Screening Topological Quantum Cathode Materials for K-Ion Batteries by Graph Neural Network and First-Principles Calculations

Abstract

Among the key parts of metal-ion batteries, cathode materials significantly affect the energy density and cycling stability. However, due to the large size of K + , not much progress has been made on cathode materials for K-ion batteries (KIBs). In this study, using the Atomistic Line Graph Neural Network and first-principles calculations, for the first time we screen cathode materials for KIBs from 7385 topological quantum materials with high electronic conductivity and reversible capacity. The experimentally synthesized K 2 MnS 2 is discovered to have a reversible capacity of 203.8 mAh/g, an energy density of 564.5 Wh/kg, a small volume change of 6.4%, and multiple channels for K + transport with fast dynamics. Furthermore, K 2 MnS 2 shows high electrochemical interface stability with the reported solid electrolytes of K 4 V 2 O 7 , and K 3 NbP 2 O 9 . These findings suggest that topological quantum materials expand the design space of battery cathodes.