ИСТИНА

Despite the tremendous progress in the field of nanoplasmonics, complex plasmonic nanostructures such as dimers still present a significant challenge for both experimental and numerical characterization. Since the size of the nanoparticles (NPs) quite often is well below the Abbe diffraction limit, one typically has to rely on electron microscopy (i.e. on electron energy loss spectroscopy - EELS) to investigate these structures. Within EELS, fast electrons are passing nearby the plasmonic structure exciting plasmonic modes of the system and therefore losing a corresponding amount of kinetic energy. By performing spectroscopy on the transmitted electrons, one can measure the whole excitation spectrum of the structure including influence of evanescent waves with high spatial resolution. EELS also allows to excite resonances that are optically dark due to their vanishing electric dipole moments. Due to high resolution EELS is especially suitable for studying dimers with very small interparticle distances. These features make EELS an attractive tool for studying surface plasmons related to various applications including nanoantennas, sensing, optical trapping, and many others. In order to better understand experimental measurements and to properly interpret the results, accurate EELS simulations are required, creating demand for flexible and reliable numerical approaches capable of efficiently modeling single NPs and NP systems. Special attention is currently devoted to the fact that small NPs, as well as systems with a small distance between particles (less than 5nm), exhibit excitation spectrum not predicted by methods based on classic electromagnetics. Although these spectral deviations have quantum origin, it has been shown that they could be accounted for within traditional numerical techniques via inclusion of the nonlocal effect. The applicant’s previous contribution to this topic consists in the implementation of the nonlocal-enabled hybrid scheme of the Discrete Sources Method (DSM) for studying single plasmonic NPs within the scope of prior G-RISC projects. Key advantages of the developed technique involve flexibility, high performance and a posteriori error estimation.