| 2023-01 | An open-source deep learning model for predicting effluent concentration in capacitive deionization | Son, Moon; Yoon, Nakyung; Park, Sanghun; Abbas, Ather; Cho, Kyung Hwa |
| 2024-08 | Artificial neural network modeling for the oxidation kinetics of divalent manganese ions during chlorination and the role of arsenite ions in the binary/ternary systems | Liao, Ziqiao; Choi, Kungwon; Ullah, Zahid; Son, Moon; Ahn, Yongtae; Khan, Moonis Ali; Prabhu, Subbaiah Muthu; Jeon, Byong-Hun |
| 2024-09 | Autonomous real-time control for membrane capacitive deionization | Shim, Jaegyu; Lee, Suin; Yun, Nakyeong; Son, Moon; Chae, Sung Ho; Cho, Kyung Hwa |
| 2024-09 | Breakthrough innovations in carbon dioxide mineralization for a sustainable future | Kumar, Ramesh; Chung, Woo Jin; Khan, Moonis Ali; Son, Moon; Park, Young-Kwon; Lee, Sang Soo; Jeon, Byong-Hun |
| 2023-10 | Clustering micropollutants and estimating rate constants of sorption and biodegradation using machine learning approaches | Lim, Seung Ji; Seo, Jangwon; Seid, Mingizem Gashaw; Lee, Jiho; Ejerssa, Wondesen Workneh; Lee, Doo-Hee; Jeong, Eunhoo; Chae, Sung Ho; Lee, Yunho; Son, Moon; Hong, Seok Won |
| 2023-07 | Comparison of tree-based model with deep learning model in predicting effluent pH and concentration by capacitive deionization | Ullah, Zahid; Yoon, Nakyung; Tarus, Bethwel Kipchirchir; Park, Sanghun; Son, Moon |
| 2024-09 | Decoupling ion concentrations from effluent conductivity profiles in capacitive and battery electrode deionizations using an artificial intelligence model | Kim, Hoo Hugo; Choi, Byeongwook; Ullah, Zahid; Jeong, Nahyeon; Cho, Kyung Hwa; Park, Sanghun; Baek, Sang-Soo; Son, Moon |
| 2022-12 | Deep reinforcement learning in an ultrafiltration system: Optimizing operating pressure and chemical cleaning conditions | Park, Sanghun; Shim, Jaegyu; Yoon, Nakyung; Lee, Sungman; Kwak, Donggeun; Lee, Seungyong; Kim, Young Mo; Son, Moon; Cho, Kyung Hwa |
| 2024-10 | Desalination performance in versatile capacitive/battery deionization configurations using a cation intercalating electrode | Tarus, Bethwel Kipchirchir; Ullah, Zahid; Jande, Yusufu A. C.; Njau, Karoli N.; Byun, Jeehye; Son, Moon |
| 2024-07 | Determining water and solute permeability of reverse osmosis membrane using a data-driven machine learning pipeline | Chae, Sung Ho; Hong, Seok Won; Son, Moon; Cho, Kyung Hwa |
| 2023-10 | Energy storage capability of seawater batteries for intermittent power generation systems: Conceptualization and modeling | Park, Sanghun; Yoon, Nakyung; Ullah, Zahid; Tarus, Bethwel Kipchirchir; Choi, Byeongwook; Kim, Hoo Hugo; Son, Moon |
| 2023-09 | Explainable deep learning model for membrane capacitive deionization operated under fouling conditions | Yoon, Nakyung; Lee, Suin; Park, Sanghun; Son, Moon; Cho, Kyung Hwa |
| 2023-12 | Influence of organic matter on seawater battery desalination performance | Kim, Sukyoung; Shim, Jaegyu; Son, Moon; Park, Sanghun; Cho, Kyung Hwa |
| 2022-08 | Membrane capacitive deionization model including fouling indexes obtained via real-time fouling layer measurements | Yoon, Nakyung; Park, Sanghun; Shim, Jaegyu; Lee, Jongbin; Son, Moon; Cho, Kyung Hwa |
| 2024-09 | Metadata and feature importance analyses of membrane capacitive deionization models: Is a water treatment artificial intelligence panacea possible? | Chae, Sung Ho; Hong, Seok Won; Son, Moon |
| 2023-12 | Metal-organic framework-based composites for biogas and natural gas uptake: An overview of adsorption and storage mechanisms of gaseous fuels | Yusuf, Mohammed; Kumar, Ramesh; Khan, Moonis Ali; Ahmed, M. J.; Otero, Marta; Prabhu, Subbaiah Muthu; Son, Moon; Hwang, Jae-Hoon; Lee, Woo Hyoung; Jeon, Byong-Hun |
| 2024-09 | Multimodal deep learning models incorporating the adsorption characteristics of the adsorbent for estimating the permeate flux in dynamic membranes | Jeong, Heewon; Yun, Byeongchan; Na, Seongyeon; Son, Moon; Chae, Sung Ho; Kim, Chang - Min; Cho, Kyung Hwa |
| 2023-02 | Opportunities and challenges of machine learning in bioprocesses: Categorization from different perspectives and future direction | Lim, Seung Ji; Son, Moon; Ki, Seo Jin; Suh, Sang-Ik; Chung, Jaeshik |
| 2024-08 | Performance investigation of osmotically assisted reverse osmosis using explainable machine learning models: A comparative study | Chae, Sung Ho; Moon, Seokyoon; Hong, Seok Won; Lee, Chulmin; Son, Moon |
| 2022-12 | Physically-assisted removal of organic fouling by osmotic backwashing coupled with chemical cleaning | Park, Sanghun; Son, Moon; Shim, Jaegyu; Jeong, Kwanho; Cho, Kyung Hwa |
| 2022-09 | Predicting the salt adsorption capacity of different capacitive deionization electrodes using random forest | Park, Sanghun; Angeles, Anne Therese; Son, Moon; Shim, Jaegyu; Chon, Kangmin; Cho, Kyung Hwa |
| 2024-11 | Reinforcement Learning and Machine Learning Controllers for Enhancing Water Quality and Process Efficiency in Electrochemical Desalination | Ullah, Zahid; Yun, Nakyeong; Rossi, Ruggero; Son, Moon |
| 2023-09 | Robust and fouling-resistant ultrathin membranes for water purification tailored via semi-dissolved electrospun nanofibers | Yanar, Numan; Liang, Yejin; Yang, Eunmok; Kim, Minbeom; Kim, Hyeonseo; Byun, Jaehyun; Son, Moon; Choi, Heechul |
| 2022-01 | Seawater battery desalination with a reverse osmosis membrane for simultaneous brine treatment and energy storage | Park, Sanghun; Kim, Namhyeok; Kim, Youngsik; Son, Moon; Cho, Kyung Hwa |
| 2023-08 | Sustainable recovery of high-valued resources from spent lithium-ion batteries: A review of the membrane-integrated hybrid approach | Kumar, Ramesh; Chakrabortty, Sankha; Chakrabortty, Prasenjit; Nayak, Jayato; Liu, Chengjia; Khan, Moonis Ali; Ha, Geon-Soo; Kim, Kwang Ho; Son, Moon; Roh, Hyun-Seog; Tripathy, Suraj K.; Jeon, Byong-Hun |
