Get Computational Nanophotonics: Modeling and Applications PDF

By Sarhan M. Musa

ISBN-10: 1466558768

ISBN-13: 9781466558762

ISBN-10: 1466558784

ISBN-13: 9781466558786

''Written in a way that's simply digestible to newcomers and precious to pro pros, this booklet introduces the main suggestions of computational Finite distinction Time area (FDTD) process utilized in nanotechnology. It covers destiny purposes of nanotechnology in technical in addition to new advancements and interdisciplinary study in engineering, technological know-how, and drugs. It contains an summary of Read more...

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Extra info for Computational Nanophotonics: Modeling and Applications

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Optical packet switching (OPS) [28] is inevitably a platform providing arbitrarily fine transmission and switching granularity, toward a flexible and efficient bandwidth. The implementation of OPS is challenging because of the significant problems in the required underlying photonics technology. The realization of OPS requires practical and cost-effective implementations for optical buffering and all-optical photonic switches that can perform all-optical packet address recognition [29]. Optical packet header recognition relies on specially designed Bragg 26 Computational Nanophotonics: Modeling and Applications gratings [30,31].

Coupled triangular nanoprisms have been investigated in [20,21]. Resonant excitation of the quadrupolar surface plasmon mode of the nanoprisms increases Raman scattering intensity from the substrate as the distance between the nanoparticle pairs decreases, as reported in [22]. Indeed, the authors used finite-element modeling, and plasmon coupling theory indicates that symmetry is reduced as the nanoparticles approach, resulting in increased dipole–quadrupole coupling. The plasmonic properties of single silver triangular nanoprisms are investigated using dark-field optical microscopy and spectroscopy, and they observed two distinct localized surface plasmon resonances (LSPR) in [23,24].

The design and optimization process can be quite complex and generally deals with pure physical properties and parameters of the amplifying systems, such as fiber’s composition, fiber’s refractive-index contrast, core radius, fiber length, pumping power, and wavelength. GAs have been applied for the optimization of an active erbium-doped fiber and the EDFA [24]. In GA optimization, a multistage EDFA with complex structures is employed to obtain flattening-based filters [25]. The combination of the gain-flattening issues in the design process can produce a quite complex multi-objective optimization problem.

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Computational Nanophotonics: Modeling and Applications by Sarhan M. Musa

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