Analytically-Supported Hybrid Photonic-Plasmonic Crystal Design Using Artificial Neural Networks

An analytical and numerical study of hybrid photonic-plasmonic crystals is presented. The proposed theoretical model describes a system composed of a dielectric photonic crystal on a metallic thin film. To show the validity and usefulness of the model, four particular structures are analyzed, a one-dimensional crystal and three lattices of two-dimensional crystals. The model can calculate the photonic band structure of photonic-plasmonic crystals as a function of structural characteristics, showing two partial bandgaps for a square lattice, and complete bandgaps for triangular lattices. Furthermore, using a particular high-symmetry path, a full bandgap emerges in rectangular lattices, even with a small index of refraction contrast. Using the analytical model, a dataset is generated to train an artificial neural network to predict the center and width of the bandgap, that is, the forward design. In addition, an artificial neural network is trained to tune the optical response, that is, to perform the inverse design. The analytical results are consistent with the physics of the system studied and are supported by numerical simulations. Moreover, the prediction accuracy of the artificial neural networks is better than 95%. Overall, this paper reports a useful tool for tuning the optical properties of hybrid photonic-plasmonic crystals with potential applications in waveguides, nanocavities, mirrors, etc.

Lorentz resonance in the homogenization of plasmonic crystals

We explain the Lorentz resonances in plasmonic crystals that consist of two-dimensional nano-dielectric inclusions as the interaction between resonant material properties and geometric resonances of electrostatic nature. One example of such plasmonic crystals are graphene nanosheets that are periodically arranged within a non-magnetic bulk dielectric. We identify local geometric resonances on the length scale of the small-scale period. From a materials perspective, the graphene surface exhibits a dispersive surface conductance captured by the Drude model. Together these phenomena conspire to generate Lorentz resonances at frequencies controlled by the surface geometry and the surface conductance. The Lorentz resonances found in the frequency response of the effective dielectric tensor of the bulk metamaterial are shown to be given by an explicit formula, in which material properties and geometric resonances are decoupled. This formula is rigorous and obtained directly from corrector fields describing local electrostatic fields inside the heterogeneous structure. Our analytical findings can serve as an efficient computational tool to describe the general frequency dependence of periodic optical devices. As a concrete example, we investigate two prototypical geometries composed of nanotubes and nanoribbons.

Plasmonic Field-Effect Transistors (TeraFETs) for 6G Communications

Ever increasing demands of data traffic makes the transition to 6G communications in the 300 GHz band inevitable. Short-channel field-effect transistors (FETs) have demonstrated excellent potential for detection and generation of terahertz (THz) and sub-THz radiation. Such transistors (often referred to as TeraFETs) include short-channel silicon complementary metal oxide (CMOS). The ballistic and quasi-ballistic electron transport in the TeraFET channels determine the TeraFET response at the sub-THz and THz frequencies. TeraFET arrays could form plasmonic crystals with nanoscale unit cells smaller or comparable to the electron mean free path but with the overall dimensions comparable with the radiation wavelength. Such plasmonic crystals have a potential of supporting the transition to 6G communications. The oscillations of the electron density (plasma waves) in the FET channels determine the phase relations between the unit cells of a FET plasmonic crystal. Excited by the impinging radiation and rectified by the device nonlinearities, the plasma waves could detect both the radiation intensity and the phase enabling the line-of-sight terahertz (THz) detection, spectrometry, amplification, and generation for 6G communication.

Digital SERS sensing platform using 3D nanolaminate plasmonic crystals coupled with Au nanoparticles for accurate quantitative detection of dopamine

We report a digital surface-enhanced Raman spectroscopy (SERS) sensing platform using the arrays of 3D nanolaminate plasmonic crystals (NLPC) coupled with Au nanoparticles and the digital (on/off) SERS signal analysis...