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-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 x 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.

Automated summary

This study presents the development of multisensory artificial synapse and neural networks based on electrolyte-gated vertical organic field-effect transistors (VOFETs). With a scaled down channel length and a large electric double layer capacitance, the artificial synapse exhibits significantly lower power consumption compared to biological synapses. It is capable of learning and memory functions, as well as emulating human brain's information processing and sound detection. Additionally, the artificial synapse can be applied in acidity discrimination as an artificial tongue.