Demonstration of cross reaction in hybrid graphene oxide/tantalum dioxide guided mode resonance sensor for selective volatile organic compound

Author:

TANTIWANICHAPAN KHWANCHAI1,JOLIVOT ROMUALD2,JOMPHOAK APICHAI1,SRIS NANTARAT1,CHANANONNAWATHORN CHANUNTHORN1,LERTVANITHPOL TOSSAPORN1,HORPRATHUM MATI1,BOONRUANG SAKOOLKAN1

Affiliation:

1. National Electronics and Computer Technology Center (NECTEC)

2. Bangkok University

Abstract

Abstract This paper experimentally demonstrates a crossed reaction of pure and hybrid graphene oxide (GO)/tantalum dioxide (TaO2) as a volatile organic compound (VOC) absorber in a guided mode resonance (GMR) sensing platform. The proposed GMR platform has a porous TaO2 film as the main guiding layer, allowing for more molecular adsorption and enhanced sensitivity. GO is applied on top as an additional VOC absorber to increase the selectivity. The hybrid sensing mechanism is introduced by varying the concentration of the GO aqueous solution. The experimental results show that the pure TaO2-GMR has a high tendency to adsorb most of the tested VOC molecules, with the resonance wavelength shifting accordingly to the physical properties of the VOCs (molecular weight, vapor pressure, etc.). The largest signal appears in the large molecule such as toluene, and its sensitivity is gradually reduced in the hybrid sensors. At the optimum GO concentration of 3 mg/mL, the hybrid GO/TaO2 -GMR is more sensitive to methanol, while the pure GO sensor coated with GO at 5 mg/mL is highly selective to ammonia. The sensing mechanisms are verified using the distribution function theory (DFT) to simulate the molecular absorption, along with the measured functional groups measured on the sensor surface by the Fourier transform infrared spectroscopy (FTIR). The crossed reaction of these sensors is further analyzed by means of machine learning, specifically the principal component analysis (PCA) method and decision tree algorithm. The results show that this sensor is a promising candidate for quantitative and qualitative VOCs detection in sensor array platform.

Publisher

Research Square Platform LLC

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