Liquid-Based Memory Devices for Next-Generation Computing

Abstract

Liquid-based devices have emerged as bioinspired neuromorphic applications owing to their high ion-diffusion coefficients, diverse structures, and controllable ion-exchange reactions. By engineering and modifying liquid materials, multifunctional liquid-based computing devices have been developed for next-generation memory and neuromorphic devices. The unique properties of liquids make them feasible for memory functions and various synaptic applications, such as emulating synaptic plasticity, homeostasis, and action potentials. Utilizing liquids in computing devices provides a promising and versatile platform for high-performance memory devices and enables the emulation of bioinspired computing functions. In this Spotlight, we highlight recent advances in liquid-based memory devices and focus on synaptic applications. We then discuss possible array structures and scaling-down technologies for liquid-based devices. Finally, the challenges and future prospects of liquid-based devices are discussed.

Single-Pore Nanofluidic Logic Memristor with Reconfigurable Synaptic Functions and Designable Combinations

“…The fundamental mechanism underlying learning and memory in biological systems is synaptic plasticity, which can be modulated by environmental chemical signals. , Previous research has employed memristors to mimic synaptic plasticity for brain-like computations. − However, the memristive devices are made of phase-change, metal-oxide, magnetic, or ferroelectric materials, in which the working mechanisms are different from the brain. In contrast, nanofluidic devices, which are in continuous development, − achieve many intelligent functions by controlling ion transport in nanochannels. − Specifically, a nanofluidic memristor is a device that can simulate synaptic behaviors depending on the ion transport in nanochannels, which is very similar to the ion-regulating mechanism in the brain. , Recent advancements in nanofluidic memristor technology have been achieved through various approaches, including the development of two-dimensional nanofluidic channels, , exploration of confined polyelectrolyte-ion interactions, , investigation into the elastic deformation of nanopores, utilization of angstrom-scale funnel-shaped channels, and implementation of multipore membranes …”

Gradual conductance modulation by defect reorganization in amorphous oxide memristors

“…7 In addition, thanks to the recent advances in neuromorphic computing, memristors have become the core components of artificial neural network (ANN) arrays. 8,9 In order to realize the switching of resistance, various principles are employed, such as electrochemical metallization (ECM), [10][11][12][13] phase transition, 14 polarization reversal, 15 ion transport, 16 etc. More intuitively, memristors can also be classified according to whether they form conductive filaments.…”

Wide-Range Synaptic Current Responses with a Liquid Ga Electrode via a Surface Redox Reaction in a NaOH Solution at Different Molar Concentrations

“…Very recently, an ionic device using liquid Ga was made to resemble neural spike signals, which is beneficial for organ cell–machine interface systems because Ga is biocompatible and flexible at room temperature. , Depending on the specific application, synaptic functions with different decay constants are required for synaptic devices because synaptic functions with different decay constants can affect the temporal dynamics of the network and its ability to perform certain computations, such as short-term memory or pattern recognition . Synaptic decay refers to the gradual decrease in the strength of a synaptic connection over time.…”