Lithium-ion batteries (LIBs) are gaining importance as they are actively utilized in electric vehicles and consumer electronics. In particular, it is crucial to diagnose the current state during the operation of LIBs and to predict the states according to future operating conditions. However, limitations exist due to the different properties of LIBs (e.g., limit charge/discharge rate) depending on their composition and cycling time or financial costs when cycling the LIB. We utilize electrochemical and equivalent circuit models to simulate the properties of LIBs under various compositions and operating conditions and conduct research to find optimal operating conditions. In particular, since it is challenging to utilize too complex models in the battery management system (BMS), we use simple models to measure the real-time state, and based on this information, we propose future operation strategies that consider the user's specific patterns.

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Associated members: Jaewook Lee, Seyeong Park, Sangjun Jeon, Yooil Son

Membranes serve as semipermeable barriers, permitting the passage of certain substances while impeding others. Their relevance has surged in recent times, primarily owing to their pivotal role in absorbing CO2. The complexity of designing and optimizing Carbon Capture, Utilization, and Storage (CCUS) processes employing selective membranes hinges upon a multitude of factors, including membrane permeability, selectivity, geed gas CO2 fraction, choice of solvent, and the persistent challenge of membrane fouling. Conventionally, selecting the appropriate module and designing optimal operating conditions for CCUS systems is a challenging task. This is further compounded by the limited consideration given to turbulent flow phenomena induced by spacers, which play a critical role in mitigating concentration polarization and membrane fouling. In light of these challenges, our research seeks to provide a more precise evaluation of membrane performance. We achieve this by employing computational fluid dynamics (CFD) simulations to model the flow dynamics within membrane modules, considering the presence and impact of spacers. This comprehensive approach promises to enhance our understanding of membrane-based CCUS processes and pave the way for more efficient and effective carbon capture technologies. 

Associated members: Seongjin Bae

The pharmaceutical and fine chemical industries are pivotal in supplying essential products that contribute to societal well-being. As these industries evolve, there is a growing recognition of the need to enhance manufacturing processes to improve efficiency, productivity, and cost-effectiveness. A significant area of interest in this regard is the shift from batch manufacturing to continuous manufacturing. Continuous manufacturing offers numerous advantages, such as improved process control, reduced batch-to-batch variability, and enhanced product quality. Moreover, its implementation can result in shorter manufacturing times, lower energy consumption, and reduced waste generation, aligning with sustainable manufacturing principles. However, despite these evident benefits, the transition to continuous manufacturing in the pharmaceutical and fine chemical industries presents certain challenges. Hence, we are interested in curating novel designs for automating real-time multi-spatial information acquisition to monitor and optimize a continuous slug-flow tubular crystallizer utilizing computer vision techniques in inline imaging system development.

Associated members: Derrick Adams