Impact of structural and material parameters on sensitivity of engineered N-pocket DGTFET biosensors

Biosensors play a crucial role in medical, agricultural, food, and environmental monitoring, where high sensitivity and label-free detection are essential. Conventional FET-based biosensors exhibit limitations including elevated subthreshold slope, leakage current, and inadequate detection of neutral biomolecules. Tunnel FETs (TFETs) utilise a band-to-band tunnelling mechanism, providing steep switching characteristics and low-power operation; however, their practical application is constrained by low ON-current and ambipolar conduction issues. This study proposes and analyses a material developed double-gate TFET featuring an N-pocket and AlGaAs-based heterostructure, utilising Silvaco ATLAS simulations to enhance biosensing capabilities. The device incorporates GaSb–AlGaAs–GaAs heterostructures, dual-gate control, bilayer dielectrics, and optimised doping profiles to enhance tunnelling efficiency and sensitivity. The results indicate that the proposed design attains a subthreshold swing of 9.2 mV/dec, an I on /I off ratio of 4 × 10 13 , and a reduced threshold voltage of 0.32 V, surpassing traditional silicon-based and non-pocket devices. Sensitivity analysis indicates a notable improvement with rising dielectric constant, molar fraction and positive biomolecule conditions, whereas negative biomolecules diminish sensitivity as anticipated due to repulsive interactions. The N-pocket DGTFET exhibits stable and reproducible sensitivity relative to conventional and pocket-less devices, with a doping dimension of 3 nm × 10 nm providing an optimal balance between sensitivity and stability. The device demonstrates a significant enhancement in selectivity, achieving sensitivity values of up to 1.20 × 10 5 , which exceeds the performance of previously reported TFET biosensors by multiple orders of magnitude. The findings demonstrate that the modified DGTFET serves as a reliable, energy-efficient, and highly sensitive platform for label-free biomolecule detection.