Detection and amplification of capacitance- and charge-based signals using printed electrolyte gated transistors with floating gates

Thomas, M.; Dorfman, Kevin D.; Frisbie, C. Daniel

doi:10.1088/2058-8585/ab4dcf

Cited by 6 publications

(16 citation statements)

References 31 publications

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“…Second, in the linear transistor regime, the inverter circuit operates at a very small bias, V S − V OUT . The current inferred from eq 1 is low and plateaus at very negative gate voltages, inconsistent with previous observations of a clear linear transistor regime when operating at a constant bias of −0.5 V. 21 We posit that the inability to capture the fully on state arises from nonidealities in the printed, electrolyte-gated organic transistor. If so, applying our model to a conventional solid-state FET should provide better agreement.…”

Section: ■ Modelingcontrasting

confidence: 85%

“…Figure 2a presents the published EGT data 21 where FG1 is 150× the channel area; Figure S1 provides new data where FG1 is 10,000× the channel area. The EGT response is fit to the model for −0.45 V < V G < −0.1 V while fixing V DD = −0.5 V and ϕ = 0 V. In the fit, we map V 0 to C i using the dimensions of the printed film (W and L) and a mobility μ = 0.4 cm 2 /V s. 40 Rather than using V T and κ EGT for the fitting, we use these 2 degrees of freedom to iteratively fit Figures 2a and S1 to obtain the ion-gel−gold specific capacitance and ion-gel− P3HT specific capacitance.…”

Section: ■ Modelingmentioning

confidence: 99%

“…Devices were fabricated and tested following the approaches established in ref 21. For completeness, a concise summary of the experimental methods is provided in the Supporting Information.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

“…45 For this reason, the C16 curve is shifted along the V G axis until V OUT crosses up above 99% of the minimum V OUT plateau at the same value of V G as the C8 curve. 21 To make this shift clear, the x-axis is labeled V G * for capacitance sensing. For charge sensing, we use the same device and expose it sequentially to different pH values, rinsing with DI water between exposures.…”

Section: ■ Experimental Sectionmentioning

confidence: 99%

“…27−37 Configuring the device in a resistor-loaded inverter circuit, referred to as an inverter henceforth, provides sensitivity beyond the standard I D −V G transfer curve; subtraction of the reference and sample inverter curves provides a difference curve with a peak that is readily interpreted as a signal. 21 Optimizing an FGT device for sensitivity to charge or capacitance changes at the floating gate is an open challenge. The device contains four interfaces and four tunable variables: the channel size, the choice of semiconductor/dielectric, load resistor, and supply voltage.…”

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confidence: 99%

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Modeling of Quasi-Static Floating-Gate Transistor Biosensors

et al. 2021

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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.

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Section: ■ Modelingcontrasting

confidence: 85%

Section: ■ Modelingmentioning

confidence: 99%

Section: ■ Experimental Sectionmentioning

confidence: 99%

Section: ■ Experimental Sectionmentioning

confidence: 99%

mentioning

confidence: 99%

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Modeling of Quasi-Static Floating-Gate Transistor Biosensors

et al. 2021

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Flexible Organic Transistors for Biosensing: Devices and Applications

et al. 2023

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Flexible and stretchable biosensors can offer seamless and conformable biological–electronic interfaces for continuously acquiring high‐fidelity signals, permitting numerous emerging applications. Organic thin film transistors (OTFTs) are ideal transducers for flexible and stretchable biosensing due to their soft nature, inherent amplification function, biocompatibility, ease of functionalization, low cost, and device diversity. In consideration of the rapid advances in flexible‐OTFT‐based biosensors and their broad applications, herein, a timely and comprehensive review is provided. It starts with a detailed introduction to the features of various OTFTs including organic field‐effect transistors and organic electrochemical transistors, and the functionalization strategies for biosensing, with a highlight on the seminal work and up‐to‐date achievements. Then, the applications of flexible‐OTFT‐based biosensors in wearable, implantable, and portable electronics, as well as neuromorphic biointerfaces are detailed. Subsequently, special attention is paid to emerging stretchable organic transistors including planar and fibrous devices. The routes to impart stretchability, including structural engineering and material engineering, are discussed, and the implementations of stretchable organic transistors in e‐skin and smart textiles are included. Finally, the remaining challenges and the future opportunities in this field are summarized.

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