Duho Kim

Harnessing reversible anionic redox is pivotal for high-energy sodium-ion batteries, yet practical use is hindered by structural instabilities from irreversible phase transitions and cation migration. Herein, we propose a kinetically induced thermodynamic non-equilibrium (TnE) strategy in a P3-type Na0.6[Li0.2Mn0.8]O2 (P3-NLMO) cathode. Contrary to conventional behavior, P3-NLMO exhibits anomalous rate performance, with higher capacity retention at 1C than at 0.1C. Combining first-principles calculations and operando synchrotron X-ray diffraction (XRD), we reveal that slow cycling follows a thermodynamic equilibrium pathway involving spontaneous Li migration from the transition-metal layer to the Na slab, triggering a deleterious P3-to-Z phase transition. Rapid charging kinetically outruns this migration, bypassing the phase transition and preserving a near-zero-strain P3 framework. High-voltage relaxation experiments confirm that degradation is driven by time-dependent Li migration, not the electrochemical process itself, establishing fast cycling as a viable stabilization strategy for anion-redox cathodes.

Achieving nonhysteretic and reversible (nHR) oxygen redox in sodium-ion batteries(SIBs) is critical for enhancing their energy density and practical viability. Herein, we present a high-throughput computational framework that integrates machine learning interatomic potentials (MLIPs) with density functional theory (DFT) to design high-entropy layered Na-based cathodes with improved redox reversibility. Using MLIP-based screening of 30,240 configurations derived from Na[Li1/6Mn2/6A1/6B1/6C1/6]O2 (A, B, C: 3d transition metals), Na[Li1/6Mn2/6Ti1/6V1/6Zn1/6]O2 (HE-NLMO) is identified as the most thermodynamically stable composition. With understanding of thermodyanmic phase stabilities, DFT calculations reveal that HE-NLMO enables spontaneous and structurally continuous Li-ion migration into tetrahedral sites within the Na layer during desodiation. Electronic structure investigations further show that the selective oxidation behaviours trigger the asymmetric Li position in the Na layer for easily returning it to the original site. This combination of structural and electronic flexibility facilitates a smooth Li-ion migration pathway and sustainable nHR oxygen redox. Our results underscore the effectiveness of entropy engineering and ML-DFT hybrid approaches in accelerating the discovery of high-performance Na-based cathodes.

Understanding and predicting battery cycle life is crucial for the reliable operation of lithium‐ion cells, particularly under fast‐charging conditions. Conventional prognostic methods predominantly rely on electrochemical measurements such as capacity fade and internal resistance, which often require specialized testing protocols and limit practical applicability. In this work, we investigate temperature as a non‐electrochemical and readily accessible signal that encodes degradation‐related information during battery cycling. Motivated by a physically grounded hypothesis informed by density functional theory, we relate the accumulation of internal resistance to increased heat generation, which manifests as characteristic temperature behavior over cycling. Using a large open‐source dataset comprising 96,700 cycles of commercial LiFePO₄/graphite cells subjected to diverse fast‐charging protocols, we systematically analyze the relationships among temperature, discharge capacity, internal resistance, and cycle life. Temperature features are extracted separately from charge and discharge temperature curves, and data‐driven cycle life prediction models based on a gradient boosting machine (GBM) framework are developed. Models using discharge‐derived temperature features significantly outperform those based solely on charge‐derived features, while combining charge and discharge features yields the highest predictive accuracy. Shapley value analysis further reveals the dominant contribution of discharge‐related temperature features to model predictions. These results demonstrate that appropriately processed temperature data can provide a practical, non‐electrochemical pathway for battery cycle life prediction without reliance on electrochemical diagnostics.

Nickel-rich cathode materials (NCM) have emerged as promising candidates for lithium-ion batteries (LIBs) and all-solid-state batteries (ASSBs) due to their high reversible capacity (>200 mAh g^-1). However, surface side reactions with liquid and solid electrolytes during cycling increase interfacial resistance and accelerate capacity fading, thereby hindering the practical implementation of NCM cathodes. To achieve high-energy LIBs and ASSBs, it is essential to control the interfacial reactions. This can be achieved by integrating coating materials that exhibit a high ionic conductivity and excellent electrochemical stability. In this paper, we propose a cationic defect concept that leads to expansion of the Li kinetic pathway and the formation of a coherent crystal framework that induces a durable interface. This concept is implemented using Li_3+xAl_1-x/3F₆ models for reducing the interfacial resistance and enhancing the structural stability of NCM cathodes in both LIBs and ASSBs. The Li_3.3Al_0.9F₆ coating layer exhibiting high ionic conductivity and superior voltage stability effectively controls interfacial side reactions at both electrolyte interfaces, reducing interfacial resistance and improving cycling performance. It can enhance the electrochemical properties of NCM cathode materials, contributing to the realization of high-energy LIBs and ASSBs. We investigate the impact of the chemical composition of the Li_3.3Al_0.9F₆ coating layer on the reversibility and interfacial stability of NCM cathodes and further identify the effectiveness of the coating under high-temperature and high-voltage conditions. Based on the intriguing cationic defect concept, our findings contribute to the development of highly stable cathode materials for the implementation of high-energy LIBs and ASSBs.

Breaking the intrinsic symmetry in crystal structures is a promising design concept for developing high-performance battery materials, providing a pathway to fast lithium-ion transport.

LiMn _y Fe _{1− y} PO ₄ (LMFP) has emerged as a promising candidate for substituting LiFePO ₄ due to its higher energy density while preserving cost‐effectiveness. However, LMFPs are veiled by their asymmetric charge‐discharge voltage profiles that arise from complex phase transitions. In this study, first‐principles calculations are employed to systematically investigate the phase transition mechanisms and electronic structure evolutions in LiFePO ₄ and LiMnPO ₄ , with a focus on elucidating the behavior of Li _{1– x} Mn _y Fe _{1− y} PO ₄ for next‐generation lithium‐ion batteries. Detailed phase diagrams across the full lithiation range, combined with partial density of states analysis, reveal that the dual voltage plateaus arise from the distinct redox processes of Fe ²⁺ /Fe ³⁺ and Mn ²⁺ /Mn ³⁺ . Notably, the thermodynamic equilibrium reaction pathway of LMFP follows a sequence of biphasic, monophasic, and biphasic transitions. In contrast, the intrinsic insulating characteristics of iron phosphate trigger a non‐equilibrium reaction during charging. This non‐equilibrium behavior, marked by phase segregation and limited electron mobility due to Mott‐insulator characteristics, leads to a stepwise (stair‐like) voltage profile during charging, whereas the discharging process follows an equilibrium pathway with a smoother voltage response. These insights into the interplay between thermodynamics, electronic structure, and insulating properties provide a theoretical foundation for understanding LMFP cathodes.

A new avenue by transforming the conventional electrochemical domain into an electro‐chemo‐mechanical domain is proposed to achieve less hysteretic fast‐charging based on the three pictures: i) electro‐chemo‐mechanics, ii) phase transition kinetics, and iii) ionic kinetics. Each concept is demonstrated leading to the electrochemical improvement using data‐driven computation and experimental analyses, and its novel framework is generalized based on alkali‐ion chalcogenide models. The mechanical strain lowers and delays the electrochemical yield point, which gives rise to extending the elastic region and enhancing the phase and ionic kinetics. This is experimentally verified with less hysteresis upon (dis)charging for all models. Implementing the electro‐chemo‐mechanical domain is central in alkali‐ion chalcogenide batteries and broadens its application in other rechargeable batteries, ultimately playing a critical role in providing practical fast‐charging solutions.