HANYANG UNIVERSITY

Member

Full-time Faculty

Jin-Kuk Kim
Hanyang University Chemical Engineering Jin-Kuk Kim Professor
Major

Computer-aided process design, integration and optimization

Data-driven process engineering with AI/Machine Learning and Analytics

Carbon capture and utilization

Clean hydrogen production and utilization

Electrification and renewable energy systems

TEA (Techno-economic analysis) & LCA (Life cycle assessment)

Subject

Numerical Analysis(Undergraduate)

Chemical Plant Design(Undergraduate)

Plant Energy Engineering(Graduate)

Smart Chemical Plant Design(Graduate)

Energy Systems Engineering(Graduate)

Theory and Applications of Chemical Process Optimization(Graduate)

Education

UMIST (University of Manchester Institute of Science and Technology), Manchester, UK (Ph.D. Process Integration)

Hanyang University, Seoul, South Korea (M.S. Chemical Engineering)

Hanyang University, Seoul, South Korea (B.S. Chemical Engineering)

Career

Professor, Chemical Engineering, Hanyang University, Korea

Lecturer/Senior Lecturer, Chemical Engineering & Analytical Sciences, The University of Manchester , Manchester, UK

Research

Kim, S.-J., Song, Y., Binns , M., Yeo, J.-G. & Kim, J.-K. Process-integrated optimization and techno-economic analysis of membrane system for biogas upgrading: Effect of membrane performance from an economic perspective. Journal of Membrane Science. 713, 123286 (2025).

Song, Y. et al. Process design and optimization of membrane-based CO2 capture process with experimental performance data for a steam methane reforming hydrogen plant and a coal-fired power plant. Journal of Cleaner Production. 475, 143643 (2024).

Lim, M. K. et al. Multi-objective optimization of ann-based vacuum pressure swing adsorption process for ethane and ethylene separation. Journal of Industrial and Engineering Chemistry; 10.1016/j.jiec.2024.08.025 (2024).

Kim, S. H., Ko, H., Lee, M. R., Kim, J.-K. & Suh, Y.-W. Hydroprocessing characteristics of palm fatty acid distillate in palm oil into low-carbon biofuel. Fuel . 364, 131058 (2024).

Lee, S. & Kim, J.-K. Sub-ambient membrane process for CO2 removal in the Industrial Sector: Iron and steel, cement, and refinery. Journal of Membrane Science. 686, 122018 (2023).

Kim, J.-K. et al. Optimization models for the cost-effective design and operation of renewable-integrated energy systems. Renewable and Sustainable Energy Reviews. 183, 113429 (2023).

Lee, J., Park, H., Yun, S. & Kim, J.-K. Energetic and economic analysis of absorption-based CO2 Capture Integrated Hydrogen Production Processes – Retrofit Perspective. Journal of Cleaner Production. 405, 136955 (2023).

Shahid, M. Z. & Kim, J.-K. Design and economic evaluation of a novel amine-based CO2 capture process for SMR-based hydrogen production plants. Journal of Cleaner Production. 402, 136704 (2023).

Kim, S., Jang, M.-G. & Kim, J.-K. Process design and optimization of single mixed-refrigerant processes with the application of deep reinforcement learning. Applied Thermal Engineering. 223, 120038 (2023).

Park, H., Kim, J.-K. & Yi, S. C. Optimization of site utility systems for Renewable Energy Integration. Energy. 269, 126799 (2023).

Lab
Laboratory for Energy and Environmental Systems Engineering (LEESE)

The Laboratory for Energy and Environmental Systems Engineering (LEESE) conducts cutting-edge research aimed at enhancing production efficiency, energy savings, economic viability, and environmental sustainability across chemical, energy, and environmental processes. To achieve these goals, we develop mathematical models of complex process systems and perform its computational simulations and optimization, assessing system performance, environmental impact, and economic feasibility. We further integrate AI- and machine learning–based intelligent design methodologies with data-driven and system-wide analysis techniques, leading to cost-effective and sustainable process designs. This carbon-neutral process system research is applied to clean hydrogen and ammonia production, electrification of the chemical industry, carbon-free power generation, Carbon Capture and Utilization (CCU), Direct Air Capture (DAC), and renewable energy–based microgrid systems. Through these efforts, we aim to determine optimal design conditions and to propose optimal pathways for minimizing carbon emission, improving energy efficiency, and enhancing economic competitiveness.