Recent Developments on Novel 2D Materials for Emerging Neuromorphic Computing Devices

The rapid advancement of artificial intelligent and information technology has led to a critical need for extremely low power consumption and excellent efficiency. The capacity of neuromorphic computing to handle large amounts of data with low power consumption has garnered a lot of interest during...

Full description

Saved in:
Bibliographic Details
Main Authors: Muhammad Hamza Pervez, Ehsan Elahi, Muhammad Asghar Khan, Muhammad Nasim, Muhammad Asim, Arslan Rehmat, Malik Abdul Rehman, Mohammed A. Assiri, Shania Rehman, Jonghwa Eom, Muhammad Farooq Khan
Format: Article
Language:English
Published: Wiley-VCH 2025-02-01
Series:Small Structures
Subjects:
Online Access:https://doi.org/10.1002/sstr.202400386
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The rapid advancement of artificial intelligent and information technology has led to a critical need for extremely low power consumption and excellent efficiency. The capacity of neuromorphic computing to handle large amounts of data with low power consumption has garnered a lot of interest during the last few decades. For neuromorphic applications, 2D layered semiconductor materials have shown a pivotal role due to their distinctive properties. This comprehensive review provides an extensive study of the recent advancements in 2D materials‐based neuromorphic devices especially in multiterminal synaptic devices, two‐terminal synaptic devices, neuronal devices, and the integration of synaptic and neuronal devices. Herein, a wide range of potential applications of memory, computation, adaptation, and artificial intelligence is incorporated. Finally, the limitations and challenges of neuromorphic devices based on novel 2D materials are discussed. Thus, this review aims to illuminate the design and fabrication of neuromorphic devices based on van der Waals (vdW) heterostructure materials, leveraging promising engineering techniques to excel the applications and potential of neuromorphic computing for hardware implementations.
ISSN:2688-4062