20 The control gate (CG) is not functionalized and is sized to be much larger than FG2, ensuring that the potential drop in the aqueous compartment takes place predominantly at FG2. 19 The sensing pad of the floating gate (FG2) can be functionalized with capture ligands using well-established self-assembled monolayer (SAM) chemistry. This challenge is met by the floating-gate transistor (FGT) design in Figure 1b, 18 also referred to as an extended gate. The lumped capacitance C 2 includes the FG2/aqueous interface and the CG/aqueous interface.įor biosensing applications, the transistor channel is often incompatible with (salty) sensing environments. To show all relevant details, the figure is not to scale. (c) Top-view scheme of the FGT device in (b). (b) Corresponding FGT device with the inverter circuit, where the CG is connected to the right arm of the floating gate (FG2) through the aqueous electrolyte (blue). The semiconductor channel (red) consists of the organic semiconductor poly(3-hexylthiophene) (P3HT) gated by an ion-gel in contact with the floating gate (FG1). The gate voltage ( V G) is applied at the gate pad, the supply voltage ( V DD) is applied across both EGT and the load resistor, and the output voltage ( V OUT) is measured between the channel and the load resistor ( R L). (a) Side-gated EGT device and inverter measurement circuit. To guide future device design, model predictions for a large range of sensing area capacitances and characteristic voltages are provided, enabling the calculation of the optimum sensing area size for maximum charge and capacitance sensitivity.ĭevice layouts for EGTs and FGTs. Experiments reveal that the model captures the inverter gain and charge signals over 3 orders of magnitude variation in the size of the sensing area and the capacitance signals over 2 orders of magnitude but deviates from experiments at lower capacitances of the sensing surface (<1 nF). Self-assembled monolayer (SAM) chemistry and quasi-statically measured resistor-loaded inverters were utilized to obtain experimentally either the capacitance signals (with alkylthiol SAMs) or charge signals (with acid-terminated SAMs) of the FGT. The model predictions were compared to experimental data obtained using a floating-gate (extended gate) electrochemical transistor, a variant of the generic FGT architecture that facilitates low-voltage operation and rapid, simple fabrication using printing. We developed a model, generalizable to many different semiconductor/dielectric materials and channel dimensions, to predict the sensor response to changes in capacitance and/or charge at the sensing surface upon target binding or other changes in surface chemistry. Floating-gate transistors (FGTs) are a promising class of electronic sensing architectures that separate the transduction elements from molecular sensing components, but the factors leading to optimum device design are unknown.
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