Plasmonic Entities within the Charge Transporting Layer

Wu, Bo; Mathews, Nripan; Sum, Tze-Chien

doi:10.1007/978-981-10-2021-6_4

Cited by 3 publications

(9 citation statements)

References 72 publications

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“…The metal NP behaves as an electric dipole under a uniform static electric field assumption, and its polarizability, α(λ), is derived as:α(λ)=4sans-serifπr3ε(λ)−εd(λ)ε(λ)+2εd(λ) When ε(λ)≈−2εd(λ), the dominator of Equation (2) approaches zero and yields maximum polarization: in order to achieve this condition, the dielectric function (real part) ε(λ) of the NP requires a negative value, where the dielectric function of the surrounding medium is considered as a constant, and the losses (imaginary part) of the NP are assumed to be small [11]. Using the Drude model, the resonance frequency (ωLSP) of a dipolar LSP can be given by [12]:ωLSP=ωp1+εd where ωp is the plasmon frequency of the NP’s material. At the resonance frequency, as shown in Figure 1, the free electrons moved away from their equilibrium p...…”

Section: Localized Surface Plasmon Resonance Sensormentioning

confidence: 99%

A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance

Alharbi

Irannejad

Yavuz

2019

Sensors

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Localized Surface Plasmon Resonance (LSPR) sensors have potential applications in essential and important areas such as bio-sensor technology, especially in medical applications and gas sensors in environmental monitoring applications. Figure of Merit (FOM) and Sensitivity (S) measurements are two ways to assess the performance of an LSPR sensor. However, LSPR sensors suffer low FOM compared to the conventional Surface Plasmon Resonance (SPR) sensor due to high losses resulting from radiative damping of LSPs waves. Different methodologies have been utilized to enhance the performance of LSPR sensors, including various geometrical and material parameters, plasmonic wave coupling from different structures, and integration of noble metals with graphene, which is the focus of this report. Recent studies of metal-graphene hybrid plasmonic systems have shown its capability of promoting the performance of the LSPR sensor to a level that enhances its chance for commercialization. In this review, fundamental physics, the operation principle, and performance assessment of the LSPR sensor are presented followed by a discussion of plasmonic materials and a summary of methods used to optimize the sensor’s performance. A focused review on metal-graphene hybrid nanostructure and a discussion of its role in promoting the performance of the LSPR sensor follow.

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Section: Localized Surface Plasmon Resonance Sensormentioning

confidence: 99%

A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance

Alharbi

Irannejad

Yavuz

2019

Sensors

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“…Simulation of plasmonic SC is one case where the FDTD method has proven its ability to simulate the near and far-field and SPP effects [ 35 ]. Plasmonic SC mainly refers to the use of plasmonic NS to overcome the limitations of third-generation SCs such as OSC and perovskite cells [ 21 , 37 ]. Initially, more attention was paid to the light trapping due to the plasmonic NSs.…”

Section: Theory and Modelingmentioning

confidence: 99%

“…MNSs with various sizes and morphologies have been generally used in photovoltaics to activate plasmonic consequences [ 21 ]. Depending on their position inside OPV, it usually leads to three conventional optical mechanisms, namely (1) light scattering, (2) LSPR, (3) surface plasmon polaritons (SPPs).…”

Section: Introductionmentioning

confidence: 99%

“…However, MNPs can be the origin of non-optical effects inside the cell. They can have other positive or negative effects on solar cell (SC) performance, such as electrical effects (such as plasmon-induced charge separation, change in surface resistance, change in electron–hole transition, change in surface recombination), and changing layer morphology [ 9 , 11 , 21 ]. Therefore, by considering the various effects mentioned above, improving the performance of the OSCs through metallic NSs can be a complex mechanism.…”

Section: Introductionmentioning

confidence: 99%

“…The potential plasmonic benefits of Al-NS over Ag and Au depend on its plasmonic wavelengths. But, that is a function of the size, shape, and surrounding material [ 21 ]. Therefore, determining the plasmonic wavelengths and usability of MNS in an SC is of great importance.…”

Section: Introductionmentioning

confidence: 99%

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Towards realistic modeling of plasmonic nanostructures: a comparative study to determine the impact of optical effects on solar cell improvement

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Plasmonic structures may improve cell performance in a variety of ways. More accurate determining of the optical influence, unlike ideal simulations, requires modeling closer to experimental cases. In this modeling and simulation, irregular nanostructures were chosen and divided into three groups and some modes. For each mode, different sizes of nanoparticles were randomly selected, which could result in pre-determined average particle size and standard deviation. By 3D finite-difference time-domain (3D-FDTD), the optical plasmonic properties of that mode in a solar cell structure were investigated when the nanostructure was added to the buffer/active layer of the organic solar cell. The far- and near-field results were used to compare the plasmonic behavior, relying on the material and geometry. By detailed simulations, Al and Ag nanostructure at the interface of the ZnO/active layer can improve organic solar cell performance optically, especially by the near-field effect. Unlike Au and relative Ag, the Al nanostructured sample showed less parasitic absorption loss. Supplementary Information The online version contains supplementary material available at 10.1007/s10825-021-01829-x.

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Computational modelling of light-matter interaction in aSi with CdSe/ZnS core/shell quantum dots and metal nanoantenna for solar cell applications

et al. 2023

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As the world population rises, energy needs are become critical. Using photovoltaic technologies like amorphous silicon solar cells (aSiSC) to harvest solar power might benefit global concern. Previous research claimed that aSiSCs were modest short-wavelength absorbers. Quantum dot (QD) may be applied to the aSiSC to enhance optical absorptions and electric fields as the QD’s bandgap is tunable, which can cover a broader electromagnetic range. This study aims are to design the 3D aSiSC with QD on the model and to investigate the optical absorption peak, electric field profiles, and light-matter interaction of the models via COMSOL Multiphysics software. From the base model, the optical absorption improved from 736 nm at 41.827% to 46.005% at 642 nm for the aSiQDSC model which developed with 0.5/3.0 nm radius of core/shell cadmium selenide/zinc sulphide (CdSe/ZnS). This study proceeded combining rectangular nanosheets gold and silver nanoantenna (Au and Ag NA) with various gap g of NA to the aSiQDSC models where g = 0.5 nm Ag NA model was presented the higher optical absorption of 47.246% at 650 nm, and electric fields of 2.53×1010 V/nm. Computationally, this ultimate design is ecologically sound for solar cell applications, which allow future direction in renewable energy research and fabrication

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Plasmonic Entities within the Charge Transporting Layer

Cited by 3 publications

References 72 publications

A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance

A Short Review on the Role of the Metal-Graphene Hybrid Nanostructure in Promoting the Localized Surface Plasmon Resonance Sensor Performance

Towards realistic modeling of plasmonic nanostructures: a comparative study to determine the impact of optical effects on solar cell improvement

Computational modelling of light-matter interaction in aSi with CdSe/ZnS core/shell quantum dots and metal nanoantenna for solar cell applications

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