• Korean Journal of Materials Research
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• v.19 no.10
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• pp.544-549
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• 2009

Activated carbon (AC) with very large surface area has high capacitance per weight. However, such activation methods tend to suffer from low yields, below 50%, and are low in electrode density and capacitance per volume. Carbon NanoFibers (CNFs) had high surface area polarizability, high electrical conductivity and chemical stability, as well as extremely high mechanical strength and modulus, which make them an important material for electrochemical capacitors. The electrochemical properties of immobilized CNF electrodes were studied for use as in electrical double layer capacitor (EDLC) applications. Immobilized CNFs on Ni foam grown by thermal chemical vapor deposition (CVD) were successfully fabricated. CNFs had a uniform diameter range from 50 to 60 nm. Surface area was 56 m$^2$/g. CNF electrodes were compared with AC and multi wall carbon nanotube (MWNT) electrodes. The electrochemical performance of the various electrodes was examined with aqueous electrolyte of 2M KOH. Equivalent series resistance (ESR) of the CNF electrodes was lower than that of AC and MWNT electrodes. The specific capacitance of 47.5 F/g of the CNF electrodes was achieved with discharge current density of 1 mA/cm$^2$.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.2
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• pp.193-200
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• 2011

A BOR(Boil-Off Rate) prediction model for the NO96 membrane-type LNG insulation containment filled with superlite powders during laden voyage is presented in this paper. Finite element model for the unsteady-state heat transfer analysis is constructed by considering the air and water conditions and by employing the homogenization method to simplify the complex insulation material composition. BOR is evaluated in terms of the total amount of heat invaded into LNGCC and its variation to the major variables is investigated by the parametric heat transfer analysis. Based upon the parametric results, a BOR prediction model which is in function of the LNG tank size, the insulation layer thickness and the powder thermal conductivity is derived. Through the verification experiment, the accuracy of the derived prediction model is justified such that the maximum relative difference is less than 1% when compared with the direct numerical estimation using the FEM analysis.