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The performance of the conventional 6T SRAM cell can be improved by using GNRFET devices with multi-threshold technology. The proposed cell shows the strong capability to operate at the minimum supply voltage of 325 mV, whereas the conventional Si-CMOS 6 T SRAM unable to operate below 725 mV, which result in an acceptable failure rate.The advance of Si-CMOS (complementary metal-oxide-semiconductor) based 6 T SRAM cell faces inherent limitation with aggressive downscaling. Hence, there is a need to propose alternatives for the conventional cells.

This study aims to improve the performance of the conventional 6T SRAM cell using dual threshold technology, device sizing, optimization of supply voltage under process variation with GNRFET technology. Further performance can be enhanced by resolving half-select issue.

The GNRFET-based 6T SRAM cell demonstrates that it is capable of continued improve the performance under the process, voltage, and temperature (PVT) variations significantly better than its CMOS counterpart.

Nano-material fabrication technology of GNRFETs is in the early stage; hence, the different transistor models can be used to evaluate the parameters of future GNRFETs circuit.

GNRFET devices are suitable for implementing low power and high density SRAM cell.

The conventional Si-CMOS 6 T SRAM cell is a core component and used as the mass storage element in cache memory in computer system organization, mobile phone and other data storage devices.

This paper presents a new approach to implement an alternative design of GNRFET -based 6T SRAM cell with doped reservoirs that also supports process variation. In addition, multi-threshold technology optimizes the performance of the proposed cell. The proposed design provides a means to analyze delay and power of GNRFET-based SRAM under process variation with considering edge roughness, and offers design and fabrication insights for cell in the future.

The purpose of this paper is to simulate and investigate the thermomechanical properties of graphene-reinforced nanocomposites.

The analysis proposed consists of two stages. In the first stage, the temperature-dependent mechanical properties of graphene are estimated while in the second stage, using the previously derived properties, the temperature-dependent properties of graphene-reinforced PMMA nanocomposites are investigated. In the first stage of the analysis, graphene is modeled discretely using molecular mechanics theory where the interatomic interactions are simulated by spring elements of temperature-dependent stiffness. The graphene sheets are composed of either one or more (up to five) monolayer graphene sheets connected via van der Waals interactions. However, in the second analysis stage, graphene is modeled equivalently as continuum medium and is positioned between two layers of PMMA. Also, the interphase between two materials is modeled as a medium with mechanical properties defined and bounded by the two materials.

The mechanical properties including Young’s modulus, shear modulus and Poisson’s ratio due to temperature changes are estimated. The numerical results show that the temperature rise and the multiplicity of graphene layers considered lead to a decrease of the mechanical properties.

The present analysis proposes an easy and accurate method for the estimation of the temperature-dependent mechanical properties of graphene-reinforced nanocomposites.

This paper aims to present the edge scattering dominant circuit modeling. The effect of crosstalk on gate oxide reliability (GOR), along with the mitigation using shielding technique is further studied.

An equivalent distributed Resistance Inductance Capacitance circuit of capacitively coupled interconnects of multilayer graphene nanoribbon (MLGNR) has been considered for T Simulation Program with Integrated Circuit Emphasis (TSPICE) simulations under functional and dynamic switching conditions. Complementary metal oxide semiconductor driver transistors are modeled by high performance predictive technology model that drive the distributed segment with a capacitive load of 0.001 fF, V_DD and clock frequency as 0.7 V and 0.2 GHz, respectively, at 14 nm technology node.

The results reveal that the crosstalk induced delay and noise area are dominated by the overall mean free path (MFP) (i.e. including the effect of edge roughness induced scattering), in contrary to, acoustic and optical scattering limited MFP with the temperature, width and length variations. Further, GOR, estimated in terms of average failure rate (AFR), shows that the shielding technique is an effective method to minimize the relative GOR failure rate by, 0.93e-7 and 0.7e-7, in comparison to the non-shielded case with variations in interconnect’s length and width, respectively.

Considering realistic circuit modeling for MLGNR interconnects by incorporating the edge roughness induced scattering mechanism, the outcomes exhibit more penalty in terms of crosstalk induced noise area and delay. The shielding technique is found to be an effective mitigating technique for minimizing AFR in coupled MLGNR interconnects.

Miniaturized smart sensors that can perform sensitive and selective real-time monitoring of target analytes are tremendously valuable for various sensing applications. So, the purpose of this paper is to provide details of sensors based on selective nanocoatings by combining trinitrotoluene (TNT) receptors bound to conjugated polydiacetylene (PDA) polymers with single-walled carbon nanotube field-effect transistors (CNTFETs) for detecting explosives TNT.

Following an introduction, this paper describes the way of creating an FET with CNTs, which are functionalized by the peptide based on TNT molecule recognition elements and PDA, to offer a system which has the capability of answering the presence of related target molecules (TNT). Finally, brief conclusions are drawn.

Single-wall nanotubes and reduced graphene oxide are interesting materials for creating biosensors of FETs at nanoscale because of unique electrical, mechanical, geometrical and biocompatible properties. Therefore, this sensor is designed and manufactured, and the results of applying TNT to sensor show good sensitivity and selectivity response.

In this timeframe of history, sensors based on CNTFET are required for different uses, including clinical diagnosis technologies, environmental tests and bioterrorism recognition technologies, that correspond to the military conflicts and terrorism. So, CNTFET sensor design provides real-time detection of TNT explosives.

Bang‐bang clock and data recovery (BBCDR) circuits are hard nonlinear systems due to the nonlinearity introduced by the binary phase detector (BPD). The specification of the CDR frequency response is determined by jitter tolerance and jitter transfer. In this paper, jitter transfer and jitter tolerance of the BBCDR are characterized.

The presented method is enough to be used for designing the BBCDR loop parameters.

In this paper, jitter characteristics of the BBCDR are characterized. As a result, a new equation is presented to obtain angular frequency. Also, the jitter tolerance is expressed in closed form as a function of loop parameters. The analysis is verified using behavioral simulations in MATLAB. Simulation results show that good conformance between analytical equations and simulation results.

The proposed approach offers two advantages compared to conventional designing methods. First, this approach does not consider any value restriction to the capacitor. Second, a new condition has been presented to guarantee that the value of jitter peaking is approximately zero.