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교수

나종걸(Jonggeol Na) 조교수
Education
  • 2013.3-2018.2 서울대학교 화학생물공학부 공학박사
  • 2009.3-2013.2 서울대학교 화학생물공학부 공학사 (Cum laude)
Career
  • 2020.3-현재 이화여자대학교 조교수
  • 2019.6-2020.2 Carnegie Mellon University 포스닥
  • 2018.3-2019.6 한국과학기술연구원 (KIST) 포스닥
  • 2017.8-2017.12 Massachusetts Institute of Technology 방문연구원
Research Interests
1. Autonomous discovery of non-intuitive process systems designs through artificial intelligence and multiscale simulations
2. Conceptual design of non-traditional processes that improve sustainability in the chemical industry
Selected Publication
1. Na, J., Seo, B., Kim, J., Lee, C. W., Lee, H., Hwang, Y. J., Min, B. K., Lee, D. K., Oh, H.-S.*, Lee, U*, General technoeconomic analysis for electrochemical coproduction coupling carbon dioxide reduction with organic oxidation. Nature Communications (2019), 10, 5193.
Also appeared in Nature Research Device and Materials Engineering Community, 2019. [Editor’s Highlights in Nature Communications]

2. Nguyen, D. L. T.†, Lee, C. W.†, Na, J.†, Kim, M.-C. Tu, N. D. K., Lee, S. Y., Sa, Y. J., Won, D. H., Oh, H.-S., Kim, H., Han, S. S., Min, B. K., Lee, U.*, Hwang Y. J.*, Mass transport control by surface graphene oxide for selective CO production from electrochemical CO2 reduction. ACS Catalysis (2020), in press.

3. Na, J.†, Park, S.†, Bak, J. H., Lee, D., Yoo, Y., Kim, I., Park, J., Lee, U., Lee, J.M.*, Bayesian Parameter Estimation of Aqueous Mineral Carbonation Kinetics. Industrial & Engineering Chemistry Research (2019), 58(19), 8246-8259.

4. Na, J., Kshetrimayum, K. S., Lee, U.*, Han, C.*, Multi-objective optimization of microchannel reactor for Fischer-Tropsch synthesis using computational fluid dynamics and genetic algorithm. Chemical Engineering Journal (2017), 313, 1521-1534.

5. Na, J., Lim, Y., Han, C.*, A modified DIRECT algorithm for hidden constraints in an LNG process optimization. Energy (2017), 126, 488-500.
Lab Overview
My research group focuses on accelerating process systems design and optimization via autonomous discovery of new designs for sustainable chemical processes through artificial intelligence and multiscale simulation.

An initial direction that I work on is to develop a (1) multiscale modeling and simulation methodology to improve the model-based concurrent design in materials and process systems. Using the proposed multiscale simulation, I develop (2) a framework to use artificial intelligence for process design and optimization. My Group apply the proposed methodology to design (3) non-traditional electrochemical processes (e-chemical), continuous pharmaceutical manufacturing, and other advanced manufacturing that improve sustainability of the chemical industry. We also collaborate with experimentalists to verify the intensified designs via pilot plant experimentation.

These short to medium-term projects will provide my group with the skills and tools to pursue my long-term goal:

“to develop process systems engineering tools that will lead to the discovery of non-intuitive designs that are not obtainable with existing techniques.”