We investigate the sensitivity and figure of merit (FOM) of a localized surface plasmon (LSP) sensor with gold nanograting on the top of planar metallic film. The sensitivity of the localized surface plasmon sensor is 317 nm/RIU, and the FOM is predicted to be above 8, which is very high for a localized surface plasmon sensor. By employing the rigorous coupled-wave analysis (RCWA) method, we analyze the distribution of the magnetic field and find that the sensing property of our proposed system is attributed to the interactions between the localized surface plasmon around the gold nanostrips and the surface plasmon polarition on the surface of the gold planar metallic film. These findings are important for developing high FOM localized surface plasmon sensors.
Plasmon resonances in graphene ribbon arrays are investigated numerically by means of the Finite Element Method. Numerical analysis shows that a series of multipolar resonances take place when graphene ribbon arrays are illuminated by a TM polarized electromagnetic wave. Moreover, these resonances are angle-independent, and can be tuned greatly by the width and the doping level of the graphene ribbons. Specifically, we demonstrate that for graphene arrays with several sets of graphene ribbons, which have different widths or doping levels, each of these multipolar resonances will be split into several ones. In addition, as plasmon resonances can confine electromagnetic field at the ribbon edges, graphene ribbons with different widths or doping levels offer intriguing application for electrically tunable spectral imaging.
We present a two-band finite difference method for the bandstructure calculation of quantum cascade lasers (QCLs) based on the equivalent two-band model of the nonparabolic Schrödinger equation. Particular backward and forward difference forms are employed in the discretization procedure instead of the common central difference form. In comparison with the linearization approach of the nonparabolic Schrödinger equation, the method is as accurate and reliable as the linearization approach, while the velocity of the method is faster and the matrix elements are more concise, therefore making the method more practical for QCLs simulations.
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