Ionics最新文献

Proton exchange membrane fuel cells (PEMFCs) are electrochemical devices that directly convert the chemical energy of hydrogen into electricity, with water as the only by-product. The bipolar plate is one of the important parts of the fuel cell, which plays roles such as connecting single cells in series, guiding gases, and providing support. The flow-field structure on the bipolar plate directly affects the distribution of reactant gases, water management, and the overall efficiency of the cell. Therefore, the design and optimization of the flow-field of the bipolar plate are one of the important methods to improve the performance of PEMFCs. This paper focuses on the optimization and improvement of a rhombic flow field with an intersecting structure. The straight edges of the diamond are changed into three different curved-edge structures that curve inward. Through simulation calculations, the oxygen distribution, water distribution, and polarization curves inside the cell after modification are analyzed. The results show that the curved flow field with a circumscribed circle structure is superior to the rhombic flow field in terms of oxygen content, uniformity, water discharge, and output power, but it also has a higher pressure drop. The elliptical flow field is superior to the rhombic flow field in terms of the uniformity of oxygen output and output power, but it also has a higher pressure drop and water accumulation. The parabolic flow field is superior to the rhombic flow field in terms of oxygen uniformity and output power, is similar to the rhombic flow field in terms of water discharge, and has a higher pressure drop than the rhombic flow field.

In the current work, Graphene Oxide (GO) nanoparticles were used to create plasticized magnesium-ion conducting polymer electrolytes. This was accomplished by integrating Cellulose Acetate (CA) doped with Magnesium trifluoromethanesulfonate (Mg(CF₃SO₃)₂) salt and Poly(ethylene glycol) (PEG) as the plasticizer using a simple solution casting technique. The impact of introducing GO particles into the polymer matrix was examined by evaluating the improvements in electrical and electrochemical properties. The interactions of the GO fillers with the polymer were examined using FTIR and XRD techniques, whereas TGA and DSC studies reveal the thermal performance of GO fillers within the polymer matrix. The inclusion of 2 wt% GO leads to a maximum ionic conductivity of 3.60 × 10^–3 S/cm, an order of magnitude greater than the membrane without the filler. The transference number investigation showed an ionic transference number of 0.98. By using LSV analysis, the membrane had an electrochemical stability of 3.6 V. CV and GCD measurements show that the prepared Electric Double-Layer Capacitor (EDLC) using the ideal membrane possesses the highest specific capacitance, measuring 65.5 F/g at 5 mV/s and 64.2 F/g at 0.5 A/g respectively.

Graphical Abstract

Flexible counter electrodes (FCEs) emerge as a promising alternative to the conventional, rigid, and expensive platinized FTO-based CEs in wearable electronics. In flexible dye-sensitized solar cells (DSSCs), the CE must have a large surface area with high conductivity for efficient electron transfer, strong catalytic activity for redox reactions, and stability in the electrolyte. Platinum (Pt) is still the standard CE material based on its excellent catalysis and conductivity. However, its rarity, high cost, and low mechanical flexibility prevent large-scale commercialization, especially in flexible DSSCs. This study critically reviews the recent developments in carbon-based materials, including carbon nanotubes (CNTs), graphene, and mesoporous carbon (MC), as well as conducting polymers, such as polyaniline (PANI), polypyrrole (PPy), and poly (3,4-ethylene dioxythiophene) (PEDOT), and transition metals. This review also examines composite FCE materials and their structural modification. Comparative understanding underlines how nanostructured carbons, polymer composites, and transition-metal-based hybrids are coming forward as sustainable alternatives that offer efficiency reaching or exceeding Pt benchmarks without losing flexibility. Lastly, this review presents existing challenges, such as interfacial stability, mass production, and long-term operating reliability, and offers future directions for the design of next-generation FCE materials to facilitate low-cost, high-efficiency DSSCs in wearable and portable energy devices.

This study proposed a novel transformer-based regression model for predicting the lifetime coefficient, using specific energy, specific power, and the remaining capacity of three cylindrical graphite/LFP batteries. Its predictive capabilities were methodically evaluated against six widely used machine learning approaches—M5, random forest, gradient boosting, stacked regressor, XGBoost, and CatBoost to benchmark in the small-data regime. A comprehensive dataset was used with 239 different cyclic conditions for 18,650 and 26,650 form factors, with form factor, capacity, cycling temperature, cycling depth, test duration, and full cycles as the input features. The seven models were pre-processed, hyperparameter-tuned, trained, and optimized to predict the target variables accurately. The study revealed vital insights into the correlation among the input features and the key trends among the target variables via violin plots, Pearson’s correlation heatmap, SHAP analysis, and feature importance analysis. The effectiveness of the proposed transformer-based regression over the commonly employed decision tree- and ensemble-based approaches was measured in terms of R², RMSE, SMAPE, MASE, and MAE. The proposed model exhibited superior performance with an R² of 0.8653, 0.8657, 0.4516, and 0.3285 for lifetime coefficient, used specific energy, used specific power, and remaining capacity, respectively. The results from the study can pave the way for extending the robustness of the proposed model by integrating time-series cycling behavior, impedance spectra, feature engineering, or aging profiles to complement and advance the existing experimental findings in the energy storage landscape.

In the present study, α-Bi₂O₃ was doped with a series of nickel concentrations (0.05 M, 0.10 M, 0.15 M, 0.20 M, and 0.25 M) manufactured by a simple co-precipitation method. The XRD analysis was confirmed by JCPDS card no. 00–041-1449, and the crystallite size was found to be 64.02 nm, 54.45 nm, 48.64 nm, 42.94 nm, 46.54 nm, and 53.48 nm. FT-IR analysis confirmed the presence of functional groups. The addition of Ni dopant showed the effective incorporation of Ni into the framework of α-Bi₂O₃, which decreases the crystallite size. Morphological evaluation by FE-SEM reveals a flake-like structure for pure α-Bi₂O₃ and an agglomerated flake-like shape for Ni-doped α-Bi₂O₃. EDX analysis confirmed the presence of pure and Ni-doping α-Bi₂O₃ without any additional impurities. The HR-TEM images showed the existence of smaller nanoparticles of 10–20 nm. The optical properties and photocatalytic degradation performance were analyzed by UV–Visible and PL studies. The UV analysis showed the red shift in the absorbance wavelength for Ni doping α-Bi₂O₃ which designates a decrease in band gap energy. PL studies showed that a bluish-green emission band is noticed at 466 nm in the visible region, and the intensities of the PL emission peak gradually decrease with the addition of Ni concentration. Finally, the superior photocatalytic degradation efficiency of methylene blue has reached 0.15 M concentration after 135 min under UV–Visible light irradiation with 91%. The charge separation of photogenerated electron–hole pairs, which is induced by nickel-doping α-Bi₂O₃, is presented in this report.

α-NaVOPO₄ has emerged as a highly promising cathode material for sodium-ion batteries, thanks to its impressive theoretical capacity (144.9 mAh g⁻¹) and elevated operating voltage. However, its practical application is hindered by poor electronic conductivity. In this study, small particle size and exceptional uniformity of α-NaVOPO₄ were successfully synthesized using a two-step hydrothermal method. This approach preserves the intrinsic advantages of α-NaVOPO₄ while improving particle microstructure, effectively boosting the electrochemical performance of the cathode. The successful synthesis of pure-phase α-NaVOPO₄, along with its desired structural and morphological properties, was rigorously confirmed through X-ray diffraction and scanning electron microscopy. To assess the material’s sodium storage performance, its electrochemical behavior was evaluated in a Na||NaVOPO₄ half-cell, employing both galvanostatic charge/discharge cycling and cyclic voltammetry for comprehensive analysis.

Oilfield brine represents a growing environmental concern, yet its high lithium content offers a cost-effective and potential recovery resource. This study focuses on lithium extraction from oilfield brines, a resource characterized by high calcium concentration, high salinity, acidic pH, and lack of sulfate ions. Since the evaporation process resulted solely in NaCl deposition, an alternative method was required. A redox-based approach, selected for its eco-friendly properties, was implemented by using anhydrous FePO₄ (sorbent) and Na₂S₂O₃ (reducing agent) to lithium sequestration. XRD and XRF results revealed that FePO₄ exhibits a trigonal crystalline structure consisting of 51 wt% Fe₂O₃ and 48 wt% P₂O₅. To enhance the trapping, a response surface methodology (RSM) is conducted in order to model and optimize the lithium and sodium retention rates by varying five independent factors. The outcomes of this approach yielded to a validate and predictive model with the optimal conditions (FePO₄, 1.0 g/L; Li⁺/S₂O₃²⁻ ratio, 0.4; temperature, 25 °C; pH, 7.5; time, 18 h) achieved at lithium and sodium retention rates of 35 and 5 mg/g FePO₄, respectively. Post-reaction analyses (XRD, FTIR, and SEM/EDX) of the optimal Li_xFePO₄ product confirmed high lithium selectivity and structural similarity to both FePO₄ and LiFePO₄, demonstrating a sustainable strategy for oilfield brine valorization which involves converting waste into valuable resources through a circular economy. This approach effectively reclaims water, extracts critical minerals, and significantly reduces environmental impact. It successfully balances economic benefits with ecological responsibility.

Accurate estimation of lithium-ion battery (LIB) remaining useful life (RUL) based on degradation data is critical for advancing battery performance optimization, yet it remains challenging due to inherent nonlinear degradation trends and prominent capacity regeneration phenomena. To address this, this study proposes a novel hybrid framework integrating complementary ensemble empirical mode decomposition (CEEMD), adaptive unscented Kalman filter (AUKF), and sparrow search algorithm-optimized gated recurrent unit (SSA-GRU) for RUL estimation. The framework features three synergistic innovations: (1) CEEMD is employed to effectively mitigate capacity regeneration and noise interference, outperforming conventional decomposition methods in preserving degradation signal integrity; (2) a double exponential state space model is constructed to characterize LIB degradation dynamics, with AUKF enabling robust prediction of global degradation trends; (3) SSA-GRU is introduced to specifically correct AUKF prediction errors and capacity regeneration, realizing high-precision multi-stage capacity prediction. Validated on NASA and CALCE Public datasets, the framework exhibits superior performance across 30% and 50% training data scenarios compared to existing single/multi-step prediction algorithms. Experimental results demonstrate its capability to capture both global trends and local characteristics of capacity degradation, with mean absolute error and root mean square error both below 1.62%, relative accuracy exceeding 96.5%, and 99.5% of capacity errors confined within 0.02 Ah.

Microbial fuel cells (MFCs) represent an emerging energy technology that generates electricity through microbial-organic interactions, with the anode serving as a critical component for wastewater-to-electron conversion. This study focuses on developing porous iron-nickel (Fe–Ni) alloys as potential anodes for MFCs, employing electrodeposition to fabricate these anodes with systematically varied Fe/Ni ratios. Through intrinsic electrochemical performance screening, the work aims to achieve composition optimization for high-performance microbial fuel cell anodes. Multi-dimensional analysis integrating linear sweep voltammetry (LSV), cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and Tafel polarization was conducted to establish structure–activity relationships and synergistic catalytic mechanisms of the alloys. Key findings reveal that compositional optimization profoundly impacts the performance of these potential anodes: the Fe₇Ni₃ alloy exhibited significantly superior electrochemical activity compared to pure Ni, characterized by dramatically enhanced peak current density, and improved charge storage capacity. Furthermore, Fe₇Ni₃ demonstrated minimal charge transfer resistance and excellent reaction kinetics. These results validate that bulk composition engineering of porous Fe₇Ni₃ offers a highly promising strategy for developing potential anode materials for high-performance MFCs, effectively addressing the stability-activity trade-off inherent in conventional surface-modified anodes. This work provides a composition-driven design paradigm for bioelectrochemical systems, paving the way for future scale-up studies focusing on long-term stability and integration into wastewater treatment modules.

Graphical abstract

The iron-based mixed polyanionic phosphate cathode material Na₃Fe₂PO₄P₂O₇ offers advantages such as high theoretical specific capacity, appropriate operating voltage, and minimal volume change during cycling. However, its synthesis conditions are demanding, being highly sensitive to raw material selection and calcination temperature control, making it difficult to obtain a pure-phase structure. Additionally, the material’s inherently low electronic conductivity adversely affects its electrochemical sodium storage performance. In this study, the composite of Na₃Fe₂(PO₄)(P₂O₇) and a small amount of carbon nanotubes was prepared via a spray drying method. The product is spherical in shape, with most particles measuring 8–12 μm in size, which is the range with good flowability. The prepared sample exhibited good electrochemical performance, delivering an initial discharge specific capacity of 90.4 mAh·g⁻¹ at 0.2 C and maintaining a reversible specific capacity of 61.4 mAh·g⁻¹ even at a high rate of 20 C. Its air sensitivity was also investigated and it displayed good air resistance performance. After being exposed to air for one month, it retained 91% of its capacity after 200 cycles at 1 C.