Search Results (3,248)

In this work, we employed an electrochemical impedance spectroscopy analysis of commercial Li-ion Panasonic NCR18650B cells in order to monitor their cycle life performance and the influence of the C-rate on the charge/discharge processes. By applying a fast charge rate of 1.5 C, we investigated their speed degradation within three distinct discharge rates, namely, 0.5 C, 1 C, and 1.5 C. In our first approach, we assessed the dynamics of the lithium-ion transport processes, as well as their dependence on discharge rates, with the aim of understanding how their performance correlates with usage conditions. We observed that, as the discharge current increases while the number of cycles decreases, the ohmic resistance in the aged state reduces. Moreover, the charge transfer resistance is not affected by the discharge current, as the values are inversely proportional to the current rate, but mostly by the number of cycles. By performing a state of health analysis of Li-ion batteries with different C-rates until they were completely discharged, we offer a clear indication of how much of the battery’s lifetime available energy was consumed and how much was left, anticipating further issues or when the battery needed replacing. Starting at 60% state of health, the battery degradation has a steeper increase at 0.5 C and 1 C, respectively, while for a deep 1.5 C discharge, it only increases when the battery charge rate can no longer be sustained. Finally, the resonance frequency results highlight a fast increase toward the end of life for 0.5 C and 1 C, which is directly correlated with the above results, as a potentiostatic electrochemical impedance spectroscopy sequence was applied every fourth charge/discharge cycle. When applied at 1.5 C, the linear trend is much more pronounced, similar to the state of health results. Full article

Doping lithium cobalt oxide (LiCoO₂) cathode materials is an effective strategy for mitigating the detrimental phase transitions that occur at high voltages. A deep understanding of the relationships between cycle capacity and the design elements of doped LiCoO₂ is critical for overcoming the existing research limitations. The key lies in constructing a robust and interpretable mapping model between data and performance. In this study, we analyze the correlations between the features and cycle capacity of 158 different element-doped LiCoO₂ systems by using five advanced machine learning algorithms. First, we conducted a feature election to reduce model overfitting through a combined approach of mechanistic analysis and Pearson correlation analysis. Second, the experimental results revealed that RF and XGBoost are the two best-performing models for data fitting. Specifically, the RF and XGBoost models have the highest fitting performance for IC and EC prediction, with R² values of 0.8882 and 0.8318, respectively. Experiments focusing on ion electronegativity design verified the effectiveness of the optimal combined model. We demonstrate the benefits of machine learning models in uncovering the core elements of complex doped LiCoO₂ formulation design. Furthermore, these combined models can be employed to search for materials with superior electrochemical performance and processing conditions. In the future, we aim to develop more accurate and efficient machine learning algorithms to explore the microscopic mechanisms affecting doped layered oxide cathode material design, thereby establishing new paradigms for the research of high-performance cathode materials for lithium batteries. Full article

As a multi-electron system material, the excellent capacity and environmentally benign properties of Li₂FeTiO₄ cathodes make them attractive for lithium-ion batteries. Nevertheless, their electrochemical performance has been hampered by poor conductivity and limited ion transport. In this work, the synthesis of Mg-doped Li₂Mg_xFe_1−xTiO₄ (LiFT-Mgx, x = 0, 0.01, 0.03, 0.05) cathode materials was successfully achieved. We observed significant gains in interlayer spacing, ionic conductivity, and kinetics. Hence, the sample of the LiFT-Mg0.03 cathode demonstrated charming initial capacity (112.1 mAh g⁻¹, 0.05 C), stability (85.0%, 30 cycles), and rate capability (96.5 mAh g⁻¹, 85.9%). This research provided precious insights into lithium storage with exceptional long-term stability and has the potential to drive the development of next-generation energy storage technologies. Full article

Ethylene carbonate is, among other applications, used in Li-ion batteries as an electrolyte solvent to dissociate Li-salt. Supercritical CO₂ extraction is a promising method for the recycling of electrolyte solvents from spent batteries. To design an extraction process, knowledge of the solute solubility is essential. In this work, the solubility of ethylene carbonate at different pressure (80–160 bar) and temperature (40 °C, and 60 °C) conditions is studied. It is shown that the solubility of ethylene carbonate increased with pressure at both temperatures, ranging from 0.24 to 8.35 g/kg CO₂. The retrieved solubility data were fitted using the Chrastil model, and the average equilibrium association number was determined to be 4.46 and 4.02 at 40 °C and 60 °C, respectively. Scanning electron microscopy, Fourier-transform infrared spectroscopy, and X-ray diffraction analysis of the collected ethylene carbonate indicated that the crystal morphology and structure remained unchanged. A proof-of-principle experiment showed that EC can be successfully extracted from Li-ion battery waste at 140 bar and 40 °C. Full article

This study proposes a novel approach to improving the crashworthiness of lithium-ion cylindrical cell packs by strategically placing spacers between the cells. The spacers transform the initial line contacts into broader surface contacts, enhancing the overall stiffness of the pack and reducing radial deformation during compression. The concept was evaluated using finite element analysis (FEA), leveraging established material models to efficiently assess the concept’s potential prior to physical testing. To validate the robustness of the homogenized cell material and its application in a full pack, a compression experiment was performed on a pack of nine cells. The experimental results aligned closely with the simulation data, underlining the reliability of the material model and simulation methodology. Across all configurations and load cases—quasi-static compression using a plate or cylinder, and dynamic impact tests simulating crash indentation with a ball—the inclusion of spacers resulted in significant reductions in cell deformation and pack intrusion. The study also examined three spacer materials: aluminum, printed PLA, and printed PLA conditioned at 60 °C. The results showed that stiffer spacers, such as those made of aluminum, were the most effective in improving crash performance. However, even the conditioned PLA spacer, despite its lower stiffness, delivered meaningful benefits by enhancing structural integrity and reducing deformation. This demonstrates the versatility of the spacer concept, which can accommodate a range of materials based on specific performance and manufacturing requirements. These findings establish a solid foundation for the practical implementation of spacers in electric vehicle battery packs. Future research should include experimental validation under real-world crash conditions and explore spacer design and material optimization to maximize crashworthiness without compromising energy density or thermal performance. Full article

Artificial enzymes or nanozymes (NZs) are gaining significant attention in biotechnology due to their stability and cost-effectiveness. NZs can offer several advantages over natural enzymes, such as enhanced stability under harsh conditions, longer shelf life, and reduced production costs. The booming interest in NZs is likely to continue as their potential applications expand. In our previous studies, we reported the “green” synthesis of copper hexacyanoferrate (gCuHCF) using the oxidoreductase flavocytochrome b₂ (Fcb₂). Organic–inorganic micro-nanoparticles were characterized in detail, including their structure, composition, catalytic activity, and electron-mediator properties. An SEM analysis revealed that gCuHCF possesses a flower-like structure well-suited for concentrating and stabilizing Fcb₂. As an effective peroxidase (PO) mimic, gCuHCF has been successfully employed for H₂O₂ detection in amperometric sensors and in several oxidase-based biosensors. In the current study, we demonstrated the uniqueness of gCuHCF that lies in its multifunctionality, serving as a PO mimic, a chemosensor for ammonium ions, a biosensor for L-lactate, and exhibiting perovskite-like properties. This exceptional ability of gCuHCF to enhance fluorescence under blue light irradiation is being reported for the first time. Using gCuHCF as a PO-like NZ, novel oxidase-based sensors were developed, including an optical biosensor for L-arginine analysis and electrochemical biosensors for methanol and glycerol determination. Thus, gCuHCF, synthesized via Fcb₂, presents a promising platform for the development of amperometric and optical biosensors, bioreactors, biofuel cells, solar cells, and other advanced devices. The innovative approach of utilizing biocatalysts for nanoparticle synthesis highlights a groundbreaking direction in materials science and biotechnology. Full article

The acidic tumor microenvironment plays a critical role in promoting liver cancer cell survival by enhancing glycolysis and adaptive mechanisms. Acid-sensing ion channel 1 (ASIC1) is a key regulator of pH sensing, but its role in liver cancer progression and underlying mechanisms remain unclear. In this study, we examined ASIC1 expression in clinical liver tumor tissues using immunohistochemistry and immunofluorescence, correlating it with tumor stages. HepG2 and Li-7 cells were cultured in tumor supernatant and acidic conditions to mimic the tumor microenvironment. Western blotting assessed the expression of ASIC1 and glycolysis-related enzymes, with siRNA transfections used to investigate ASIC1 and phosphofructokinase muscle-type (PFKM) in liver cancer cell survival. Our results showed that ASIC1 expression was significantly elevated in liver tumor tissues and correlated with tumor progression. Acidic conditions increased ASIC1 expression in both cell lines, enhancing cell survival, while knockdown of ASIC1 reduced viability and increased apoptosis, particularly under acidic conditions. Moreover, PFKM silencing reversed the survival advantage conferred by ASIC1, confirming PFKM as a critical downstream effector. Additionally, lactate dehydrogenase (LDH) and phosphofructokinase (PFK) activity assays showed no significant changes, suggesting other regulatory mechanisms may also be involved. These findings suggest that the ASIC1/PFKM pathway promotes liver cancer cell survival in acidic environments, representing a potential therapeutic target for disrupting tumor adaptation in liver malignancies. Full article

Lithium-ion batteries are the core energy storage technology for electric vehicles and energy storage systems. Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. This review systematically examines the research progress on SOC estimation techniques over a wide temperature range, focusing on two mainstream approaches: model improvement and data-driven methods. The model improvement method enhances temperature adaptability through temperature compensation and dynamic parameter adjustment. Still, it has limitations in dealing with the nonlinear behavior of batteries and accuracy and real-time performance at extreme temperatures. In contrast, the data-driven method effectively copes with temperature fluctuations and complex operating conditions by extracting nonlinear relationships from historical data. However, it requires high-quality data and substantial computational resources. Future research should focus on developing high-precision, temperature-adaptive models and lightweight real-time algorithms. Additionally, exploring the deep coupling of physical models and data-driven methods with multi-source heterogeneous data fusion technology can further improve the accuracy and robustness of SOC estimation. These advancements will promote the safe and efficient application of lithium batteries in electric vehicles and energy storage systems. Full article

The growing demand for lithium-ion batteries (LIBs), driven by their use in portable electronics and electric vehicles (EVs), has led to an increasing volume of spent batteries. Effective end-of-life (EoL) management is crucial to mitigate environmental risks and prevent depletion of valuable raw materials like lithium (Li), cobalt (Co), nickel (Ni), and manganese (Mn). Sustainable, high-volume recycling and material recovery are key to establishing a circular economy in the battery industry. This paper investigates challenges and proposes innovative solutions for high-volume LIB recycling, focusing on automation for large-scale recycling. Key issues include managing variations in battery design, chemistry, and topology, as well as the availability of sustainable raw materials and low-carbon energy sources for the recycling process. The paper presents a comparative study of emerging recycling techniques, including EV battery sorting, dismantling, discharge, and material recovery. With the expected growth in battery volume by 2030 (1.4 million per year by 2040), automation will be essential for efficient waste processing. Understanding the underlying processes in battery recycling is crucial for enabling safe and effective recycling methods. Finally, the paper emphasizes the importance of sustainable LIB recycling in supporting the circular economy. Our proposals aim to overcome these challenges by advancing automation and improving material recovery techniques. Full article

With the accelerated application of lithium-ion batteries, the design and optimization of their safety features have become increasingly important. However, the mechanisms by which different safety vent bursting pressures affect thermal runaway and its product compositions remain unclear. This study comparatively investigates the effects of safety vent bursting pressures of 1 MPa, 2 MPa, and 3 MPa on thermal runaway characteristics and product compositions. The results indicate that, under these three conditions, the safety vent bursts at approximately 800 s, 1000 s, and 1300 s after heating begins, with gas volumes of 5.3 L, 6.1 L, and 6.5 L, respectively. Additionally, higher bursting pressures lead to increased H₂ production during thermal runaway. The characterization of solid product compositions reveals that the aluminum current collector participates in internal thermal runaway reactions, resulting in substances such as LiAlO₂ or metallic Al in the solid products under different bursting pressures. This study provides important references for improving existing battery safety standards and optimizing battery safety designs. It also provides insights and references for metal recovery from batteries and investigations into battery fires. Full article

Lithium-ion batteries that use lithium iron phosphate (LiFePO₄) as the cathode material and carbon (graphite or MCMB) as the anode have gained significant attention due to their cost-effectiveness, low environmental impact, and strong safety profile. These advantages make them suitable for a wide range of applications including electric vehicles, stationary energy storage, and backup power systems. However, their adoption is hindered by a critical challenge: capacity degradation at elevated temperatures. This review systematically summarizes the corresponding modification strategies including surface modification of the anode and cathode as well as modification of the electrolyte, separator, binder, and collector. We further discuss the control of the charge state, early warning prevention, control of thermal runaway, and the rational application of ML and DFT to enhance the LFP/C high temperature cycling stability. Finally, in light of the current research challenges, promising research directions are presented, aiming at enhancing their performance and stability in such harsh thermal environments. Full article

In this study, nitrogen- and sulfur-co-doped MXene (NS-MXene) was developed as a high-performance cathode material for lithium–sulfur (Li-S) batteries. Heterocyclic Se₂S₆ molecules were successfully confined within the NS-MXene structure using a simple melt impregnation method. The resulting NS-MXene exhibited a unique wrinkled morphology with a stable structure which facilitated rapid ion transport and provided a physical barrier to mitigate the shuttle effect of polysulfide. The introduction of nitrogen and sulfur heteroatoms into the MXene structure not only shifted the Ti d-band center towards the Fermi level but also significantly polarizes the MXene, enhancing the conversion kinetics and ion diffusion capability while preventing the accumulation of Li₂S₆. Additionally, the incorporation of Se and S in Se₂S₆ improved the conductivity compared to S alone, resulting in reduced polarization and enhanced electrical properties. Consequently, NS-MXene/Se₂S₆ exhibited excellent cycling stability, high reversible capacity, and reliable performance at high current densities and under extreme conditions, such as high sulfur loading and low electrolyte-to-sulfur ratios. This work presents a simple and effective strategy for designing heteroatom-doped MXene materials, offering promising potential for the development of high-performance, long-lasting Li-S batteries for practical applications. Full article

With the rapid development of lithium-ion batteries, predicting battery life is critical to the safe operation of devices such as electric ships, electric vehicles, and energy storage systems. Given the complexity of the internal aging mechanism of batteries, their aging process exhibits prominent nonlinear characteristics. Knee point, as a distinctive sign of this nonlinear aging process, plays a crucial role in predicting the battery’s lifetime. In this paper, the cycle life and cycle to the knee point of the battery are firstly predicted using the time dimension and space dimension features of the early external characteristics of the battery, respectively. Then, to capture the aging characteristics of batteries more comprehensively, we innovatively propose a joint prediction method of battery cycle life and knee point. Knee point features are incorporated into the battery cycle life prediction model in this method to fully account for the nonlinear aging characteristics of batteries. The experimental validation results show that the TECAN model, which combines time series features and knee point information, performs well, with a root mean square error (RMSE) of 106 cycles and a mean absolute percentage error (MAPE) of only 12%. Full article

The rapid rise in the power conversion efficiency (PCE) of perovskite solar cells (PSCs) has opened the door for diverse potential applications in powering indoor Internet of Things (IoT) devices. An energy harvesting system (EHS) powered by a PSC module with a backup Li-ion battery, which stores excess power at moments of high irradiances and delivers the stored power to drive the load during operation scenarios with low irradiances, has been designed. A DC-DC boost converter is engaged to match the voltage of the PSC and Li-ion battery, and maximum power point tracking (MPPT) is achieved by a perturb and observe (P&O) algorithm, which perturbs the photovoltaic (PV) system by adjusting its operating voltage and observing the difference in the output power of the PSC. Furthermore, the charging and discharging rate of the battery storage is controlled by a DC-DC buck–boost bidirectional converter with the incorporation of a proportional–integral (PI) controller. The bidirectional DC-DC converter operates in a dual mode, achieved through the anti-parallel connection of a conventional buck and boost converter. The proposed EHS utilizes DC-DC converters, MPPT algorithms, and PI control schemes. Three different case scenarios are modeled to investigate the system’s behavior under varying irradiances of 200 W/m², 100 W/m², and 50 W/m². For all three cases with different irradiances, MPPT achieves tracking efficiencies of more than 95%. The laboratory-fabricated PSC operated at MPP can produce an output power ranging from 21.37 mW (50 W/m²) to 90.15 mW (200 W/m²). The range of the converter’s output power is between 5.117 mW and 63.78 mW. This power range can sufficiently meet the demands of modern low-energy IoT devices. Moreover, fully charged and fully discharged battery scenarios were simulated to study the performance of the system. Finally, the IoT load profile was simulated to confirm the potential of the proposed energy harvesting system in self-sustainable IoT applications. Upon review of the current literature, there are limited studies demonstrating a combination of EHS with PSCs as an indoor power source for IoT applications, along with a bidirectional DC-DC buck–boost converter to manage battery charging and discharging. The evaluation of the system performance presented in this work provides important guidance for the development and optimization of new-generation PV technologies like PSCs for practical indoor applications. Full article

Solid-state lithium-ion batteries are gaining attention as a promising alternative to traditional lithium-ion batteries. By utilizing a solid electrolyte instead of a liquid, these batteries offer the potential for enhanced safety, higher energy density, and longer life cycles. The solid electrolyte typically consists of a polymer matrix integrated with ceramic fillers, which can significantly boost ionic conductivity. Research efforts are currently focused on advancing materials for the battery’s three primary components: the electrolyte, anode, and cathode. Furthermore, innovative strategies are being developed to optimize the interfaces between these components, addressing key challenges in performance and durability. Cutting-edge manufacturing techniques are also being explored to improve production efficiency and reduce costs. With continued advancements, solid-state lithium-ion batteries are poised to become integral to next-generation technologies, including electric vehicles and wearable electronics. Full article