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Abstract
A porous silicon thin film photonic crystal (rugate) sample with both a radial gradient in the rugate reflectance band wavelength and two spatially separated pore-wall surface chemistries (methylated and oxidized) was monitored by hyperspectral and color imaging while it was dosed with vapors of acetone, ethanol, heptane, 2-propanol, and toluene at concentrations ranging from 100 to 3,000 mg m−3. The shift in the wavelength of the rugate reflectance band maximum at each position along a transect across the two surface chemistries, as derived from the hyperspectral imaging, could discriminate between the different solvents and concentrations of solvents, while the change in hue derived from the color camera data along an analogous transect did not provide discrimination. The discrimination between solvents was mainly due to the two different surface chemistries, and the gradient associated with the change in the rugate reflectance band wavelength did not affect the selectivity significantly. There was spatial variability in the spectral and color responses along the transect independent of the overall rugate reflectance band wavelength gradient and pore-wall surface chemistries, and this was attributed to factors such as the presence of striations in the silicon wafer from which the porous silicon was prepared.
Highlights
Porous silicon photonic crystal substrates can act as optical transducers for the detection of volatile organic compounds (VOCs) that sorb or capillary condense within the pores
Previous studies have investigated enhancing the selectivity of porous silicon sensors to detect and discriminate a wide range of vapors
Different solvent vapors were used in this study, and were grouped into hydrophilic and hydrophobic vapors
Summary
Porous silicon photonic crystal (rugate) substrates can act as optical transducers for the detection of volatile organic compounds (VOCs) that sorb or capillary condense within the pores. Most previous studies have monitored the response of porous silicon photonic crystal substrates to environmental conditions either via point measurements (e.g., Ruminski et al, 2010, 2011; Kelly et al, 2011b; Jalkanen et al, 2014) or using measurements integrated across an area of the porous silicon (e.g., Ariza-Avidad et al, 2014). An alternative approach is to individually monitor selected spatial areas across the substrate, and combine those individual responses using multivariate analysis techniques. This approach can probe variability in the response due to deliberately imposed changes (e.g., surface chemistry or pore-size gradients) or other causes of heterogeneity (e.g., uncontrolled pore-size variations due to the substrate or experimental conditions). Wu et al (2013) prepared uniformly-etched porous silicon and used a masking technique to prepare sensors that were methylated on one half and oxidized
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