Two-Dimensional Near-Atom-Thickness Materials for Emerging Neuromorphic Devices and Applications

Area of Science:

• Materials Science
• Nanotechnology
• Computer Engineering

Background:

• Two-dimensional (2D) layered materials possess unique properties like atomic thickness and tunable electronic/optical characteristics.
• These properties are advantageous for developing next-generation brain-like neuromorphic computing devices.
• Traditional materials lack the attributes necessary for high-performance artificial neurons and synapses.

Purpose of the Study:

• To provide a comprehensive overview of 2D materials for neuromorphic applications.
• To discuss the suitability of material properties and device operation principles.
• To present current demonstrations and future prospects of 2D material-based neuromorphic devices.

Main Methods:

• Review of diverse 2D materials including graphene, transition metal dichalcogenides, hexagonal boron nitride, and black phosphorus.
• Analysis of material properties relevant to artificial neurons and synapses.
• Examination of device operation principles and recent experimental demonstrations.

Main Results:

• 2D materials exhibit exceptional potential for energy-efficient, highly integrated, and scalable neuromorphic computing.
• Graphene, TMDs, h-BN, and black phosphorus show promise due to their unique physical and chemical attributes.
• Current research demonstrates viable neuromorphic device functionalities using 2D materials and heterostructures.

Conclusions:

• 2D materials are key candidates for realizing advanced neuromorphic computing architectures.
• Addressing challenges in large-scale implementation and material quality control is crucial for future development.
• Emergent 2D materials hold significant promise for the future of artificial intelligence hardware.