Meisam Rahmani

Analytical modeling of glucose biosensors based on carbon nanotubes

In recent years, carbon nanotubes have received widespread attention as promising carbon-based nanoelectronic devices. Due to their exceptional physical, chemical, and electrical properties, namely a high surface-to-volume ratio, their enhanced electron transfer properties, and their high thermal conductivity, carbon nanotubes can be used effectively as electrochemical sensors. The integration of carbon nanotubes with a functional group provides a good and solid support for the immobilization of enzymes. The determination of glucose levels using biosensors, particularly in the medical diagnostics and food industries, is gaining mass appeal. Glucose biosensors detect the glucose molecule by catalyzing glucose to gluconic acid and hydrogen peroxide in the presence of oxygen. This action provides high accuracy and a quick detection rate. In this paper, a single-wall carbon nanotube field-effect transistor biosensor for glucose detection is analytically modeled. In the proposed model, the glucose concentration is presented as a function of gate voltage. Subsequently, the proposed model is compared with existing experimental data. A good consensus between the model and the experimental data is reported. The simulated data demonstrate that the analytical model can be employed with an electrochemical glucose sensor to predict the behavior of the sensing mechanism in biosensors.

Analytical modelling of monolayer graphene-based ion-sensitive FET to pH changes

Graphene has attracted great interest because of unique properties such as high sensitivity, high mobility, and biocompatibility. It is also known as a superior candidate for pH sensing. Graphene-based ion-sensitive field-effect transistor (ISFET) is currently getting much attention as a novel material with organic nature and ionic liquid gate that is intrinsically sensitive to pH changes. pH is an important factor in enzyme stabilities which can affect the enzymatic reaction and broaden the number of enzyme applications. More accurate and consistent results of enzymes must be optimized to realize their full potential as catalysts accordingly. In this paper, a monolayer graphene-based ISFET pH sensor is studied by simulating its electrical measurement of buffer solutions for different pH values. Electrical detection model of each pH value is suggested by conductance modelling of monolayer graphene. Hydrogen ion (H+) concentration as a function of carrier concentration is proposed, and the control parameter (Ƥ) is defined based on the electro-active ions absorbed by the surface of the graphene with different pH values. Finally, the proposed new analytical model is compared with experimental data and shows good overall agreement.

Analytical modeling of trilayer graphene nanoribbon Schottky-barrier FET for high-speed switching applications

Recent development of trilayer graphene nanoribbon Schottky-barrier field-effect transistors (FETs) will be governed by transistor electrostatics and quantum effects that impose scaling limits like those of Si metal-oxide-semiconductor field-effect transistor s. The current–voltage characteristic of a Schottky-barrier FET has been studied as a function of physical parameters such as effective mass, graphene nanoribbon length, gate insulator thickness, and electrical parameters such as Schottky barrier height and applied bias voltage. In this paper, the scaling behaviors of a Schottky-barrier FET using trilayer graphene nanoribbon are studied and analytically modeled. A novel analytical method is also presented for describing a switch in a Schottky-contact double-gate trilayer graphene nanoribbon FET. In the proposed model, different stacking arrangements of trilayer graphene nanoribbon are assumed as metal and semiconductor contacts to form a Schottky transistor. Based on this assumption, an analytical model and numerical solution of the junction current–voltage are presented in which the applied bias voltage and channel length dependence characteristics are highlighted. The model is then compared with other types of transistors. The developed model can assist in comprehending experiments involving graphene nanoribbon Schottky-barrier FETs. It is demonstrated that the proposed structure exhibits negligible short-channel effects, an improved on-current, realistic threshold voltage, and opposite subthreshold slope and meets the International Technology Roadmap for Semiconductors near-term guidelines. Finally, the results showed that there is a fast transient between on-off states. In other words, the suggested model can be used as a high-speed switch where the value of subthreshold slope is small and thus leads to less power consumption.

Current–voltage modeling of graphene-based DNA sensor

Graphene is considered as an excellent biosensing material due to its outstanding and unique electronic properties such as providing large area detection, ultra-high mobility and ambipolar field-effect characteristic. In this paper, general conductance model of DNA sensor-based graphene is obtained, and the electrical performance of nanostructured graphene-based DNA sensor is evaluated by the current–voltage characteristic. As a result, by increasing the complementary DNA concentration, the drain current is going toward higher amounts.

Bilayer graphene application on NO 2 sensor modelling

Graphene is one of the carbon allotropes which is a single atom thin layer with sp2 hybridized and two-dimensional (2D) honeycomb structure of carbon. As an outstanding material exhibiting unique mechanical, electrical, and chemical characteristics including high strength, high conductivity, and high surface area, graphene has earned a remarkable position in todays experimental and theoretical studies as well as industrial applications. One such application incorporates the idea of using graphene to achieve accuracy and higher speed in detection devices utilized in cases where gas sensing is required. Although there are plenty of experimental studies in this field, the lack of analytical models is felt deeply. To start with modelling, the field effect transistor- (FET-) based structure has been chosen to serve as the platform and bilayer graphene density of state variation effect by NO2 injection has been discussed. The chemical reaction between graphene and gas creates new carriers in graphene which cause density changes and eventually cause changes in the carrier velocity. In the presence of NO2 gas, electrons are donated to the FET channel which is employed as a sensing mechanism. In order to evaluate the accuracy of the proposed models, the results obtained are compared with the existing experimental data and acceptable agreement is reported.

The effect of concentration on gas sensor model based on graphene nanoribbon

Graphene nanoribbon (GNR), a superior material with two-dimensional structure and monolayer honeycomb of carbon, is noteworthy and important in all fields’ mainly electronic, chemistry, biology, physics and nanotechnology. Recently, observing about sensors demonstrates that for better accuracy, faster response time and enlarged sensitivity, it needs to be improved. Nowadays, carbon-based equipments as an exclusive substance are remarkable in the sensing technology. High conductivity as unique properties caused that graphene can be used in biological applications. Gas sensor based on graphene can be supposed to have great sensitivity for gas molecules detection. In this study, graphene-based carbon dioxide sensor analytically is modeled. In addition, new methods of gas sensor model based on the gradient of GNR conductance are provided. Also, a field effect transistor-based structure as a modeling platform is suggested. Ultimately, optimum model is evaluated by comparison study between analytical model and experimental performance.

Modelling and simulation of saturation region in double gate graphene nanoribbon transistors

Novel analytical models for surface field distribution and saturation region length for double gate graphene nanoribbon transistors are proposed. The solutions for surface potential and electric field are derived based on Poisson equation. Using the proposed models, the effects of several parameters such as drain-source voltage, oxide thickness and channel length on the length of saturation region and electric field near the drain are studied.

Ionization coefficient of monolayer graphene nanoribbon

A semi-analytical model for impact ionization coefficient of graphene nanoribbon (GNR) is presented. The model is derived by calculating probability of electrons reaching ionization threshold energy Et and the distance travelled by electron gaining Et. In addition, ionization threshold energy is semi-analytically modelled for GNR. During modelling, we justify our assumptions using analytical modelling and comparison with simulation. Furthermore, it is shown that conventional silicon models are not valid for calculation of ionization coefficient of GNR. Finally, the profile of ionization is presented using the proposed models and the results are compared with that of silicon.

Conductance modulation of charged lipid bilayer using electrolyte-gated graphene-field effect transistor

Graphene is an attention-grabbing material in electronics, physics, chemistry, and even biology because of its unique properties such as high surface-area-to-volume ratio. Also, the ability of graphene-based materials to continuously tune charge carriers from holes to electrons makes them promising for biological applications, especially in lipid bilayer-based sensors. Furthermore, changes in charged lipid membrane properties can be electrically detected by a graphene-based electrolyte-gated graphene field effect transistor (GFET). In this paper, a monolayer graphene-based GFET with a focus on the conductance variation caused by membrane electric charges and thickness is studied. Monolayer graphene conductance as an electrical detection platform is suggested for neutral, negative, and positive electric-charged membrane. The electric charge and thickness of the lipid bilayer (QLP and LLP) as a function of carrier density are proposed, and the control parameters are defined. Finally, the proposed analytical model is compared with experimental data which indicates good overall agreement.

Analytical Modeling of Bilayer Graphene Based Biosensor

Recently, great attention has been devoted to the graphene because of its unique properties, such as high charge carrier mobility even at a high charge carrier concentration at room temperature, the existence of massless Dirac fermions, Quantum Hall effect at room temperature, gas sensing at the single molecule level and gate controlled transport (electron or hole) properties. Gas concentration effect on electrical conductivity of graphene by Green function method has been modeled however sensor analytical modeling needs to be done. In this paper injected carriers by Prostate Specific Antigen (PSA) concentration are simulated and carrier controlling parameters (F, pH) are suggested. Injected carriers from PSA to the graphene surface are monitored and their effect on the capacitance is modeled. Finally comparison with experimental data which illustrates good agreement between them is considered.