Graphene is a promising material for vapor sensor applications because of its potential to be functionalized for specific chemical gases. In this work, we present a graphene gas sensor that uses single-stranded DNA (ssDNA) molecules as its sensing agent. We investigate the characteristics of graphene field effect transistors (FETs) coated with different ssDNAs. The sensitivity and recovery rate for a specific gas are modified according to the differences in the DNA molecules’ Guanine (G) and Cytosine (C) content. ssDNA-functionalized devices show a higher recovery rate compared to bare graphene devices. Pattern analysis of a 2-by-2 sensor array composed of graphene devices functionalized with different-sequence ssDNA enables identification of NH3, NO2, CO, SO2 using Principle Component Analysis (PCA).
Graphene is a promising material for its exceptional electrical and mechanical properties. Starting with the initial demonstration of isolating a single graphene sheet from graphite, much progress has been made in realizing graphene based devices for diverse applications. Here, we introduce an experiment in which the electrical properties of graphene are modified by coating different-sequence single-stranded deoxyribonucleic acid (ssDNA) molecules. We fabricated a graphene-field effect transistor (FET) by transferring CVD graphene on copper foil onto a Si/SiO2 wafer. A passivation layer opened up windows on the surface of the graphene to enable interaction with liquid buffers. ssDNA molecules with different base sequences were coated onto the active graphene channels. We observed a variation in the Dirac voltage of the ssDNA-coated graphene FETs according to the ssDNA base sequences. Electrical control of the graphene FET is obtained via gating effect of the deposited ssDNAs. We conduct a systematic study of this ssDNAinduced gating effect with different base sequences, concentrations, and lengths of molecules, leading to extraction of characteristic parameters of the graphene FET accordingly.
Arrays of partially selective chemical sensors have been the focus of extensive research over the past decades because of their potential for widespread application in ambient air monitoring, health and safety, and biomedical diagnostics. Especially, vapor sensor arrays based on functionalized nanomaterials have shown great promise with their high sensitivity by dimensionality and outstanding electronic properties. Here, we introduce experiments where individual vapors and mixtures of them are examined by different chemical sensor arrays. The collected data from those sensor arrays are further analyzed by a principal component analysis (PCA) and targeted vapors are recognized based on prepared database.