Performance Optimization of High-κ Engineered TM-DG-InP/GaAs-TFET for Ultra-Sensitive Biosensing Applications: Mechanistic Insights and TCAD Simulation Analysis

This study presents a computational model for an advanced dopamine biosensing platform based on a halo-doped dual-gate tunnel field-effect transistor (DGTFET) incorporating high-k dielectrics and a silicon carbide (SiC) substrate. The proposed model utilizes a heterostructure composed of indium phosphide (InP) and gallium arsenide (GaAs), optimized for high-sensitivity biomolecule detection. The computational framework is developed by solving the two-dimensional Poisson equation within a scaled graphene channel region, ensuring boundary conditions that enhance sensing performance. Key structural enhancements, including halo doping and the integration of high-k dielectric materials such as titanium dioxide (TiO 2 ), are implemented to improve the device’s electrical behaviour. The proposed DGTFET exhibits significant performance improvements, including optimized electric field distribution, reduced drain-induced barrier lowering, controlled threshold voltage roll-off, and enhanced channel potential. The device achieves an exceptionally high I ON /I OFF ratio of 10 10 , with an off-state current minimized to approximately 10 −15 A μm −1 and an on-state current increased to around 10 −5 A μm −1 . These advancements make the halo-doped DGTFET highly suitable for ultra-sensitive dopamine detection. Moreover, the optimized subthreshold characteristics further enhance its capability for detecting low-concentration biomolecules. The analytical findings are corroborated through Silvaco TCAD simulations, validating the model’s accuracy and effectiveness in real-world biosensing applications.