Energy Storage最新文献

The development of an efficient and eco-friendly spent lithium-ion batteries (LIBs) recycling strategy is vital for economic and environmental sustainability. This study reports a green, efficient and economic method to convert the cathode portion of spent LIB (LiCoO₂) into a high-performance nonprecious Co-oxalate (CoC₂O₄·2H₂O) electrocatalyst for the oxygen evolution reaction (OER). Here, LiCoO₂ collected from the spent LIB cathode was leached in oxalic acid and gallic acid (200:20 mM) mixture at 80°C using a solid-to-liquid ratio of 2 g/L for 1 h. Soon after the dissolution of Co and Li, in situ precipitation of CoC₂O₄ 2H₂O was observed in the reaction mixture and soluble Li was precipitated as Li₂CO₃ and LiHC₂O₄ H₂O when stoichiometric excess of Na₂CO₃ and oxalic acid were added, respectively. The recovered CoC₂O₄·2H₂O deposited on stainless steel plate was utilized as an anode for electrochemical OER. It showed an overpotential of 320 mV at 10 mA cm⁻², a low Tafel slope (49 mV dec⁻¹) and stable performance over 12 h. Furthermore, the battery grade LiCoO₂ was re-synthesized using the stoichiometric amounts of LiHC₂O₄ H₂O and CoC₂O₄ 2H₂O. The re-synthesized LiCoO₂ showed almost 100% coulombic efficiency with a minimal capacity loss. Thus, we have demonstrated an effective recovery and reuse of cathode material for energy devices.

Photo-assisted supercapacitors represent a promising strategy for efficient solar energy utilization by enabling simultaneous energy harvesting and storage. In this study, LaNiO₃ and NdNiO₃ perovskite materials were investigated as photoactive electrode candidates due to their favorable photoelectronic properties and the unique role of rare earth elements. Comprehensive material characterizations were performed using FESEM, STEM, EDX, XRD, FT-IR, Raman, BET, and UV–Vis analyses. Electrochemical performance was evaluated under UV illumination (20 W, 365 nm) and dark conditions. Cyclic voltammetry (CV) measurements at 100 mV/s revealed a 9% increase in areal capacitance for LaNiO₃ and a more substantial 14% enhancement for NdNiO₃ under UV light. This performance improvement is attributed to enhanced electron–hole pair generation, particularly in NdNiO₃, whose band gap lies closer to the UV region. These results underscore the potential of rare earth-based perovskites in advancing photo-assisted supercapacitor technology. The findings contribute to the development of next-generation energy storage systems capable of directly integrating solar energy.

This research focuses on enhancing chitosan's role as a binder in lithium-sulfur (Li-S) batteries through its modification with carboxylic acids. The structural analyses using FTIR and XRD reveal that incorporating specific poly-substituted acids alters chitosan's molecular alignment and polymorph formation, inducing a mixture of Type I and Type II polymorphs. Mechanical testing shows that the Ch + Lactic binder provides improved toughness and ductility, properties essential for accommodating volume changes during Li-S battery cycling. The electrochemical characterization demonstrates that chitosan-aliphatic binders, particularly the Ch + Lactic binder, lead to higher specific capacities (e.g., 930 mAh·g⁻¹ at C/10), improved rate capability, and notable long-term cycling stability (0.057% capacity fade per cycle) compared to pristine chitosan. This enhanced performance is linked to more effective polysulfide management and structural integrity. Post-mortem SEM analysis confirms the mechanical stability of the optimized cathodes, which remain crack-free even after extensive cycling. This work illustrates that careful selection of carboxylic acids can effectively tailor chitosan's properties, contributing to the development of better performance of Li-S battery technologies.

We employed machine learning classification algorithms to predict the crystal systems, specifically triclinic, monoclinic, and orthorhombic, associated with Li–P–TM–O; (TM = Mn, Fe Co, Ni, V) based-phosphate cathodes. Feature evaluation revealed that cathode properties depend on the crystal structure, and optimized classification strategies yield better predictability. Gradient Boosting Machines, Extremely Randomized Trees, and Random Forest-based ensemble machine learning algorithms have demonstrated the best predictive capabilities for crystal systems in the Monte Carlo cross-validation test. Additionally, sequential forward selection (SFS) is performed to find the utmost critical features influencing the accuracy of prediction for different machine learning models, with Volume, Band gap, and Sites as input features. The ensemble machine learning algorithms with 80.69% for Random Forest, 78.96% for Extremely Randomized Tree, and 80.40% for Gradient Boosting Machine approaches lead to the maximum accuracy toward crystallographic classification with stability, and the predicted materials can be the possible cathodes for lithium ion batteries. More importantly, the present approach can be extended to other groups of materials.

Advancements in electrode materials with a high potential window and elevated energy density are essential to meet the growing demands of high-performance supercapacitors. Ferrites are a promising family of electrode materials. Among them, calcium ferrite (CaFe₂O₄) has excellent structural stability. However, the low specific capacitance and high agglomeration rate of CaFe₂O₄ limit its applications. The addition of carbonaceous material to the ferrite host matrix is expected to modify the supercapacitor electrode characteristics. CaFe₂O₄ has not been explored yet as a composite of CNTs. In this work, robust (CaFe₂O₄)_1-x(CNTs)_x nanocomposites are synthesized through a simple sol–gel method via an ex-situ approach with extraordinary electrochemical properties. The prepared nanocomposites have unambiguously shown a polycrystalline nature, defective vibrational bonding, and a tuned band gap towards the low-frequency region due to the formation of heterojunctions, confirmed through XRD, FTIR, XPS, UV, and PL. The electrochemical studies reveal that the (CaFe₂O₄)_0.8(CNTs)_0.2 nanocomposites have the highest specific capacitance of 530.54 Fg⁻¹ at 0.5 Ag⁻¹ with the lowest ohmic and solution resistance, along with remarkable cyclic stability and columbic efficiency, making them an efficient electrode material.

Polypyrrole composited NiS₂ composite was easily synthesized using a hydrothermal and chemical polymerization technique. Two distinct composites (NS@P1 and NS@P3) were created by varying the polymer precursors stoichiometric ratio. The NS@P3 electrode exhibits a high surface area of 68 m² g¹ compared to other NS (46.4 m² g⁻¹) and NS@P1 (59.3 m² g⁻¹). The polypyrrole composited electrode exhibits excellent performance in electrochemical behavior. The NS@P3 electrode gives a huge specific capacitance of 1356 Fg⁻¹ at 0.5 Ag⁻¹ compared to other electrode of NS (452 g⁻¹) and NS@P1 (874 g⁻¹). The NS@P3 electrode's capacitive and diffusive mechanism were analyzed by using the Trasatti method. The assembled ASC-NS@P3//AC exhibits a high energy density of 68 Wh/kg and a power density of 646 W/kg. The prospective utilization of the NS@P3 composite as energy storage electrode materials for supercapacitor applications is confirmed by the enormous specific capacitance, energy and power delivered by the built ASC device.

In this work, zinc oxide (ZnO) and zinc oxide/zinc fluoride (ZnO/ZnF₂) nano composites were prepared by the hydrothermal method for asymmetric supercapacitor applications. ZnO/ZnF₂ composites represent a new class of electrode materials for supercapacitors with synergistic electrochemical properties. Incorporating fluorine into ZnO introduces additional charge carriers and decreases defect-related recombination losses, enhancing its electrical conductivity. ZnF₂ in the composite contributes to structural stability and offers more redox-active sites, allowing an enhancement in charge storage ability. The XRD confirms the formation of ZnO, ZnO/ZnF₂, and ACGS and is supported by the micro-Raman analysis. The oxidation states of zinc, oxygen, and fluorine in ZnO/ZnF₂ composites are confirmed by the XPS analysis. The ZnO nanoparticles had a coral-like structure, while the ZnO/ZnF₂ had a needle-like morphology. The surface areas of the by BET analysis are found to be 65.021,14.77, and 433.37 m²/g, respectively, for ZnO, ZnO/ZnF₂, and activated carbon from groundnut shell (ACGS). From the three-electrode analysis, the specific capacitances of ZnO, ZnO/ZnF₂, and ACGS were found to be 138.70 F/g @ 2.5 A/g, 667.06 F/g @ 2.5 A/g, and 15.672 F/g @ 3 A/g, respectively. The two-electrode system, ZnO-ZnF₂//ACGS device, has a specific capacitance of 184.3 F/g with capacitance retention of 92.84% over 4000 cycles @ 3 A/g current density.

Alkane-based heneicosane is potentially employed as phase change material (PCM) for thermal energy storage. Molecular dynamic (MD) simulation has been carried out to investigate the thermal performance of heneicosane by adding single-layer graphene at various weights. Mean square displacement of atoms (MSD), self-diffusion coefficient, and radial distribution function (RDF) were also examined to investigate the thermal properties of PCM and graphene composite. Furthermore, the thermal conductivity was calculated by nonequilibrium molecular dynamic (NEMD) method at different temperatures. Due to the introduction of graphene, results showed the thermal performance of composite PCM could be improved by about 63% to 88% than the pure heneicosane. Another interesting finding indicated the increase of energy storage capacity by about 3.3%. Despite the fact that this research has revealed graphene's potential to enhance the thermal performance of PCM, more empirical studies are highly advisable to support the simulation findings.