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. 2023 Aug 25;14(9):1664.
doi: 10.3390/mi14091664.

Geometrical Characterisation of TiO2-rGO Field-Effect Transistor as a Platform for Biosensing Applications

Affiliations

Geometrical Characterisation of TiO2-rGO Field-Effect Transistor as a Platform for Biosensing Applications

Anis Amirah Alim et al. Micromachines (Basel). .

Abstract

The performance of the graphene-based field-effect transistor (FET) as a biosensor is based on the output drain current (Id). In this work, the signal-to-noise ratio (SNR) was investigated to obtain a high-performance device that produces a higher Id value. Using the finite element method, a novel top-gate FET was developed in a three-dimensional (3D) simulation model with the titanium dioxide-reduced graphene oxide (TiO2-rGO) nanocomposite as the transducer material, which acts as a platform for biosensing application. Using the Taguchi mixed-level method in Minitab software (Version 16.1.1), eighteen 3D models were designed based on an orthogonal array L18 (6134), with five factors, and three and six levels. The parameters considered were the channel length, electrode length, electrode width, electrode thickness and electrode type. The device was fabricated using the conventional photolithography patterning technique and the metal lift-off method. The material was synthesised using the modified sol-gel method and spin-coated on top of the device. According to the results of the ANOVA, the channel length contributed the most, with 63.11%, indicating that it was the most significant factor in producing a higher Id value. The optimum condition for the highest Id value was at a channel length of 3 µm and an electrode size of 3 µm × 20 µm, with a thickness of 50 nm for the Ag electrode. The electrical measurement in both the simulation and experiment under optimal conditions showed a similar trend, and the difference between the curves was calculated to be 28.7%. Raman analyses were performed to validate the quality of TiO2-rGO.

Keywords: ANOVA; DOE; Taguchi; TiO2-rGO; field-effect transistor.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(a) Working principle of the FET biosensor. (b) I–V measurement of the FET biosensor.
Figure 2
Figure 2
Illustration of the fabrication flow ((ai) in sequence) of the electrode: (a) a cleaned p-type silicon wafer, (b) application of photoresist and UV exposure on the exposed surface for patterning, (c) development of photoresist, (d) deposition of Cr/Au using the electron beam, (e) removal of photoresist and lift-off, (f) second mask application for patterning, (g) development of photoresist, (h) deposition of TEOS and (i) removal of photoresist.
Figure 3
Figure 3
Illustration of the material synthesis and deposition process.
Figure 4
Figure 4
Pictorial representation of the simulated design: (a) schematic of the FET on a wafer with the source (S), gate (G) and drain (D), (b) schematic design from the top view and (c) design simulation in CTS for electrical characterisation with the electrode width (W) at the X, Y, Z view.
Figure 5
Figure 5
Schematic of the FET from the X, Z view for electrical characterisation, with channel length (LC) and electrode length (L).
Figure 6
Figure 6
Flow chart of the Taguchi method.
Figure 7
Figure 7
Drain current (Id) of all simulated designs.
Figure 8
Figure 8
Plot of the main effects for the mean of the SNR of the drain current (Id) for optimisation of the TiO2-rGO FET.
Figure 9
Figure 9
The standardised residuals in normal probability plots in response to SNRs.
Figure 10
Figure 10
I–V graph of the FET device with TiO2-rGO deposition (labelled as experimental) compared to the simulation value (labelled as simulation).
Figure 11
Figure 11
Raman spectra of TiO2 and the TiO2-rGO nanocomposite.

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