Brain-inspired computer architectures have emerged as promising solutions for enhancing energy efficiency of machine learning models such as artificial neuronal networks (ANNs), typically characterized by high energy consumptions when implemented with conventional CMOS processors. Among other emerging components for ANNs, Synaptic Electrolyte-Gated Transistors (EGTs) have emerged as promising solutions to overcome the Van Neumann bottleneck, which is the fundamental limitation in traditional digital computing systems caused by the separation of data memory and processing units. EGTs are essentially conventional Field-Effect Transistors where the gate dielectric is replaced by an electrolyte with mobile ions. These ions can accumulate or intercalate in the channel modifying its conductance in an analogic and permanent way, mimicking the behaviour of a natural synapsis and drastically reducing the energy consumptions. However, they are currently based on electrolytes that are intrinsically unstable and difficult to integrate such as ionic liquids or proton conducting polymers, which are obviously sensitive to humidity and temperature and present a poor compatibility with mainstream microelectronics fabrication processes.

In this work, we will present an all-solid-state oxygen-ion synaptic transistor based on a symmetric battery-like device in which oxygen-ions are transferred between two mixed ionic-electronic conducting (MIEC) perovskite oxide thin-films (i.e. channel and gate) through a solid-state electrolyte. Oxygen ions intrinsically present an enhanced stability and compatibility compared to other smaller ions such as Li+ or H+ but the sluggish oxygen diffusivity of solid-state materials has typically limited the application to liquid electrolytes. In order to address this important issue, a superior oxide-ion conducting thin film of Bi2V1‑xCuxO(11/2)‑x (BICUVOX) with highest oxygen conductivities at low temperature ever reported is used as low temperature electrolyte.[1] The device was manufactured by pulsed laser deposition (PLD) and conventional microfabrication techniques. The conductance of the channel is controlled via a gate bias, allowing for oxygen-ions intercalation between gate and channel as well as multistate operation in the millisecond range. In-situ electrical conductivity measurements at low temperatures (< 150 °C) reveal fast and remarkable low energy consumption. Due to its multi-states, the presented EGT reveals synaptic features such as short-term plasticity (STP) and paired pulse facilitation (PPF), which are known as fundamental properties of synaptic plasticity in biological neural networks. The proposed synaptic transistor has the potential to lead to a breakthrough in energy efficiency and processor performance in information technology.