The Significance of Nonlinear Screening and the pH Interference Mechanism in Field-Effect Transistor Molecular Sensors

Abstract

Electrolyte screening is well known for its detrimental impact on the sensitivity of liquid-gated field-effect transistor (FET) molecular sensors and is mostly described by the linearized Debye−Huckel model. However, charged and pH-sensitive FET sensing surfaces can limit the FET molecular sensitivity beyond the Debye−Huckel screening formalism. Pre-existing surface charges can lead to the breakdown of Debye−Huckel screening and induce enhanced nonlinear Poisson−Boltzmann screening. Moreover, the charging of the pH-sensitive surface groups interferes with biomolecule sensing resulting in a pH interference mechanism. With analytical equations and TCAD simulations, we highlight that the Debye−Huckel approximation can underestimate screening and overestimate FET molecular sensitivity by more than an order of magnitude. Screening strengthens significantly beyond Debye− Huckel in the proximity of even moderately charged surfaces and biomolecule charge densities (≥1 × 10 12 q/cm 2 ). We experimentally show the strong impact of both nonlinear screening and the pH interference effect on charge-based biomolecular sensing using a model system based on the covalent binding of single-stranded DNA on silicon FET sensors. The DNA signal increases from 24 mV at pH 7 to 96 mV at pH 3 in 1.5 mM PBS for a DNA density of 7 × 10 12 DNA/cm 2 . Our model quantitatively explains the signal's pH dependence with roughly equal nonlinear screening and pH interference contributions. This work shows the importance of reducing the net charge and the pH sensitivity of the sensing surface to improve molecular sensing. Therefore, tailoring the gate dielectric and functional layer of FET sensors is a promising route to strong silicon FET molecular sensitivity boosts.

Unraveling the impact of nano-scaling on silicon field-effect transistors for the detection of single-molecules

“…This is caused by nonlinear screening which leads to the saturation of the molecule signal as a function of increasing molecule charge. 43 But also due to the more elongated shape of the DNA molecule such that the charges are on average further away from the surface. The DNA SNR for an optimal FET device with high and low noise power density is ∼11 and ∼36 respectively.…”

“…This model accounts for steric effects when high ion concentrations arise. [41][42][43] To identify the underlying physical mechanisms that explain the influence of the FET geometry on the singlemolecule SNR, we initially omit the presence of additional phenomena like the typical pH sensitivity of a charged oxide surface, the dynamic behavior of molecules, a functional layer, etc. At a later stage, we specifically treat the impact of oxide surface charges on the geometry dependence of the singlemolecule signal.…”

“…Various papers have demonstrated the use of TCAD software to simulate ISFETs and molecular FET sensors including a continuum electrolyte ion distribution model. [38][39][40] Here, we use a 3D TCAD model that includes the Bikerman ion distribution model [41][42][43] and accounts for steric effects. 42 This framework has previously been used to quantitatively describe the measured signal for a layer of DNA molecules binding to a silicon FET sensor.…”

Acrylamide Hydrogel-Modified Silicon Nanowire Field-Effect Transistors for pH Sensing

“…It can be described by the site-binding model [11], triggering the redistribution of the surface charge or potential of the silicon nanowire, ultimately leading to significant changes in drain current and voltage in changes of H + concentration [12][13][14]. However, there is an equilibrium of the (de)protonation reaction of oxide OH groups at the local interface, and the results of the reaction directly affect the interface charge density [15]. The model can become quite complicated when surface-modified probe molecules are used for biosensing because of possible interference of protonation of OH groups, which may counteract the charge of the target molecule [16,17].…”

Effects of Buffer Concentration on the Sensitivity of Silicon Nanobelt Field-Effect Transistor Sensors

“…Field-effect transistor (FET)-based sensors have drawn increasing attention on account of their favorable properties [ 19 , 20 , 21 , 22 ]. Compared with the aforementioned conventional methods, FET-based sensors are advantageous for their small dimensions, low cost, fast response, label-free operation, and integration capability [ 23 , 24 ].…”