Related papers: Exploiting Dual-Gate Ambipolar CNFETs for Scalable…
We have fabricated air-stable n-type, ambipolar carbon nanotube field effect transistors (CNFETs), and used them in nanoscale memory cells. N-type transistors are achieved by annealing of nanotubes in hydrogen gas and contacting them by…
Mixed-signal machine-learning classification has recently been demonstrated as an efficient alternative for classification with power expensive digital circuits. In this paper, a high-COnfidence high-REsolution (CORE) mixed-signal…
State-of-the-art carbon nanotube field-effect transistors (CNFETs) behave as Schottky barrier (SB)-modulated transistors. It is known that vertical scaling of the gate oxide significantly improves the performance of these devices. However,…
Traditional silicon binary circuits continue to face challenges such as high leakage power dissipation and large area of interconnections. Multiple-Valued Logic (MVL) and nano devices are two feasible solutions to overcome these problems.…
In recent years, neuromorphic computing has gained attention as a promising approach to enhance computing efficiency. Among existing approaches, neurotransistors have emerged as a particularly promising option as they accurately represent…
This article presents novel high speed and low power full adder cells based on carbon nanotube field effect transistor (CNFET). Four full adder cells are proposed in this article. First one (named CN9P4G) and second one (CN9P8GBUFF)…
This paper investigates the use of carbon nanotube field effect transistors (CNFETs) for the design of ternary full adder cells. The proposed circuits have been designed based on the unique properties of CNFETs such as having desired…
Advanced electronic device technologies require a faster operation and smaller average power consumption, which are the most important parameters in very large scale integrated circuit design. The conventional Complementary Metal-Oxide…
High speed Full-Adder (FA) module is a critical element in designing high performance arithmetic circuits. In this paper, we propose a new high speed multiple-valued logic FA module. The proposed FA is constructed by 14 transistors and 3…
Recent advances in artificial intelligence, coupled with increasing data bandwidth requirements, in applications such as video processing and high-resolution sensing, have created a growing demand for high computational performance under…
High performance enhancement mode semiconducting carbon nanotube field-effect transistors (CNTFETs) are obtained by combining ohmic metal-tube contacts, high dielectric constant HfO2 films as gate insulators, and electrostatically doped…
This paper presents a ternary half adder and a 1-trit multiplier using carbon nanotube transistors. The proposed circuits are designed using pass transistor logic and dynamic logic. Ternary logic uses less connections than binary logic, and…
In this work, we have implemented an accurate machine-learning approach for predicting various key analog and RF parameters of Negative Capacitance Field-Effect Transistors (NCFETs). Visual TCAD simulator and the Python high-level language…
Carbon Nanotube Field Effect Transistor (CNFET) is a promising new technology that overcomes several limitations of traditional silicon integrated circuit technology. In recent years, the potential of CNFET for analog circuit applications…
Carbon nanotube field-effect transistors (CNT FETs) have been proposed as possible building blocks for future nano-electronics. But a challenge with CNT FETs is that they appear to randomly display varying amounts of hysteresis in their…
Junctionless Nanowire Field-Effect Transistors (JNFETs), where the channel region is uniformly doped without the need for source-channel and drain-channel junctions or lateral doping abruptness, are considered an attractive alternative to…
With decreasing device dimensions, the performance of carbon nanotube field-effect transistors (CNFETs) is limited by high Off currents except at low drain voltages. We show that an asymmetric design improves the performance, reducing Off…
Automatic modulation classification (AMC) is an essential technique for noncooperative spectrum monitoring and intelligent wireless receivers. However, practical AMC models must identify modulation formats from short and noisy I/Q…
In this thesis, I explored the use of several machine learning techniques, including neural networks, simulation-based inference, and generative flow networks, on predicting CNTFETs performance, probing the conductivity properties of CNT…
An analog neural network computing engine based on CMOS-compatible charge-trap transistor (CTT) is proposed in this paper. CTT devices are used as analog multipliers. Compared to digital multipliers, CTT-based analog multiplier shows…