Numerical modeling and performance analysis of underlap gate cavity-integrated reconfigurable silicon nanowire Schottky barrier transistor biosensors.

This study presents the numerical modeling of an underlap gate cavity-integrated reconfigurable silicon nanowire Schottky barrier transistor (UGC-RSiNW SBT) that features a gate-drain underlap region, specifically designed for biosensing applications. The proposed device features a cavity under the control gate on the source side, allowing the immobilization of neutral and charged biomolecules having different dielectric constants. The program gate is specifically placed over the channel-drain Schottky junction to reduce the ambipolar behavior of the device. Using the 2D Poisson equation, we model electrostatic characteristics such as electric potential, threshold voltage, electric field, and drain current. Biomolecules in a cavity can be detected and identified by measuring the variation in threshold voltage ( V Th ), which is caused by the biomolecules' interactions with the local electric field and their influence on charge carrier transport. Simulation results using Silvaco TCAD tools demonstrate significant improvements in sensitivity of the proposed biosensor as compared to conventional RFET biosensors. The study shows a 97.91% increase in the V Th sensitivity of the device for the N-channel and a 16% improvement for the P-channel. The drain current sensitivity and the linearity of proposed biosensor is enhanced upto the values of 2792 and 0.997 respectively in n-mode configuration whereas in p-mode configuration, the drain current sensitivity and the linearity comes out to be 968 and 0.995 respectively. These high sensitivity and linearity values make this biosensor superior to the existing state-of-the-art biosensors. The simulated results were validated when compared with existing literature, confirming the effectiveness of the Silvaco TCAD tool in accurately modeling the biosensor's performance These findings offer valuable insights for developing highly sensitive biosensors for healthcare and biotechnology applications. [ABSTRACT FROM AUTHOR]