Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks.

ABSTRACT: Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation is the ultimate goal of emerging memristor technology, in which the storage and computation can be done in the same memory crossbar. In this work, an analog memristor device is fabricated utilizing the unique characteristics of single-wall carbon nanotubes (SWCNTs) to act as the switching medium of the device. Via the planar structure, the memristor device exhibits analog switching ability with high state stability. The device's conductance and capacitance can be tuned simultaneously, increasing the device's potential and broadening its applications' horizons. The multi-state storage capability and long-term memory are the key factors that make

SUBMITTER: Abunahla H 

PROVIDER: S-EPMC10696067 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature