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KyuJung Jun

Postdoctoral Associate, Department of Materials Science and Engineering

Email: kyujung@mit.edu

Education

2024: Ph.D. in Materials Science and Engineering, UC Berkeley
2018 : B.S. in Nuclear Engineering & minor in Materials Science and Engineering, Seoul National University

Background and Research Interests

During my Ph.D, I worked on computational modeling of inorganic lithium superionic conductors (and other energy storage materials) using first-principles calculations, molecular dynamics, and neural network force fields. I identified several structural descriptors of superionic conductors, which led to the discovery of many novel crystal frameworks for fast lithium-ion diffusion. I also developed an event-based algorithm to detect and quantify various types of rotational events of anion groups (e.g. PS4, SO4) in inorganic crystals where the paddlewheel effect has been claimed. This enabled a statistical analysis on the correlation between rotational dynamics of anion groups and translational motion of lithium-ions to elucidate the origin of fast Li-ion diffusion in conductors claimed to exhibit paddlewheel effect.

During my postdoc, my research aims to expand these insights to lithium polymer electrolytes to quantify Li transport mechanisms in them. I am also interested in using machine learning algorithms to inverse-design superionic conductors.

External links

Google Scholar | ORCID | LinkedIn