Calculating and analyzing time delay in zigzag graphene nanoscrolls based complementary metal-oxide-semiconductors.

Graphene Nano Scrolls (GNSs) and Zigzag graphene nanoscrolls (ZGNSs) are semi-one-dimensional materials with exceptional electrical and optical properties, making them attractive to be used in nanoelectronics and complementary metal-oxide-semiconductor (CMOS) technology. With in CMOS device technology, time delay is a crucial issue in the design and implementation of CMOS based ZGNSs. Current paper focus is on ZGNSs application in the channel area of metal-oxide-semiconductor field-effect transistors (MOSFETs) in CMOS technology. We studied analytically, the importance of different parameters on time delay reduction, resulting in faster switching and higher frequency in integrated circuits (ICs). The results of this research demonstrates that, the ZGNS-based CMOS proves considerable variations in the current due to the geometrical parameters, such as chirality number, channel length, and nanoscroll length which can be engineered to produce faster ICs.

Engineering Heat Transport Across Epitaxial Lattice-Mismatched van der Waals Heterointerfaces.

Artificially engineered 2D materials offer unique physical properties for thermal management, surpassing naturally occurring materials. Here, using van der Waals epitaxy, we demonstrate the ability to engineer extremely insulating thermal metamaterials based on atomically thin lattice-mismatched Bi2Se3/MoSe2 superlattices and graphene/PdSe2 heterostructures with exceptional thermal resistances (70-202 m2 K/GW) and ultralow cross-plane thermal conductivities (0.012-0.07 W/mK) at room temperature, comparable to those of amorphous materials. Experimental data obtained using frequency-domain thermoreflectance and low-frequency Raman spectroscopy, supported by tight-binding phonon calculations, reveal the impact of lattice mismatch, phonon-interface scattering, size effects, temperature, and interface thermal resistance on cross-plane heat dissipation, uncovering different thermal transport regimes and the dominant role of long-wavelength phonons. Our findings provide essential insights into emerging synthesis and thermal characterization methods and valuable guidance for the development of large-area heteroepitaxial van der Waals films of dissimilar materials with tailored thermal transport characteristics.

A Phenomenological Model for Electrical Transport Characteristics of MSM Contacts Based on GNS.

Graphene nanoscroll, because of attractive electronic, mechanical, thermoelectric and optoelectronics properties, is a suitable candidate for transistor and sensor applications. In this research, the electrical transport characteristics of high-performance field effect transistors based on graphene nanoscroll are studied in the framework of analytical modeling. To this end, the characterization of the proposed device is investigated by applying the analytical models of carrier concentration, quantum capacitance, surface potential, threshold voltage, subthreshold slope and drain induced barrier lowering. The analytical modeling starts with deriving carrier concentration and surface potential is modeled by adopting the model of quantum capacitance. The effects of quantum capacitance, oxide thickness, channel length, doping concentration, temperature and voltage are also taken into account in the proposed analytical models. To investigate the performance of the device, the current-voltage characteristics are also determined with respect to the carrier density and its kinetic energy. According to the obtained results, the surface potential value of front gate is higher than that of back side. It is noteworthy that channel length affects the position of minimum surface potential. The surface potential increases by increasing the drain-source voltage. The minimum potential increases as the value of quantum capacitance increases. Additionally, the minimum potential is symmetric for the symmetric structure (Vfg = Vbg). In addition, the threshold voltage increases by increasing the carrier concentration, temperature and oxide thickness. It is observable that the subthreshold slope gets closer to the ideal value of 60 mV/dec as the channel length increases. As oxide thickness increases the subthreshold slope also increases. For thinner gate oxide, the gate capacitance is larger while the gate has better control over the channel. The analytical results demonstrate a rational agreement with existing data in terms of trends and values.

Schemes for Single Electron Transistor Based on Double Quantum Dot Islands Utilizing a Graphene Nanoscroll, Carbon Nanotube and Fullerene.

The single electron transistor (SET) is a nanoscale switching device with a simple equivalent circuit. It can work very fast as it is based on the tunneling of single electrons. Its nanostructure contains a quantum dot island whose material impacts on the device operation. Carbon allotropes such as fullerene (C60), carbon nanotubes (CNTs) and graphene nanoscrolls (GNSs) can be utilized as the quantum dot island in SETs. In this study, multiple quantum dot islands such as GNS-CNT and GNS-C60 are utilized in SET devices. The currents of two counterpart devices are modeled and analyzed. The impacts of important parameters such as temperature and applied gate voltage on the current of two SETs are investigated using proposed mathematical models. Moreover, the impacts of CNT length, fullerene diameter, GNS length, and GNS spiral length and number of turns on the SET's current are explored. Additionally, the Coulomb blockade ranges (CB) of the two SETs are compared. The results reveal that the GNS-CNT SET has a lower Coulomb blockade range and a higher current than the GNS-C60 SET. Their charge stability diagrams indicate that the GNS-CNT SET has smaller Coulomb diamond areas, zero-current regions, and zero-conductance regions than the GNS-C60 SET.

Monolayer Twisted Graphene-Based Schottky Transistor.

The outstanding properties of graphene-based components, such as twisted graphene, motivates nanoelectronic researchers to focus on their applications in device technology. Twisted graphene as a new class of graphene structures is investigated in the platform of transistor application in this research study. Therefore, its geometry effect on Schottky transistor operation is analyzed and the relationship between the diameter of twist and number of twists are explored. A metal-semiconductor-metal twisted graphene-based junction as a Schottky transistor is considered. By employing the dispersion relation and quantum tunneling the variation of transistor performance under channel length, the diameter of twisted graphene, and the number of twists deviation are studied. The results show that twisted graphene with a smaller diameter affects the efficiency of twisted graphene-based Schottky transistors. Additionally, as another main characteristic, the ID-VGS is explored, which indicates that the threshold voltage is increased by diameter and number of twists in this type of transistor.

Graphene Nanoparticle-Based, Nitrate Ion Sensor Characteristics.

Gathering and sensing of nitrate ions in the environment due to the abundant use in industry and agriculture have become an important problem, which needs to be overcome. On the other hand, new materials such as carbon-based materials with unique properties have become an ideal choice in sensing technology. In this research, the high-density polyethylene (HDPE) polymer as a carbon source in the melted form was used and carbon nanoparticles in the form of a strand between two electrodes were analyzed. It was fabricated between copper electrodes by the pulsed arc discharge method. Subsequently, the constructed metal-nanoparticle-metal (MNM) contact was employed to recognize the nitrate ions. Therefore, NaNO3, Pb(NO3)2, Zn(NO3)2, and NH4NO3 samples as a usual pollutant of industrial and agricultural wastewater were examined. All nitrate compounds in ten different densities were tested and sensor I-V characteristic was investigated, which showed that all the aforesaid compounds were recognizable by the graphene nano-strand. Additionally, the proposed structure in the presence of ions was simulated and acceptable agreement between them was reported. Additionally, the proposed structure analytically was investigated, and a comparison study between the proposed model and measured results was carried out and realistic agreement reported.

Coulomb Blockade Effect in Well-Arranged 2D Arrays of Palladium Nano-Islands for Hydrogen Detection at Room Temperature: A Modeling Study.

The fast growth of hydrogen usage as a clean fuel in civil applications such as transportation, space technology, etc. highlights the importance of the reliable detection of its leakage and accumulation under explosion limit by sensors with a low power consumption at times when there is no accumulation of hydrogen in the environment. In this research, a new and efficient mechanism is presented for hydrogen detection-using the Coulomb blockade effect in a well-arranged 2D array of palladium nano-islands-which can operate at room temperature. We demonstrated that under certain conditions of size distribution and the regularity of palladium nano-islands, with selected sizes of 1.7, 3 and 6.1 nm, the blockade threshold will appear in current-voltage (IV) characteristics. In reality, it will be achieved by the inherent uncertainty in the size of the islands in nano-scale fabrication or by controlling the size of nanoparticles from 1.7 to 6.1 nm, considering a regular arrangement of nanoparticles that satisfies single-electron tunneling requirements. Based on the simulation results, the threshold voltage is shifted towards lower ones due to the expansion of Pd nanoparticles exposed to the environment with hydrogen concentrations lower than 2.6%. Also, exploring the features of the presented structure as a gas sensor, provides robustness against the Gaussian variation in nano-islands sizes and temperature variations. Remarkably, the existence of the threshold voltage in the IV curve and adjusting the bias voltage below this threshold leads to a drastic reduction in power consumption. There is also an improvement in the minimum detectable hydrogen concentration as well as the sensor response.

Carbon-Based Band Gap Engineering in the h-BN Analytical Modeling.

The absence of a band gap in graphene is a hindrance to its application in electronic devices. Alternately, the complete replacement of carbon atoms with B and N atoms in graphene structures led to the formation of hexagonal boron nitride (h-BN) and caused the opening of its gap. Now, an exciting possibility is a partial substitution of C atoms with B and N atoms in the graphene structure, which caused the formation of a boron nitride composite with specified stoichiometry. BC2N nanotubes are more stable than other triple compounds due to the existence of a maximum number of B-N and C-C bonds. This paper focused on the nearest neighbor's tight-binding method to explore the dispersion relation of BC2N, which has no chemical bond between its carbon atoms. More specifically, the band dispersion of this specific structure and the effects of energy hopping in boron-carbon and nitrogen-carbon atoms on the band gap are studied. Besides, the band structure is achieved from density functional theory (DFT) using the generalized gradient approximations (GGA) approximation method. This calculation shows that this specific structure is semimetal, and the band gap energy is 0.167 ev.

An Analytical Conductance Model for Gas Detection Based on a Zigzag Carbon Nanotube Sensor.

Recent advances in nanotechnology have revealed the superiority of nanocarbon species such as carbon nanotubes over other conventional materials for gas sensing applications. In this work, analytical modeling of the semiconducting zigzag carbon nanotube field-effect transistor (ZCNT-FET) based sensor for the detection of gas molecules is demonstrated. We propose new analytical models to strongly simulate and investigate the physical and electrical behavior of the ZCNT sensor in the presence of various gas molecules (CO2, H2O, and CH4). Therefore, we start with the modeling of the energy band structure by acquiring the new energy dispersion relation for the ZCNT and introducing the gas adsorption effects to the band structure model. Then, the electrical conductance of the ZCNT is modeled and formulated while the gas adsorption effect is considered in the conductance model. The band structure analysis indicates that, the semiconducting ZCNT experiences band gap variation after the adsorption of the gases. Furthermore, the bandgap variation influences the conductance of the ZCNT and the results exhibit increments of the ZCNT conductance in the presence of target gases while the minimum conductance shifted upward around the neutrality point. Besides, the I-V characteristics of the sensor are extracted from the conductance model and its variations after adsorption of different gas molecules are monitored and investigated. To verify the accuracy of the proposed models, the conductance model is compared with previous experimental and modeling data and a good consensus is observed. It can be concluded that the proposed analytical models can successfully be applied to predict sensor behavior against different gas molecules.

Effect of solution pH and adsorbent concentration on the sensing parameters of TGN-based electrochemical sensor.

The response of trilayer graphene nanoribbon (TGN)-based ion-sensitive field-effect transistor (ISFET) to different pH solutions and adsorption effect on the sensing parameters are analytically studied in this research. The authors propose a TGN-based sensor to electrochemically detect pH. To this end, absorption effect on the sensing area in the form of carrier concentration, carrier velocity, and conductance variations are investigated. Also, the caused electrical response on TGN as a detection element is analytically proposed, in which significant current decrease of the sensor is observed after exposure to high pH values. In order to verify the accuracy of the model, it is compared with recent reports on pH sensors. The TGN-based pH sensor exposes higher current compared to that of carbon nanotube (CNT) counterpart for analogous ambient conditions. While, the comparative results demonstrate that the conductance of proposed model is lower than that of monolayer graphene-counterpart for equivalent pH values. The results confirm that the conductance of the sensor is decreased and Vg-min is obviously right-shifted by increasing value of pH. The authors demonstrate that although there is not the experimental evidence reported in the part of literature for TGN sensor, but the model can assist in comprehending experiments involving nanoscale pH sensors.

A carrier velocity model for electrical detection of gas molecules.

Nanomaterial-based sensors with high sensitivity, fast response and recovery time, large detection range, and high chemical stability are in immense demand for the detection of hazardous gas molecules. Graphene nanoribbons (GNRs) which have exceptional electrical, physical, and chemical properties can fulfil all of these requirements. The detection of gas molecules using gas sensors, particularly in medical diagnostics and safety applications, is receiving particularly high demand. GNRs exhibit remarkable changes in their electrical characteristics when exposed to different gases through molecular adsorption. In this paper, the adsorption effects of the target gas molecules (CO and NO) on the electrical properties of the armchair graphene nanoribbon (AGNR)-based sensor are analytically modelled. Thus, the energy dispersion relation of AGNR is developed considering the molecular adsorption effect using a tight binding (TB) method. The carrier velocity is calculated based on the density of states (DOS) and carrier concentration (n) to obtain I-V characteristics and to monitor its variation in the presence of the gas molecules. Furthermore, the I-V characteristics and energy band structure of the AGNR sensor are simulated using first principle calculations to investigate the gas adsorption effects on these properties. To ensure the accuracy of the proposed model, the I-V characteristics of the AGNR sensor that are simulated based both on the proposed model and first principles calculations are compared, and an acceptable agreement is achieved.

Experimental and theoretical investigation of sensing parameters in carbon nanotube-based DNA sensor.

Nowadays, sensitive biosensors with high selectivity, lower costs and short response time are required for detection of DNA. The most preferred materials in DNA sensor designing are nanomaterials such as carbon and Au nanoparticles, because of their very high surface area and biocompatibility which lead to performance and sensitivity improvements in DNA sensors. Carbon nanomaterials such as carbon nanotubes (CNTs) can be considered as a suitable DNA sensor platform due to their high surface-to-volume ratio, favourable electronic properties and fast electron transfer rate. Therefore, in this study, the CNTs which are synthesised by pulsed AC arc discharge method on a high-density polyethylene substrate are used as conducting channels in a chemiresistor for the electrochemical detection of double stranded DNA. Moreover, the response of the proposed sensor is investigated experimentally and analytically in different temperatures, which confirm good agreement between the presented model and experimental data.

Graphene Based Biosensor Model for Escherichia Coli Bacteria Detection.

As a new nanomaterial, graphene demonstrates great potential as an electrode for biomedical applications in sensing molecules and cells. Thus, development of biosensors based on graphene is gaining much interest due to its exceptional properties such as, large surface-to-volume ratio, high conductivity and high flexibility. In this work a liquid gated graphene field effect transistor based biosensor model is analytically developed for electrical detection of Escherichia Coli O157:H7 bacteria. The effect of graphene functionalization on the graphene conductance in the presence of E. coli is investigated. E. coli absorption effects on the graphene surface in the form of conductance variation are considered. Therefore the graphene conductance as a function of E. coli concentration which controls the current­voltage characteristics of biosensors is presented. According to the simulated results, the proposed sensor model can be applied as a powerful tool to predict the biosensor performance.

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 (Q LP and L LP) 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 calculation of sensing parameters on carbon nanotube based gas sensors.

Carbon Nanotubes (CNTs) are generally nano-scale tubes comprising a network of carbon atoms in a cylindrical setting that compared with silicon counterparts present outstanding characteristics such as high mechanical strength, high sensing capability and large surface-to-volume ratio. These characteristics, in addition to the fact that CNTs experience changes in their electrical conductance when exposed to different gases, make them appropriate candidates for use in sensing/measuring applications such as gas detection devices. In this research, a model for a Field Effect Transistor (FET)-based structure has been developed as a platform for a gas detection sensor in which the CNT conductance change resulting from the chemical reaction between NH3 and CNT has been employed to model the sensing mechanism with proposed sensing parameters. The research implements the same FET-based structure as in the work of Peng et al. on nanotube-based NH3 gas detection. With respect to this conductance change, the I-V characteristic of the CNT is investigated. Finally, a comparative study shows satisfactory agreement between the proposed model and the experimental data from the mentioned research.

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 transistors. 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.