Ionics最新文献

This work focuses on the development of high-performance electrode materials for supercapacitor applications by combining nickel-doped α-bismuth oxide (Ni-α-Bi₂O₃) with activated carbon (AC) derived from biomass waste date seeds via thermal activation. Ni-α-Bi₂O₃ nanorods (NRs) were synthesized through a co-precipitation method, and the Ni-α-Bi₂O₃/AC composite was prepared by combining the two components via a sonication method. Structural characterization via X-ray diffraction (XRD) analysis confirmed the formation of a highly crystalline monoclinic phase of α-Bi₂O₃ with an average crystallite size ranging from 63.52 to 57.93 nm for the Ni-α-Bi₂O₃/AC composite. Raman analysis revealed peak shifts indicating successful doping and lattice distortion, whereas Fourier transform infrared (FTIR) analysis revealed metal‒oxygen and carbon‒hydrogen functional groups, indicating the successful integration of AC. UV‒Vis spectroscopy revealed a red shift and band gap reduction from 2.55 to 1.84 eV in the Ni-α-Bi₂O₃ composite, reflecting enhanced Light absorption and electrical conductivity. SEM analysis revealed a nanorod-like morphology with increased porosity, and EDX confirmed the presence of Bi, Ni, O, and C. The BET surface analysis confirmed the reduced mesoporous size of 2.4 nm and increased BET surface area 87.198 m²g⁻¹. Electrochemical analysis via cyclic voltammetry (CV) and galvanostatic charge‒discharge (GCD) demonstrated the superior performance of the Ni-α-Bi₂O₃ composite, with high specific capacitances of 174 Fg⁻¹ @ 5 mVs⁻¹ and 153 Fg⁻¹ @ 0.5 Ag⁻¹.The cyclic stability investigated over 2000 GCD cycles revealed stable capacitance retention. Notably, electrochemical impedance spectroscopy (EIS) and Bode plot revealed a lower charge transfer resistance and improved ion diffusion in the composite, confirming the enhanced conductivity and capacitive behavior. The synergistic effect between Ni-doped α-Bi₂O₃ and activated carbon resulted in improved energy storage performance, positioning the Ni-α-Bi₂O₃/AC composite as an efficient, low-cost, and eco-friendly electrode material for next-generation supercapacitors.

Graphical Abstract

In proton exchange membrane fuel cells (PEMFCs), coolant flow uniformity is a key element to ensure efficient and stable operation of stacks. As the source of the coolant inflow channel, the coolant manifold structure directly affects the coolant flow characteristics. In order to improve the coolant flow uniformity in the stack, this paper proposes a novel manifold design with intervals and systematically explores the influence mechanism of interval number and interval-rib ratio on the coolant flow uniformity in PEMFC stacks by using computational fluid dynamics (CFD) numerical simulation. The results show that there is a nonlinear relationship between interval number, interval-rib ratio, and flow uniformity. When interval number is 2, the coefficient of variation of mass flow rate is 1.29%, which indicates that the coolant flow uniformity in the stack is optimal. Too few or too many interval numbers and interval-rib ratios result in non-uniform flow distribution. In terms of pressure characteristics, stack pressure drop and channel pressure drop increase significantly with increasing interval number and interval-rib ratio. Additionally, the coolant flow distribution uniformity directly determines the channel temperature uniformity. Some channels have low cooling efficiency due to large flow fluctuations, and the average temperature and temperature uniformity index are significantly high.

The accurate estimation of temperature states in lithium-ion batteries is crucial for the performance and reliability of battery management systems. Reliable temperature estimation plays a vital role in ensuring safe operation, extending service life, and preventing thermal runaway in batteries. However, existing studies exhibit deficiencies in parameter sensitivity and noise adaptability, which limit the accuracy and reliability of temperature estimations. In this paper, we propose a novel method for battery temperature state estimation that combines a polynomial approximate thermal model with an adaptive unscented Kalman filter (AUKF). To achieve accurate and efficient parameter identification, we introduce an enhanced parrot optimization algorithm (EPO). Building upon this, the AUKF is employed to estimate both the surface and core temperatures of the battery, thereby improving the accuracy and robustness of the estimations. Experimental results demonstrate the effectiveness of the proposed method. Compared to other optimization algorithms, the EPO shows enhanced speed and accuracy in parameter recognition. At various test conditions, including the federal urban driving schedule (FUDS), dynamic stress test (DST), and hybrid electric vehicle (HEV) scenarios, the maximum root mean square error (RMSE) for the core temperature estimate using AUKF is 0.2705 °C, while the maximum RMSE for the surface temperature estimate is 0.0308 °C. These results indicate that the proposed method offers good accuracy and adaptability and is low-cost, simple to implement, and suitable for practical applications.

SnO₂-based materials are important for supercapacitors due to their high theoretical capacitance, good chemical stability, and excellent electrical conductivity. In this study, a nanocomposite (NC) material composed of tin oxide (SnO₂) and titanium dioxide (TiO₂) was successfully synthesized using the mechanical alloying technique, a solid-state process known for producing fine, homogeneously mixed nanostructures. The combination of SnO₂ and TiO₂ resulted in the formation of a well-defined heterojunction at their interface. This heterojunction plays a crucial role in enhancing the electronic interactions between the two semiconductor oxides, facilitating more efficient charge transfer and improving the material’s overall electrical conductivity. Comprehensive characterization techniques were employed to analyze the structural, morphological, and electrochemical properties of the synthesized SnO₂–TiO₂ NC. The electrochemical behavior was evaluated in a three-electrode configuration, where the nanocomposite demonstrated a significantly enhanced specific capacitance of 162 Fg⁻¹ at a current density of 1 Ag⁻¹. As-synthesized NC exhibited significant capacitance and coulombic retention percentage (~ 88%) over 5000 cycles. This performance was markedly superior to that of the individual SnO₂ and TiO₂ oxides, highlighting the advantage of the composite structure.

Graphical Abstract

Biomass-derived activated carbon (AC) from Mahogany seed shells (MSS) was successfully synthesized and modified with carbon nanotubes (CNTs) through chemical and physical activation processes that are reproducible to apply as high-performance supercapacitor electrodes. Various additions of CNT (2%, 4%, 8%, and 10% of the mass of 30 g of activated carbon) were made during the chemical activation stage to evaluate their effects on the structural and electrochemical properties of the material, which were then coded as MSS-02, MSS-04, MSS-08, and MSS-10, respectively. The results showed that increasing the percentage of CNTs increased the crystallinity and promoted the formation of conductive nanotube networks on the porous carbon surface. The specific surface areas ranged from 422 to 594 m²/g, with 2.3–3.9 nm pore diameters, indicating a well-developed mesoporous structure. Electrochemical tests in 1 M H₂SO₄ electrolyte showed that the MSS-08 provided the highest specific capacitance of 366 F/g, and energy and power density of 50 Wh/kg and 183 W/kg, respectively. The improved electrochemical performance was due to the synergistic effect of CNTs, which could increase electrical conductivity, accelerate electron and ion transport, and maintain structural stability during charge and discharge cycles. In addition, the improved wettability and connectivity of the CNT network allowed more active sites to be accessible to ions, thereby enhancing ion diffusion and charge storage capacity. Based on these results, AC-MSS modified CNTs are a promising and sustainable electrode material candidate for high-performance supercapacitor applications.

State-of-health (SOH) estimation and remaining useful life (RUL) prediction of lithium-ion batteries are of great importance in ensuring safe and reliable management of electric vehicles. However, due to the phenomena of capacity regeneration and nonlinear degradation, SOH estimation faces challenges in achieving high precision while maintaining a low model parameter count. Additionally, accurate prediction of RUL throughout the battery’s entire lifecycle is a challenge. To solve the problems, FISNet is proposed to predict SOH and the Phased-RUL Approach is proposed to estimate RUL. FISNet employs a complex-valued linear layer to learn the periodic patterns of the SOH curve and perform reasonable interpolation, specifically capturing degradation trends at low frequencies and regeneration phenomena at high frequencies. The Phased-RUL Approach employs different techniques in two phases of the battery to achieve high precision. In the first phase, it employs a data-driven approach to directly predict RUL through a hybrid model integrating convolutional neural networks, Box-Cox transformation, and multi-layer perceptron block. In the second phase, it employs FISNet to predict SOH and calculate RUL. The experimental results demonstrate that FISNet significantly reduces the model parameter count to 1/250 of the average of four current models and ensures high accuracy with a root mean square error of 0.39%. Furthermore, the Phased-RUL Approach attains high precision across the battery’s full lifecycle with the minimum mean absolute error of 3.7 cycles (1.38% of the full lifecycle). It shows superior accuracy in the second phase with an error below 2 cycles and achieves particularly reliable EOL prediction with a maximum error of one cycle.

The influence of different electrolytes, such as 1 M NaOH, KOH and Na₂SO₄, was investigated for the large-scale production of graphene nanosheets (GNs) from graphite sheets via electrochemical exfoliation at room temperature. The main advantage of this method lies in its ability to produce defect-free graphene nanosheets compared to conventional chemical and physical approaches. The synthesized GN was characterized using X-ray diffraction (XRD), Raman spectroscopy and field-emission scanning electron microscopy (FE-SEM). The results revealed that 1 M KOH serves as the most effective alkaline medium for the electrochemical exfoliation of graphite, yielding high-quality graphene nanosheets. The resulting GN shows great potential as an electrode material for electrochemical energy conversion and storage devices. The electrical double-layer capacitor (EDLC) performance of the GN electrode was evaluated in a Li₂SO₄ electrolyte. The GN synthesized using 1 M KOH exhibited a high specific capacitance of 170 F g⁻¹ and superior electrochemical reversibility compared to those obtained using 1 M NaOH and 1 M Na₂SO₄. Finally, a symmetric supercapacitor device (GN-KOH||GN-KOH) was fabricated using Li₂SO₄ as the electrolyte, which delivered a high specific energy of 15.6 Wh kg⁻¹ at a working potential of 1.6 V.

This report demonstrates the synergistic enhancement in intrinsic electrochemical performance of a novel nanocomposite, copper oxide/barium oxide (CuO/BaO), for supercapacitor applications. The CuO/BaO nanocomposite was synthesized via a simple one-step wet chemical route. Its crystalline structure, surface morphological features, compositional confirmation, and particle size distribution were examined using powder XRD, SEM, EDAX, elemental mapping, TEM, and SAED pattern analyses. Electrochemical measurements were performed in a three-electrode system using 3 M KOH electrolyte, with the CuO/BaO nanocomposite coated on Ni foam as the working electrode. Cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) studies evidenced an enhanced electrochemical performance of the synthesized nanocomposite over its counterparts. Electrochemical impedance spectroscopy (EIS) confirmed reduced internal and charge transfer resistances, indicating enhanced conductivity. GCD-derived specific capacitance of the CuO/BaO nanocomposite was found to be 1392.2 F/g at a current density of 0.6 A/g. Owing to its high-specific capacitance, simple synthesis procedure, and cost-effectiveness, the CuO/BaO nanocomposite is proposed as a promising electrode material for supercapacitor applications.

We have strategically converted α-Fe₂O₃ into an amorphous iron oxide/iron/boron composite (Fe-O/B) amicable for use as a supercapacitor electrode material. The conversion of α-Fe₂O₃ involves two combustion processes: (i) foamy combustion resulting in a reduction of α-Fe₂O₃ to nano zero-valent iron (nZVI) and (ii) smoldering combustion from the oxidation of nZVI to Fe-O/B composite. The obtained composite was characterized by powder XRD, FT-IR, SEM, HRTEM, BET, and XPS, confirming the amorphous nature and presence of boron in the composite. Vibrating sample magnetometry studies showed M_s and M_r were 38.59 emu/g and 15.75 emu/g, respectively. Electrochemical studies of α-Fe₂O₃, nZVI, and Fe-O/B composite in three-electrode configurations in 1 M KOH electrolyte solution were performed wherein Fe-O/B exhibited a high specific capacitance of 1900 F/g at 1 A/g, with a capacitance retention of 74.2% over 4000 cycles between −0.45 and 0.2 V. The high electrochemical performance can be attributed to the amorphous nature and the role of iron and boron in redox reactions. Hence, Fe-O/B composite can be a promising electrode material for various electrochemical applications.

As an anode in Li-ion batteries, cubic or cage forms derived from Prussian blue (PB) analogues have been so attractive although studies are limited for the PB nanoparticle form. In addition, the nanoparticle size affects the electrode performance while such influence on the sono-chemical route mechanism remains largely unexplored in Li-ion batteries. Here, we report a facile co-precipitation method to produce PB nanoparticles, which compare with the addition of sono-chemical route by metal (Cu- and Ti-) doping. The average grain size and fractal dimension of the synthesized PB particles were measured in the range of 18–23 nm and 1.879 ± 0.009–1.812 ± 0.016, respectively. By using sono-chemical route assisted co-precipitation, pure and metal-doped PB electrodes reach more than the specific capacity of traditional graphite anodes for 100 cycles. The preferential orientation shifts from (200) to (400) with Ti-doping and improved electrochemical stability with increasing coating ratio. With the decreasing average crystallite size of Cu-doping (18 nm for Debye–Scherrer method), cycle stability also improves. This study presents a new approach by presenting reduced cluster size as well as average particle size of nanoparticles that contribute to the anode performance.