Toward Super-Resolution Imaging at Green Wavelengths Employing Stratified Metal-Insulator Metamaterials

Metamaterials (MMs) are subwavelength-structured materials that have been rapidly developed in this century and have various potentials to realize novel phenomena, such as negative refraction, cloaking and super-resolution. Theoretical proposals for super-resolution image transfer using metallic thi...

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Bibliographic Details
Main Author: Masanobu Iwanaga
Format: Article
Language:English
Published: MDPI AG 2015-05-01
Series:Photonics
Subjects:
Online Access:http://www.mdpi.com/2304-6732/2/2/468
Description
Summary:Metamaterials (MMs) are subwavelength-structured materials that have been rapidly developed in this century and have various potentials to realize novel phenomena, such as negative refraction, cloaking and super-resolution. Theoretical proposals for super-resolution image transfer using metallic thin films were experimentally demonstrated at ultraviolet and violet wavelengths from 365 to 405 nm. However, the most preferred wavelengths of optical imaging are green wavelengths around 500 nm, because optical microscopy is most extensively exploited in the area of biotechnology. In order to make the super-resolution techniques using MMs more practical, we propose the design of a stratified metal-insulator MM that has super-resolution image transfer modes at green wavelengths, which we here call hyper modes. The design assumed only Ag and SiO2 as constituent materials and was found employing Bloch-state analysis, which is based on a rigorous transfer-matrix method for the metal-insulator MMs. It is numerically substantiated that the designed stratified metal-insulator metamaterial (SMIM) is capable of forming super-resolution images at the green wavelengths, and optical loss reduction is also studied. We discuss the results derived by the Bloch-state analysis and by effective medium models usually used for the metal-insulator MMs and show that the Bloch-state analysis is more suitable to reproduce the experimental data.
ISSN:2304-6732