Ion-Selective Membrane-Coated Graphene-Hexagonal Boron Nitride Heterostructures for Field-Effect Ion Sensing.

An intrinsic ion sensitivity exceeding the Nernst-Boltzmann limit and an sp 2 -hybridized carbon structure make graphene a promising channel material for realizing ion-sensitive field-effect transistors with a stable solid-liquid interface under biased conditions in buffered salt solutions. Here, we examine the performance of graphene field-effect transistors coated with ion-selective membranes as a tool to selectively detect changes in concentrations of Ca2+, K+, and Na+ in individual salt solutions as well as in buffered Locke's solution. Both the shift in the Dirac point and transconductance could be measured as a function of ion concentration with repeatability exceeding 99.5% and reproducibility exceeding 98% over 60 days. However, an enhancement of selectivity, by about an order magnitude or more, was observed using transconductance as the indicator when compared to Dirac voltage, which is the only factor reported to date. Fabricating a hexagonal boron nitride multilayer between graphene and oxide further increased the ion sensitivity and selectivity of transconductance. These findings incite investigating ion sensitivity of transconductance in alternative architectures as well as urge the exploration of graphene transistor arrays for biomedical applications.

Ion Sensing with Solution-Gated Graphene Field-Effect Sensors in the Frequency Domain.

Here, we examine the concept of frequency domain sensing with solution-gated graphene field-effect transistors, where a sine wave of primary frequency (1f) was applied at the gate and modulation of the power spectral density (PSD) of the drain-source current at 1f, 2f, and 3f was examined as the salt in the gate electrolyte was switched from KCl to CaCl2, and their concentrations were varied. The PSD at 1f, 2f, and 3f increased with the concentration of KCl or CaCl2, with the PSD at 1f being the most sensitive. We further correlated these changes to the shift in Dirac point. Switching the graphene substrate from oxide to hexagonal boron nitride, led to an improved device-to-device reproducibility and a significant reduction of noise, which translated to a higher signal-to-noise ratio and resolution in sensing salt concentrations. The signal-to-noise ratio at 1f was found to be a logarithmic function of KCl or CaCl2 concentration in the 0.1 to 1000 mM range.

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.