Yonsei University · Engineering
Professor Jeongdong Kim's research lab specializes in sustainable energy systems and advanced materials for environmental remediation and resource recovery. The lab focuses on innovative processes such as autothermal reforming with integrated cold energy utilization, carbon-free lithium-ion battery recycling using hydrogen roasting and CO2 capture, and biocatalytic conversion of waste biomass using engineered enzymes. Key research directions include energy-efficient hydrogen production, circular economy approaches in battery recycling, and microbial enzyme applications for degrading recalcitrant organic wastes like keratin and xylan. The lab integrates chemical engineering, biotechnology, and environmental systems to develop low-carbon, resource-efficient technologies.
Figures are computed from collected data and may differ slightly.
The autothermal reforming (ATR) process for hydrogen production saves considerable energy for the reaction compared with endothermic steam methane reforming (SMR). However, it requires a supply of pure oxygen, for which an air separation unit (ASU) is needed; this hinders the adoption of ATR in industrial applications because of both the high capital and operating costs. At the same time, in liquefied natural gas (LNG) regasification terminals, the cold energy from the regasification process is
In the lithium-ion battery (LIB) recycling process, the roasting step decomposes the complex cathode material into metal oxides before leaching and precipitation. Hydrogen gas is a potential candidate among various roasting agents because of its rapid roasting time and zero CO2 emission. However, additional flue gas emission is unavoidable on the industrial scale to meet the roasting temperature and further crystallization of the produced LiOH slurry. This study proposed and simulated a carbon-f
The growing use of lithium nickel manganese cobalt oxide (NCM) batteries has necessitated increased recovery of cathode materials for sustainable battery recycling given the limited metal source, and to mitigate the negative environmental impact of battery disposal. Acid leaching and the use of precipitants are essential for selective metal extraction in the recycling process. However, the excessive use of chemicals degrades the economic performance of the recycling process. In this study, we pr
oC. No relationship existed between the enzyme yield and increase of biomass. Enzyme production was suppressed by exogenous sugars in descending order arabinose>maltose>mannose>fructose. But glucose did not influence the enzyme activity. The keratinolytic enzyme released by the fungus demonstrated the ability to decompose keratin substrates as chicken feather when exogenous glucose was present. The keratinolytic activity was inhibited by HgCl 2 and serine-protease inhibitors such as phenymethyls
Extracellular keratinase isolated from Aspergillus flavus K-03 was immobilized on calcium alginate. The properties and reaction activities of free and immobilized keratinase with calcium alginate were characterized. The immobilized keratinase showed proteolytic activity against soluble azo-casein and azo-keratin, and insoluble feather keratin. Heat stability and pH tolerance of keratinase were greatly enhanced by immobilization. It also displayed a higher level of heat stability and an increased
Five types of agricultural wastes were used for the production of xylanolytic enzyme by Aspergillus flavus K-03. All wastes materials supported high levels of xylanase and β-xylosidase production. A high level of proteolytic activity was observed in barley and rice bran cultures, while only a weak proteolytic activity was detected in corn cob, barley and rice straw cultures. Maximum production of xylanase was achieved in basal liquid medium containing rice barn as carbon source for 5 days of cul
This research explores the deep reinforcement learning (DRL) based planning strategies of power-to-X (PtX) systems under uncertainties of renewable and price through a detailed case study and comparative analysis of system planning. A DRL-based hourly planning model is proposed to minimize operational costs for a PtX system, incorporating a hybrid energy storage system. The model employs a grid-penalized reward function to manage grid power usage while accounting for temporal uncertainties in re
This study proposes a multiobjective optimization for a hybrid hydrogen-battery energy storage system based on hierarchical control and flexible integration for green methanol processes. The optimized energy management strategy aims to comprehensively enhance the economic viability, safety, and resilience of the hybrid system. The optimal solution was identified by nondominated sorting genetic algorithm II (NSGA-II) and the method of criteria importance through intercriteria correlation with the
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