Plasmonics on Optical Fiber Platforms

Kim, Hyuntai

doi:10.5772/intechopen.79146

Cited by 3 publications

(4 citation statements)

References 40 publications

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“…The example is the Poisson equation due to a white noise charged disorder (which is equivalent to GFF) in the presence of metallic regions whose formation pattern are modeled by the Ising model with an artificial temperature [4]. Such a study is expected to be relevant in understanding of many solid state systems which are doped with the metallic particles with a vast applications ranging from optical devices [14][15][16][17][18][19][20][21][22] and random lasers [23], to sensor technology [24] and solar cells [25][26][27]. Along with the experimental interests, there are also theoretical interests on the various versions of the GFF model.…”

Section: Introductionmentioning

confidence: 99%

Gaussian free field in the iso-height random islands tuned by percolation model

Cheraghalizadeh¹,

Najafi²,

Mohammadzadeh³

2018

J. Stat. Mech.

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The Gaussian free field (GFF) is considered in the background of random iso-height islands which is modeled by the site percolation with the occupation probability p. To realize GFF, we consider the Poisson equation in the presence of normal distributed white-noise charges, as the stationary state of the Edwards-Wilkinson (EW) model. The iso-potential (metallic in the terminology of the electrostatic problem) sites are chosen over the lattice according to the percolation problem, giving rise to some metallic islands and some active (not metallic, nor surrounded by a metallic island) area. We see that the dilution of the system by incorporating metallic particles (or equivalently considering the iso-height islands) annihilates the spatial correlations and also the potential fluctuations. Some local and global critical exponents of the problem are reported in this work. The GFF, when simulated on the active area show a cross over between two regimes: small (UV) and large (IR) scales. Importantly, by analyzing the change of exponents (in and out of the critical occupation pc) under changing the system size and the change of the cross-over points, we find two fixed points and propose that GFFp=p c is unstable towards GFFp=1.

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Section: Introductionmentioning

confidence: 99%

Gaussian free field in the iso-height random islands tuned by percolation model

Cheraghalizadeh¹,

Najafi²,

Mohammadzadeh³

2018

J. Stat. Mech.

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“…2 , to the amount D T =Tc F = 1.4 ± 0.01 which is closer to the fractal dimension of the fractal dimension of the external perimeter of the 2D critical Ising model D Ising F = 11 8 , although the other critical exponents are significantly different. The paper has been organized as follows: In the following section, we motivate this study and introduce and describe the model.…”

Section: Introductionmentioning

confidence: 51%

“…The disorder, produced by doping neutral metallic nanoparticles (MNPs) in a d-dimensional (d = two or three) solid state system, has an impressive impact in the transport of the media and can be tracked in both quantum and classical levels. The examples are incorporation of MNPs in graphene [1][2][3][4], enhancement of optical properties in optical devices using MNPs [5][6][7][8][9][10][11][12] and the random laser [13], improving photocatalytic activity of TiO 2 films [14], its application in the sensor technology [15] and solar cells [16,17] and other thin films [18]. MNPs cause a wide variety of physical phenomena in the condensed matter systems, such as the Anderson localization [19], catalytic materials when incorporated to the porous media [20], the effect of MPNs on organic nanofloating-gate memory devices [21], and on the acoustic vibrations in dielectric shells [22].…”

Section: Introductionmentioning

confidence: 99%

Gaussian Free Field in the background of correlated random clusters, formed by metallic nanoparticles

Cheraghalizadeh,

Najafi,

Mohammadzadeh

2018

Preprint

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The effect of metallic nano-particles (MNPs) on the electrostatic potential of a disordered 2D dielectric media is considered. The disorder in the media is assumed to be white-noise Coulomb impurities with normal distribution. To realize the correlations between the MNPs we have used the Ising model with an artificial temperature T that controls the number of MNPs as well as their correlations. In the T → 0 limit, one retrieves the Gaussian free field (GFF), and in the finite temperature the problem is equivalent to a GFF in iso-potential islands. The problem is argued to be equivalent to a scale-invariant random surface with some critical exponents which vary with T and correspondingly are correlation-dependent. Two type of observables have been considered: local and global quantities. We have observed that the MNPs soften the random potential and reduce its statistical fluctuations. This softening is observed in the local as well as the geometrical quantities. The correlation function of the electrostatic and its total variance are observed to be logarithmic just like the GFF, i.e. the roughness exponent remains zero for all temperatures, whereas the proportionality constants scale with T − Tc. The fractal dimension of iso-potential lines (D f ), the exponent of the distribution function of the gyration radius (τr), and the loop lengths (τ l ), and also the exponent of the loop Green function x l change in terms of T − Tc in a power-law fashion, with some critical exponents reported in the text. Importantly we have observed that, in which ξ(T ) is the spin correlation length in the Ising model.

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“…Plasmonic fiber-optic sensors have captured intensive research attention in recent years due to their high degree of integration, high sensitivity, flexibility and remote-sensing capability [1][2][3]. Fiber-optic plasmonic sensors can be generally classified into two categories, surface plasmon resonance (SPR)-based sensors and localized surface plasmon resonance (LSPR)-based sensors.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Plasmonic Fiber-Optic Sensors

Miao

Zhang

et al. 2020

Sensors

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With the increasing demand of achieving comprehensive perception in every aspect of life, optical fibers have shown great potential in various applications due to their highly-sensitive, highly-integrated, flexible and real-time sensing capabilities. Among various sensing mechanisms, plasmonics based fiber-optic sensors provide remarkable sensitivity benefiting from their outstanding plasmon–matter interaction. Therefore, surface plasmon resonance (SPR) and localized SPR (LSPR)-based hybrid fiber-optic sensors have captured intensive research attention. Conventionally, SPR- or LSPR-based hybrid fiber-optic sensors rely on the resonant electron oscillations of thin metallic films or metallic nanoparticles functionalized on fiber surfaces. Coupled with the new advances in functional nanomaterials as well as fiber structure design and fabrication in recent years, new solutions continue to emerge to further improve the fiber-optic plasmonic sensors’ performances in terms of sensitivity, specificity and biocompatibility. For instance, 2D materials like graphene can enhance the surface plasmon intensity at the metallic film surface due to the plasmon–matter interaction. Two-dimensional (2D) morphology of transition metal oxides can be doped with abundant free electrons to facilitate intrinsic plasmonics in visible or near-infrared frequencies, realizing exceptional field confinement and high sensitivity detection of analyte molecules. Gold nanoparticles capped with macrocyclic supramolecules show excellent selectivity to target biomolecules and ultralow limits of detection. Moreover, specially designed microstructured optical fibers are able to achieve high birefringence that can suppress the output inaccuracy induced by polarization crosstalk and meanwhile deliver promising sensitivity. This review aims to reveal and explore the frontiers of such hybrid plasmonic fiber-optic platforms in various sensing applications.

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Plasmonics on Optical Fiber Platforms

Cited by 3 publications

References 40 publications

Gaussian free field in the iso-height random islands tuned by percolation model

Gaussian free field in the iso-height random islands tuned by percolation model

Gaussian Free Field in the background of correlated random clusters, formed by metallic nanoparticles

Hybrid Plasmonic Fiber-Optic Sensors

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