Graphene-Based Artificial Synapses with Tunable Plasticity

Design and implementation of artificial neuromorphic systems able to provide brain akin computation and/or bio-compatible interfacing ability are crucial for understanding the human brain's complex functionality and unleashing brain-inspired computation's full potential. To this end, the realization of energy-efficient, low-area, and bio...

Graphene Nanoribbon-based Synapses with Versatile Plasticity

Designing and implementing artificial systems that can be interfaced with the human brain or that can provide computational ability akin to brain's processing information efficient style is crucial for understanding human brain fundamental operating principles and to unleashing the full potential of brain-inspired computing. As basic neural...

Compact Graphene-Based Spiking Neural Network with Unsupervised Learning Capabilities

To fully unleash the potential of graphene-based devices for neuromorphic computing, we propose a graphene synapse and a graphene neuron that form together a basic Spiking Neural Network (SNN) unit, which can potentially be utilized to implement complex SNNs. Specifically, the proposed synapse enables two fundamental synaptic functionalities,...

Ultra-Compact, Entirely Graphene-based Nonlinear Leaky Integrate-and-Fire Spiking Neuron

Designing and implementing artificial neuromorphic systems, which can provide biocompatible interfacing, or the human brain akin ability to efficiently process information, is paramount to the understanding of the human brain complex functionality. Energy-efficient, low-area, and biocompatible artificial neurons are key ubiquitous components of...

A study of graphene nanoribbon-based gate performance robustness under temperature variations

As CMOS scaling is reaching its limits, high power density and leakage, low reliability, and increasing IC production costs are prompting for developing new materials, devices, architectures, and computation paradigms. Additionally, temperature variations have a significant impact on devices and circuits reliability and performance. Graphene...

On Basic Boolean Function Graphene Nanoribbon Conductance Mapping

In this paper, we augment a trapezoidal Quantum Point Contact topology with top gates to form a butterfly Graphene Nanoribbon (GNR) structure and demonstrate that by adjusting its topology, its conductance map can mirror basic Boolean functions, thus one can use such structures instead of transistors to build carbon-based gates and circuits....

Graphene Nanoribbon Based Complementary Logic Gates and Circuits

As CMOS feature size is reaching atomic dimensions, unjustifiable static power, reliability, and economic implications are exacerbating, thereby prompting for conducting research on new materials, devices, and/or computation paradigms. Within this context, graphene nanoribbons (GNRs), owing to graphene's excellent electronic properties, may...