Physics of sensing for graphene solution gated field effect transistors

Abstract

Graphene is a promising material for chemical sensing applications and many studies have focused on incorporating graphene into \sgfet s sensors. The purpose of this work is to get a deeper understanding of the physics governing the surface interaction of graphene in \sgfet s with ions and charged molecules. With a clearer understanding of how these interactions register in the conductivity of graphene, it then may be possible to design the ultrasensitive sensors that are often predicted to be possible when using graphene.

Epitaxial graphene (EG) and graphene produced by chemical vapor deposition (CVD) were used to fabricate \sgfet s that were tested under different ionic strength conditions and concentrations of charged proteins. To get a clearer picture of the electrostatic gating effect in ionic solutions, we analyzed our data combining two models: the electrical double layer model, which accounts for the distribution of ions inside the solution, and a ionization model that accounts for ionizable groups on the graphene surface. This gave us an insight into the influence of charged groups fixed to the surface on the gating effect which is fundamental to the performance of \sgfet s as sensors.

Using our experimental data we were also able to estimate the density of charged impurities in two carrier density regimes. For high densities, we found a correlation between our estimated impurities and the surface charge that suggests that the ionizable groups act as impurities. For small carrier densities, we modeled the carriers using a self-consistent approximation (SCA). The impurities estimated from the SCA model do not seem to be related to the ionizable groups and so the origin of the conductivity for small density seems to be originated by the permanently charged impurities only.

Our estimation of the charged impurities for our charged-protein adsorption experiments showed a relation between their values and the protein concentration. This shows that the proteins interact with the graphene as charged impurities. Overall, our experiments allowed us to gain a deeper understanding of the interaction of charged particles with graphene. The analysis performed in this work gives a guide for the development of graphene \sgfet s sensors by engineering the impurities at the surface to optimize the sensitivity. The design of receptors for specific sensing that do not require charged targets is possible with engineering the charge that the receptor presents to graphene when the analyte concentration changes.