Introduction of Near to Far Infrared Range Direct Band Gaps in Graphene: A First Principle Insight

Abstract

Lack of band gaps hinders application of graphene in the fields like logic, optoelectronics, and sensing despite its various extraordinary properties. In this work, we have done systematic investigations on direct band gap opening in graphene by hydrogenation and fluorination of carbon vacancies using the density functional theory computational approach. We have seen that although a carbon vacancy (void) opens an indirect band gap in graphene, it also creates unwanted mid gap (trap) states, which is attributed to unbound orbitals of the nearest unsaturated carbon atoms at the vacant site. The unsaturated carbon atoms and corresponding trap states can degrade the stability of graphene and create band gaps particularly for large size vacancies. We have proposed that hydrogenation or fluorination of the unsaturated carbon atoms near the vacant site helps in disappearance of the trap states while contributing to promising direct band gaps in graphene. The opened band gap is tunable in the infrared regime and persists for different sizes and densities of hydrogenated or fluorinated patterns. In addition, we have also found that the proposed approach is thermodynamically favorable as well as stable. This keeps the planar nature of the graphene monolayer, despite creation of defects and subsequent functionalization, thereby making it useful for 2D material-based electronics, optoelectronics, and sensing applications.

A Roadmap for Disruptive Applications and Heterogeneous Integration Using Two-Dimensional Materials: State-of-the-Art and Technological Challenges

“…This makes BL graphene offer a better thermal conductivity as compared to monolayer graphene despite increasing its effective electronic mass. It should be noted that the bandgap of graphene can be tuned by introducing unique defect sites in the lattice, as disclosed by Kumar et al…”

“…The fundamental properties of some of the materials are reviewed below by using density functional theory-based computations. The computational method used here is explained in detail in our earlier works …”