• 한국전기화학회:학술대회논문집
• /
• 2001.04a
• /
• pp.32-32
• /
• 2001

• 한국전기화학회:학술대회논문집
• /
• 2000.10a
• /
• pp.30-30
• /
• 2000

• Proceedings of the Materials Research Society of Korea Conference
• /
• 1999.05a
• /
• pp.141-141
• /
• 1999

• Proceedings of the Materials Research Society of Korea Conference
• /
• 1999.05a
• /
• pp.82-82
• /
• 1999

• Proceedings of the Materials Research Society of Korea Conference
• /
• 1996.05a
• /
• pp.126-126
• /
• 1996

• 한국전기화학회:학술대회논문집
• /
• 2001.10a
• /
• pp.9-9
• /
• 2001

• Applied Chemistry for Engineering
• /
• v.5 no.5
• /
• pp.904-909
• /
• 1994

Cure kinetics of DGEBA(diglycidyl ether of bisphenol A)/MDA(4,4'-methylene dianiline)/GN(glutaronitrile) system with and without HQ(hydroquinone) as a catalyst was studied by Kissinger equation and Fractional life method. The activation energy of the system with HQ was somewhat lower and the pre-exponential factor of that was higher by about 30% than those of the system without HQ. As 1.25phr of HQ was added, reaction rates increased about 1.8 times.

• Resources Recycling
• /
• v.11 no.6
• /
• pp.38-46
• /
• 2002

Fundamental investigations were conducted far the recovery process of waste organic solvent by fractional distillation in the aspects of equilibrium and kinetics. Mixture of toluene and xylene, which were both being used in the largest amount as industrial organic solvent, was taken as the artificial waste organic solvent and their distillation behaviors were studied. The purity of recovered solvent was investigated by Cir Chromatography and shown to be in the range of 94～98%. Based upon equilibrium calculations, the changes in the Gibbs free energy, standard enthalpy, and standard entropy for distillation reaction have been estimated. The standard enthalpy changes for toluene and xylene were shown to be 44.833 and 47.044 kJ $mol^{-1}$ respectively, which were similar to their molar heats of evaporation. The activation energies of distillation fur toluene and xylene obtained from kinetic studies were 3.281 and 2.699 kJ $mol^{-1}$ and they were about one tenths of the standard enthalpy changes of distillation reaction. The highness of the purity of recovered organic solvents suggested the possibility that the recovered waste organic sol-vent could partly replace the original solvent.

• Journal of the Korean Chemical Society
• /
• v.37 no.8
• /
• pp.695-701
• /
• 1993

Rate constants of solvolysis of 2-thiophenesulfonyl chloride were determined in aqueous binary mixtures with methanol, ethanol, acetone in water and in methanol. These data are interpreted using the equation of Grunwald-Winstein and Kivinen relationship. Also, kinetic solvent isotope effects in water and in methanol and product selectivities in alcohol-water mixtures were determined. Kinetic solvent isotope effect for hydrolysis of 2-thiopenesulfonyl chloride was 2.24 and 1.47 for methanol and water, respectively. Selectivity values for formation of ester relative to acid in ethanol-water mixtures show maximum S value. From kinetic solvent isotope effect in methanol and water, selectivity data in aqueous alcoholic solvents and solvent effects, it is proposed that the reaction channel favoured in low polarity solvents is general-base catalysis and/or is possibly addition elimination (S$_A$N) reaction pathway and in high polarity solvents iS S$_N$2 reaction mechanism.

• Journal of the Korea Convergence Society
• /
• v.13 no.1
• /
• pp.51-62
• /
• 2022

AI-based speed prediction studies have been conducted quite actively. However, while the importance of explainable AI is emerging, the study of interpreting and reasoning the AI-based speed predictions has not been carried out much. Therefore, in this paper, 'Explainable Deep Graph Neural Network (GNN)' is devised to analyze the speed prediction and assess the nearby road influence for reasoning the critical contributions to a given road situation. The model's output was explained by comparing the differences in output before and after masking the input values of the GNN model. Using TOPIS traffic speed data, we applied our GNN models for the major congested roads in Seoul. We verified our approach through a traffic flow simulation by adjusting the most influential nearby roads' speed and observing the congestion's relief on the road of interest accordingly. This is meaningful in that our approach can be applied to the transportation network and traffic flow can be improved by controlling specific nearby roads based on the inference results.