Showing results 1 to 19 of 19
Applications of machine learning in metal-organic frameworks Chong, Sanggyu; Lee, Sangwon; Kim, Baekjun; Kim, Jihan, COORDINATION CHEMISTRY REVIEWS, v.423, pp.213487, 2020-11 |
Computational Analysis of Linker Defective Metal-Organic Frameworks for Membrane Separation Applications Kim, Hoeyeon; Lee, Sangwon; Kim, Jihan, LANGMUIR, v.35, no.11, pp.3917 - 3924, 2019-03 |
Computational Design of Metal-Organic Frameworks with Unprecedented High Hydrogen Working Capacity and High Synthesizability Park, Junkil; Lim, Yunsung; Lee, Sangwon; Kim, Jihan, CHEMISTRY OF MATERIALS, v.35, no.1, pp.9 - 16, 2023-01 |
Computational Screening of Trillions of Metal-Organic Frameworks for High-Performance Methane Storage Lee, Sangwon; Kim, Baekjun; Cho, Hyun; Lee, Hooseung; Lee, Sarah Yunmi; Cho, Eun Seon; Kim, Jihan, ACS APPLIED MATERIALS & INTERFACES, v.13, no.20, pp.23647 - 23654, 2021-05 |
Connection of molecular and process simulation for adsorbent evaluation and its improvement with machine learning method Ga, Seongbin; Lee, Sangwon; Lee, Jay Hyung, The 8th Korea CCUS International Conference, KCRC, 2018-01-25 |
Deep learning-based initial guess for minimum energy path calculations Park, Hyunsoo; Lee, Sangwon; Kim, Jihan, KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.38, no.2, pp.406 - 410, 2021-02 |
Finding Hidden Signals in Chemical Sensors Using Deep Learning Cho, Soo-Yeon; Lee, Youhan; Lee, Sangwon; Kang, Hohyung; Kim, Jaehoon; Choi, Junghoon; Ryu, Jin; et al, ANALYTICAL CHEMISTRY, v.92, no.9, pp.6529 - 6537, 2020-05 |
Finely tuned inverse design of metal-organic frameworks with user-desired Xe/Kr selectivity Lim, Yunsung; Park, Junkil; Lee, Sangwon; Kim, Jihan, JOURNAL OF MATERIALS CHEMISTRY A, v.9, no.37, pp.21175 - 21183, 2021-10 |
General Adsorbent Library and Evaluation (GALE) Software Tool for CO2 Capture Ga, Seongbin; Lee, Sangwon; Kim, Jihan; Lee, Jay Hyung, 19th AIChE Annual Meeting, AIChE, 2019-11-10 |
Inverse design of porous materials using artificial neural networks![]() Kim, Baekjun; Lee, Sangwon; Kim, Jihan, SCIENCE ADVANCES, v.6, no.1, 2020-01 |
Isotherm Model for S-Shaped Data for Process Modeling and Its Model Reduction with Machine Learning Techniques Ga, Seongbin; Lee, Sangwon; Kim, Jihan; Lee, Jay Hyung, 8th International Symposium on Design, Operation and Control of Chemical Processes, PSE, 2019-01-14 |
Machine learning-based discovery of molecules, crystals, and composites: A perspective review Lee, Sangwon; Byun, Haeun; Cheon, Mujin; Kim, Jihan; Lee, Jay Hyung, KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.38, no.10, pp.1971 - 1982, 2021-10 |
Nanoporous materials discovery for energy and environmental applications using machine learning = 기계 학습을 이용한 에너지 및 환경 응용 목적의 다공성 나노 재료 개발link Lee, Sangwon; Kim, Jihan; et al, 한국과학기술원, 2020 |
New model for S-shaped isotherm data and its application to process modeling using IAST Ga, Seongbin; Lee, Sangwon; Park, Gwanhong; Kim, Jihan; Realff, Matthew; Lee, Jay Hyung, CHEMICAL ENGINEERING JOURNAL, v.420, no.2, pp.127580, 2021-09 |
Pore site partition by Size-Matching Ligand Insertion of Metal-Organic Frameworks for CO2 Capture in the Presence of Water Suh, Bonglim; Kim, Jihan; Lee, Sangwon, The 11th International Conference on Separation Science and Technology(ICSST 17), 한국화학공학회, 2017-11-10 |
Predicting performance limits of methane gas storage in zeolites with an artificial neural network Lee, Sangwon; Kim, Baekjun; Kim, Jihan, JOURNAL OF MATERIALS CHEMISTRY A, v.7, no.6, pp.2709 - 2716, 2019-02 |
Sensitivity Analysis of CO2 Capture Materials in Post-Combustion Flue Gas Lee, Sangwon; Kim, Jihan, ChemIndix 2016, ChemIndix, 2016-11-22 |
Size-Matching Ligand Insertion in MOF-74 for Enhanced CO2 Capture under Humid Conditions Suh, Bong Lim; Lee, Sangwon; Kim, Jihan, JOURNAL OF PHYSICAL CHEMISTRY C, v.121, no.44, pp.24444 - 24451, 2017-11 |
User-friendly graphical user interface software for ideal adsorbed solution theory calculations Lee, Sangwon; Lee, Jay Hyung; Kim, Jihan, KOREAN JOURNAL OF CHEMICAL ENGINEERING, v.35, no.1, pp.214 - 221, 2018-01 |
Discover