• Korean Chemical Engineering Research
• /
• v.60 no.4
• /
• pp.588-593
• /
• 2022

Terephthalaldehyde (TPA) is introduced as a cross liker to enhance electron transfer of hemin-based cathodic catalyst consisting of polyethyleneimine (PEI), carbon nanotube (CNT) for hydrogen peroxide reduction reaction (HPRR). In the cyclic voltammetry (CV) test with 10 mM H₂O₂ in phosphate buffer solution (pH 7.4), the current density for HPRR of the suggested catalyst (CNT/PEI/hemin/PEI/TPA) shows 0.2813 mA cm^-2 (at 0.2 V vs. Ag/AgCl), which is 2.43 and 1.87 times of non-cross-linked (CNT/PEI/hemin/PEI) and conventional cross liker (glutaraldehyde, GA) used catalyst (CNT/PEI/hemin/PEI/GA), respectively. In the case of onset potential for HPRR, that of CNT/PEI/hemin/PEI/TPA is observed at 0.544 V, while those of CNT/PEI/hemin/PEI and CNT/PEI/hemin/PEI/GA are 0.511 and 0.471 V, respectively. These results indicate that TPA plays a role in facilitating electron transfer between the electrodes and substrates due to the π-conjugated cross-linking bonds, whereas conventional GA cross-linker increases the overpotential by interrupting electron and mass transfer. Electrochemical impedance spectroscopy (EIS) results also display the same tendency. The charge transfer resistance (R_ct) of CNT/PEI/hemin/PEI/TPA decreases about 6.2% from that of CNT/PEI/hemin/PEI, while CNT/PEI/hemin/PEI/GA shows the highest R_ct. The polarization curve using each catalyst also supports the superiority of TPA cross liker. The maximum power density of CNT/PEI/hemin/PEI/TPA (36.34±1.41 μWcm^-2) is significantly higher than those of CNT/PEI/hemin/PEI (27.87±0.95 μWcm^-2) and CNT/PEI/hemin/PEI/GA (25.57±1.32 μWcm^-2), demonstrating again that the cathode using TPA has the best performance in HPRR.

• Journal of the Microelectronics and Packaging Society
• /
• v.31 no.1
• /
• pp.16-22
• /
• 2024

Along with the high interest in electric vehicles and new renewable energy, there is a growing demand to apply lithium-ion batteries in the construction equipment industry. The capacity of heavy construction equipment that performs various tasks at construction sites is rapidly decreasing. Therefore, it is essential to accurately predict the state of batteries such as SOC (State of Charge) and SOH (State of Health). In this paper, the errors between actual electrochemical measurement data and estimated data were compared using the Dual Extended Kalman Filter (DEKF) algorithm that can estimate SOC and SOH at the same time. The prediction of battery charge state was analyzed by measuring OCV at SOC 5% intervals under 0.2C-rate conditions after the battery cell was fully charged, and the degradation state of the battery was predicted after 50 cycles of aging tests under various C-rate (0.2, 0.3, 0.5, 1.0, 1.5C rate) conditions. It was confirmed that the SOC and SOH estimation errors using DEKF tended to increase as the C-rate increased. It was confirmed that the SOC estimation using DEKF showed less than 6% at 0.2, 0.5, and 1C-rate. In addition, it was confirmed that the SOH estimation results showed good performance within the maximum error of 1.0% and 1.3% at 0.2 and 0.3C-rate, respectively. Also, it was confirmed that the estimation error also increased from 1.5% to 2% as the C-rate increased from 0.5 to 1.5C-rate. However, this result shows that all SOH estimation results using DEKF were excellent within about 2%.