Nanoionics from Biological to Artificial Systems: An Alternative Beyond Nanoelectronics

Abstract

Ion transport under nanoconfined spaces is a ubiquitous phenomenon in nature and plays an important role in the energy conversion and signal transduction processes of both biological and artificial systems. Unlike the free diffusion in continuum media, anomalous behaviors of ions are often observed in nanostructured systems, which is governed by the complex interplay between various interfacial interactions. Conventionally, nanoionics mainly refers to the study of ion transport in solid‐state nanosystems. In this review, to extent this concept is proposed and a new framework to understand the phenomena, mechanism, methodology, and application associated with ion transport at the nanoscale is put forward. Specifically, here nanoionics is summarized into three categories, i.e., biological, artificial, and hybrid, and discussed the characteristics of each system. Compared with nanoelectronics, nanoionics is an emerging research field with many theoretical and practical challenges. With this forward‐looking perspective, it is hoped that nanoionics can attract increasing attention and find wide range of applications as nanoelectronics.

Advancement in Soft Iontronic Resistive Memory Devices and Their Application for Neuromorphic Computing

“…[149] While iontronic devices may not be able to perform high-level information processing, they may be able to perform low-energy information processing, such as writing and erasing information under certain conditions. [145,152] As a result, iontronic-based memory devices can be developed that will last much longer than the electronic memory devices currently in use, and such applications will be required for secure, long-term data storage. [149,155] Meanwhile, iontronics are predicted to play a key role in the storage of information and sensory technologies.…”

“…[149,155] Meanwhile, iontronics are predicted to play a key role in the storage of information and sensory technologies. [145,149,152] In order to understand data storage phenomena, iontronic devices are discussed as aqueous electrolyte modulators to achieve resistive switching behavior.…”

“…[156] Synaptic plasticity provides the basis for learning, memory, and development in neural circuits by enabling external stimuli to be processed and stored as changes in synaptic weights, providing the basis for learning, memory, and development in neural circuits as a result. [145,152] To achieve brain-inspired computing, both solid-state memristors and nanofluidic iontronic memristors have been used to emulate synaptic plasticity of different levels. [145,149,152] In this way, biologicalartificial iontronic systems can be realized for the fabrication of the iontronic neuromorphic resistive switching memory devices.…”

“…[145,152] To achieve brain-inspired computing, both solid-state memristors and nanofluidic iontronic memristors have been used to emulate synaptic plasticity of different levels. [145,149,152] In this way, biologicalartificial iontronic systems can be realized for the fabrication of the iontronic neuromorphic resistive switching memory devices.…”

“…In summary, although some plasticity patterns are yet not obtained by memristor-based systems, the nature of nanofluidics may make it possible to realize these dynamics using memristors. [145,149,152] Synaptic scaling, which multiplicatively adjusts the synaptic weights of a group of synapses, is one major difficulty for memristor systems. [149,152] When a stimulus causes excessive LTP, this action helps maintain the homeostasis of the cell and shields the system from epileptogenic excitement or quiescence.…”