Computational Exploration of high energy density Metal Ion Electrode Materials

The current demand for power electronics and electric cars requires extensive exploration of Li-ion materials and similar technologies to meet the crucial factors of cost, safety, lifetime, durability, power density, and energy density in rechargeable batteries. In search for potential battery electrodes, Machine Learning techniques were used to predict average voltages and volume changes on metal ion electrodes, in our previous work. Through Machine Learning methods, various high energy density and small volume cell Li-ion electrodes were found. In this study, Li-ions were replaced with Na-ions to produce Na-ion electrodes in addition to the Li-ion materials. Voltage profiles and volume changes of several Li-ion and Na-ion electrodes were computed using DFT methods that showcase potential novel Li-ion and Na-ion materials for application as battery electrodes.