Ultralow‐Power and Multisensory Artificial Synapse Based on Electrolyte‐Gated Vertical Organic Transistors

TLDR

Bioinspired electronics hold great promise for AI and brain‑like science, with low energy consumption and multifunctionality being key for application. The study develops multisensory artificial synapses and neural networks using electrolyte‑gated vertical organic field‑effect transistors. The authors employ 30‑nm channel VOFETs achieved via cross‑linking and design an artificial tongue capable of acidity discrimination. The 30‑nm VOFET synapses consume only 0.06 fJ per event—far below biological synapses—and can learn and remember images in a 5 × 5 array, emulate spatiotemporal processing and sound azimuth detection, and enable an acidity‑discriminating artificial tongue, demonstrating energy‑efficient artificial synapses that mimic biological sensory systems.

Abstract

Abstract 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.