Reusable macroporous photonic crystal-based ethanol vapor detectors by doctor blade coating.
This research reports the development of sensitive and reversible vapor detection by using three-dimensional macroporous photonic crystals. A scalable and roll-to-roll compatible doctor blade coating technology is utilized to fabricate flexible macroporous poly(ethoxylated trimethylolpropane triacrylate) (PETPTA) films with hexagonal close-packed pores which are interconnected. The pores are then coated with a layer of poly(2-hydroxyethyl methacrylate) (PHEMA) to create macroporous PHEMA/PETPTA films. The condensation of vapors in the PHEMA coated macroporous films leads to the increase of both the PHEMA swelling degree and the effective refractive index of the diffractive medium, resulting in the red-shift and amplitude reduction of the optical stop bands. The optical measurements reveal that the diffraction from the as-prepared macroporous photonic crystals sensitively monitors the vapor pressure of ethanol since the PHEMA layer displays a great volume dependence on ethanol due to a decreased Flory-Huggins mixing parameter. The dependence of the diffraction wavelength on vapor pressure and the reproducibility of vapor sensing have also been investigated in this study.
Department of Chemical Engineering, National Chung Hsing University, 145 Xingda Road, Taichung City 40227, Taiwan.
Ya-Ling
YL
Ko
Department of Civil Engineering, National Chung Hsing University, 145 Xingda Road, Taichung City 40227, Taiwan.
Hui-Ping
HP
Tsai
Department of Environmental Engineering, National Chung Hsing University, 145 Xingda Road, Taichung City 40227, Taiwan.
Kun-Yi
KY
Lin
Department of Chemical Engineering, National Chung Hsing University, 145 Xingda Road, Taichung City 40227, Taiwan.
Ying-Chu
YC
Chen
Department of Chemical Engineering, National Chung Hsing University, 145 Xingda Road, Taichung City 40227, Taiwan. Electronic address: hyang@dragon.nchu.edu.tw.
Hongta
H
Yang
Bragg diffraction; Photonic crystals; Reusable; Self-assembly; Vapor detection