First Principles Study of the Role of Defects for Graphene Lithiation

Since the discovery of freestanding graphene, this 2D structure is considered as a potential alternative for graphite, because of its outstanding electronic and mechanical properties. It has attracted much attention as a promising electrode material for electrochemical energy storage devices such as Li-ion batteries due to high surface area and superior electronic conductivity. For Li-ion battery applications, graphene is used as a buffer layer to suppress the large volume expansion observed in high capacity anode materials and as a coating material to enhance conductivity. It was shown that graphene sheets prepared by reduction of graphite oxide (GO) deliver a reversible capacity and good cycling stability. Large variation in the capacity is reported by several studies for graphene, which is prepared with the exact similar techniques. Such discrepancy is suggested to result from the disordered and/or ordered structure of graphene sheets affecting lithium storage capacity, suggesting that the structural characteristics influence the resulting electrochemical performance.

Note that earlier experimental studies have identified the existence of defects such as Stone-Wales and double vacancy defects, as well as grain boundaries in graphene. Thus, for complete understanding of the electrochemical performance of graphene, the role of different types of defects on the electrochemical performance should be identified as well as the defect density influence should be evaluated. Such comparative study along with pristine graphene can provide vast amount of information not only for the electrochemical performance, but also, for the structural and electronic structure differences with the types of defects, defect densities, and Li concentration.

In this study, we use density functional theory to build atomistic level understanding of topological defects in graphene and their role on the electrochemical performance. Li configurations are generated combining an algorithm whose results are tested using a genetic algorithm method. We explore the effect of each defect type on Li adsorption and obtain an atomic level understanding of the interaction between defected graphene and Li. The electrochemical performance of these defective sheets under varying Li concentration is studied, and compared with those obtained for pristine graphene. Furthermore, the effect of defect density on the electrochemical performance is evaluated. Lithiation voltages as function of each defect type will be reported and compared with those of the pristine graphene. The results are expected to shed light on the role of each defect type on the electrochemical performance of graphene as an alternative anode material for Li ion batteries.