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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…
Graphene provides a fascinating testbed for new physics and exciting opportunities for future applications based on quantum phenomena. To understand the coherent flow of electrons through a graphene device, we employ a nanoscale probe that…
A low complexity computational model of the current-voltage characteristics for graphene nano-ribbon (GNR) field effect transistors (FET), able to simulate a hundred of points in few seconds using a PC, is presented. For quantum capacitance…
The use of graphene for antennas and other electromagnetic passives could bring significant benefit such as extreme miniaturization, monolithic integration with graphene RF nanoelectronics, efficient dynamic tuning, and even transparency…
We investigate the transport of electrons in disordered and pristine graphene devices. Fano shot noise, a standard metric to assess the mechanism for electronic transport in mesoscopic devices, has been shown to produce almost the same…
Microphones exploit the motion of suspended membranes to detect sound waves. Since the microphone performance can be improved by reducing the thickness and mass of its sensing membrane, graphene-based microphones are expected to outperform…
Atomically precise graphene nanoribbons are a promising emerging class of designer quantum materials with electronic properties that are tunable by chemical design. However, many challenges remain in the device integration of these…
We fabricated a large number of single and bilayer graphene transistors and carried out a systematic experimental study of their low-frequency noise characteristics. A special attention was given to determining the dominant noise sources in…
Graphene has been considered as a promising material for opto-electronic devices, because of its tunable and wideband optical properties. In this work, we demonstrate electro-refractive phase modulation in graphene at wavelengths from 1530…
Resistive random access memory (RRAM) is very well known for its potential application in in-memory and neural computing. However, they often have different types of device-to-device and cycle-to-cycle variability. This makes it harder to…
The performance limits of the multilayer graphene nanoribbon (GNR) field-effect transistor (FET) are assessed and compared to those of monolayer GNR FET and carbon nanotube (CNT) FET. The results show that with a thin high-k gate insulator…
Modern microelectronic devices are composed of interfaces between a large number of materials, many of which are in amorphous or polycrystalline phases. Modeling such non-crystalline materials using first-principles methods such as density…
Graphene, a 2-dimensional monolayer form of sp2 hybridizated carbon atoms, is attracting increasing attention due to its unique and superior physicochemical properties. Covalently functionalized graphene layers, with their modifiable…
This paper presents an electrolytically gated broadband microwave sensor where atomically-thin graphene layers are integrated into coplanar waveguides and coupled with microfluidic channels. The interaction between a solution under test and…
The main target of this article is to propose for the first time a physics-based continuous and symmetric compact model that accurately captures IV experimental dependencies induced by geometrical scaling effects for graphene transistor…
We present a novel, graphene-based device concept for high-frequency operation: a hot electron graphene base transistor (GBT). Simulations show that GBTs have high current on/off ratios and high current gain. Simulations and small-signal…
Graphene opens up for novel optoelectronic applications thanks to its high carrier mobility, ultra-large absorption bandwidth, and extremely fast material response. In particular, the opportunity to control optoelectronic properties through…
Analog neuromorphic computing systems emulate the parallelism and connectivity of the human brain, promising greater expressivity and energy efficiency compared to digital systems. Though many devices have emerged as candidates for…
Graph Signal Processing has become a very useful framework for signal operations and representations defined on irregular domains. Exploiting transformations that are defined on graph models can be highly beneficial when the graph encodes…
The emerging paradigm of abundant-data computing requires real-time analytics on enormous quantities of data collected by a mushrooming network of sensors. Todays computing technology, however, cannot scale to satisfy such big data…