Jonggeol Na Assistant Professor

Department of Chemical Engineering and Materials Science/

나종걸 프로필 사진

				
  • Asan Engineering Building #527
  • 0232774202
  • Office hours
    • 목요일 14:00-18:00
Research Record
  • A chemically inspired convolutional neural network using electronic structure representation JOURNAL OF MATERIALS CHEMISTRY A, 2023, v.11 no.19, 0
    SCIE Scopus dColl.
  • Comparison of Derivative-Free Optimization: Energy Optimization of Steam Methane Reforming Process INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2023, v.2023, 8868540
    SCIE Scopus dColl.
  • Explainable Artificial Intelligence (XAI) Surrogate Models for Chemical Process Design and Analysis; [화학 공정 설계 및 분석을 위한 설명 가능한 인공지능 대안 모델] Korean Chemical Engineering Research, 2023, v.61 no.4, 542-549
    Scopus KCI dColl.
  • Green hydrogen and sustainable development – A social LCA perspective highlighting social hotspots and geopolitical implications of the future hydrogen economy Journal of Cleaner Production, 2023, v.395, 136438
    SCIE Scopus dColl.
  • Microkinetic study of syngas conversion to dimethyl ether over a bifunctional catalyst: CZA/FER Korean Journal of Chemical Engineering, 2023, v.40 no.11, 2632-2645
    SCIE Scopus KCI dColl.
  • Multi-objective optimization of explosive waste treatment process considering environment via Bayesian active learning Engineering Applications of Artificial Intelligence, 2023, v.117, 105463
    SCIE Scopus dColl.
  • Optimal planning of hybrid energy storage systems using curtailed renewable energy through deep reinforcement learning Energy, 2023, v.284, 128623
    SCIE Scopus dColl.
  • A stochastic agent-based cooperative scheduling model of a multi-vector microgrid including electricity, hydrogen, and gas sectors JOURNAL OF POWER SOURCES, 2022, v.546, 231989
    SCIE Scopus dColl.
  • Adversarial Autoencoder Based Feature Learning for Fault Detection in Industrial Processes IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, v.18 no.2, 827-834
    SCIE Scopus dColl.
  • CFD modeling for the prediction of molecular weight distribution in the LDPE autoclave reactor: Effects of non-ideal mixing Chemical Engineering Journal, 2022, v.427, 131829
    SCIE Scopus dColl.
  • Data-driven robust optimization for minimum nitrogen oxide emission under process uncertainty Chemical Engineering Journal, 2022, v.428, 130971
    SCIE Scopus dColl.
  • Deep Neural Network-based Optimization Framework for Safety Evacuation Route during Toxic Gas Leak Incidents Reliability Engineering and System Safety, 2022, v.218, 108102
    SCIE Scopus dColl.
  • Microenvironments of Cu catalysts in zero-gap membrane electrode assembly for efficient CO2 electrolysis to C2+ products JOURNAL OF MATERIALS CHEMISTRY A, 2022, v.10 no.19, 10363-10372
    SCIE Scopus dColl.
  • Origin of Hydrogen Incorporated into Ethylene during Electrochemical CO2 Reduction in Membrane Electrode Assembly ACS Energy Letters, 2022, v.7 no.3, 939-945
    SCIE Scopus dColl.
  • Physics-informed deep learning for data-driven solutions of computational fluid dynamics Korean Journal of Chemical Engineering, 2022, v.39 no.3, 515-528
    SCIE Scopus KCI dColl.
  • Bayesian Optimization of Semicontinuous Carbonation Process Operation Recipe INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2021, v.60 no.27, 9871-9884
    SCIE Scopus dColl.
  • Bayesian optimization of industrial-scale toluene diisocyanate liquid-phase jet reactor with 3-D computational fluid dynamics model Journal of Industrial and Engineering Chemistry, 2021, v.98, 327-339
    SCIE Scopus KCI dColl.
  • Clustered Manifold Approximation and Projection for Semisupervised Fault Diagnosis and Process Monitoring INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2021, v.60 no.26, 9521-9531
    SCIE Scopus dColl.
  • Design methodology for mass transfer-enhanced large-scale electrochemical reactor for CO2 reduction Chemical Engineering Journal, 2021, v.424, 130265
    SCIE Scopus dColl.
  • Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models Computers and Chemical Engineering, 2021, v.151, 107322
    SCIE Scopus dColl.
  • Efficient Discovery of Active, Selective, and Stable Catalysts for Electrochemical H2O2 Synthesis through Active Motif Screening ACS CATALYSIS, 2021, v.11 no.5, 2483-2491
    SCIE Scopus dColl.
  • Electrocatalytic Reduction of Low Concentrations of CO2 Gas in a Membrane Electrode Assembly Electrolyzer ACS ENERGY LETTERS, 2021, v.6 no.10, 3488-3495
    SCIE Scopus dColl.
  • Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2021, v.61 no.12, 5804-5814
    SCIE Scopus dColl.
  • Learning the properties of a water-lean amine solvent from carbon capture pilot experiments Applied Energy, 2021 , 116213
    SCIE Scopus dColl.
  • Machine learning-based utilization of renewable power curtailments under uncertainty by planning of hydrogen systems and battery storages JOURNAL OF ENERGY STORAGE, 2021, v.41, 103010
    SCIE Scopus dColl.
  • Towards the large-scale electrochemical reduction of carbon dioxide Catalysts, 2021 , 1-30
    SCIE Scopus dColl.
  • Catalyst-electrolyte interface chemistry for electrochemical CO(2)reduction CHEMICAL SOCIETY REVIEWS, 2020, v.49 no.18, 6632-6665
    SCIE Scopus dColl.
  • Data-driven pilot optimization for electrochemical CO mass production JOURNAL OF MATERIALS CHEMISTRY A, 2020, v.8 no.33, 16943-16950
    SCIE Scopus dColl.
  • In silicodiscovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2020, v.22 no.35, 19454-19458
    SCIE Scopus dColl.
  • Mass Transport Control by Surface Graphene Oxide for Selective CO Production from Electrochemical CO2 Reduction ACS CATALYSIS, 2020, v.10 no.5, 3222-3231
    SCIE Scopus dColl.
  • Toward the practical application of direct CO2 hydrogenation technology for methanol production International Journal of Energy Research, 2020, v.44 no.11, 8781-8798
    SCIE Scopus dColl.
  • An experimental based optimization of a novel water lean amine solvent for post combustion CO2 capture process APPLIED ENERGY, 2019, v.248, 174-184
    SCIE Scopus dColl.
  • Bayesian Inference of Aqueous Mineral Carbonation Kinetics for Carbon Capture and Utilization INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, v.58 no.19, 8246-8259
    SCIE Scopus dColl.
  • Development of surrogate model using CFD and deep neural networks to optimize gas detector layout KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2019, v.36 no.3, 325-332
    SCIE Scopus KCI dColl.
  • General technoeconomic analysis for electrochemical coproduction coupling carbon dioxide reduction with organic oxidation NATURE COMMUNICATIONS, 2019, v.10, 5193
    SCIE Scopus dColl.
  • Multicompartment Model of an Ethylene-Vinyl Acetate Autoclave Reactor: A Combined Computational Fluid Dynamics and Polymerization Kinetics Model INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, v.58 no.36, 16459-16471
    SCIE Scopus dColl.
  • [학술지논문] A chemically inspired convolutional neural network using electronic structure representation JOURNAL OF MATERIALS CHEMISTRY A, 2023, v.11 no.19 , 10184-10184
    SCIE
  • [학술지논문] Comparison of Derivative-Free Optimization: Energy Optimization of Steam Methane Reforming Process INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2023, v.2023 no.1 , 1-20
    SCIE
  • [학술지논문] Explainable Artificial Intelligence for Fault Diagnosis of Industrial Processes IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, v.1 no.1 , 1-1
    SCIE
  • [학술지논문] Green hydrogen and sustainable development-A social LCA perspective highlighting social hotspots and geopolitical implications of the future hydrogen economy JOURNAL OF CLEANER PRODUCTION, 2023, v.395 no.1 , 136438-136438
    SCIE
  • [학술지논문] Microkinetic study of syngas conversion to dimethyl ether over a bifunctional catalyst: CZA/FER KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2023, v.40 no.11 , 2632-2645
    SCIE
  • [학술지논문] Multi-objective optimization of explosive waste treatment process considering environment via Bayesian active learning ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2023, v.117 no.0 , 105463-105463
    SCIE
  • [학술지논문] Optimal planning of hybrid energy storage systems using curtailed renewable energy through deep reinforcement learning ENERGY, 2023, v.284 no.1 , 128623-128623
    SCIE
  • [학술지논문] Techno-economic analysis and life-cycle assessment of the electrochemical conversion process with captured CO2 in an amine-based solvent GREEN CHEMISTRY, 2023, v.25 no.24 , 10398-10414
    SCIE
  • [학술지논문] Adversarial Autoencoder Based Feature Learning for Fault Detection in Industrial Processes IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2022, v.18 no.2 , 827-834
    SCIE
  • [학술지논문] CFD modeling for the prediction of molecular weight distribution in the LDPE autoclave reactor: Effects of non-ideal mixing CHEMICAL ENGINEERING JOURNAL, 2022, v.427 no.0 , 131829-131829
    SCI
  • [학술지논문] Data-driven robust optimization for minimum nitrogen oxide emission under process uncertainty CHEMICAL ENGINEERING JOURNAL, 2022, v.428 no.0 , 130971-130971
    SCI
  • [학술지논문] Deep Neural Network-based Optimization Framework for Safety Evacuation Route during Toxic Gas Leak Incidents RELIABILITY ENGINEERING & SYSTEM SAFETY, 2022, v.218 no.0 , 108102-108102
    SCI
  • [학술지논문] Microenvironments of Cu catalysts in zero-gap membrane electrode assembly for efficient CO2 electrolysis to C2+ products JOURNAL OF MATERIALS CHEMISTRY A, 2022, v.10 no.19 , 10363-10372
    SCI
  • [학술지논문] Origin of Hydrogen Incorporated into Ethylene during Electrochemical CO2 Reduction in Membrane Electrode Assembly ACS ENERGY LETTERS, 2022, v.7 no.3 , 939-945
    SCIE
  • [학술지논문] Physics-informed deep learning for data-driven solutions of computational fluid dynamics KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2022, v.39 no.3 , 515-528
    SCIE
  • [학술지논문] Bayesian Optimization of Semicontinuous Carbonation Process Operation Recipe INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2021, v.60 no.27 , 9871-9884
    SCI
  • [학술지논문] Bayesian optimization of industrial-scale toluene diisocyanate liquid-phase jet reactor with 3-D computational fluid dynamics model JOURNAL OF INDUSTRIAL AND ENGINEERING CHEMISTRY, 2021, v.98 no.0 , 327-339
    SCIE
  • [학술지논문] Clustered Manifold Approximation and Projection for Semisupervised Fault Diagnosis and Process Monitoring INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2021, v.60 no.26 , 9521-9531
    SCI
  • [학술지논문] Design methodology for mass transfer-enhanced large-scale electrochemical reactor for CO2 reduction CHEMICAL ENGINEERING JOURNAL, 2021, v.424 no.0 , 130265-130265
    SCI
  • [학술지논문] Efficient Bayesian inference using adversarial machine learning and low-complexity surrogate models COMPUTERS & CHEMICAL ENGINEERING, 2021, v.151 no.0 , 107322-107322
    SCI
  • [학술지논문] Efficient Discovery of Active, Selective, and Stable Catalysts for Electrochemical H2O2 Synthesis through Active Motif Screening ACS CATALYSIS, 2021, v.11 no.5 , 2483-2491
    SCIE
  • [학술지논문] Electrocatalytic Reduction of Low Concentrations of CO2 Gas in a Membrane Electrode Assembly Electrolyzer ACS ENERGY LETTERS, 2021, v.6 no.10 , 3488-3495
    SCIE
  • [학술지논문] Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2021, v.61 no.12 , 5804-5814
    SCI
  • [학술지논문] Learning the properties of a water-lean amine solvent from carbon capture pilot experiments APPLIED ENERGY, 2021, v.283 no.0 , 116213-116213
    SCI
  • [학술지논문] Machine learning-based utilization of renewable power curtailments under uncertainty by planning of hydrogen systems and battery storages Journal of Energy Storage, 2021, v.41 no.1 , 103010-103010
    SCIE
  • [학술지논문] Towards the Large-Scale Electrochemical Reduction of Carbon Dioxide CATALYSTS, 2021, v.11 no.2 , 253-253
    SCIE
  • [학술지논문] Catalyst-electrolyte interface chemistry for electrochemical CO(2)reduction CHEMICAL SOCIETY REVIEWS, 2020, v.49 no.18 , 6632-6665
    SCI
  • [학술지논문] Data-driven pilot optimization for electrochemical CO mass production JOURNAL OF MATERIALS CHEMISTRY A, 2020, v.8 no.33 , 16943-16950
    SCI
  • [학술지논문] In silicodiscovery of active, stable, CO-tolerant and cost-effective electrocatalysts for hydrogen evolution and oxidation PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2020, v.22 no.35 , 19454-19458
    SCI
  • [학술지논문] Mass Transport Control by Surface Graphene Oxide for Selective CO Production from Electrochemical CO2 Reduction ACS CATALYSIS, 2020, v.10 no.5 , 3222-3231
    SCIE
  • [학술지논문] Toward the practical application of direct CO2 hydrogenation technology for methanol production INTERNATIONAL JOURNAL OF ENERGY RESEARCH, 2020, v.44 no.11 , 8781-8798
    SCIE
  • [학술지논문] An experimental based optimization of a novel water lean amine solvent for post combustion CO2 capture process APPLIED ENERGY, 2019, v.248 no.0 , 174-184
    SCI
  • [학술지논문] Bayesian Inference of Aqueous Mineral Carbonation Kinetics for Carbon Capture and Utilization INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, v.58 no.19 , 8246-8259
    SCI
  • [학술지논문] Development of surrogate model using CFD and deep neural networks to optimize gas detector layout KOREAN JOURNAL OF CHEMICAL ENGINEERING, 2019, v.36 no.3 , 325-332
    SCIE
  • [학술지논문] General technoeconomic analysis for electrochemical coproduction coupling carbon dioxide reduction with organic oxidation NATURE COMMUNICATIONS, 2019, v.10 no.0 , 5193-5193
    SCI
  • [학술지논문] Multicompartment Model of an Ethylene-Vinyl Acetate Autoclave Reactor: A Combined Computational Fluid Dynamics and Polymerization Kinetics Model INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2019, v.58 no.36 , 16459-16471
    SCI
Courses
  • 2024-1st

    • Chemical Engineering Lab Ⅱ

      • Subject No 37516Class No 02
      • 3Year ( 3Credit , 4.5Hour) Thu 6~8 (ENG )
    • Chemical Process Design

      • Subject No 37525Class No 01
      • 4Year ( 3Credit , 3Hour) Mon 4~4 (ESEA) , Thu 5~5 (CH)
    • Chemical Engineering Mathematics

      • Subject No 38776Class No 01
      • 2Year ( 3Credit , 3Hour) Mon 2~2 (ENG A) , Thu 3~3 (101)
    • Advanced Convergent Materials for System Healthcare

      • Subject No G18278Class No 01
      • Year ( 3Credit , 3Hour) Tue 6~7 (ENG )
  • 2023-2nd

    • Process Control Systems

    • Systems Science Machine Learning

      • Subject No G18280Class No 01
      • Year ( 3Credit , 3Hour) Thu 4~5 (ENG )
  • 2023-1st

    • Chemical Process Design

    • Chemical Engineering Mathematics

    • Introduction to System Health 강의 계획서 상세보기

      • Subject No G18067Class No 01
      • Year ( 3Credit , 3Hour) Thu 7~8
    • Advanced convergent materials for system healthcare

      • Subject No G18278Class No 01
      • Year ( 3Credit , 3Hour) Thu 3~4 (ENG )
    • Introduction to System Health

      • Subject No G18441Class No 01
      • Year ( 3Credit , 3Hour) Thu 7~8
  • 2022-2nd

    • Chemical Engineering Lab I

      • Subject No 37513Class No 02
      • 2Year ( 3Credit , 4.5Hour) Tue 5~7 (ENG A407-1)
    • Process Control Systems

      • Subject No 37520Class No 01
      • 3Year ( 3Credit , 3Hour) Wed 3~3 (ENG ) , Fri 2~2 (159)
    • Systems Science Machine Learning

      • Subject No G18280Class No 01
      • Year ( 3Credit , 3Hour) Fri 4~5 (ENG )
  • 2022-1st

    • Chemical Process Design

      • Subject No 37525Class No 01
      • 4Year ( 3Credit , 3Hour) Mon 2~2 (ENG ) , Thu 3~3 (161)
    • Chemical Engineering Mathematics

      • Subject No 38776Class No 01
      • 2Year ( 3Credit , 3Hour) Mon 5~5 (ENG A) , Wed 4~4 (101)
    • Introduction to System Health

      • Subject No G18067Class No 01
      • Year ( 3Credit , 3Hour) Thu 7~8
  • 2021-2nd

    • Process Control Systems

      • Subject No 37520Class No 01
      • 3Year ( 3Credit , 3Hour) Wed 3~3 , Fri 2~2
    • Systems Science Machine Learning

      • Subject No G18081Class No 01
      • Year ( 3Credit , 3Hour) Thu 5~6
  • 2021-1st

    • Chemical Process Design

      • Subject No 37525Class No 01
      • 4Year ( 3Credit , 3Hour) Mon 3~3 , Wed 2~2
    • Chemical Engineering Mathematics

      • Subject No 38776Class No 01
      • 2Year ( 3Credit , 3Hour) Tue 2~2 , Fri 3~3
    • Introduction to System Health

      • Subject No G18067Class No 01
      • Year ( 3Credit , 3Hour) Thu 7~8
Academic Background

Seoul Nat'l Univ. 공학박사(화학생물공학부)

Seoul Nat'l Univ. 공학사(화학생물공학부)

Work Experience

Carnegie Mellon University 2019-07-01 ~ 2020-02-29

한국과학기술연구원(KIST) 2018-03-01 ~ 2019-06-21

Massachusetts Institute of Technology 2017-08-21 ~ 2017-12-08