A Physics-Based (Verilog-A) Compact Model for DC, Quasi-Static Transient, Small-Signal, and Noise Analysis of MOSFET-Based pH Sensors

Dak, Piyush; Seo, Weeseong; Jung, Byunghoo; Alam, Muhammad A.

doi:10.1109/ted.2017.2651905

Cited by 10 publications

(17 citation statements)

References 26 publications

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“…where εW is the electrolyte dielectric permittivity; n0 is the ionic charge concentration; NA is Avogadro constant (1/mol) and i0 is the ionic molar concentration of the solution. This way, the solid-liquid interface is modelled in (2) by a nonlinear voltage source (Ψ0) which is dependent on pH, ionic concentration, the density of the surface ionizable sites, and their respective dissociation constants [16]. We combine such a dependent voltage source with an established compact model for 2DFETs [11].…”

Section: Drain Current Modeling Of 2d-isfetsmentioning

confidence: 99%

Compact Modeling of pH-Sensitive FETs Based on 2-D Semiconductors

Grour

Pasadas

Najari

et al. 2021

IEEE Trans. Electron Devices

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We present a physics-based circuit-compatible model for pH-sensitive field-effect transistors based on twodimensional (2D) materials. The electrostatics along the electrolyte-gated 2D-semiconductor stack is treated by solving the Poisson equation including the Site-Binding model and the Gouy-Chapman-Stern approach, while the carrier transport is described by the drift-diffusion theory. The proposed model is provided in an analytical form and then implemented in Verilog-A, making it compatible with standard technology computer-aided design tools employed for circuit simulation. The model is benchmarked against two experimental transition-metal-dichalcogenide (MoS2 and ReS2) based ion sensors, showing excellent agreement when predicting the drain current, threshold voltage shift, and current/voltage sensitivity measurements for different pH concentrations.

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Section: Drain Current Modeling Of 2d-isfetsmentioning

confidence: 99%

Compact Modeling of pH-Sensitive FETs Based on 2-D Semiconductors

Grour

Pasadas

Najari

et al. 2021

IEEE Trans. Electron Devices

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“…The electrolyte is modeled starting from the derivation in ref. 26 for a pH sensor. The effect of charged biomolecules, , is included in the charge neutrality equation as following:…”

mentioning

confidence: 99%

“…where is the double-layer charge, is the surface charge due to screening effects and is the MOSFET charge. In a first-order approximation can be neglected as almost entirely neutralizes and 26 . This phenomenon is at the origin of the so-called screening limited response of FET-based biosensors 7 .…”

mentioning

confidence: 99%

“…Site-binding model parameters 27 are taken by considering HfO2 as the interfacial insulator with the electrolyte. The model takes also into account the screening due to salt ions in the solution and the additional potential drop due to the finite size of charges building up at the interface with the oxide 26,28 (i.e., the so-called Stern layer).…”

mentioning

confidence: 99%

“…To avoid confusion with the symbol for sensitivity , we refer to the noise power spectral density with . The electrolytic solution contributes with thermal noise due its finite conductivity 26 . The negative capacitor contributes to the overall with thermal noise associated with dissipative process due to the damped ferroelectric switching 32 , and can be quantified from the last term in Eq.…”

mentioning

confidence: 99%

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Two-dimensional MoS2 negative capacitor transistors for enhanced (super-Nernstian) signal-to-noise performance of next-generation nano biosensors

Zagni

Pavan

Alam

2019

Applied Physics Letters

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The successful detection of biomolecules by a Field Effect Transistor-based biosensor (BioFET) is dictated by the sensor's intrinsic Signal-to-Noise Ratio (SNR). The detection limit of a traditional BioFET is fundamentally limited by biomolecule diffusion, charge screening, linear charge to surface-potential transduction, and Flicker noise. In this paper, we demonstrate that the recently introduced transistor technology called Negative Capacitor Field effect transistor (NCFET) offers nonlinear charge transduction and suppression of Flicker noise to dramatically improve the SNR over classical Boltzmann sensors. We quantify the SNR improvement by interpreting the experimental results associated with the signal and noise characteristics of 2D MoS2-based transistors. The combined sensitivity enhancement and noise rejection guarantee a high SNR of the NC-BioFET, making this device a promising candidate for realizing advanced integrated nanobiosensors. KEYWORDS 2D MoS2 FETs, Negative Capacitor Transistors, Nano Biosensors, Signal-to-Noise Ratio (SNR), Nonlinear response, SensitivityMany research groups worldwide are focused on developing highly sensitive, fast responding, and selective transistor-based biosensors. These sensors, known as BioFETs, allow label-free detection of biomolecules with the Limit of Detection (LOD) in the nano-and pico-molar concentration ranges 1 , potentially enabling many applications in personalized medicine 2 , early detection of diseases 3 , genome sequencing 4,5 , etc. A BioFET relies on the modulation of surface potential due to the charged biomolecules adsorbed on the gate electrode. Thus, the fundamental sensitivity limit of BioFETs depends on the diffusion of biomolecules 6 , surface charge screening, and linear "charge-to-surface potential" relationship 7 . These limitations apply to all FET-based biosensors, e.g. Dual-Gate FET 8 ; Silicon Nanowire *

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Graphene‐on‐Silicon Hybrid Field‐Effect Transistors

Fomin

Marín

Pasadas

et al. 2023

Adv Elect Materials

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This continuous downsizing has brought numerous advantages but also relevant challenges, coming hand-in-hand with the conception of novel and varied applications. [3][4][5][6] Among them, biosensing and bioelectronic applications have been successfully explored [7,8] , e.g., employing functionalized specific biomarkers on SiFETs surface, enabling selective label-free detection. [9,10] Silicon has also been utilized for numerous in vitro recordings of electrogenic cells (cardiac or neural) or even in vivo mapping of the whole brain. [11,12] However, it is known to be a bioresorbable material that degrades over time once immersed in saline, thus, suffering from a limited operation time for in vivo applications. [13,14] While silicon still dominates the industrial semiconductor scene, a new material has emerged rather recently, transforming materials science: graphene. Accompanied by other two-dimensional (2D) materials, graphene has already opened new prospects in modern nanoelectronic applications [15][16][17][18] and also holds a great promise for bio-and neuroapplications due to its extraordinary conductivity and good biocompatibility. [19][20][21] In particular, graphene-based FETs (GFETs) and microelectrode arrays (MEAs), both rigid and flexible, have been reported to successfully interface with electrogenic cellsThe combination of graphene and silicon in hybrid electronic devices has attracted increasing attention over the last decade. Here, a unique technology of graphene-on-silicon heterostructures as solution-gated transistors for bioelectronics applications is presented. The proposed graphene-onsilicon field-effect transistors (GoSFETs) are fabricated by exploiting various conformations of channel doping and dimensions. The fabricated devices demonstrate hybrid behavior with features specific to both graphene and silicon, which are rationalized via a comprehensive physics-based compact model which is purposely implemented and validated against measured data. The developed theory corroborates that the device hybrid behavior can be explained in terms of two independent silicon and graphene carrier transport channels, which are, however, strongly electrostatically coupled. Although GoSFET transconductance and carrier mobility are found to be lower than in conventional silicon or graphene field-effect transistors, it is observed that the combination of both materials within the hybrid channel contributes uniquely to the electrical response. Specifically, it is found that the graphene sheet acts as a shield for the silicon channel, giving rise to a nonuniform potential distribution along it, which impacts the transport, especially at the subthreshold region, due to non-negligible diffusion current.

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A Physics-Based (Verilog-A) Compact Model for DC, Quasi-Static Transient, Small-Signal, and Noise Analysis of MOSFET-Based pH Sensors

Cited by 10 publications

References 26 publications

Compact Modeling of pH-Sensitive FETs Based on 2-D Semiconductors

Compact Modeling of pH-Sensitive FETs Based on 2-D Semiconductors

Two-dimensional MoS2 negative capacitor transistors for enhanced (super-Nernstian) signal-to-noise performance of next-generation nano biosensors

Graphene‐on‐Silicon Hybrid Field‐Effect Transistors

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