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Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems

With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the des...

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Autores principales: Lu, Qifeng, Zhao, Yinchao, Huang, Long, An, Jiabao, Zheng, Yufan, Yap, Eng Hwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921566/
https://www.ncbi.nlm.nih.gov/pubmed/36770333
http://dx.doi.org/10.3390/nano13030373
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author Lu, Qifeng
Zhao, Yinchao
Huang, Long
An, Jiabao
Zheng, Yufan
Yap, Eng Hwa
author_facet Lu, Qifeng
Zhao, Yinchao
Huang, Long
An, Jiabao
Zheng, Yufan
Yap, Eng Hwa
author_sort Lu, Qifeng
collection PubMed
description With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored.
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spelling pubmed-99215662023-02-12 Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems Lu, Qifeng Zhao, Yinchao Huang, Long An, Jiabao Zheng, Yufan Yap, Eng Hwa Nanomaterials (Basel) Review With the rapid development of artificial intelligence and the Internet of Things, there is an explosion of available data for processing and analysis in any domain. However, signal processing efficiency is limited by the Von Neumann structure for the conventional computing system. Therefore, the design and construction of artificial synapse, which is the basic unit for the hardware-based neural network, by mimicking the structure and working mechanisms of biological synapses, have attracted a great amount of attention to overcome this limitation. In addition, a revolution in healthcare monitoring, neuro-prosthetics, and human–machine interfaces can be further realized with a flexible device integrating sensing, memory, and processing functions by emulating the bionic sensory and perceptual functions of neural systems. Until now, flexible artificial synapses and related neuromorphic systems, which are capable of responding to external environmental stimuli and processing signals efficiently, have been extensively studied from material-selection, structure-design, and system-integration perspectives. Moreover, low-dimensional materials, which show distinct electrical properties and excellent mechanical properties, have been extensively employed in the fabrication of flexible electronics. In this review, recent progress in flexible artificial synapses and neuromorphic systems based on low-dimensional materials is discussed. The potential and the challenges of the devices and systems in the application of neuromorphic computing and sensory systems are also explored. MDPI 2023-01-17 /pmc/articles/PMC9921566/ /pubmed/36770333 http://dx.doi.org/10.3390/nano13030373 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Lu, Qifeng
Zhao, Yinchao
Huang, Long
An, Jiabao
Zheng, Yufan
Yap, Eng Hwa
Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title_full Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title_fullStr Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title_full_unstemmed Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title_short Low-Dimensional-Materials-Based Flexible Artificial Synapse: Materials, Devices, and Systems
title_sort low-dimensional-materials-based flexible artificial synapse: materials, devices, and systems
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9921566/
https://www.ncbi.nlm.nih.gov/pubmed/36770333
http://dx.doi.org/10.3390/nano13030373
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