A calibration method for nanowire biosensors to suppress device-to-device variation

Abstract

Nanowire/nanotube biosensors have stimulated significant interest; however, the inevitable device-to-device variation in the biosensor performance remains a great challenge. We have developed an analytical method to calibrate nanowire biosensor responses that can suppress the device-to-device variation in sensing response significantly. The method is based on our discovery of a strong correlation between the biosensor gate dependence (dI(ds)/dV(g)) and the absolute response (absolute change in current, DeltaI). In(2)O(3) nanowire-based biosensors for streptavidin detection were used as the model system. Studying the liquid gate effect and ionic concentration dependence of strepavidin sensing indicates that electrostatic interaction is the dominant mechanism for sensing response. Based on this sensing mechanism and transistor physics, a linear correlation between the absolute sensor response (DeltaI) and the gate dependence (dI(ds)/dV(g)) is predicted and confirmed experimentally. Using this correlation, a calibration method was developed where the absolute response is divided by dI(ds)/dV(g) for each device, and the calibrated responses from different devices behaved almost identically. Compared to the common normalization method (normalization of the conductance/resistance/current by the initial value), this calibration method was proven advantageous using a conventional transistor model. The method presented here substantially suppresses device-to-device variation, allowing the use of nanosensors in large arrays.

Figure 1

a) An optical micrograph of a 3″ wafer with multiple biosensor chips. b) A photograph of one chip with an inset showing an optical image of the interdigitated electrodes. c) A SEM image of multiple In₂O₃ nanowires between the source and drain electrodes. The inset is a magnified image of an individual nanowire. d) I_ds-V_ds plots under different V_g. e) Schematic diagram of the sensing setup illustrating an FET biosensor device operated by the liquid gate. f) Typical plots of the change in current versus time for three devices which were exposed to streptavidin (S-Av) of 100 nM at t = 100 s in 0.01× PBS. V_ds of 0.2 V and V_g of 0.6 V were used for the measurement.

Figure 2

a) I_ds versus V_g using the liquid gate before (red) and after (blue) exposure to streptavidin of 100 nM in 0.01× PBS. b) Plots of current versus time in PBS of different levels of dilution. The devices were exposed to 100 nM streptavidin at t = 100 s. V_ds of 0.2 V and V_g of 0.6 V were used for the measurement. c) Relative responses extracted from Figure 2b plotted against the logarithm of the ionic concentration.

Figure 3

Plots of absolute response versus dI_ds/dV_g for five devices. The solid line represents the fitting assuming a linear correlation, which yielded a correlation coefficient of ~0.98.

Figure 4

a) Plots of the absolute responses for five devices versus the device identification number before the calibration. b) Same plots after the calibration. The vertical axis was switched to the calibrated response. c) Same plots after the conventional normalization. The vertical axis is the normalized response.

Figure 5

Plots of the calibrated response using the data shown in Figure 1d.