Abstract
SummaryTwo-dimensional (2D) layered materials and their heterostructures have recently been recognized as promising building blocks for futuristic brain-like neuromorphic computing devices. They exhibit unique properties such as near-atomic thickness, dangling-bond-free surfaces, high mechanical robustness, and electrical/optical tunability. Such attributes unattainable with traditional electronic materials are particularly promising for high-performance artificial neurons and synapses, enabling energy-efficient operation, high integration density, and excellent scalability. In this review, diverse 2D materials explored for neuromorphic applications, including graphene, transition metal dichalcogenides, hexagonal boron nitride, and black phosphorous, are comprehensively overviewed. Their promise for neuromorphic applications are fully discussed in terms of material property suitability and device operation principles. Furthermore, up-to-date demonstrations of neuromorphic devices based on 2D materials or their heterostructures are presented. Lastly, the challenges associated with the successful implementation of 2D materials into large-scale devices and their material quality control will be outlined along with the future prospect of these emergent materials.
Highlights
The past couple of decades have been characterized by drastic technological advances leading to the emergence of the era of ‘‘big data,’’ necessitating the study and development of technologies capable of handling colossal amounts of data (LeCun et al, 2015)
There have been extensive studies and significant breakthroughs in the field of artificial intelligence (AI) technology, which enables complex computation and processing of big data at human-level complexity (Lawrence et al, 1997; LeCun et al, 2015). These AI programs employ artificial neural networks (ANNs), which have been proved to outperform traditional algorithms; their computations are based on classic von Neumann architectures (Nawrocki et al, 2016)
Von Neumann architectures have been widely used in computing, yet they are characterized by physical separation and linear interaction between the logic and memory components with a slow data transfer rate leading to high power consumption, and affecting the overall efficiency (Von Neumann, 1993)
Summary
Two-dimensional (2D) layered materials and their heterostructures have recently been recognized as promising building blocks for futuristic brain-like neuromorphic computing devices. They exhibit unique properties such as near-atomic thickness, dangling-bond-free surfaces, high mechanical robustness, and electrical/optical tunability. Diverse 2D materials explored for neuromorphic applications, including graphene, transition metal dichalcogenides, hexagonal boron nitride, and black phosphorous, are comprehensively overviewed. Their promise for neuromorphic applications are fully discussed in terms of material property suitability and device operation principles. The challenges associated with the successful implementation of 2D materials into large-scale devices and their material quality control will be outlined along with the future prospect of these emergent materials
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