Near-Field Properties of Plasmonic Nanostructures With High Aspect Ratio

Agha, Yacoub Ould; Demichel, Olivier; Girard, Christian; Bouhélier, Alexandre; Francs, Gérard Colas des

doi:10.2528/pier14012904

Cited by 12 publications

(13 citation statements)

References 45 publications

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“…The use of high-aspect-ratio particles in nanoplasmonics is primarily based on the excitation of low-order longitudinal modes; the latter are characterized by long wavelengths (roughly proportional to aspect ratio) and surfacecharge densities that vary mainly along the long scale of the geometry. Such longitudinal modes efficiently couple to both light and near-field sources, enabling low-frequency (near-infrared), high-quality-factor, optical resonances [26][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Slender-body theory for plasmonic resonance

Ruiz

Schnitzer

2019

Proc. R. Soc. A.

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We develop a slender-body theory for plasmonic resonance of slender metallic nanoparticles, focusing on a general class of axisymmetric geometries with locally paraboloidal tips. We adopt a modal approach where one first solves the plasmonic eigenvalue problem, a geometric spectral problem which governs the surface-plasmon modes of the particle; then, the latter modes are used, in conjunction with spectral-decomposition, to analyse localized-surface-plasmon resonance in the quasi-static limit. We show that the permittivity eigenvalues of the axisymmetric modes are strongly singular in the slenderness parameter, implying widely tunable, high-quality-factor, resonances in the near-infrared regime. For that family of modes, we use matched asymptotics to derive an effective eigenvalue problem, a singular non-local Sturm–Liouville problem, where the lumped one-dimensional eigenfunctions represent axial voltage profiles (or charge line densities). We solve the effective eigenvalue problem in closed form for a prolate spheroid and numerically, by expanding the eigenfunctions in Legendre polynomials, for arbitrarily shaped particles. We apply the theory to plane-wave illumination in order to elucidate the excitation of multiple resonances in the case of non-spheroidal particles.

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Section: Introductionmentioning

confidence: 99%

Slender-body theory for plasmonic resonance

Ruiz

Schnitzer

2019

Proc. R. Soc. A.

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“…The full optical response of both dielectric [12] or plasmonic nanostructures is accessible [13,14]. The GDM can describe well nano-plasmonics in general [15,16], but in particular it is an almost ideal method to describe "flat plasmonics", hence large planar nanostructures of thicknesses smaller than the skin depth [17,18,19,20,21,22]. Concerning dielectric materials, low-index dielectric nanostructures can be described very accurately [9], but also high-index dielectric nanostructures are within the scope of the GDM [23,24,25].…”

Section: Additional Comments Including Restrictions and Unusualmentioning

confidence: 99%

“pyGDM” - new functionalities and major improvements to the python toolkit for nano-optics full-field simulations

Wiecha

Majorel

Arbouet

et al. 2022

Computer Physics Communications

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pyGDM is a python toolkit for electro-dynamical simulations of individual nano-structures, based on the Green Dyadic Method (GDM). pyGDM uses the concept of a generalized propagator, which allows to solve cost-efficiently monochromatic problems with a large number of varying illumination conditions such as incident angle scans or focused beam raster-scan simulations. We provide an overview of new features added since the initial publication [Wiecha, Computer Physics Communications 233, pp.167-192 (2018)]. The updated version of pyGDM is implemented in pure python, removing the former dependency on fortran-based binaries. In the course of this re-write, the toolkit's internal architecture has been completely redesigned to offer a much wider range of possibilities to the user such as the choice of the dyadic Green's functions describing the environment. A new class of dyads allows to perform 2D simulations of infinitely long nanostructures. While the Green's dyads in pyGDM are based on a quasistatic description for interfaces, we also provide as new external python package "pyGDM2_retard" a module with retarded Green's tensors for an environment with two interfaces. We have furthermore added functionalities for simulations using fast-electron excitation, namely electron energy loss spectroscopy and cathodoluminescence. Along with several further new tools and improvements, the update includes also the possibility to calculate the magnetic field and the magnetic LDOS inside nanostructures, field-gradients in-and outside a nanoparticle, optical forces or the chirality of nearfields. All new functionalities remain compatible with the evolutionary optimization module of pyGDM for nano-photonics inverse design.

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“…Other geometries like cuboids [23] or tetrahedrons [24] can be used for the mesh as well, but are not implemented in pyGDM so far. Because it accounts for the field of a point dipole at the location of the dipole itself, the sub-matrix M ii is also called "self-term".…”

Section: Renormalization Of the Green's Dyadmentioning

confidence: 99%

“…∆x and ∆y are the distances to the beam axis in X and Y direction, respectively. In equation (23) we introduced furthermore the z-dependent beam waist…”

Section: Paraxial Gaussian Beammentioning

confidence: 99%

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pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures

Wiecha

2018

Computer Physics Communications

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pyGDM is a python toolkit for electro-dynamical simulations in nano-optics based on the Green Dyadic Method (GDM). In contrast to most other coupled-dipole codes, pyGDM uses a generalized propagator, which allows to cost-efficiently solve large monochromatic problems such as polarization-resolved calculations or raster-scan simulations with a focused beam or a quantum-emitter probe. A further peculiarity of this software is the possibility to very easily solve 3D problems including a dielectric or metallic substrate. Furthermore, pyGDM includes tools to easily derive several physical quantities such as far-field patterns, extinction and scattering cross-section, the electric and magnetic near-field in the vicinity of the structure, the decay rate of quantum emitters and the LDOS or the heat deposited inside a nanoparticle. Finally, pyGDM provides a toolkit for efficient evolutionary optimization of nanoparticle geometries in order to maximize (or minimize) optical properties such as a scattering at selected resonance wavelengths.

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Near-Field Properties of Plasmonic Nanostructures With High Aspect Ratio

Cited by 12 publications

References 45 publications

Slender-body theory for plasmonic resonance

Slender-body theory for plasmonic resonance

“pyGDM” - new functionalities and major improvements to the python toolkit for nano-optics full-field simulations

pyGDM—A python toolkit for full-field electro-dynamical simulations and evolutionary optimization of nanostructures

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