학술논문

Density Functional Theory and Machine Learning‐Based Analyses for Improved Surface Stability of a BaTiO3‐Coated LiCoO2 Positive Electrode Material.
Document Type
Article
Source
Physica Status Solidi (B). Sep2022, Vol. 259 Issue 9, p1-7. 7p.
Subject
*LITHIUM-ion batteries
*DENSITY functional theory
*SURFACE stability
*MACHINE theory
*SURFACE analysis
*OXIDE coating
Language
ISSN
0370-1972
Abstract
The application of oxide coating on the surfaces of active cathode materials is an effective method for improving the electrochemical durability of lithium‐ion batteries because it suppresses oxygen gas release from the surface of the cathode material. This report summarizes a study conducted on verifying the suppression of oxygen release from a LiCoO2 cathode material using BaTiO3 (BT), which has recently attracted attention as a new coating material. The use of first‐principles calculations and machine learning as verification methods is described. In addition to the discussion of interfacial properties based on atomic‐ and electronic‐level considerations, comprehensive verification of the interface with several junction patterns is described. The verification results suggest that the desorption of oxygen from the surface of the active material is hindered by the oxide coating, indicating the effectiveness of BT as a coating material. [ABSTRACT FROM AUTHOR]