Few-Flakes Reduced Graphene Oxide Sensors for Organic Vapors with a High Signal-to-Noise Ratio

This paper reports our findings on how to prepare a graphene oxide-based gas sensor for sensing fast pulses of volatile organic compounds with a better signal-to-noise ratio. We use rapid acetone pulses of varying concentrations to test the sensors. First, we compare the effect of graphene oxide deposition method (dielectrophoresis versus solvent evaporation) on the sensor’s response. We find that dielectrophoresis yields films with uniform coverage and better sensor response. Second, we examine the effect of chemical reduction. Contrary to prior reports, we find that graphene oxide reduction leads to a reduction in sensor response and current noise, thus keeping the signal-to-noise ratio the same. We found that if we sonicated the sensor in acetone, we created a sensor with a few flakes of reduced graphene oxide. Such sensors provided a higher signal-to-noise ratio that could be correlated to the vapor concentration of acetone with better repeatability. Modeling shows that the sensor’s response is due to one-site Langmuir adsorption or an overall single exponent process. Further, the desorption of acetone as deduced from the sensor recovery signal follows a single exponent process. Thus, we show a simple way to improve the signal-to-noise ratio in reduced graphene oxide sensors.

Graphene on SiC Substrate as Biosensor: Theoretical Background, Preparation, and Characterization

This work is devoted to the development and optimization of the parameters of graphene-based sensors. The graphene films used in the present study were grown on semi-insulating 6H-SiC substrates by thermal decomposition of SiC at the temperature of ~1700 °C. The results of measurements by Auger and Raman spectroscopies confirmed the presence of single-layer graphene on the silicon carbide surface. Model approach to the theory of adsorption on epitaxial graphene is presented. It is demonstrated that the Green-function method in conjunction with the simple substrate models permit one to obtain analytical results for the charge transfer between adsorbed molecules and substrate. The sensor structure was formed on the graphene film by laser. Initially, a simpler gas sensor was made. The sensors developed in this study demonstrated sensitivity to the NO₂ concentration at the level of 1–0.01 ppb. The results obtained in the course of development and the results of testing of the graphene-based sensor for detection of protein molecules are also presented. The biosensor was fabricated by the technology previously developed for the gas sensor. The working capacity of the biosensor was tested with an immunochemical system constituted by fluorescein and monoclonal antibodies (mAbs) binding this dye.

UV Illumination as a Method to Improve the Performance of Gas Sensors Based on Graphene Field-Effect Transistors

The ability to detect and recognize airborne chemical species is essential to enable applications in security, health, and environmental monitoring. Here, we report a sensing platform based on graphene field-effect transistor (GFET) devices combined with optical illumination for the detection of volatile compounds. We compare the change in resistance of GFET sensors upon exposure to analytes such as ethanol, dimethyl methylphosphonate (DMMP), and water vapors with and without the presence of a local illuminating ultraviolet (UV) light-emitting diode (LED). Our results show that UV illumination acts as a control knob for the electronic transport properties of graphene, increasing the device's response to ethanol, water, and DMMP, up to a factor of 54, and enabling ppb-level detection of DMMP at 800 ppb without chemical functionalization of the graphene layer. The sensing response can be optimized to reveal an analyte-specific interplay between the induced changes in carrier concentration and mobility of the GFET. These findings provide a pathway to enhancing the sensitivity of GFET sensors and a differentiation channel to improve their selectivity.