Single-electron counting statistics and DNA-based biosensors

Abstract With the fast-shrinking of the transistor dimensions, the low-frequency noise level considerably increases emerging as an important parameter for the design of advanced devices for information technologies. Single-trap phenomena (STP) is a promising approach for the low-frequency noise suppression technique in nanotransistor biosensors by considering trapping/detrapping noise as a signal. We show a noise reduction mechanism offered by STP in nanoscale devices making the analogy with stochastic resonance effect found in biological systems by considering a single trap as a bistable stochastically driven nonlinear system which transmits and amplifies the weak signals. The STP noise suppression effect is experimentally demonstrated for the fabricated liquid-gated nanosensors exploiting STP. We found the optimal conditions and parameters including optimized gate voltages to implement a stochastic switching effect for the extraction of useful signals from the background noise level. These results should be considered for the development of reliable and highly sensitive nanoscale biosensors.

AbstractTransistor biosensors are mass-fabrication-compatible devices of interest for point of care diagnosis as well as molecular interaction studies. While the actual transistor gates in processors reach the sub-10 nm range for optimum integration and power consumption, studies on design rules for the signal-to-noise ratio (S/N) optimization in transistor-based biosensors have been so far restricted to 1 µm2 device gate area, a range where the discrete nature of the defects can be neglected. In this study, which combines experiments and theoretical analysis at both numerical and analytical levels, we extend such investigation to the nanometer range and highlight the effect of doping type as well as the noise suppression opportunities offered at this scale. In particular, we show that, when a single trap is active near the conductive channel, the noise can be suppressed even beyond the thermal limit by monitoring the trap occupancy probability in an approach analog to the stochastic resonance effect used in biological systems.