Journal
ACS SENSORS
Volume 6, Issue 5, Pages 1910-1917Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acssensors.1c00261
Keywords
extended gate; floating gate; field-effect transistor; biosensing; electronic detection; modeling
Funding
- National Science Foundation through the National Nano Coordinated Infrastructure Network (NNIN) [ECCS-1542202, ECCS-2025124]
- Michael H. Baker Foundation
- IPRIME
- [NIH T32GM008347]
Ask authors/readers for more resources
Researchers developed a model to predict the sensor response to changes in capacitance and/ or charge at the sensing surface, guiding future device design. Experimental results showed that the model effectively captures the trends of charge signals and capacitance signals on the sensing surface, with some deviation at lower capacitances.
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. 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. 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. 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. 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). 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available