Tuning the Electronic and Magnetic Properties of Phosphorene by Vacancies and Adatoms

We report a density functional theory (DFT) study regarding the effects of atomic defects, such as vacancies and adatom adsorption, on the electronic and magnetic properties of phosphorene (a two-dimensional monolayer of black phosphorus). A monovacancy in the phosphorene creates an in-gap state in the band gap of pristine phosphorene and induces a magnetic moment, even though pristine phosphorene is nonmagnetic. In contrast, both planar and staggered divacancies do not change the magnetic properties of phosphorene, although a staggered divacancy creates states in the gap. Our DFT calculations also show that adsorption of nonmetallic elements (C, N, and O) and transition metal elements (Fe, Co, and Ni) can change the magnetic properties of phosphorene with or without vacancies. For example, the nonmagnetic pristine phosphorene becomes magnetic after the adsorption of N, Fe, or Co adatoms, and the magnetic phosphorene with a monovacancy becomes nonmagnetic after the adsorption of C, N, or Co atoms. We also demonstrate that for O- or Fe-adsorbed monovacancy structure the electronic and magnetic properties are tunable via the control of charge on the phosphorene system. These results provide insight for achieving metal-free magnetism and a tunable band gap for various electronic and spintronic devices based on phosphorene

Raman Radial Mode Revealed from Curved Graphene

One of the unsolved fundamental issues of graphene is establishing an appropriate way to discern layers of graphene structures. We report a simple methodology to analyze graphene structures using Raman signals in the range of ∼100 to ∼500 cm^–1 comprising clear 118 or 175 cm^–1 peaks. We demonstrate that the low-energy signals on Raman spectra of plasma-seeded grown graphene sheets originated from nanocurvature (<i>c</i>) of mono- (175 and 325–500 cm^–1 signals) (<i>c</i> ≈ 1 nm) and bilayer (118 cm^–1 peak) (<i>c</i> ≈ 2 nm) graphene with Raman simulations, based on Raman radial mode (RM) Eigen vectors. Our RM model provides a standard way of identifying and evaluating graphene structures