Journal of Power Sources Advances最新文献

We demonstrate, as proof of concept, a materials design path that allows us to exploit thermal deposition technique to fabricate sodium (Na) metal anodes at the microscale. Our study reveals that Na thin anodes <10 μm, directly coated on a stainless-steel current collector, reduces the energy barrier of Na nucleation during plating process. Likewise, evaporated thin-film sodium anodes enable achieving a cycling in a full battery configuration as stable as with bulk Na anode, and considerably more stable than the here presented anode-less case. These insights may lead to practical design changes toward the efficient use of metallic Na, alleviating weight and costs. In addition, they provide a solid starting point for future developments that focus on improving the stability and extending the life of Na-metal batteries. All this paves the way for the next-generation of sodium-based energy storage technologies, where energy density and cost are key factors.

In this study, we propose an effective strategy to improve the electrochemical performance of a P2-Na_0.67Mn_0.75Ni_0.25O₂ (P2-MNO) cathode material for Na-ion batteries based on MgO surface coating. The MgO coating, with a thickness of ∼20–50 nm, is obtained by means of a facile wet-chemistry approach followed by heat treatment carried out at comparatively low temperatures (400–500 °C) in order to avoid possible Mg doping in the bulk of the P2-MNO. Detailed electrochemical investigations demonstrate improved electrochemical performance of the MgO-coated material (M-P2-MNO) in comparison to pristine bare one at both room and elevated (40 °C) temperatures. Operando differential electrochemical mass spectroscopy (DEMS) demonstrate that the MgO coating is effective in suppressing unwanted gas evolution due to side reactions thus stabilizing the cathode/electrolyte interface.

This study investigates the impact of water ratio on the direct aqueous recycling of NMC811. Three different ratios of NMC811 to water were examined. The results demonstrate that the water ratio significantly affects the electrochemical performance of NMC811. Capacity fading is observed in all water-exposed samples, with the sample having the lowest water ratio showing less fading compared to the samples processed with higher water ratios. Both samples with higher water ratios exhibit similar performance, suggesting an equilibrium at the NMC811-water interface is established. Characterization of the cathode materials reveals variations in the amount and type of surface species. The pristine sample, not exposed to water, only shows Li₂CO₃ and NiO as surface species, while the water-exposed NMC811 samples exhibit nickel carbonates and hydroxides along with associated water. The poorer performance of samples exposed to higher water ratios is likely due to higher amounts of these species forming on the particle surface. Additionally, lithium, cobalt, and manganese carbonates, as well as lithium hydroxide with associated water, are detected and could further contribute to the poorer performance.

A novel approach to develop a low-temperature lithium-ion battery (LIB) based on tin selenide (SnSe) and carbon (C) nanofibers as the active electrode material has been successfully achieved. The SnSe@C nanofiber anode exhibited excellent electrochemical properties, such as high capacity and good rate capability. The anode maintained a consistent charge capacity of ∼923 mAh g⁻¹ at a current rate of 0.1 A g⁻¹ over 100 cycles at room temperature. Furthermore, investigated for the first time at low temperatures, the SnSe@C nanofiber anode exhibited superior capacity (∼430 mAh g⁻¹ at −20 °C) compared to conventional graphite electrode (∼25 mAh g⁻¹ at −20 °C). The proposed SnSe@C nanofiber anode demonstrated a great potential to be applied for developing next-generation LIBs with improved low-temperature performance.

Li-ion capacitors (LICs) have emerged as promising energy storage devices within the electronic industry. The performance of LICs is predominantly influenced by the electrode material utilized, making the proper selection and development of said material of utmost importance. This study focuses on fabricating a composite electrode material using a simple, cost-effective, and environmentally friendly technique, combining Manganese dioxide (MnO₂) nanotube and graphene oxide (GO). The low cost, high natural abundance, and high theoretical specific capacity (1230 mAh/g) of MnO2 enables it to be effectively used in energy storage systems. The resulting material showcases a distinctive architecture where MnO₂ nanotube nanorods are enveloped by GO nanosheets. By employing a binder-free buckypaper approach, the MnO₂ nanotube/GO composite anode exhibits exceptional electrochemical performance, including high energy (213.29 Wh/kg) and power density (28.5 kW/kg), improved rate capability, and excellent cyclic stability. These findings undoubtedly indicate a promising future for the MnO₂ nanotube/GO composite anode in lithium-ion-based energy storage systems.

The Proton Exchange Membrane Fuel Cell (PEMFC), known for its efficient energy conversion, minimal electrolyte leakage, and low operating temperature, shows great potential as a clean energy source. However, its lifespan is limited due to degradation during normal operation, which, if uncontrolled, can result in dangerous failures such as explosions. Hence, accurately estimating the remaining useful life (RUL) is vital. In this research, a combined prediction method using genetic algorithms (GA) and nonlinear autoregressive neural networks (NARX) with external inputs is proposed. The method's performance was trained and validated using the 2014 IEEE PHM Data Challenge dataset, and it was compared to two commonly used artificial neural network algorithms: GA-based backpropagation neural network (GA-BPNN) and GA-based time delay neural network (GA-TDNN). The findings demonstrate that the proposed approach surpasses the other two artificial neural network algorithms in terms of prediction accuracy. Although GA is known for its computational requirement, optimization is performed offline. Once optimal neural network (NN) hyper-parameters are determined, the optimized NN is used online for RUL prediction.

Non-aqueous Li–O₂ batteries offer an extremely high energy density, but suffer from high overvoltage on charge and poor cycle characteristics. In the past decade, soluble redox mediators (RMs) have been utilized to reduce the charge overvoltage. However, the use of RMs inhibits the effective decomposition of Li₂O₂ due to the shuttling of RMs between the cathode and anode. In this study, 2,2,6,6-tetramethylpiperidinyloxyl (TEMPO), which was previously proposed as an RM, was immobilized on the electrode surface by immersing carbon paper in a solution of the synthesized 4-(N-(3-triethoxysilyl-propyl) carbamoyloxy)-2,2,6,6-tetramethyl-1-piperidinoxyl (TESPCP), followed by a heat treatment. Charge–discharge testing of Li–O₂ batteries using the TEMPO-immobilized cathode with a Li anode exhibited a charge plateau of about 3.7 V, indicating that the immobilized TEMPO could react electrochemically as a redox mediator. No overcharge behavior was observed in the cell, suggesting the RM shuttling effect was suppressed. Furthermore, SEM and XPS analyses of the cathode surface confirmed that no Li₂O₂ residues remained on the cathode after charging, unlike the control sample that utilized soluble RMs. These results indicate that a TEMPO-immobilized cathode can successfully mitigate RM shuttling while maintaining the benefits of RMs, allowing effective decomposition of Li₂O₂, during charging without leading to overcharging.

Numerical modeling of thermal runaway in Lithium-ion batteries has become a critical tool for designing safer battery systems. Significant progress has been made in developing kinetic mechanisms for decomposition reactions and including additional physics such as venting and combustion. However, the governing heat conduction equation and decomposition reaction equations become numerically stiff during thermal runaway, which limits the utility of thermal abuse models to low-dimensional formulations. The present work introduces a new solution strategy, which switches from the full, 3D transient heat conduction formulation to an adiabatic, 0D lumped body formulation only during the stiff portion of the simulation, i.e., only during thermal runaway. To test the new solver, a 3D thermal abuse model was configured to simulate an oven test of an 18650-format cell. The new solver was exercised for scenarios of varying degrees of stiffness, and the results were compared with a baseline solver using typical integration methods. For an extremely stiff scenario, computation speed was increased by a factor of 183x relative to the baseline solver, with little impact on solution accuracy, thus effectively alleviating the numerical stiffness issue. The new solution strategy addresses the poor scalability of high-dimensional models, such as 3D-CFD-based thermal abuse models, and improves their practicality for industrial use.

Baffles in flow field channels for air in a polymer electrolyte fuel cell are known to enhance the performance by inducing convective flow through the gas diffusion layer (GDL) with smaller pressure loss than interdigitated flow fields. This work experimentally correlates performance enhancement with the amount of liquid water in a GDL. A parallel flow field (PFF) that has different inlet and outlet opening sizes is applied to induce cross-flow in the GDL under the rib between adjacent air channels. Operando synchrotron X-ray radiography experiments are conducted to compare the amount of water in the GDL with that for a PFF having the same inlet and outlet sizes. The performance enhancement by application of different opening sizes increases with decreasing relative humidity and increasing air flow rate. A significant performance enhancement is observed when the amount of water in the GDL substrate under the rib becomes almost zero. No performance enhancement is observed under over-humidified conditions, although a decrease in the amount of water in the GDL is still observed, which suggests that the performance becomes insensitive to the difference in the liquid water saturation as the saturation increases.

At present, it would be desirable to improve the C-rate values of bulk-type all-solid-state lithium-ion batteries by optimizing the electrode structures. Although simulations are an effective means of determining optimal structures, a high degree of accuracy is required. The present study demonstrates a pseudo-two-dimensional (P2D) method of simulating cathodes providing improved accuracy along with low computational cost and based on actual three-dimensional electrode structures. This method incorporates the volume fraction and tortuosity of the solid electrolyte (SE) and active material (AM), both of which are widely used in conventional simulations, and takes into account the specific contact area diameter (D_SCA) of the AM. The latter parameter reflects the extent of AM particle aggregation and is obtained from the analysis of three-dimensional X-ray computed tomography images. The validity of these P2D simulations is confirmed by comparison with experimental results for three electrodes having different SE particle sizes. The experimental result shows that battery capacity is increased with decreases in the SE particle sizes. This effect is not predicted using conventional P2D simulations employing only volume fraction and tortuosity but is reproduced by P2D simulations in which D_SCA values are used to model AM particle aggregation and Li diffusion within AM particles.