Search

Advancement in energy storage technologies is closely related to social development. However, a significant conflict has arisen between the explosive growth in battery demand and resource availability. Facing the upcoming large-scale disposal problem of spent lithium-ion batteries (LIBs), their recycling technology development has become key. Emerging direct recycling has attracted widespread attention in recent years because it aims to 'repair' the battery materials, rather than break them down and extract valuable products from their components. To achieve this goal, a profound understanding of the failure mechanisms of spent LIB electrode materials is essential. This review summarizes the failure mechanisms of LIB cathode and anode materials and the direct recycling strategies developed. We systematically explore the correlation between the failure mechanism and the required repair process to achieve efficient and even upcycling of spent LIB electrode materials. Furthermore, we systematically introduce advanced in situ characterization techniques that can be utilized for investigating direct recycling processes. We then compare different direct recycling strategies, focussing on their respective advantages and disadvantages and their applicability to different materials. It is our belief that this review will offer valuable guidelines for the design and selection of LIB direct recycling methods in future endeavors. Finally, the opportunities and challenges for the future of battery direct recycling technology are discussed, paving the way for its further development. [ABSTRACT FROM AUTHOR]

The structure instability issues of the highly delithiated LiCoO2 have significantly hindered its high‐voltage applications (≥4.55 V vs Li/Li+). Herein, for the first time, multiple modifications of Li0.9Mg0.05CoO2 (L0.9M0.05CO) via a simple one‐step sintering synthesis are reported. A combination of the bulk Li/Co antisites, a Mg‐pillar enriched surface, and a thin MgO coating layer is achieved to maintain both the bulk and surface structural stability of L0.9M0.05CO upon cycling at an upper cut‐off voltage of 4.6 V. The bulk Li/Co antisites are discovered to enhance the H1‐3 phase evolution reversibility, the Mg pillars that substitute the Li sites effectively reinforces the surface structure, and the thin MgO coating layer can effectively prevent the cathode from severe side reactions. Benefiting from the reduced but reversible H1‐3 phase transition and the reinforced surface structure, L0.9M0.05CO shows an excellent cycle stability. This work provides a new structure modulation route for developing high‐voltage LiCoO2 cathodes. [ABSTRACT FROM AUTHOR]

Compressors are important components in various power systems in the field of energy and power. In practical applications, compressors often operate under non-design conditions. Therefore, accurate calculation on performance under various operating conditions is of great significance for the development and application of certain power systems equipped with compressors. To calculate and predict the performance of a compressor under all operating conditions through limited data, the interpolation method was combined with a support vector machine (SVM). Based on the known data points of compressor design conditions, the interpolation method was adopted to obtain training samples of the SVM. In the calculation process, preliminary screening was conducted on the kernel functions of the SVM. Two interpolation methods, including linear interpolation and cubic spline interpolation, were used to obtain sample data. In the subsequent training process of the SVM, the genetic algorithm (GA) was used to optimize its parameters. After training, the available data were compared with the predicted data of the SVM. The results show that the SVM uses the Gaussian kernel function to achieve the highest prediction accuracy. The prediction accuracy of the SVM trained with the data obtained from linear interpolation was higher than that of cubic spline interpolation. Compared with the back propagation neural network optimized by the genetic algorithm (GA-BPNN), the genetic algorithm optimization of extreme learning machine neural network (GA-ELMNN), and the genetic algorithm optimization of generalized regression neural network (GA-GRNN), the support vector machine optimized by the genetic algorithm (GA-SVM) has a better generalization, and GA-SVM is more accurate in predicting boundary data than the GA-BPNN. In addition, reducing the number of original data points still enables the GA-SVM to maintain a high level of predictive accuracy. [ABSTRACT FROM AUTHOR]

The cathode materials work as the host framework for both Li+ diffusion and electron transport in Li‐ion batteries. The Li+ diffusion property is always the research focus, while the electron transport property is less studied. Herein, we propose a unique strategy to elevate the rate performance through promoting the surface electric conductivity. Specifically, a disordered rock‐salt phase was coherently constructed at the surface of LiCoO2, promoting the surface electric conductivity by over one magnitude. It increased the effective voltage (Veff) imposed in the bulk, thus driving more Li+ extraction/insertion and making LiCoO2 exhibit superior rate capability (154 mAh g−1 at 10 C), and excellent cycling performance (93 % after 1000 cycles at 10 C). The universality of this strategy was confirmed by another surface design and a simulation. Our findings provide a new angle for developing high‐rate cathode materials by tuning the surface electron transport property. [ABSTRACT FROM AUTHOR]

The cathode materials work as the host framework for both Li+ diffusion and electron transport in Li‐ion batteries. The Li+ diffusion property is always the research focus, while the electron transport property is less studied. Herein, we propose a unique strategy to elevate the rate performance through promoting the surface electric conductivity. Specifically, a disordered rock‐salt phase was coherently constructed at the surface of LiCoO2, promoting the surface electric conductivity by over one magnitude. It increased the effective voltage (Veff) imposed in the bulk, thus driving more Li+ extraction/insertion and making LiCoO2 exhibit superior rate capability (154 mAh g−1 at 10 C), and excellent cycling performance (93 % after 1000 cycles at 10 C). The universality of this strategy was confirmed by another surface design and a simulation. Our findings provide a new angle for developing high‐rate cathode materials by tuning the surface electron transport property. [ABSTRACT FROM AUTHOR]

In the process of upgrading energy storage structures, sodium‐ion batteries (SIBs) are regarded as the most promising candidates for large‐scale grid storage systems. However, the difficulty in further improving their specific capacity and lifespan has become a major obstacle to promoting extensive application. Herein, by optimizing synthesis conditions, a biphasic‐Na2/3Ni1/3Mn2/3O2 cathode that exhibits an ultrahigh capacity of ≈200 mAh g‐1 without the involvement of anion redox reactions is successfully synthesized. Nevertheless, there is significant electrochemical performance degradation because of failure at the cathode‐electrolyte interface as revealed by comprehensive analyses. Further in‐depth research proves that the surface side reactions that occur at high operating voltages and the transition metal dissolution that occurs in low voltage are the root causes of electrode surface failure. Therefore, the metal oxide atomic layer deposition (ALD) protective layer is deliberately chosen to suppress such failures. The coating effectively blocks corrosion of the cathode material by the electrolyte and successfully anchors the transition metal ions on the particle surface. As a result, the cycle stability and rate performance of the electrode are improved considerably. This surface engineering strategy could provide concepts with broad applicability for suppressing the failure of sodium layered cathodes. [ABSTRACT FROM AUTHOR]