Renato Iovine

Electromagnetic modeling of ellipsoidal nanoparticles for sensing applications

Abstract. We present a new analytical study of metallic nanoparticles, working in the infrared and visible frequency range. The structure consists of triaxial ellipsoidal resonating inclusions embedded in a dielectric environment. Our aim is to develop a new analytical model for the ellipsoidal nanoparticles to describe their resonant behaviors and design structures that satisfy specific electromagnetic requirements. The obtained models are compared to the numerical values, performed by full-wave simulations, as well as to the experimental ones reported in literature. A good agreement among these results was obtained. The proposed formula is a useful tool to design such structures for sensing applications.

Nanoparticle device for biomedical and optoelectronics applications

Purpose – In this contribution, the aim is to present a nanoparticle device, operating in the visible regime based on the localized surface plasmon resonance (LSPR) phenomenon. Design/methodology/approach – The nanoparticle electromagnetic properties are evaluated by a new analytical model and compared to the results obtained by numerical analysis. Findings – A near-field enhancement is obtained by arranging the nanoparticles in a linear array. Analytical formulas, describing such enhancement, are presented. Originality/value – The results demonstrate the possibility to use the proposed device for medical diagnostics and optoelectronics applications.

Optical Properties of Modified Nanorod Particles for Biomedical Sensing

In this paper, an analytical and numerical investigation for modified gold nanorod particles, operating in the visible and in the infrared regime is proposed. The modified particles consist in a core/shell structure (dielectric core/metallic shell) embedded in a dielectric environment. Their electromagnetic properties, in terms of extinction cross section (absorption and scattering) for both longitudinal and transverse modes excitation, are evaluated. In particular, new analytical models are developed, describing their resonant behavior. Good agreement among the analytical, numerical, and experimental results was achieved. Exploiting the obtained models, the nanoparticle sensitivity was studied. Analytical and full wave results validate the high sensitivity performances and the potential role of such structures to be used for sensing applications.

Surface plasmon resonance of nanoshell particles with PMMA-graphene core

Purpose – The purpose of this paper is to contribute an analytical and numerical study of a new type of nanoshell particles operating in the visible regime. Design/methodology/approach – The structure consists of a core/shell particle, arranged in a planar array configuration, with a polymethyl methacrylate (PMMA)-graphene core and gold thin shell. Findings – By exploiting the proposed analytical model the design of a metamaterial-based sensor, operating in the optical frequency range, for the detection of tissue diseases is shown. Originality/value – Full-wave simulations confirm the capability of the proposed sensor to identify different compounds by refractive index measurement.

Spectral Green's Function for SPR Meta-Structures

In this paper we propose a new approach to study the electromagnetic field in Surface Plasmon Resonance (SPR) meta-structures. The geometry is a planar structure infinitely extended with a pulse excitation current embedded in the substrate. The general solution has been applied to a specific geometry that is frequently employed to model practical problems. The minimization of the thickness changes spectral Greens function in a more efficient form, suitable for calculations. Plasmon electric field expression on interface plane is obtained. This kind of meta-structures is suitable in various fields of application (e.g. optoelectronics and electromagnetic sensors).

Nanoplasmonic sensor for chemical measurements

In this paper plasmonic nanoparticles arranged in an array configuration for the detection of glycerol concentration in aqueous solution, are presented. Glycerol concentration measurement is crucial for several application fields, such as biomedical engineering, medicine and biofuels fabrication. The detection of glycerol presence in aqueous solution is not simple, due to the fact that its refractive index shows small changes when different concentrations are considered. For this purpose, an LSPR (Localized Surface Plasmon Resonance) sensor, based on near field interaction of non-spherical dielectric-filled metallic particles (nanoshell) deposited on a silica substrate, is proposed. In this configuration an enhancement of the LSPR phenomenon with high sensitivity performances and a uniform near electric field distribution are obtained. In this way a shift in the position of the sensor response is related to the different concentration of the material under test. Numerical results, performed by full-wave simulations, show that the sensor can be used for the recognition of glycerol and its concentration in a highly accurate and sensitive way.

Electromagnetic Modeling of Dielectric Mixtures

Electromagnetic modeling of dielectric materials allows us to study the effects of electromagnetic wave propagation and how such electromagnetic fields influence and interact with them. Dielectric materials are composites or mixtures, which often are made up of at least two constituents or phases. Modelling the electromagnetic behaviour of dielectric mixtures is crucial to understand how geometrical factors (shape and concentration), electromagnetic properties of inclusions and background medium, influence the permittivity of the overall material. The aim of this work is to develop new analytical models for dielectric mixtures, in order to describe their electromagnetic behaviour and design them with desired electromagnetic properties, for specific required applications. In particular, in this paper a new general expression for the effective permittivity of dielectric mixture is presented. The mixtures consist of inclusions, with arbitrary shapes, embedded in a surrounding dielectric environment. We consider the hosting environment and the hosted material as real dielectrics, both of them as dispersive dielectrics. The proposed analytical models simplify practical design tasks for dielectric mixtures and allow us to understand their physical phenomena and electromagnetic behaviours.

Graphene Bow-tie Nanoantenna for Wireless Communications in the Terahertz Band

The interconnection of nanoscale devices (i.e., nanonodes) within a nanonetwork with existing communication networks, as well as the Internet, defines a new networking paradigm, namely the Internet of Nano-Things. Within this context, the definition of a nanonode requires specific features, especially for what concerns novel nanomaterial and components. Graphene-enabled wireless communications is emerging as a novel paradigm, which has been proposed to implement wireless communications among nanosystems. Indeed, graphene-based plasmonic nanoantennas, namely graphennas, are just a few micrometers in size, and are accordingly tuned to radiate electromagnetic waves in the terahertz band. In this work, the important role of the graphene conductivity in the contest of the characteristics of graphene-based nanoantennas is analyzed. Basically, we propose a particular shape for a nanoantenna (i.e., a bow-tie nanoantenna), and we study its radiation performance both in transmission, and reception. The resonance frequency of this kind of antenna is achieved by full-wave simulation. Moreover, the influence of the geometrical parameters is also evaluated. Numerical results will prove useful for designers of future graphene-based antennas, which are estimated to enable wireless communications in nanosystems.

Electromagnetic analysis of deep brain stimulation

In this contribution the stimulus complications in DBS (Deep Brain Stimulation) are evaluated and discussed. In particular we present a new method to predict the network response when a DBS stimulus is applied. A neural network similarly to ipsi-contralateral nerve topology is presented. The network consists of 175 neurons arranged in three layers. To validate the DBS stimulus propagation extensive numerical analyses have been conducted through Neuron software simulations. Results confirm the possibility to predict the correct stimulation parameters.

Multi resonant platform based on modified metallic nanoparticles for biological tissue characterization

In this contribution optical properties of new metallic nanoparticles for biomedical applications are investigated. These particles consist of a pair of opposing gold prisms with asymmetric dielectric holes. In this configuration the structure exhibits multi-resonant behavior in the Visible and Near Infrared Region, useful tool for multi-sensing platform based on local refractive index measurements. The electromagnetic properties of the structure are evaluated in terms of extinction cross-section through proper full-wave simulations. The sensitivity performances for the local refractive index variation are discussed. The obtained results show that the proposed particles could be efficiently applied for sensing applications.