial capacity of ~140 mAh g⁻¹ at 0.2 C, excellent cycling stability with over 95% capacity retention after 30 cycles, and superior rate capability. The RS-LFP also exhibited a remarkable capacity recovery of ~99% when the current returned to 0.2 C. These findings highlight that engineering porous architectures through template-assisted spray drying is a promising and scalable strategy for developing high-performance phosphate-based cathodes for advanced energy storage applications. Full article

This study aimed to develop and apply a novel zeolite-modified electrode (ZME), integrating Cu-exchanged zeolite Y (Cu-ZY) with a conductive carbon matrix composed of multi-walled carbon nanotubes (MWCNTs), for the sensitive and selective voltammetric determination of agomelatine (AGO), an important antidepressant, the accurate determination of which in pharmaceutical and biological samples is critical for therapeutic monitoring and quality control. Drop-casting the Cu-ZY/MWCNTs composite onto the surface of a glassy carbon electrode (GCE) resulted in the formation of a unique sensing platform, which exhibited a significantly improved electrochemical response for the oxidation of AGO. The enhanced activity of Cu-ZY/MWCNTs-GCE, attributed to the synergistic combination of Cu-ZY and MWCNTs, was confirmed by morphological, textural, and voltammetric analyses. Differential pulse voltammetry (DPV) was utilized for the quantitative determination of AGO, with optimization performed on instrumental parameters, supporting electrolyte pH, and preconcentration time (t_acc). Using the Britton–Robinson buffer (BRB) solution at pH 3.0, the Cu-ZY/MWCNTs-GCE exhibited a linear response to AGO concentrations ranging from 8.2 × 10⁻⁹–9.6 × 10⁻⁷ mol L⁻¹ (0.002–0.23 mg L⁻¹), achieving a detection limit (LOD) of 4.3 × 10⁻⁹ mol L⁻¹ (1.04 µg L⁻¹) with a preconcentration time of 60 s. The successful determination of AGO in pharmaceutical formulations, wastewater, and biological fluids, with recoveries ranging from 98.0 to 113.0%, demonstrates the effectiveness and practical applicability of the Cu-ZY/MWCNT-GCE-based voltammetric method for agomelatine analysis in complex matrices. Full article

Optimizing the MEA structure is crucial for enhancing the performance of open-cathode PEMFCs under water shortage conditions. By investigating the impact of gradient ambient temperature on performance, it is highlighted that cathode catalyst layer hydration deeply affects proton conduction in the membrane and three-phase boundary formation. These issues consequently increase ohmic resistance and cathode activation resistance as seen via polarization curve comparison and the electrochemical impedance spectroscopy analysis method, ultimately degrading overall stack voltage output under the same current density. Under indoor temperature and humidity conditions, an orthogonal experiment was designed to validate the sensitivity analysis on the cathode I/C ratio (0.74–0.9) and catalyst layer thickness (8, 12 μm) by controlling the catalyst-coated membrane manufacture process; GDL thickness (185–324 μm) and pore structure were also investigated, combining parameter characterization techniques like MIP and BET. It is shown that with an I/C ratio of 0.86, a medium GDL pore structure and a higher catalyst layer thickness of 12 μm bring better performance output, especially when the OC PEMFC is 700 mA/cm² @ 0.62 V. Full article

Background: Echinacea purpurea (L.) Moench (EP) and Onopordum acanthium (L.) (OA) are promising medicinal plants with diverse biological activities but there is no information on the effects of their combinations. To harness the therapeutic potential of both while minimizing the risk of adverse effects, we prepared two combinations (CE1 and CE2) of EP and OA in ratios 1:1 and 3:1, respectively. Methods: Oxygen radical absorbance capacity (ORAC), hydroxyl radical absorbance capacity (HORAC), and an electrochemical assay were used to determine the antioxidant activity of the extracts in vitro. The anxiolytic and immunomodulatory properties were studied in rats. Animals were subjected to acute cold stress and anxiety-like behavior was evaluated by the elevated plus maze (EPM) and social interaction test (SIT). Serum IFN-γ, TNF-α and IL-10 levels were measured by ELISA. Results: CE2 demonstrated the highest antioxidant activity (1841.7 μmolTE/g by ORAC, 277.2 GAE/g by HORAC, and 39.6 by electrochemical method). Moreover CE2 produced anxiolytic-like effects—significantly increasing the open arms entries ratio (OAER; p < 0.001), open arms time ratio (OATR; p < 0.01) in the EPM, and prolonging the social interaction time (p < 0.05) versus the stressed control. OA increased OAER (p < 0.01) and OATR (p < 0.001), while EP increased only OAER (p < 0.01). CE1 showed no significant behavioral consequences. CE2 significantly reduced IFN-γ (p < 0.05), and IL-10 levels were elevated in OA and CE2 groups (p < 0.01). No significant changes in TNF-α levels were observed across groups. Conclusions: These findings indicate that CE2 and OA attenuate anxiety-like behavior and modulate the immune response primarily by stimulating IL-10 production. Full article

Solid-state batteries (SSBs) are regarded as one of the most promising next-generation energy storage technologies due to their high energy density and improved safety. To achieve this goal, the development of solid-state electrolytes with high ionic conductivity and low interfacial resistance is essential. In recent years, composite polymer electrolytes (CPEs) have garnered extensive attention due to their ability to combine the intrinsic flexibility of polymers with the enhanced ionic conductivity and mechanical robustness provided by inorganic fillers. Metal–organic frameworks (MOFs), characterized by tunable pore structures, high surface areas, and excellent thermal and mechanical stability, are considered ideal fillers for constructing MOF–polymer composite electrolytes (MPCEs). This review summarizes the performance enhancement mechanisms of MPCEs and strategies for electrode–electrolyte interface stability. First, the primary preparation methods of MPCEs are introduced. Subsequently, the roles of MOFs in regulating ionic transport, suppressing dendrite growth, improving electrochemical stability, and optimizing the solid electrolyte interphase (SEI) layer are discussed. In addition, various interface engineering strategies are highlighted, including in situ polymerization of the polymer matrix, in situ growth of MOF fillers, integration of liquid plasticizers forming gel-like ionic conductor, and design of composite electrode to enhance interfacial compatibility and stability. Finally, the significant challenges and future research directions of MPCEs are outlined. This review provides valuable insights into the rational design of MPCEs and offers guidance for the development and practical application of high-performance SSBs. Full article