The further development of traditional von Neumann-architecture computers is limited by the breaking of Moore’s law and the von Neumann bottleneck, which make them unsuitable for future high-performance artificial in...The further development of traditional von Neumann-architecture computers is limited by the breaking of Moore’s law and the von Neumann bottleneck, which make them unsuitable for future high-performance artificial intelligence (AI)systems. Therefore, new computing paradigms are desperately needed. Inspired by the human brain, neuromorphic computing is proposed to realize AI while reducing power consumption. As one of the basic hardware units for neuromorphic computing, artificial synapses have recently aroused worldwide research interests. Among various electronic devices that mimic biological synapses, synaptic transistors show promising properties, such as the ability to perform signal transmission and learning simultaneously, allowing dynamic spatiotemporal information processing applications. In this article, we provide a review of recent advances in electrolyte-and ferroelectric-gated synaptic transistors. Their structures, materials,working mechanisms, advantages, and disadvantages will be presented. In addition, the challenges of developing advanced synaptic transistors are discussed.展开更多
基金Project supported by the National Key R&D Program of China(Grant Nos.2017YFA0303604 and 2019YFA0308500)the Youth Innovation Promotion Association of Chinese Academy of Sciences(Grant No.2018008)+1 种基金the Key Research Program of Frontier Sciences of Chinese Academy of Sciences(Grant No.QYZDJSSW-SLH020)the National Natural Science Foundation of China(Grant Nos.11674385,11404380,11721404,and 11874412)。
文摘The further development of traditional von Neumann-architecture computers is limited by the breaking of Moore’s law and the von Neumann bottleneck, which make them unsuitable for future high-performance artificial intelligence (AI)systems. Therefore, new computing paradigms are desperately needed. Inspired by the human brain, neuromorphic computing is proposed to realize AI while reducing power consumption. As one of the basic hardware units for neuromorphic computing, artificial synapses have recently aroused worldwide research interests. Among various electronic devices that mimic biological synapses, synaptic transistors show promising properties, such as the ability to perform signal transmission and learning simultaneously, allowing dynamic spatiotemporal information processing applications. In this article, we provide a review of recent advances in electrolyte-and ferroelectric-gated synaptic transistors. Their structures, materials,working mechanisms, advantages, and disadvantages will be presented. In addition, the challenges of developing advanced synaptic transistors are discussed.
