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Correlated mobility fluctuations are considered in the physics-based carrier number fluctuation deltaN low-frequency noise (LFN) compact model of single-layer graphene field effect transistors (GFET) in the present study. Trapped charge…
Analog circuit design consists of the pre-layout and layout phases. Among them, the pre-layout phase directly decides the final circuit performance, but heavily depends on experienced engineers to do manual design according to specific…
Graphene nanoribbons (GNRs) are one-dimensional nanostructures predicted to display a rich variety of electronic behaviors. Depending on their structure, GNRs realize metallic and semiconducting electronic structures with band gaps that can…
Thickness engineered tunneling field-effect transistors (TE-TFET) as a high performance ultra-scaled steep transistor is proposed. This device exploits a specific property of 2D materials: layer thickness dependent energy bandgap (Eg).…
Defects in semiconductors, traditionally seen as detrimental to electronic device performance, have emerged as potential assets in quantum technologies due to their unique quantum properties. This study investigates the interaction between…
Transformers have recently emerged as powerful neural networks for graph learning, showcasing state-of-the-art performance on several graph property prediction tasks. However, these results have been limited to small-scale graphs, where the…
Straightforward contact resistance extraction methods based on electrical device characteristics are described and applied here to graphene field-effect transistors from different technologies. The methods are an educated adaptation of…
Being able to predict the performance of circuits without running expensive simulations is a desired capability that can catalyze automated design. In this paper, we present a supervised pretraining approach to learn circuit representations…
Graph Transformers (GTs) have significantly advanced the field of graph representation learning by overcoming the limitations of message-passing graph neural networks (GNNs) and demonstrating promising performance and expressive power.…
The scaling behaviors of graphene nanoribbon (GNR) Schottky barrier field-effect transistors (SBFETs) are studied by solving the non-equilibrium Green's function (NEGF) transport equation in an atomistic basis set self-consistently with a…
This paper reviews the emergence and progress of phosphorene FETs, all within about a year. In such a short time, back-gated FETs evolved into top-gated FETs, gate length was reduced to the sub-micron range, passivation by high-k…
Graphdiyne (GDY) is recognized as a compelling candidate for the fabrication of next-generation high-speed low-energy electronic devices due to its inherent p-type semiconductor characteristics. However, the development of GDY for…
We develop a semianalytical model for monolayer graphene field-effect transistors in the ballistic limit. Two types of devices are considered: in the first device, the source and drain regions are doped by charge transfer with Schottky…
Many complex engineering systems can be represented in a topological form, such as graphs. This paper utilizes a machine learning technique called Geometric Deep Learning (GDL) to aid designers with challenging, graph-centric design…
As integrated circuit scale grows and design complexity rises, effective circuit representation helps support logic synthesis, formal verification, and other automated processes in electronic design automation. And-Inverter Graphs (AIGs),…
The recent works proposing transformer-based models for graphs have proven the inadequacy of Vanilla Transformer for graph representation learning. To understand this inadequacy, there is a need to investigate if spectral analysis of the…
In many state-of-the-art compression systems, signal transformation is an integral part of the encoding and decoding process, where transforms provide compact representations for the signals of interest. This paper introduces a class of…
Graphene nanoribbon (GNR) emerges as an exceptionally promising channel candidate due to its tunable sizable bandgap (0-3 eV), ultrahigh carrier mobility (up to 4600 cm^(2) V^(-1) s^(-1)), and excellent device performance (current on-off…
Printed and flexible electronics (PFE) have emerged as the ubiquitous solution for application domains at the extreme edge, where the demands for low manufacturing and operational cost cannot be met by silicon-based computing. Built on…
We invented a method to fabricate graphene transistors on oxidized silicon wafers without the need to transfer graphene layers. To stimulate the growth of graphene layers on oxidized silicon a catalyst system of nanometer thin…