• Korean Journal of Materials Research
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• v.27 no.11
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• pp.590-596
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• 2017

We demonstrated a CNT synaptic transistor by integrating 6,6-phenyl-C61 butyric acid methyl ester(PCBM) molecules as charge storage molecules in a polyimide(PI) dielectric layer with carbon nanotubes(CNTs) for the transistor channel. Specifically, we fabricated and compared three different kinds of CNT-based synaptic transistors: a control device with $Al_2O_3/PI$, a single PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%), and a double PCBM device with $Al_2O_3/PI:PCBM$(0.1 wt%)/PI:PCBM(0.05 wt%). Statistically, essential device parameters such as Off and On currents, On/Off ratio, device yield, and long-term retention stability for the three kinds of transistor devices were extracted and compared. Notably, the double PCBM device exhibited the most excellent memory transistor behavior. Pulse response properties with postsynaptic dynamic current were also evaluated. Among all of the testing devices, double PCBM device consumed such low power for stand-by and its peak current ratio was so large that the postsynaptic current was also reliably and repeatedly generated. Postsynaptic hole currents through the CNT channel can be generated by electrons trapped in the PCBM molecules and last for a relatively short time(~ hundreds of msec). Under one certain testing configuration, the electrons trapped in the PCBM can also be preserved in a nonvolatile manner for a long-term period. Its integrated platform with extremely low stand-by power should pave a promising road toward next-generation neuromorphic systems, which would emulate the brain power of 20 W.

• Ceramist
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• v.21 no.2
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• pp.4-18
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• 2018

Lastly, neuromorphic computing chip has been extensively studied as the technology that directly mimics efficient calculation algorithm of human brain, enabling a next-generation intelligent hardware system with high speed and low power consumption. Three-terminal based synaptic transistor has relatively low integration density compared to the two-terminal type memristor, while its power consumption can be realized as being so low and its spike plasticity from synapse can be reliably implemented. Also, the strong electrical interaction between two or more synaptic spikes offers the advantage of more precise control of synaptic weights. In this review paper, the results of synaptic transistor mimicking synaptic behavior of the brain are classified according to the channel material, in order of silicon, organic semiconductor, oxide semiconductor, 1D CNT(carbon nanotube) and 2D van der Waals atomic layer present. At the same time, key technologies related to dielectrics and electrolytes introduced to express hysteresis and plasticity are discussed. In addition, we compared the essential electrical characteristics (EPSC, IPSC, PPF, STM, LTM, and STDP) required to implement synaptic transistors in common and the power consumption required for unit synapse operation. Generally, synaptic devices should be integrated with other peripheral circuits such as neurons. Demonstration of this neuromorphic system level needs the linearity of synapse resistance change, the symmetry between potentiation and depression, and multi-level resistance states. Finally, in order to be used as a practical neuromorphic applications, the long-term stability and reliability of the synapse device have to be essentially secured through the retention and the endurance cycling test related to the long-term memory characteristics.