Byungjin Choi

Characterization of a P2-type chelating-agent-assisted Na2/3Fe1/2Mn1/2O2 cathode material for sodium-ion batteries

A chelating-agent-assisted Na2/3Fe1/2Mn1/2O2 material is studied as a cathode for sodium-ion batteries. The addition of NH4OH results in the formation of a homogeneous powder with a lower resistance and larger carbon content on the cathode surface. The formation of a thin and stable solid-electrolyte interface layer leads to its enhanced electrochemical performance.

Enhancement in the electrochemical performance of zirconium/phosphate bi-functional coatings on LiNi0.8Co0.15Mn0.05O2 by the removal of Li residuals

The effect of bi-functional coatings consisting of Zr and phosphate (P) on the electrochemical performance of Li1.0Ni0.8Co0.15Mn0.05O2 (NCM) has been investigated. The presence of various types of Zr and P compounds such as oxides (ZrO2 and Li2ZrO3) and phosphates (Zr2P2O9, ZrP2O7 and LiZr2(PO4)3) in the coating was confirmed by experiments as well as density functional theory (DFT) calculations. When the NCM samples were coated with the Zr/P hybrid material, the cycle retention and the amount of removed Li residuals (LiOH, Li2CO3) were enhanced by the synergistic effect from Zr and P. The NCM sample coated with a Zr/P layer with a Zr/P ratio of 1 : 1 exhibited an increase in the initial capacity (209.3 mA h g-1) compared to the pristine sample (207.4 mA h g-1) at 0.1C, owing to the formation of the coating layer. The capacity retention of the Zr/P coated sample (92.4% at the 50th cycle) was also improved compared to that of the pristine NCM sample (90.6% at the 50th cycle). Moreover, the amount of Li residuals in the Zr/P coated NCM sample was greatly reduced from 3693 ppm (pristine NCM) to 2525 ppm (Zr/P = 5 : 5).

Computational Screening for Design of Optimal Coating Materials to Suppress Gas Evolution in Li-Ion Battery Cathodes

Ni-rich layered oxides are attractive materials owing to their potentially high capacity for cathode applications. However, when used as cathodes in Li-ion batteries, they contain a large amount of Li residues, which degrade the electrochemical properties because they are the source of gas generation inside the battery. Here, we propose a computational approach to designing optimal coating materials that prevent gas evolution by removing residual Li from the surface of the battery cathode. To discover promising coating materials, the reactions of 16 metal phosphates (MPs) and 45 metal oxides (MOs) with the Li residues, LiOH, and Li2CO3 are examined within a thermodynamic framework. A materials database is constructed according to density functional theory using a hybrid functional, and the reaction products are obtained according to the phases in thermodynamic equilibrium in the phase diagram. In addition, the gravimetric efficiency is calculated to identify coating materials that can eliminate Li residues with a minimal weight of the coating material. Overall, more MP and MO materials react with LiOH than with Li2CO3. Specifically, MPs exhibit better reactivity to both Li residues, whereas MOs react more with LiOH. The reaction products, such as Li-containing phosphates or oxides, are also obtained to identify the phases on the surface of a cathode after coating. On the basis of the Pareto-front analysis, P2O5 could be an optimal material for the reaction with both Li residuals. Finally, the reactivity of the coating materials containing 3d/4d transition metal elements is better than that of materials containing other types of elements.

Re-construction layer effect of LiNi 0.8 Co 0.15 Mn 0.05 O 2 with solvent evaporation process

The solvent evaporation method on the structural changes and surface chemistry of the cathode and the effect of electrochemical performance of Li1.0Ni0.8Co0.15Mn0.05O2 (NCM) has been investigated. After dissolving of Li residuals using minimum content of solvent in order to minimize the damage of pristine material and the evaporation time, the solvent was evaporated without filtering and remaining powder was re-heated at 700 °C in oxygen environment. Two kinds of solvent, de-ionized water and diluted nitric acid, were used as a solvent. The almost 40% of Li residuals were removed using solvent evaporation method. The NCM sample after solvent evaporation process exhibited an increase in the initial capacity (214.3 mAh/g) compared to the pristine sample (207.4 mAh/g) at 0.1C because of enhancement of electric conductivity caused by decline of Li residuals. The capacity retention of NCM sample after solvent evaporation process (96.0% at the 50th cycle) was also improved compared to that of the pristine NCM sample (90.6% at the 50th cycle). The uniform Li residual layer after solvent treated and heat treatment acted like a coating layer, leading to enhance the cycle performance. The NCM sample using diluted nitric acid showed better performance than that using de-ionized water.

Improved electrochemical properties of LiNi 0.91 Co 0.06 Mn 0.03 O 2 cathode material via Li-reactive coating with metal phosphates

Ni-rich layered oxides are promising cathode materials due to their high capacities. However, their synthesis process retains a large amount of Li residue on the surface, which is a main source of gas generation during operation of the battery. In this study, combined with simulation and experiment, we propose the optimal metal phosphate coating materials for removing residual Li from the surface of the Ni-rich layered oxide cathode material LiNi0.91Co0.06Mn0.03O2. First-principles-based screening process for 16 metal phosphates is performed to identify an ideal coating material that is highly reactive to Li2O. By constructing the phase diagram, we obtain the equilibrium phases from the reaction of coating materials and Li2O, based on a database using a DFT hybrid functional. Experimental verification for this approach is accomplished with Mn3(PO4)2, Co3(PO4)2, Fe3(PO4)2, and TiPO4. The Li-removing capabilities of these materials are comparable to the calculated results. In addition, electrochemical performances up to 50 charge/discharge cycles show that Mn-, Co-, Fe-phosphate materials are superior to an uncoated sample in terms of preventing capacity fading behavior, while TiPO4 shows poor initial capacity and rapid reduction of capacity during cycling. Finally, Li-containing equilibrium phases examined from XRD analysis are in agreement with the simulation results.

Machine learning assisted optimization of electrochemical properties for Ni-rich cathode materials

Optimizing synthesis parameters is the key to successfully design ideal Ni-rich cathode materials that satisfy principal electrochemical specifications. We herein implement machine learning algorithms using 330 experimental datasets, obtained from a controlled environment for reliability, to construct a predictive model. First, correlation values showed that the calcination temperature and the size of the particles are determining factors for achieving a long cycle life. Then, we compared the accuracy of seven different machine learning algorithms for predicting the initial capacity, capacity retention rate, and amount of residual Li. Remarkable predictive capability was obtained with the average value of coefficient of determinant, R2 = 0.833, from the extremely randomized tree with adaptive boosting algorithm. Furthermore, we propose a reverse engineering framework to search for experimental parameters that satisfy the target electrochemical specification. The proposed results were validated by experiments. The current results demonstrate that machine learning has great potential to accelerate the optimization process for the commercialization of cathode materials.