Strongly Iridescent Hybrid Photonic Sensors Based on Self-Assembled Nanoparticles for Hazardous Solvent Detection

Facile detection and the identification of hazardous organic solvents are essential for ensuring global safety and avoiding harm to the environment caused by industrial wastes. Here, we present a simple method for the fabrication of silver-coated monodisperse polystyrene nanoparticle photonic struct...

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Bibliographic Details
Main Authors: Ayaka Sato, Yuya Ikeda, Koichi Yamaguchi, Varun Vohra
Format: Article
Language:English
Published: MDPI AG 2018-03-01
Series:Nanomaterials
Subjects:
Online Access:http://www.mdpi.com/2079-4991/8/3/169
Description
Summary:Facile detection and the identification of hazardous organic solvents are essential for ensuring global safety and avoiding harm to the environment caused by industrial wastes. Here, we present a simple method for the fabrication of silver-coated monodisperse polystyrene nanoparticle photonic structures that are embedded into a polydimethylsiloxane (PDMS) matrix. These hybrid materials exhibit a strong green iridescence with a reflectance peak at 550 nm that originates from the close-packed arrangement of the nanoparticles. This reflectance peak measured under Wulff-Bragg conditions displays a 20 to 50 nm red shift when the photonic sensors are exposed to five commonly employed and highly hazardous organic solvents. These red-shifts correlate well with PDMS swelling ratios using the various solvents, which suggests that the observable color variations result from an increase in the photonic crystal lattice parameter with a similar mechanism to the color modulation of the chameleon skin. Dynamic reflectance measurements enable the possibility of clearly identifying each of the tested solvents. Furthermore, as small amounts of hazardous solvents such as tetrahydrofuran can be detected even when mixed with water, the nanostructured solvent sensors we introduce here could have a major impact on global safety measures as innovative photonic technology for easily visualizing and identifying the presence of contaminants in water.
ISSN:2079-4991