Optimization of nanowire DNA sensor sensitivity using self-consistent simulation

Abstract

In order to facilitate the rational design and the characterization of nanowire field-effect sensors, we have developed a model based on self-consistent charge-transport equations combined with interface conditions for the description of the biofunctionalized surface layer at the semiconductor/electrolyte interface. Crucial processes at the interface, such as the screening of the partial charges of the DNA strands and the influence of the angle of the DNA strands with respect to the nanowire, are computed by a Metropolis Monte Carlo algorithm for charged molecules at interfaces. In order to investigate the sensing mechanism of the device, we have computed the current–voltage characteristics, the electrostatic potential and the concentrations of electrons and holes. Very good agreement with measurements has been found and optimal device parameters have been identified. Our approach provides the capability to study the device sensitivity, which is of fundamental importance for reliable sensing.

DNA detection with top–down fabricated silicon nanowire transistor arrays in linear operation regime

“…Most of the time, the recordings are done using high‐precision semiconductor analyzers and wafer probe stations. In the linear operation regime, where the drift carrier conduction is dominating over the diffusion‐based conduction, the typically‐used readout can be regarded as potentiometric mode (dc‐readout), where the FET's transfer characteristic and the shift in threshold‐voltage ( V TH ) of the FET devices are measured.…”

Analysis of the drift-diffusion-Poisson–Boltzmann system for nanowire and nanopore sensors in the alternating-current regime

“…− ∇ · (D n ∇a 5 ) + ∇ · μ n ∇V * a 5 = ωa 6 + g 5 in Ω Si , (3.51i) − ∇ · (D n ∇a 6 ) + ∇ · μ n ∇V * a 6 = −ωa 5 + g 6 in Ω Si , (3.51j) a 1 (0+,y) − a 1 (0−,y) = a 7 on Γ, (3.51k) A(0+)∂ x a 1 (0+,y) − A(0−)∂ x a 1 (0−,y) = a 8 on Γ, (3.51l) a 2 (0+,y) − a 2 (0−,y) = 0 on Γ, (3.51m) A(0+)∂ x a 2 (0+,y) − A(0−)∂ x a 2 (0−,y) = 0 on Γ, (3.51n) a 7 = M α ( (Ṽ e ))a 1 + M α ( (Ṽ e ))a 2 + g 7 on Γ, (3.51o) a 8 = M γ ( (Ṽ e ))a 1 + M γ ( (Ṽ e ))a 2 + g 8 on Γ, (3.51p) a 1 = a 2 = 0 on ∂Ω D , (3.51q) a 3 = a 4 = a 5 = a 6 = 0 on ∂Ω D,Si , (3.51r) ∇a 1 · n = ∇a 2 · n = 0 on ∂Ω N , (3.51s) ∇a 3 · n = ∇a 4 · n = ∇a 5 · n = ∇a 6 · n = 0 on ∂Ω N,Si .…”

“…A parallel numerical method was developed in [3]. These mathematical results have then been used to provide quantitative understanding and to optimize sensor design [4,5].More recently, such nanowire field-effect sensors have been fabricated for use in the AC regime and characterized [14,[18][19][20][21]. In the experiments, the electric potentials around the DC equilibrium are small and the frequencies are low enough to ensure that the free charge carriers in the liquid are equilibrated, avoiding spurious signals.…”

“…A parallel numerical method was developed in [3]. These mathematical results have then been used to provide quantitative understanding and to optimize sensor design [4,5].…”

Use and comparative assessment of the CVFEM method for Poisson–Boltzmann and Poisson–Nernst–Planck three dimensional simulations of impedimetric nano-biosensors operated in the DC and AC small signal regimes

“…Nanoelectronic biosensor models are typically based on the Poisson-Boltzmann (PB) [4] equations for DC conditions and the Poisson-Nernst-Planck (PNP), also known as Poisson-drift-diffusion equations in engineering, for the transient or small signal AC regimes [9]. An alternative model for DC conditions using a Poisson-drift-diffusion system of equations in a homogenized system has been proposed in [10,11] and extensively applied in [12,13]. Oxide-electrolyte interfaces are described by the site-binding model [14,15] while corrections are sometimes included to account for steric effects stemming from the finite size of anions and cations that adhere to the interfaces [16].…”