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Low-Concentration Ethanol Vapor Sensing With Nanostructured Porous Silicon Interferometers Using Interferogram Average Over Wavelength Reflectance Spectroscopy

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Herein, we report low-concentration ethanol vapor detection with nanostructured porous silicon (PSi) interferometers using interferogram average over wavelength reflectance spectroscopy (IAWRS), a novel interferometric technique recently developed for ultrasensitive (bio)sensing… Click to show full abstract

Herein, we report low-concentration ethanol vapor detection with nanostructured porous silicon (PSi) interferometers using interferogram average over wavelength reflectance spectroscopy (IAWRS), a novel interferometric technique recently developed for ultrasensitive (bio)sensing applications in liquid using miniaturized integrated interferometers. Ethanol vapors at concentrations of 100, 500, and 1000 ppm (in synthetic dry air) are reliably monitored in real-time using IAWRS by monitoring changes on the reflectance spectrum of PSi interferometers after ethanol physisorption onto the nanopore surface. Good signal-to-noise ratio, high sensitivity, and low resolution are achieved at any of the tested concentrations, leading to a theoretical detection limit (DL) of 0.9 ppm. Fast response times of a few tens of seconds are estimated from time-resolved sensorgrams, both for adsorption and desorption, which confirm that physisorption takes place into the nanopores. Capillary condensation of ethanol in the pores of our PSi interferometers is further ruled out using the Kelvin theory, at least at the concentrations tested in this paper. These results represent a remarkable improvement compared to the state-of-the-art literature on gas/vapor optical sensing using nanostructured PSi, according to which sub-ppm DLs can only be achieved exploiting either capillary condensation in the nanopores or through the assembling PSi-polymer composites.

Keywords: ethanol vapor; ethanol; spectroscopy; nanostructured porous; low concentration; concentration ethanol

Journal Title: IEEE Sensors Journal
Year Published: 2018

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