people

Biography

Young-Woon Byeon is a group leader of the Advanced Electron Microscopy Group (AEMG) at Advanced Analysis and Data Center (AADC), KIST. He received his Ph.D. in materials sciences and engineering from Korea University (Seoul, Korea) in 2020 under the supervision of Dr. Jae-Pyoung Ahn and Prof. Jae-Chul Lee. During his doctorate courses, he studied the diffusion kinetics of lithium (Li⁺) and sodium (Na⁺) ions in alloying anodes (tin, silicon, antimony, etc.). By leveraging his in-situ/operando electron microscopy (EM) techniques, he revealed the mechanism how the diffusion of charge-carrier-ions was mitigated at the migrating interface during the volume expansion.

After his Ph.D. courses, he joined Lawrence Berkeley National Laboratory (LBNL) as a postdoctoral research employee. Under the supervision of Dr. Haegyeom Kim and Dr. Peter Ercius, Young-Woon delved into the complexities of material properties per various processing. He investigated their implications in multiple applications, including all-solid-state batteries (ASSB), proton exchange membrane fuel cells (PEMFC), and nanoporous bio-ceramics. In November 2023, Young-Woon started his new career in a tenure-track position as a senior research scientist at AADC, KIST in Seoul, Korea.

Research Interests

Dr. Byeon utilizes the correlative analysis capabilities of the Titan, Talos, and Tecnai transmission electron microscopes (TEMs) with the other analytical techniques (FIB, SEM, XRD, XPS, and APT). He also focuses on the application of damage-less TEM analysis techniques, such as cryogenic TEM, low-acceleration voltage, utilizing direct electron detector, etc. He belives the TEM-based spectroscopy is the most powerful tool that can unravel the misteries in nano-scale worlds. He also utilizes the high-resolution imaging capabilities coupled with in-situ/operando TEM holders to study materials processes in various environments. His broad range of research interests include:

• Correlation study between performance degradation of battery material
• In situ / operando studies on the diffusion of charge-carrier (H⁺/Li⁺/Na⁺/K⁺, etc.) ions during reactions.
• Diffraction and spectrum data processing for statistical analysis in a large area at materials interfaces.
• Low e-beam dose / Cryo-EM techniques to minimize the sample damage during the observation.
• STEM / FIB tomography of the environment sensitive materials and their data processing.
• Machine Learning / Automation on the EM analysis process (Sample prep./Transfer/Data acquisition/Data processing)