Near-Field Mapping of Photonic Eigenmodes in Patterned Silicon Nanocavities by Electron Energy-Loss Spectroscopy

Recently, there has been significant interest in using dielectric nanocavities for the controlled scattering of light, owing to the diverse electromagnetic modes that they support. For plasmonic systems, electron energy-loss spectroscopy (EELS) is now an established method enabling structure-optical property analysis at the scale of the nanostructure. Here, we instead test its potential for the near-field mapping of photonic eigenmodes supported in planar dielectric nanocavities, which are lithographically patterned from amorphous silicon according to standard photonic principles. By correlating results with finite element simulations, we demonstrate how many of the EELS excitations can be directly corresponded to various optical eigenmodes of interest for photonic engineering. The EELS maps present a high spatial definition, displaying intensity features that correlate precisely to the impact parameters giving the highest probability of modal excitation. Further, eigenmode characteristics translate into their EELS signatures, such as the spatially and energetically extended signal of the low Q-factor electric dipole and nodal intensity patterns emerging from excitation of toroidal and second-order magnetic modes within the nanocavity volumes. Overall, the spatial-spectral nature of the data, combined with our experimental-simulation toolbox, enables interpretation of subtle changes in the EELS response across a range of nanocavity dimensions and forms, with certain simulated resonances matching the excitation energies within +/- 0.01 eV. By connecting results to far-field simulations, perspectives are offered for tailoring the nanophotonic resonances via manipulating nanocavity size and shape.

Automated summary

This study explores the potential of near-field mapping of photonic eigenmodes supported in planar dielectric nanocavities using electron energy-loss spectroscopy (EELS). The results show a correlation between EELS excitations and optical eigenmodes, providing insights for photonic engineering applications. The study also demonstrates the high spatial definition of EELS maps and how eigenmode characteristics can be translated into their EELS signatures.