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Convolutional neural networks have become an essential element of spatial deep learning systems. In the prevailing architecture, the convolution operation is performed with Fast Fourier Transforms (FFT) electronically in GPUs. The…
Circuit quantum electrodynamics, where photons are coherently coupled to artificial atoms built with superconducting circuits, has enabled the investigation and control of macroscopic quantum-mechanical phenomena in superconductors.…
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…
Ubiquitous graphene is a stricly 2D material representing an ideal adsorbing platform due to its large specific surface area as well as its mechanical strength and resistance to both thermal and chemical stresses. However, graphene as a…
Substrate plays a crucial role in determining transport and low frequency noise behavior of graphene field effect devices. Typically, heavily dope Si/SiO$_2$ substrate is used to fabricate these devices for efficient gating.…
Graphene nano-ribbons, GNRs, are promising channel materials for next-generation ultra-miniaturised devices due to their exceptional electrical and thermal properties which arise from their atomic thickness, as well as their ability to have…
Generating spintronic devices has been a goal for the nano-science. We have used density function theory to determine magnetic phases of single layer and bilayer lithium doped graphene nanoflakes. We have introduced graphene flakes as…
The directional control of light in miniaturized plasmonic waveguides holds appealing possibilities for emerging nanophotonic technologies, but is hindered by the intrinsic reciprocal optical response of conventional plasmonic materials.…
The electrostatic coupling between singled-walled carbon nanotube (SWNT) networks/arrays and planar gate electrodes in thin-film transistors (TFTs) is analyzed both in the quantum limit with an analytical model and in the classical limit…
Designing platforms to control phase-coherence and interference of electron waves is a cornerstone for future quantum electronics, computing or sensing. Nanoporous graphene (NPG) consisting of linked graphene nanoribbons has recently been…
We report the fabrication of electrostatically defined nanostructures in encapsulated bilayer graphene, with leakage resistances below depletion gates as high as $R \sim 10~$G$\Omega$. This exceeds previously reported values of $R =~$10 -…
Graphene field-effect transistors are fabricated utilizing single-crystal hexagonal boron nitride (h-BN), an insulating isomorph of graphene, as the gate dielectric. The devices exhibit mobility values exceeding 10,000 cm2/V-sec and current…
Neuromorphic Computing (NC), which emulates neural activities of the human brain, is considered for low-power implementation of artificial intelligence. Towards realizing NC, fabrication, and investigations of hardware elements such as…
Solid-state memory is an essential component of the digital age. With advancements in healthcare technology and the Internet of Things (IoT), the demand for ultra-dense, ultra-low-power memory is increasing. In this review, we present a…
We show that reversible two- and three-input logic gates, among which we mention the universal Toffoli gate, can be implemented with three tilted gating electrodes patterned on a monolayer graphene flake. These low-dissipation gates are…
Three types of first generation epitaxial graphene field effect transistors (FET) are presented and their relative merits are discussed. Graphene is epitaxially grown on both the carbon and silicon faces of hexagonal silicon carbide and…
Recently synthesized Porous 12-Atom-Wide Armchair Graphene Nanoribbons Nano Lett. 2024, 24, 10718-10723 exhibit tunable properties through periodic porosity, enabling precise control over their electronic, optical, thermal, and mechanical…
On-chip learning in a crossbar array based analog hardware Neural Network (NN) has been shown to have major advantages in terms of speed and energy compared to training NN on a traditional computer. However analog hardware NN proposals and…
The paradigm of graphene transistors is based on the gate modulation of the channel carrier density by means of a local channel gate. This standard architecture is subject to the scaling limit of the channel length and further restrictions…
From the moment atomic precision control of the growth process of graphene was achieved, more elaborated carbon allotropes were proposed opening new channels for flat optoelectronics at the nanoscale. A special type of this material…