journal article·2021

Bi-mode electrolyte-gated synaptic transistor via additional ion doping and its application to artificial nociceptors

Rengjian Yu, Yujie Yan, Enlong Li, Xiaomin Wu, Xianghong Zhang, Jinwei Chen, Yuanyuan Hu, Huipeng Chen, Tailiang Guo

Materials Horizons· Volume 8· Issue 10
Publisher page

Abstract

Multiple types of synaptic transistors that are capable of processing electrical signals similar to the biological neural system hold enormous potential for application in parallel computing, logic circuits and peripheral detection. However, most of these presented synaptic transistors are confined to a single mode of synaptic plasticity under an electrical stimulus, which tremendously limits efficient memory formation and the multifunctional integration of synaptic transistors. Here, we proposed a bi-mode electrolyte-gated synaptic transistor (BEST) with two dynamic processes, the formation of an electrical double layer (EDL) and electrochemical doping (ECD) by tuning the applied voltages, thereby allowing volatile and non-volatile behavior, which is associated with additional ion doping and nanoscale ionic transport. Benefiting from two controllable dynamic processes, we surprisingly found a third state in the transfer curves besides the "off" and "on" states. Moreover, utilizing this unique property, an artificial nociceptor with multilevel modulation of sensitivity was realized based on our bi-mode device. Finally, a haptic sensory system was constructed to exhibit robotic motion that revealed a unique threshold switching behavior, indicating the applicability to peripheral sensing circuits. Hence, the presented bi-mode synaptic transistor provides promising prospects in achieving multiple-mode integrated devices and simplifying neural circuits, which shows great potential in the development of artificial intelligence.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Neuroscience and Neural Engineering · Neural dynamics and brain function

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Institute of Optoelectronic Display, National & Local United Engineering Lab of Flat Panel Display Technology, Fuzhou University, Fuzhou 350002, China

State Key Laboratory for Chemo/Biosensing and Chemometrics, School of Physics and Electronics, Hunan University, Changsha 410082, China

Fujian Science & Technology Innovation Laboratory for Optoelectronic Information of China, Fuzhou 350100, China

Funding

National Natural Science Foundation of China · National Key Research and Development Program of China

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