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Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors
Bioinspired electronics have shown great potential in the field of artificial intelligence and brain‐like science. Low energy consumption and multifunction are key factors for its application. Here, multisensory artificial synapse and neural networks based on electrolyte‐gated vertical organic field...
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Published in: | Advanced functional materials 2022-07, Vol.32 (27), p.n/a |
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Main Authors: | , , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Bioinspired electronics have shown great potential in the field of artificial intelligence and brain‐like science. Low energy consumption and multifunction are key factors for its application. Here, multisensory artificial synapse and neural networks based on electrolyte‐gated vertical organic field‐effect transistors (VOFETs) are first developed. The channel length of the organic transistor is scaled down to 30 nm through cross‐linking strategy. Owing to the short channel length and extremely large capacitance of the electric double layer formed at the electrolyte–channel interface, the minimum power consumption of one synaptic event is 0.06 fJ, which is significantly lower than that required by biological synapses (1–10 fJ). Moreover, the artificial synapse can be trained to learn and memory images in a 5 × 5 synapse array and emulate the human brain's spatiotemporal information processing and sound azimuth detection. Finally, the artificial tongue is designed using the synaptic transistor that can discriminate acidity. Overall, this study provides new insights into realizing energy‐efficient artificial synapses and mimicking biological sensory systems.
Multisensory artificial synapses based on electrolyte‐gated vertical organic field‐effect transistors are first developed. The artificial synapse can emulate human multiple perceptions, such as image learning and memorizing, sound localization, and taste detection. The minimum energy consumption (Ec) of one synaptic event is 0.06 fJ, which is significantly lower than that of biological synapses (1–10 fJ). |
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ISSN: | 1616-301X 1616-3028 |
DOI: | 10.1002/adfm.202200959 |