Brain-inspired neuromorphic computing is expected for breaking through the bottleneck of the computer of conventional von Neumann architecture. To this end, the first step is to mimic functions of biological neurons a...Brain-inspired neuromorphic computing is expected for breaking through the bottleneck of the computer of conventional von Neumann architecture. To this end, the first step is to mimic functions of biological neurons and synapses by electronic devices. In this paper, synaptic transistors were fabricated by using carbon nanotube (CNT) thin films and interface charge trapping effects were confirmed to dominate the weight update of the synaptic transistors. Large synaptic weight update was realized due to the high sensitivity of the CNTs to the trapped charges in vicinity. Basic synaptic functions including inhibitory post-synaptic current (IPSC), excitatory post-synaptic current (EPSC), spike-timing-dependent plasticity (STDP), and paired-pulse facilitation (PPF) were mimicked. Large dynamic range of STDP (> 2,180) and low power consumption per spike (∼ 0.7 pJ) were achieved. By taking advantage of the long retention time of the trapped charges and uniform device-to-device performance, long-term image memory behavior of neural network was successfully imitated in a CNT synaptic transistor array.展开更多
Semiconducting single-walled carbon nanotubes (s-SWCNTs) are the foundation of CNT-based electronics and optoelectronics. For practical applications, s-SWCNTs should be produced with high purity, high structural quali...Semiconducting single-walled carbon nanotubes (s-SWCNTs) are the foundation of CNT-based electronics and optoelectronics. For practical applications, s-SWCNTs should be produced with high purity, high structural quality, low cost, and high yield. Currently conjugated polymer wrapping method shows great potential to fulfill these requirements due to its advantages of simple operation process, high purity separation, and easy scaling-up. However, only a small portion of both CNTs and polymers go into the final solution, and most of them are discarded after a single use, resulting in high cost and low yield. In this paper, we introduce a closed-loop recycling strategy, in which raw materials (CNTs and polymers) and solvents were all recycled and reused for multiple separation cycles. In each cycle, high-purity (> 99.9%) s-SWCNTs were obtained with no significant change of structural quality. After 7 times of recycling and separation, the material cost was reduced to ∼ 1% in comparison with commercially available products, and total yield was increased to 36% in comparison with 2%–5% for single cycle separation. Our proposed closed-loop recycling strategy paves the way for low-cost and high-yield mass production of high-quality s-SWCNTs.展开更多
基金This work was supported by the National Key Research and Development Program (No. 2016YFA0201902)the National Natural Science Foundation of China (No. 51991341)the Open Research Fund of Key Laboratory of Space Utilization, and Chinese Academy of Sciences (No. LSU-KFJJ-2020-06).
文摘Brain-inspired neuromorphic computing is expected for breaking through the bottleneck of the computer of conventional von Neumann architecture. To this end, the first step is to mimic functions of biological neurons and synapses by electronic devices. In this paper, synaptic transistors were fabricated by using carbon nanotube (CNT) thin films and interface charge trapping effects were confirmed to dominate the weight update of the synaptic transistors. Large synaptic weight update was realized due to the high sensitivity of the CNTs to the trapped charges in vicinity. Basic synaptic functions including inhibitory post-synaptic current (IPSC), excitatory post-synaptic current (EPSC), spike-timing-dependent plasticity (STDP), and paired-pulse facilitation (PPF) were mimicked. Large dynamic range of STDP (> 2,180) and low power consumption per spike (∼ 0.7 pJ) were achieved. By taking advantage of the long retention time of the trapped charges and uniform device-to-device performance, long-term image memory behavior of neural network was successfully imitated in a CNT synaptic transistor array.
基金This work was supported by the National Key Research and Development Program(No.2016YFA0201902)the National Natural Science Foundation of China(No.51991341)+1 种基金Young Talents Program of Beijing(No.2018000020028G349)the Open Research Fund of Key Laboratory of Space Utilization,Chinese Academy of Sciences(No.LSU-KFJJ-2020-06).
文摘Semiconducting single-walled carbon nanotubes (s-SWCNTs) are the foundation of CNT-based electronics and optoelectronics. For practical applications, s-SWCNTs should be produced with high purity, high structural quality, low cost, and high yield. Currently conjugated polymer wrapping method shows great potential to fulfill these requirements due to its advantages of simple operation process, high purity separation, and easy scaling-up. However, only a small portion of both CNTs and polymers go into the final solution, and most of them are discarded after a single use, resulting in high cost and low yield. In this paper, we introduce a closed-loop recycling strategy, in which raw materials (CNTs and polymers) and solvents were all recycled and reused for multiple separation cycles. In each cycle, high-purity (> 99.9%) s-SWCNTs were obtained with no significant change of structural quality. After 7 times of recycling and separation, the material cost was reduced to ∼ 1% in comparison with commercially available products, and total yield was increased to 36% in comparison with 2%–5% for single cycle separation. Our proposed closed-loop recycling strategy paves the way for low-cost and high-yield mass production of high-quality s-SWCNTs.