• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.6
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• pp.627-632
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• 2023

Lithium-ion batteries are widely used in various applications, including electric vehicles and portable electronics, due to their high energy density and long cycle life. The performance of lithium-ion batteries can be improved by using solid electrolytes, in terms of higher safety, stability, and energy density. Li_1.5Al_0.5Ti_1.5(PO₄)₃ (LATP) is a promising solid electrolyte for all-solid-state lithium batteries due to its high ionic conductivity and excellent stability. However, the ionic conductivity of LATP needs to be improved for commercializing all-solid-state lithium battery systems. In this study, we investigate the microstructures and ionic conductivities of LATP by incorporating B₂O₃ glass ceramics. The smaller grain size and narrow size distribution were obtained after the introduction of B₂O₃ in LATP, which is attributed to the B₂O₃ glass on grain boundaries of LATP. Moreover, higher ionic conductivity can be obtained after B₂O₃ incorporation, where the optimal composition is 0.1 wt% B₂O₃ incorporated LATP and the ionic conductivity reaches 8.8×10^-5 S/cm, more than 3 times higher value than pristine LATP. More research could be followed for having higher ionic conductivity and density by optimizing the processing conditions. This facile approach for establishing higher ionic conductivity in LATP solid electrolytes could accelerate the commercialization of all-solid-state lithium batteries.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.34 no.2
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• pp.73-77
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• 2024

The spinel-type oxide (Ni_x, Mn_y, Co_3-x-y)O₄ (NMC) is widely utilized as a material for temperature sensors with a negative temperature coefficient (NTC), finding applications across various industries including electric vehicle battery management systems. Typically, NMC is manufactured using solid-state reaction methods employing powders of Ni, Mn, and Co compounds, with the densification process through sintering recognized as a crucial factor determining the electrical properties of the temperature sensor material. In this study, NMC pellets were synthesized via solid-state reaction and their crystallographic and microstructural characteristics were investigated. Also, the activation energy for densification behavior during the sintering process was determined. According to the analysis results, the room temperature resistance of the NMC pellets was measured at 10.03 Kohm, with the sensitivity parameter, B-value, recorded at 3601.8 K, indicating their potential applicability as temperature sensors across various industrial fields. Furthermore, the activation energy for densification was found to be 273.3 ± 0.4 kJ/mol, providing valuable insights into the thermodynamic aspects of the sintering process of the NMC.

• Resources Recycling
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• v.33 no.1
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• pp.58-68
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• 2024

Critical minerals such as nickel, cobalt and lithium, are known as materials for cathodic active materials of lithium ion batteries. The consumption of the minerals is expected to grow with increasing the demands of electric vehicles, resulting from carbon neutrality. Especially, the demand for LIB (lithium ion battery) recycling is expected to increase to meet the supply of nickel, cobalt and lithium for LIB. The recycling of EOL (end-of-life) LIB can be achieved by leaching EOL LIB using inorganic acid such as HCl, HNO₃ and H₂SO₄, which are regarded as hazardous materials. In the present study, the potential use of MSA (Methanesulfonic acid), as an alternative lixiviant replacing sulfuric acid was investigated. In addition, leaching behaviors of NCM black mass leaching with MSA was also investigated by studying various leaching factors such as chemical concentration, leaching time, pulp density (P/D) and temperatures. The leaching efficiency of nickel (Ni), cobalt (Co), lithium (Li), and manganese (Mn) from LIB was enhanced by increasing concentration of lixiviant and reductant, leaching time and temperature. The maximum leaching of the metals was above 99% at 80℃. In addition, MSA can replace sulfuric acid to recover Ni, Co, Li, Mn from NCM black mass.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.99-107
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• 2024

Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.