• Composites Research
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• v.32 no.6
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• pp.301-306
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• 2019

Triboelectric nanogenerator (TENG) is one of the energy harvesting methods in spotlight that can convert mechanical energy into electricity. As TENGs produce high electrical output, previous studies have shown TENGs that can power small electronics independently. However, recent studies have reported limitations of TENG due to air breakdown and field emission. In this study, we developed a triboelectric nanogenerator that utilizes the metal-to-metal surface contact to induce ion-enhanced field emission and electron avalanche for electrons to flow directly between two electrodes. The average peak open-circuit voltage of this TENG was measured as 340 V, and average peak closed-circuit current was measured as 10 mA. The electrical output of this TENG has shown different value depending on the surface charge of surface charge generation layer. The TENG developed in this study have produced RMS power of 0.9 mW, which is 2.4 times higher compared to conventional TENGs. The TENG developed in this study can be utilized in charging batteries and capacitors to power portable electronics and sensors independently.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.15-23
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• 2017

This paper reports a SOC(State-of-Charge) estimation method using the extended Kalman filter(EKF) algorithm, which can allow real-time implementation and reduce the error of the model and be robust against noise, to accurately estimate and evaluate the charging/discharging state of the EV(Electric Vehicle) battery. The battery was modeled as the first order Thevenin model for the EKF algorithm and the parameters were derived through experiments. This paper proposes the changed method, which can have the SOC to 0% ~ 100% regardless of the aging of the battery by replacing the rated capacity specified in the battery with the maximum chargeable capacity. In addition, This paper proposes the EKF algorithm to estimate the non-linearity interval of the battery and simulation result based on Ah-counting shows that the proposed algorithm reduces the estimation error to less than 5% in all intervals of the SOC.

• Journal of the Korean Electrochemical Society
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• v.6 no.4
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• pp.242-249
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• 2003

Zn electrode was widely used as an anode material in alkaline battery systems in highly concentrated KOH electrolyte, however it was well known that its cycle life is significantly shortened by growth of dendrite due to the high dissolution of $Zn(OH)_2$ and rapid electrochemical reaction. In this study when by the additives such as $Ca(OH)_2$, Citrate, tartrate and Gluconate were added to $40\%$ KOH electrolyte at solution temperature of $25^{\circ}C$ and the amount of $5wt\%\;Pb_3O_4$ was mixed to Zn electrode and then the effect of $Pb_3O_4$ and additives on the electrochemical behavior of Zn electrode was investigated by Potentiodynamic Polarization Curves, Cyclic Voltammetry, Accelerated Life Cycle lest, and SEM image analyses. The addition of $Pb_3O_4$ reduced the corrosion rate of Zn electrode. The corrosion potential of Zn electrode with $Pb_3O_4$ was higher or lower than that of pure Zn electrode however was not influenced practically to the open circuit voltage. And the addition of 4 type additives had an important role in improving both cycle life in accelerated cycle life test and corrosion resistance. Furthermore the additive of Tartrate indicated comparatively a good effect to corrosion resistance as well as charging-discharging property Improvement among those four type additives.

• Korean Chemical Engineering Research
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• v.60 no.1
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• pp.86-92
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• 2022

Recently, the bio-healthcare market is enlarging worldwide due to various reasons such as the COVID-19 pandemic. Among them, biometric measurement and analysis technology are expected to bring about future technological innovation and socio-economic ripple effect. Existing systems require a large-capacity battery to drive signal processing, wireless transmission part, and an operating system in the process. However, due to the limitation of the battery capacity, it causes a spatio-temporal limitation on the use of the device. This limitation can act as a cause for the disconnection of data required for the user's health care monitoring, so it is one of the major obstacles of the health care device. In this study, we report the concept of a standalone healthcare monitoring module, which is based on both triboelectric effects and electromagnetic effects, by converting biomechanical energy into suitable electric energy. The proposed system can be operated independently without an external power source. In particular, the wireless foot pressure measurement monitoring system, which is rationally designed triboelectric sensor (TES), can recognize the user's walking habits through foot pressure measurement. By applying the triboelectric effects to the contact-separation behavior that occurs during walking, an effective foot pressure sensor was made, the performance of the sensor was verified through an electrical output signal according to the pressure, and its dynamic behavior is measured through a signal processing circuit using a capacitor. In addition, the biomechanical energy dissipated during walking is harvested as electrical energy by using the electromagnetic induction effect to be used as a power source for wireless transmission and signal processing. Therefore, the proposed system has a great potential to reduce the inconvenience of charging caused by limited battery capacity and to overcome the problem of data disconnection.