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Effective Surface Susceptibility Models for Periodic Metafilms Within the Dipole Approximation Technique

A.I. Dimitriadis1, N.V. Kantartzis1 and T.D. Tsiboukis1

1 Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece.

Computers, Materials & Continua 2014, 39(3), 231-265. https://doi.org/10.3970/cmc.2014.039.231

Abstract

The most important surface susceptibility models for the electromagnetic characterization of periodic metafilms, based on the dipole approximation method, are systematically analyzed in this paper. Specifically, two well-known techniques, which lead to a set of local effective surface parameters, are investigated along with a new dynamic non-local modeling algorithm. The latter formulation is properly expanded, in order to be applicable for any arbitrary periodic metafilm, irrespective of its way of excitation. The featured schemes are then directly compared toward their ability to efficiently predict the reflection and transmission properties of several lossless and lossy metafilms. Their outcomes are carefully verified through an assortment of numerical simulations, while novel physical insights of the observed phenomena and diverse implementation aspects of the models are extensively discussed

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APA Style
Dimitriadis, A., Tsiboukis, N.K.A.T. (2014). Effective surface susceptibility models for periodic metafilms within the dipole approximation technique. Computers, Materials & Continua, 39(3), 231-265. https://doi.org/10.3970/cmc.2014.039.231
Vancouver Style
Dimitriadis A, Tsiboukis NKAT. Effective surface susceptibility models for periodic metafilms within the dipole approximation technique. Comput Mater Contin. 2014;39(3):231-265 https://doi.org/10.3970/cmc.2014.039.231
IEEE Style
A. Dimitriadis and N.K.A.T. Tsiboukis, “Effective Surface Susceptibility Models for Periodic Metafilms Within the Dipole Approximation Technique,” Comput. Mater. Contin., vol. 39, no. 3, pp. 231-265, 2014. https://doi.org/10.3970/cmc.2014.039.231



cc Copyright © 2014 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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