AXIS Lab mark AXIS Lab
Publications 논문

Research Achievements 연구 실적

CV (PDF) 이력서 (PDF) Google Scholar ORCID
01
Published 게재

Journal articles 논문

  2. Oh, S., Roh, J., Park, H., Lee, D., Joo, C. et al.

    Enhancing catalyst performance prediction with hybrid quantum neural networks: a comparative study on data consistency variation

    ACS Sustainable Chemistry & Engineering

  3. Kim, M., Joo, C. co-first 공동 제1저자 , Lim, J. et al.

    Novel inverse predictive system integrated with industrial lubricant information

    Engineering Applications of Artificial Intelligence

  5. Park, H., Joo, C. , Lim, J. et al.

    Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data

    Engineering Applications of Artificial Intelligence

  6. Joo, C. , Lee, J., Lim, J. et al.

    A genetic algorithm-based optimal selection and blending ratio of plastic waste for maximizing economic potential

    Process Safety and Environmental Protection

  8. Ga, S., An, N., Lee, G., Joo, C. et al.

    Multidisciplinary high-throughput screening of metal–organic framework for ammonia-based green hydrogen production

    Renewable and Sustainable Energy Reviews

  9. Roh, J., Oh, S., Lee, D., Joo, C. et al.

    Hybrid quantum neural network model with catalyst experimental validation: application for the dry reforming of methane

    ACS Sustainable Chemistry & Engineering

  14. Ga, S., An, N., Joo, C. co-first 공동 제1저자 et al.

    pyAPEP: an all-in-one software package for the automated preparation of adsorption process simulations

    Computer Physics Communications

  15. Jeong, S., Joo, C. co-first 공동 제1저자 , Lim, J., Cho, H. et al.

    A novel graph-based missing values imputation method for industrial lubricant data

    Computers in Industry

  16. Kim, J., Joo, C. co-first 공동 제1저자 , Kim, M., An, N. et al.

    Multi-objective robust optimization of profit for a naphtha cracking furnace considering uncertainties in the feed composition

    Expert Systems with Applications

  19. Lee, J., Joo, C. co-first 공동 제1저자 , Cho, H., Kim, Y. et al.

    Design of multistage fixed bed reactors for SMR hydrogen production based on the intrinsic kinetics of Ru-based catalysts

    Energy Conversion and Management

  20. Joo, C. , Park, H., Lim, J., Cho, H. et al.

    Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

    International Journal of Intelligent Systems

Conference presentations 학회 발표

Selected oral presentations 주요 구두 발표

Temperature-conditioned data-driven modeling for organic solubility prediction
The Society of Adhesion and Interface, Korea 한국접착및계면학회, 한국

Chemical Property-Guided Neural Networks for Naphtha Composition Prediction
IEEE INDIN, Germany IEEE INDIN, Germany

Data-Driven Modeling to Predict the Physical Properties of the Lubricant
AIChE Annual Meeting, Phoenix, USA AIChE Annual Meeting, Phoenix, USA

Intellectual property 지식재산권

Patent applications 특허 출원

Three patent applications covering blended absorbent prediction, hybrid quantum neural networks for catalyst performance, and machine-learning-based lubricant recipe recommendation. 혼합 흡수제 성능 예측, 촉매 성능 예측용 하이브리드 양자 신경망, 머신러닝 기반 윤활유 배합 추천에 관한 3건의 특허를 출원했습니다.