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Digital Chemistry for Sustainable Energy
We advance sustainable energy science by integrating theory, computation, and data.
AI4Science: Interpretable AI frameworks for understanding, forecasting, and controlling energy systems
Data4Matter: Data-driven and AI-enabled design of next-generation energy materials
Chem4Energy: Multiscale chemical theories for complex energy systems
Electrolytes: Towards conquering "the uncharted"
Developing fast solid ion conductors is a primary challenge in all-solid-state batteries. Designing solid electrolytes requires considering several physicochemical properties, from short-range ion solvation to long-range ion transport. The Kim group focuses on uncovering the relationships between molecular properties across multiple time/length scales, such as ion solvation and ion transport, in the context of nanoscale ion network formation. We aim to establish molecular principles for the innovative design of solid polymer electrolytes through systematic investigation using computation, expanding their design space across a wide range of salt concentrations.
Developing fast solid ion conductors is a primary challenge in all-solid-state batteries. Designing solid electrolytes requires considering several physicochemical properties, from short-range ion solvation to long-range ion transport. The Kim group focuses on uncovering the relationships between molecular properties across multiple time/length scales, such as ion solvation and ion transport, in the context of nanoscale ion network formation. We aim to establish molecular principles for the innovative design of solid polymer electrolytes through systematic investigation using computation, expanding their design space across a wide range of salt concentrations.
Towards molecular control of electrochemical interfaces
Stabilizing the electrochemical interface is a great challenge in energy storage technology for large-scale energy grid systems, electric vehicles, and even small electronics. The Kim group is interested in understanding molecular processes that involve coupled charge/mass transfer and transport at electrochemical interfaces. We are developing a theory-/computation-driven "bridge" between molecular properties at the microscale and the energy device performance at the macroscale. Ultimately, we aim to provide molecular control of the electrochemical interfaces for enhanced safety and better performance.
Stabilizing the electrochemical interface is a great challenge in energy storage technology for large-scale energy grid systems, electric vehicles, and even small electronics. The Kim group is interested in understanding molecular processes that involve coupled charge/mass transfer and transport at electrochemical interfaces. We are developing a theory-/computation-driven "bridge" between molecular properties at the microscale and the energy device performance at the macroscale. Ultimately, we aim to provide molecular control of the electrochemical interfaces for enhanced safety and better performance.
Towards AI/ML-assisted performance optimization
Computation plays a variety of roles in facilitating the advancement of energy materials, from providing fundamentals of their physicochemical properties to predicting their performance. However, there exists a fundamental trade-off in computation in chemical research between accuracy and speed, which sometimes limits its utility in spanning a wide range of chemical spaces. Now is a perfect time to develop new methods of molecular materials design that enable us to explore vast chemical spaces at unprecedented efficiency thanks to recent developments in AI and machine learning techniques. Currently, we are working on computation-aided battery health management. We are looking forward to sharing our fruits soon!
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