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Electric double layer effect in solid electrochemical systems is a key topic in energy storage applications. In this review, we outline recent investigations on the electric double layer effect of solid electrolyte interfaces by utilizing a semiconducting diamond surface as a probe of electrical charges at the solid/solid interfaces. Hall measurements with various solid electrolyte-based transistors evidenced that the electric double-layer effect strongly depends on the properties of the electrolyte and the very thin region from the interface. The unveiled features of the electric double layer at solid electrolyte interfaces are quantitatively discussed from the viewpoint of charge density and charging-discharging rate. Furthermore, applications of the unique switching response of the electric double layer transistors to neuromorphic computing are also demonstrated. [ABSTRACT FROM AUTHOR]

The electric double layer (EDL) effect at solid electrolyte/electrode interfaces has been a key topic in many energy and nanoelectronics applications (e.g., all-solid-state Li+ batteries and memristors). However, its characterization remains difficult in comparison with liquid electrolytes. Herein, we use a novel method to show that the EDL effect, and its suppression at solid electrolyte/electronic material interfaces, can be characterized on the basis of the electric conduction characteristics of hydrogenated diamond(H-diamond)-based EDL transistors (EDLTs). Whereas H-diamond-based EDLT with a Li-Si-Zr-O Li+ solid electrolyte showed EDL-induced hole density modulation over a range of up to three orders of magnitude, EDLT with a Li-La-Ti-O (LLTO) Li+ solid electrolyte showed negligible enhancement, which indicates strong suppression of the EDL effect. Such suppression is attributed to charge neutralization in the LLTO, which is due to variation in the valence state of the Ti ions present. The method described is useful for quantitatively evaluating the EDL effect in various solid electrolytes. The effect of the electric double layer with solid electrolytes remains hard to characterize. In this study, the authors show how to evaluate the electric double layer effect with various lithium solid electrolytes using a hydrogenated diamond-based transistor. [ABSTRACT FROM AUTHOR]

Memory is believed to occur in the human brain as a result of two types of synaptic plasticity: short-term plasticity (STP) and long-term potentiation (LTP; refs , , , ). In neuromorphic engineering, emulation of known neural behaviour has proven to be difficult to implement in software because of the highly complex interconnected nature of thought processes. Here we report the discovery of a Ag2S inorganic synapse, which emulates the synaptic functions of both STP and LTP characteristics through the use of input pulse repetition time. The structure known as an atomic switch, operating at critical voltages, stores information as STP with a spontaneous decay of conductance level in response to intermittent input stimuli, whereas frequent stimulation results in a transition to LTP. The Ag2S inorganic synapse has interesting characteristics with analogies to an individual biological synapse, and achieves dynamic memorization in a single device without the need of external preprogramming. A psychological model related to the process of memorizing and forgetting is also demonstrated using the inorganic synapses. Our Ag2S element indicates a breakthrough in mimicking synaptic behaviour essential for the further creation of artificial neural systems that emulate characteristics of human memory. [ABSTRACT FROM AUTHOR]

We demonstrate memristive operations using gap-type AgS atomic switches, in which the growth and shrinkage of an Ag protrusion are controlled by using solid-electrochemical reactions. In addition to conventional memristive operations such as those proposed and demonstrated by resistive random-access memories (ReRAMs) using metal oxide compounds, gap-type AgS atomic switches also show new types of memristive operations by storing information from input signals without changing their output until a sufficient number of signals are inputted. The new types of memristive operations resemble the learning process seen in neuroplasticity, where changes occur in the organization of the human brain as a result of experience. [ABSTRACT FROM AUTHOR]