Deriving a novel methodology for Nano-BioFETs and analyzing the effect of high-k oxides on the amino-acids sensing application

In this paper, a novel methodology is presented with the analytical simulations of BioFETs using the Gouy-Chapman-Stern and Modified Site-binding model. The derived approach is used to detect different amino acids such as Arginine (R), Aspartic Acid (D) and Proline (P), functionalized with the help of a linker over the gate-oxide. The performance of the BioFETs is optimized while analyzing the effect of high-k dielectrics as the gate oxide. High-k oxides are responsible for tuning the parameters such as sensitivity, surface potential and intrinsic buffer capacity. The variation of differential capacitance with the second gradient of drain current and surface potential are used to identify the signatures of different amino acids. The proposed method can be helpful in defining an efficient method for protein sequencing.