Correlation function of specific capacity and electrical conductivity on carbon materials by multivariate analysis

An attention for a Li ion battery for electric vehicles has been attracted, but there are two huge problems: a short mileage and slow charging speed. Therefore, it is required to improve the specific capacity and electrical conductivity of the carbon material used for an anode and a conductive agent. To solve these problems, this study organized a descriptor vector by collecting experimental properties including capacity and conductivity from 21 various types of carbon materials. Focusing on the flux of Li ion, the capacity was found to be dependent on the intercalation of Li ions, which lead to propose the correlation equation based on the Hill equation. Furthermore, the intercalation occurred at the edge of basal plane lead an increase of the width of the gap between two graphene layers, following a diffusion through the basal plane, finally the expanded gap recovered its original width. Also, it was found that the variables which are sensitive to the conductivity are dependent on the defects and especially the number of graphene layers around the surface with a larger effect, which proposed a correlation equation that can predict the capacity and conductivity. To validate these functions, we checked the effectiveness of it with experimental data from 27 previous studies and statistical method. As a result, it was confirmed enough to predict them. Finally, a candidate structure for improving the battery performance was proposed, thus our study aims to guide the exploration of electrode materials for LIBs.