First Demonstration of Yttria‐Stabilized Hafnia‐Based Long‐Retention Solid‐State Electrolyte‐Gated Transistor for Human‐Like Neuromorphic Computing

Abstract

Electrolyte‐gated transistors have strong potential for high‐performance artificial synapses in neuromorphic bio‐interfaces owing to their outstanding synaptic characteristics, low power consumption, and human‐like mechanisms. However, the short retention time is a hurdle to overcome owing to the natural diffusion of protons. Here, a novel modulation technique of ionic conductivity is proposed with yttria‐stabilized hafnia for the first time to enhance the retention characteristic of a solid‐state electrolyte‐gated transistor‐based artificial synapse. With the optimization of the ionic conductivity in yttria‐stabilized hafnia, a high retention time of over 300 s and remarkable synaptic characteristics are accomplished by regulating channel conductance with precise modulation of the strength of the proton‐electron coupling intensity along the input signals. Furthermore, pattern recognition simulation is conducted based on the measured synaptic characteristics, exhibiting 94.41% of operation accuracy, which implies a promising solution for neuromorphic in‐memory computing systems with a high operation accuracy and low power consumption.