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Lithium battery, as its main power source, needs to ensure the safety of drivers and passengers not only under some complex external conditions, but also under harsh use conditions, even when damaged. At some point throughout this process, it is required to evaluate the status of the battery itself in order to assure safe usage of the battery and to develop a more effective battery management plan. SOC, SOH, and condition of power are all variables that are commonly used to describe the state of a lithium battery (SOP). The ability of the battery to constantly provide or receive power, the remaining service the life cycle of the battery, and the ability of the battery to output or receive power promptly are all described by these three characteristics. In order to effectively evaluate the health status of batteries, this paper proposes a dual-mode extended Kalman filter (EKF) algorithm for the remote estimation of SOC and SOH of high-energy lithium batteries. In the estimating procedure, the open circuit voltage (OCV) is also included as a state variable in the iterative process, which allows for more accurate results. In this paper, the state space equation is established based on the first-order RC equivalent circuit model, and the battery state estimation and parameter identification are completed by using the double EKF (the dual extended Kalman filtering, DEKF) algorithm, resulting in the realization of the estimation of SOC and SOH.

Based on the first-principles study, the adsorption and electron transfer properties of Li atom at different sites of SnS₂ monolayer, SnS₂@Graphene 2D-nanocomposite are analyzed. The differential charge density and density of states (DOS) analysis show that the graphene substrate as an electron donor can change the 2D-nanocomposite from a semiconductor to a metal, and reduce the adsorption energy of Li atom by decreasing the charge transferring from Li atom to SnS₂. This indicates that graphene substrate is beneficial for improving the performance of SnS₂@Graphene. Meanwhile, the Li atoms tend not to cluster on the SnS₂@Graphene 2D-nanocomposite, which is useful to prolong the lifespan of the SnS₂@Graphene. The functionality of graphene in SnS₂@Graphene 2D-nanocomposite is proved by other electron donor substrates, such as a two-H-atom model and a Sn (111) substrate model. All the results indicate that the graphene, as an electron donor in SnS₂@Graphene 2D-nanocomposite, plays a key role in improving the performance of SnS₂ in rechargeable lithium batteries.

Energy storage systems are crucial for the advancement of modern technology, yet achieving optimal efficiency in these systems remains a significant challenge. This study investigates how spatial distribution impacts energy diffusion within battery electrodes using Gaussian peak models. We explore two distinct configurations of Gaussian peaks separate and overlapping to understand their effects on diffusion patterns. Separate Gaussian peaks produce simpler diffusion profiles with well-defined influence regions, while overlapping peaks create complex diffusion patterns with intricate contours reflecting the combined effects of multiple sources. To enhance the accuracy and efficiency of our simulations, we leverage machine learning (ML) optimization techniques. An ML-based optimizer is employed to refine the parameters of the diffusion model, resulting in more precise and efficient simulations. This approach allows us to better understand and predict how different peak arrangements affect diffusion dynamics. By simulating these scenarios in rectangular and square electrode geometries, we reveal how the spatial arrangement of energy sources influences diffusion behavior. Our findings provide valuable insights for optimizing battery designs, suggesting that tailored diffusion profiles can significantly improve energy storage efficiency and reliability. This research not only advances the theoretical understanding of energy diffusion processes but also demonstrates how ML optimization can be used to enhance the performance of lithium-ion batteries and other energy storage systems.

Transition metal oxides as Li-ion batteries (LIBs) anodes have attracted much attention because of their high theoretical capacity. However, the large volume change and low electrical conductivity still hinder their application in LIBs. In this work, a new strategy is proposed to enhance the electrochemical performance by anchoring ultrafine MnFe₂O₄ and MnCO₃ ($\sim 5$nm) on amorphous carbon-coated carbon nanotubes. Benefiting from the unique structure, the electrode displays excellent cyclability with a reversible specific capacity of 1012mAh g${}^{-1}$ at 0.1A g${}^{-1}$ after 100 cycles and outstanding rate performance accompanied by a high specific capacity of 568mAh g${}^{-1}$ at 5A g${}^{-1}$ as anode for lithium batteries. When evaluated as supercapacitors, the electrode delivers the specific capacitance of 588.9F g${}^{-1}$ at a current density of 1A g${}^{-1}$ and maintains the capacitance retention 94.7% after 4000 cycles at 5A g${}^{-1}$.

The nondegradable nature and toxicity of organic liquid electrolytes reveal the design deficiency of lithium batteries in environmental protection. Biopolymers can be extracted from biomass under mild conditions, thus they are usually low cost and renewable. The unique characteristics of biopolymers such as water solubility, film-forming capability and adhesive property are of importance for lithium battery. The studies on the biopolymer materials for lithium batteries have been reviewed in this work. Although a lot of work on the biopolymer-based battery materials has been reported, it is still a challenge in the design of lithium battery with zero pollution and zero waste.

Li-based rechargeable batteries are becoming popular power sources for biomedical devices and healthcare equipment. In nanoscale, lithium bonds may associate with intermolecular noncovalent interactions when Li atoms are shared by adjacent atoms inside rechargeable Li batteries. Theoretical study of lithium boding interactions thus is of paramount importance for a better understanding of the working mechanisms and designing high-efficient electrode–electrolyte interfaces from nanolevel for Li-based batteries. In this study, we used state-of-the-art theoretical methods, with inclusion of density functional theory/symmetry-adapted perturbation theory (DFT/SAPT), density functional reactivity theory (DFRT) and energy decomposition analysis (EDA), to delve into the nature of lithium bonding interactions. Our results showed that B3LYP outperforms all other functionals under consideration in the conventional supramolecular scheme, indicating that the formation of a lithium bond is not dispersion-driven. The calculated PBE0/SAPT and B3LYP/EDA data are consistent with each other, unravelling that the lithium bond is mainly of an electrostatically driven nature. Both steric hindrance and exchange-correlation potentials also make important contributions when two-variable fitting is considered. These results provide new sight in understanding lithium atom interactions for potential lithium-based batteries applications.

This paper describes the synthesis and electrochemical behavior of the oxygen deficient brannerite LiVWO_6-δ Brannerite LiVWO_6-δ has been synthesized by means of a simple aqueous solution reaction (ASR) technique namely soft-combustion process employing glycine as a soft combustion agent. The synthesized product has been subjected to thermal treatment in various stages in order to best understand the phase formation and study their redox behavior in lithium-containing cells. Electrochemical studies such as Cyclic voltammetry, Galvanostatic (constant current) charge-discharge curves and Galvanostatic Intermittent Titration Technique (GITT) on this oxygen deficient product show that this material could be regarded as 4-volt class category with specific capacities as high as ~ 95 mAh/g in the voltage regime 4.9 V to 2.8 V vs Li⁺/Li.

Proposed herein is a new ambient temperature Li⁺ conducting PVDF-HFP-co-polymer based hybrid polymer electrolyte with polyvinyl carbozole (PVK) as additive. The addition of the latter provides high ambient temperature electrolytic conductivity (σ_i) 0.7 × 10^-3S/cm with an ionic transference number of 0.6, besides providing the thermoplastic flexibility to the whole matrix. The membrane is found to exhibit a wide electrochemical potential window, >4.5V against Li/Li⁺. When prepared properly, the membrane is dry and free standing, yet totally suitable for lithium polymer rechargeable batteries. This paper presents the preparation, microstructure and electrochemical characteristics of this new hybrid polymeric membrane. Finally, the dry polymeric electrolyte membrane has been employed in a lithium polymer cell against LT-LiCo_0.8Ni_0.2O₂ as positive electrode and its interfacial behavior and electrochemical cycling results are presented.

Orthorhombic LiMnO₂ nanoparticles have been synthesized through one-step hydrothermal method as a cathode material for lithium batteries. The synthesized material was characterized by scanning electron microscopy, energy-dispersive X-ray analysis, transmission electron microscopy, X-ray diffraction and the electrochemical impedance spectroscopy. The results showed that the size of nanoparticles is about 50 to 100 nm and the best d.c. conductance with the PVDF content of 2.5% is around 3.0 × 10⁻⁷