Kyujeong Jeon
Korea University · Engineering
About the Lab
Professor Kyujeong Jeon's research lab specializes in computational materials science and machine learning for energy materials, with a focus on solid-state batteries, ion conductors, and interatomic potentials. The lab develops advanced machine learning interatomic potentials (MLIPs) such as CHGNet and investigates ion conduction mechanisms in solid electrolytes, including structural and dynamic factors that govern superionic conductivity. Their work bridges atomistic simulations, materials design, and experimental validation to address challenges in next-generation energy storage technologies.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Abstract Large-scale simulations with complex electron interactions remain one of the greatest challenges for atomistic modelling. Although classical force fields often fail to describe the coupling between electronic states and ionic rearrangements, the more accurate ab initio molecular dynamics suffers from computational complexity that prevents long-time and large-scale simulations, which are essential to study technologically relevant phenomena. Here we present the Crystal Hamiltonian Graph
Abstract Machine learning interatomic potentials (MLIPs) have introduced a new paradigm for atomic simulations. Recent advancements have led to universal MLIPs (uMLIPs) that are pre-trained on diverse datasets, providing opportunities for universal force fields and foundational machine learning models. However, their performance in extrapolating to out-of-distribution complex atomic environments remains unclear. In this study, we highlight a consistent potential energy surface (PES) softening ef
Abstract The key component in lithium solid‐state batteries (SSBs) is the solid electrolyte composed of lithium superionic conductors (SICs). Lithium oxide SICs offer improved electrochemical and chemical stability compared with sulfides, and their recent advancements have largely been achieved using materials in the garnet‐ and NASICON (sodium superionic conductor)‐ structured families. In this work, using the ion‐conduction mechanisms in garnet and NASICON as inspiration, a common pattern of a
Since the 1980s, the paddlewheel effect has been suggested as a mechanism to boost lithium-ion diffusion in inorganic materials via the rotation of rotor-like anion groups. However, it remains unclear whether the paddlewheel effect, defined as large-angle anion group rotations assisting Li hopping, indeed exists; furthermore, the physical mechanism by which the anion-group dynamics affect lithium-ion diffusion has not yet been established. In this work, we differentiate various types of rotation
Abstract The use of a sacrificial cathode additive that contains a large amount of lithium is one potential solution to compensate for the irreversible capacity loss associated with next‐generation anodes such as silicon. Antifluorite‐type Li 6 CoO 4 has attracted attention as a potential cathode additive owing to its remarkably high theoretical lithium extraction capacity. However, the complex mechanism of lithium extraction as well as the oxygen loss from Li 6 CoO 4 is not well understood. A g
Revealing the local structure of solid electrolytes (SEs) with electron microscopy is critical for the fundamental understanding of the performance of solid-state batteries (SSBs). However, the intrinsic structural information in the SSB can be misleading if the sample's interactions with the electron beams are not fully understood. In this work, we systematically investigate the effect of electron beams on Al-doped lithium lanthanum zirconium oxide (LLZO) under different imaging conditions. Li
High Resolution Image Download MS PowerPoint Slide Amorphous Li–P–S materials have been widely used as solid-state electrolytes for all-solid-state batteries because of their high ionic conductivity (10 –4 to 10 –3 S cm –1 ) as well as good synthetic accessibility and processability. Despite the potential of these materials, their amorphous structures have made it challenging to quantify the relation between the structure and conductivity. In this paper, we use ab initio molecular dynamics simul
Metastable polymorphs often result from the interplay between thermodynamics and kinetics. Despite advances in predictive synthesis for solution-based techniques, there remains a lack of methods to design solid-state reactions targeting metastable materials. Here, we introduce a theoretical framework to predict and control polymorph selectivity in solid-state reactions. This framework presents reaction energy as a rarely used handle for polymorph selection, which influences the role of surface e
Li 2 ZrCl 6 (LZC) is a promising solid-state electrolyte due to its affordability, moisture stability, and high ionic conductivity. We computationally investigate the role of cation disorder in LZC and its effect on Li-ion transport by integrating thermodynamic and kinetic modeling. The results demonstrate that fast Li-ion conductivity requires Li-vacancy disorder, which is dependent on the degree of Zr disorder. The high temperature required to form equilibrium Zr disorder precludes any equilib
LiMXCl 4 , a recently discovered lithium superionic conductor, achieves Li conductivity up to 12.4 mS/cm at room temperature. Notably, LiNbOCl 4 features flexible, rotating polyhedra, potentially explaining its high ionic conductivity. However, the generalizability of these findings across different chemistries and the direct link between polyhedra rotations and Li-ion mobility remain unclear. In this study, we explore various M-cation and X-anion substitutions in the LiMXCl 4 system, identifyin
Abstract Phase diagrams offer substantial predictive power for materials synthesis by identifying the stability regions of target phases. However, thermodynamic phase diagrams do not offer explicit information regarding the kinetic competitiveness of undesired by-product phases. Here we propose a quantitative and computable thermodynamic metric to identify synthesis conditions under which the propensity to form kinetically competing by-products is minimized. We hypothesize that thermodynamic com
Uranium hydride is a promising material for stationary hydrogen storage in fusion reactors. In this work, various material properties of uranium hydride in both ferromagnetic (FM) and paramagnetic (PM) states are calculated to determine the optimal first-principles calculation method. For the treatment of strongly correlated f-electrons, the PBE functional with a Hubbard U parameter of 0.6 eV is selected as the optimal method and provides accurate formation energies and reasonable structural pro
It is desirable to develop solid electrolytes that have both excellent reductive stability against lithium metal and oxidative stability against high-voltage cathodes. However, no inorganic superionic conductors reported thus far satisfy these criteria. Nitrides exhibit intrinsically superior stability against reduction but are often readily oxidized at voltages as low as 0.6 V. In this article, we investigated all nitride-based compounds to search for materials with improved oxidative stabiliti
Research Areas
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