logo
ResearchBunny Logo
Abstract
This work investigates the use of microfabricated, graphene-based Vertical RRAM (VRRAM) in neuromorphic computing. By using graphene, the VRRAM array shows improved read/write margins and reduced read inaccuracy, leading to significant energy reduction. An XNOR logic-inspired architecture with 1-bit ternary precision synaptic weights is introduced. Simulations show 83.5% and 94.1% recognition accuracy for VRRAMs with metal and graphene word-planes, respectively, highlighting the benefits of graphene.
Publisher
npj 2D Materials and Applications
Published On
May 14, 2021
Authors
Batyrbek Alimkhanuly, Joon Sohn, Ik-Joon Chang, Seunghyun Lee
Tags
Graphene
Vertical RRAM
Neuromorphic Computing
Energy Reduction
Recognition Accuracy
Synaptic Weights
XNOR Logic

Related Publications

Explore these studies to deepen your understanding of the subject.

Electron-beam-irradiated rhenium disulfide memristors with low variability for neuromorphic computing
Engineering and Technology

Electron-beam-irradiated rhenium disulfide memristors with low variability for neuromorphic computing

S. Li, B. Li, et al.

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles
Engineering and Technology

3D printed graphene-based self-powered strain sensors for smart tires in autonomous vehicles

D. Maurya, S. Khaleghian, et al.

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction
Engineering and Technology

Toward grouped-reservoir computing: organic neuromorphic vertical transistor with distributed reservoir states for efficient recognition and prediction

C. Gao, D. Liu, et al.

Transistors with ferroelectric ZrxAl₁₋ₓOY crystallized by ZnO growth for multi-level memory and neuromorphic computing
Engineering and Technology

Transistors with ferroelectric ZrxAl₁₋ₓOY crystallized by ZnO growth for multi-level memory and neuromorphic computing

M. M. Islam, A. Ali, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs—just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny