Dual-Metal Double-Gate with Low-k/High-k Oxide Stack Junctionless MOSFET for a Wide Range of Protein Detection: a Fully Electrostatic Based Numerical Approach

We investigate the performance of a dielectric modulated dual-metal double-gate with low-k/high-k oxide stack junctionless MOSFET (DM-DG-LK/HK-S JL-MOSFET) based sensor device for successful detection of different protein molecules in dry environment condition, in terms of the absolute and relative change in the threshold voltage (V-th), called V-th-responsivity and V-th-sensitivity, respectively. The influence of work-function difference of the DM-gate along with the position of cavity containing biomolecules, followed by the impact of cavity dimension, on the sensing metrics, have been thoroughly inspected. Furthermore, the optimization of cavity dimension, along with proper DM-gate work-function engineering is done for the wide range of protein detection. For the sensor device, having channel length (L-ch) of 1 mu m, this optimum cavity dimension is found to be (400 nm x 10 nm). It is observed that, the device with L-ch = 1 mu m exhibits superior sensing performance when, along with the source-side cavity, the drain-side gate metal has got higher work-function than the source-side gate metal (i.e., Phi(M2) > Phi(M1)), compared to the case when Phi(M1) > Phi(M2) and the cavity is located near the drain-side. Respective performance enhancements, in terms of percentage improvement of V-th-responsivity and V-th-sensitivity, are found to be 250% and 263% for the detection of Staphylococcal nuclease. Similar trend is found for the sensor devices with L-ch = 50 nm.

Automated summary

This study investigates the performance of a novel dual-metal double-gate junctionless MOSFET sensor device for successful detection of different protein molecules in a dry environment, analyzing the impact of various factors on sensing metrics. Optimal cavity dimensions and DM-gate work-function engineering are found to significantly enhance the detection capabilities for a wide range of proteins, leading to improved sensor performance. The study demonstrates superior sensitivity and responsivity when specific conditions are met, resulting in substantial percentage improvements for the detection of specific protein molecules.