• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2005.07a
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• pp.418-419
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• 2005

$\o-LiMnO_2$ is known to have poor cycle performance causing the irreversible phase transformation on cycling. In this paper, the effect of chemical substitution on improving cycle performance of $o-LiMnO_2$ was studied at the compositions of $LiCr_xMn_{1-x}O_2$(x=0, 0.1, 0.2, 0.4). XRD is showed that structure of $LiCr_xMn_{1-x}O_2$ transformed from orthorhombic to spinel according to the increase of substitute degree. For lithium ion battery applications, $LiCr_xMn_{1-x}O_2$/Li cell were characterized electrochemically by charge/discharge cycling.

• Applied Chemistry for Engineering
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• v.9 no.5
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• pp.781-785
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• 1998

Material and electrochemical characteristics of petroleum coke of the nongraphitic carbon prepated with attrition milling for 6~48 hours and heat-treatment at $700^{\circ}C$ for 1 hour was investigated. The milling condition affects the particle size distribution, BET specific surface area and interlayer distance of petroleum cokes. Carbon electrode with petroleum cokes prepared at the milling time of 12~24 hours and having average particle size of $6{\sim}8{\mu}m$ showed best electrochemical characteristics form the investigation of cyclic voltammogram and charge-discharge characteristics.

• Journal of Electrochemical Science and Technology
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• v.9 no.4
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• pp.330-338
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• 2018

The adhesion strength as well as the electrochemical properties of $LiNi_{0.4}Mn_{0.4}Co_{0.2}O_2$ electrodes containing various conductive carbons (CC) such as fiber-like carbon, vapor-grown carbon fiber, carbon nanotubes, particle-like carbon, Super P, and Ketjen black is compared. The morphological properties is investigated using scanning electron microscope to reveal the interaction between the different CC and the active material. The surface and interfacial cutting analysis system is also used to measure the adhesion strength between the aluminum current collector and the composite film, and the adhesion strength between the active material and the CC of the electrodes. The results obtained from the measured adhesion strength points to the fact that the structure and the particle size of CC additives have tremendous influence on the binding property of the composite electrodes, and this in turn affects the electrochemical property of the configured electrodes.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.3
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• pp.183-191
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• 2021

A battery management system (BMS) provides some functions for ensuring safety and reliability that includes algorithms estimating battery states. Given the changes caused by various operating conditions, the state-of-health (SOH), which represents a figure of merit of the battery's ability to store and deliver energy, becomes challenging to estimate. Machine learning methods can be applied to perform accurate SOH estimation. In this study, we propose a Long-Term Recurrent Convolutional Network (LRCN) that combines the Convolutional Neural Network (CNN) and Long Short-term Memory (LSTM) to extract aging characteristics and learn temporal mechanisms. The dataset collected by the battery aging experiments of NASA PCoE is used to train models. The input dataset used part of the charging profile. The accuracy of the proposed model is compared with the CNN and LSTM models using the k-fold cross-validation technique. The proposed model achieves a low RMSE of 2.21%, which shows higher accuracy than others in SOH estimation.

• Journal of Electrochemical Science and Technology
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• v.12 no.3
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• pp.317-322
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• 2021

Silicon (Si) has been considered as a promising anode material because of its abundant reserves in nature, low lithium ion (Li⁺) intercalation/de-intercalation potential (below 0.5 V vs. Li/Li⁺) and high theoretical capacity of 4200 mA h/g. In this paper, we prepared a silicon-based (Si-based) anode material containing a small amount of silicon carbide by using magnesiothermic coreduction of silica and hexachlorobenzene. Because of good conductivity of silicon carbide, the cycle performance of the silicon-based anode materials containing few silicon carbide is greatly improved compared with pure silicon. The raw materials were formulated according to a silicon-carbon molar ratio of 10:0, 10:1, 10:2 and 10:3, and the obtained products were purified and tested for their electrochemical properties. After 1000 cycles, the specific capacities of the materials with silicon-carbon molar ratios of 10:0, 10:1, 10:2 and 10:3 were still up to 412.3 mA h/g, 970.3 mA h/g, 875.0 mA h/g and 788.6 mA h/g, respectively. Although most of the added carbon reacted with silicon to form silicon carbide, because of the good conductivity of silicon carbide, the cycle performance of silicon-based anode materials was significantly better than that of pure silicon.

• Journal of the Korean Electrochemical Society
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• v.24 no.1
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• pp.1-6
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• 2021

In this study, new morphology of NCA cathode material for lithium ion batteries was obtained through the electrospinning method. The prepared NCA nanofibers formed a nano-bush structure, and the primary particles were formed on the surface of the nanofibers. The embossing primary particles increased the surface area thus increasing the reactivity of lithium ions. The nano-bush structure could shorten the Li+ diffusion path and improve the Li+ diffusion coefficient. Scanning electron microscopy (SEM) revealed that the synthesized material consisted of nanofibers. The surface area of the nanofibers increased by primary particles was measured using atomic force microscopy (AFM). X-ray diffraction (XRD) analysis was carried out to determine the structure of the NCA nanofibers.

• Journal of Hydrogen and New Energy
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• v.32 no.6
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• pp.592-611
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• 2021

In this study a rarely available high-throughput cycling data set of 124 commercial lithium iron phosphate/graphite cells cycled under fast-charging conditions, with widely varying cycle lives ranging from 150 to 2,300 cycles including in-cycle temperature and per-cycle IR measurements. We worked out own Python codes which reproduced the various data plots and machine learning approaches for cycle life prediction using early cycles and more details not presented in the article and the supplementary information. Particularly, we applied regularized ridge, lasso and elastic net linear regression models using features extracted from capacity fade curves, discharge voltage curves, and other data such as internal resistance and cell can temperature. We found that due to the limitation in the quantity and quality of the data from costly and lengthy battery testing a careful hyperparameter tuning may be required and that model features need to be extracted based on the domain knowledge.

• Journal of Electrochemical Science and Technology
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• v.13 no.1
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• pp.159-166
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• 2022

The assembly of the micron-sized Si/CNT/carbon composite wrapped with graphene (SCG composite) is designed and synthesized via a spray drying process. The spherical SCG composite exhibits a high discharge capacity of 1789 mAh g^-1 with an initial coulombic efficiency of 84 %. Moreover, the porous architecture of SCG composite is beneficial for enhancing cycling stability and rate capability. In practice, a blended electrode consisting of spherical SCG composite and natural graphite with a reversible capacity of ~500 mAh g^-1, shows a stable cycle performance with high cycling efficiencies (> 99.5%) during 100 cycles. These superior electrochemical performance are mainly attributed to the robust design and structural stability of the SCG composite during charge and discharge process. It appears that despite the fracture of micro-sized Si particles during repeated cycling, the electrical contact of Si particles can be maintained within the SCG composite by suppressing the direct contact of Si particles with electrolytes.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.6
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• pp.89-97
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• 2022

Ultrasonic metal welding has been widely used for joining lithium-ion battery tabs. Weld quality monitoring has been an important issue in lithium-ion battery manufacturing. This study focuses on the weld quality monitoring in ultrasonic metal welding with the longitudinal-torsional vibration mode horn developed newly. As the quality of ultrasonic welding depends on welding parameters like pressure, time, and amplitude, the suitable values of these parameters were selected for experimentation. The welds were tested via tensile testing machine and weld strengths were investigated. The dataset collected for performance test was used to train the multi-layer perceptron neural network. The three layer neural network was used for the study and the optimum number of neurons in the first and second hidden layers were selected based on performances of each models. The best models were selected for the horn and then tested to see their performances on an unseen dataset. The neural network models for the longitudinal-torsional mode horn attained test accuracy of 90%. This result implies that proposed models has potential for the weld quality monitoring.

• Journal of Powder Materials
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• v.29 no.3
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• pp.252-261
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• 2022

Cobalt is a vital metal in the modern society because of its applications in lithium-ion batteries, super alloys, hard metals, and catalysts. Further, cobalt is a representative rare metal and is the 30th most abundant element in the Earth's crust. This study reviews the current status of cobalt extraction and recycling processes, along with the trends in its production amount and use. Although cobalt occurs in a wide range of minerals, such as oxides and sulfides of copper and nickel ores, the amounts of cobalt in the minerals are too low to be extracted economically. The Democratic Republic of Congo (DRC) leads cobalt mining, and accounts for 68.9 % of the global cobalt reserves (142,000 tons in 2020). Cobalt is mainly extracted from copper-cobalt and nickel-cobalt concentrates and is occasionally extracted directly from the ore itself by hydro-, pyro-, and electro-metallurgical processes. These smelting methods are essential for developing new recycling processes to extract cobalt from secondary resources. Cobalt is mainly recycled from lithium-ion batteries, spent catalysts, and cobalt alloys. The recycling methods for cobalt also depend on the type of secondary cobalt resource. Major recycling methods from secondary resources are applied in pyro- and hydrometallurgical processes.