Journal
NANO RESEARCH
Volume 14, Issue 11, Pages 4258-4263Publisher
TSINGHUA UNIV PRESS
DOI: 10.1007/s12274-021-3611-9
Keywords
carbon nanotube; charge trap; synaptic transistor; long-term memory
Categories
Funding
- National Key Research and Development Program [2016YFA0201902]
- National Natural Science Foundation of China [51991341]
- Open Research Fund of Key Laboratory of Space Utilization, and Chinese Academy of Sciences [LSU-KFJJ-2020-06]
Ask authors/readers for more resources
In this study, carbon nanotube thin films were used to fabricate synaptic transistors, successfully demonstrating weight updates of synapses and mimicking various basic synaptic functions. The research achieved good performance in terms of computational capabilities and power consumption.
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 (similar to 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available