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Seung-Mo Kim

Researcher at Chungbuk National University

Publications -  5
Citations -  38

Seung-Mo Kim is an academic researcher from Chungbuk National University. The author has contributed to research in topics: Aqueous solution & Chemistry. The author has an hindex of 2, co-authored 3 publications receiving 5 citations.

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Amine blending optimization for maximizing CO2 absorption capacity in a diisopropanolamine – methyldiethanolamine – H2O system using the electrolyte UNIQUAC model

TL;DR: In this article, experimental data on CO2 solubility in diisopropanolamine (DIPA) and methyldiethanolamine (MDEA) blended aqueous solutions were measured at different amine blending ratios and working temperatures.
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Effect of Blending Ratio and Temperature on CO2 Solubility in Blended Aqueous Solution of Monoethanolamine and 2-Amino-2-methyl-propanol: Experimental and Modeling Study Using the Electrolyte Nonrandom Two-Liquid Model.

TL;DR: Using the abovementioned thermodynamic models, the partial pressures of CO2 in the gas phase, mole fractions of all components in the liquid phase, pH variations, heats of absorption, and cyclic capacities ofCO2 according to the absorption/desorption temperature and the blending ratio of MEA/AMP were estimated.
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CO2 absorption mechanism in aqueous ternary solutions of alkanolamines: Experimental and thermodynamic modeling approaches

TL;DR: In this article, the absorption mechanism of CO2 in an aqueous solution containing three alkanolamines was analyzed experimentally and theoretically, and the vapor-liquid equilibrium of a CO2-monoethanolamine (MEA)-diisopropanolamines (DIPA)-2-amino-2-methyl-propanol (AMP) and H2O system was evaluated experimentally over a wide temperature range (323.15-393.15 K).
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Comparative assessment and multi-objective optimization for the gray and blue ammonia synthesis processes: Energy, Economic and Environmental (3E) analysis

TL;DR: In this article , a blue ammonia process was designed by incorporating the carbon capture and storage process into the gray ammonia process, and both processes were optimized by genetic algorithm based multi-objective optimization (MOO) technique for the 3E features, SEC, LCOA, and GWP.