Spatially Variant Periodic Structures In Electromagnetics

Keywords

Functionally graded; Metamaterials; Metasurfaces; Photonic crystals; Spatially variant; Transformation optics

Abstract

Spatial transforms are a popular technique for designing periodic structures that are macroscopically inhomogeneous. The structures are often required to be anisotropic, provide a magnetic response, and to have extreme values for the constitutive parameters in Maxwell's equations. Metamaterials and photonic crystals are capable of providing these, although sometimes only approximately. The problem still remains about how to generate the geometry of the final lattice when it is functionally graded, or spatially varied. This paper describes a simple numerical technique to spatially vary any periodic structure while minimizing deformations to the unit cells that would weaken or destroy the electromagnetic properties. New developments in this algorithm are disclosed that increase efficiency, improve the quality of the lattices and provide the ability to design aplanatic metasurfaces. The ability to spatially vary a lattice in this manner enables new design paradigms that are not possible using spatial transforms, three of which are discussed here. First, spatially variant self-collimating photonic crystals are shown to flow unguided waves around very tight bends using ordinary materials with low refractive index. Second, multi-mode waveguides in spatially variant band gap materials are shown to guide waves around bends without mixing power between the modes. Third, spatially variant anisotropic materials are shown to sculpt the near-field around electric components. This can be used to improve electromagnetic compatibility between components in close proximity.

Publication Date

8-28-2015

Publication Title

Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Volume

373

Issue

2049

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1098/rsta.2014.0359

Socpus ID

84938151629 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84938151629

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