Experimental Demonstration of In‐Memory Computing in a Ferrofluid System

Abstract

Magnetic fluids are excellent candidates for several important research fields including energy harvesting, biomedical applications, soft robotics, and exploration. However, notwithstanding relevant advancements such as shape reconfigurability, that have been demonstrated, there is no evidence for their computing capability, including the emulation of synaptic functions, which requires complex non‐linear dynamics. Here, it is experimentally demonstrated that a Fe3O4 water‐based ferrofluid (FF) can perform electrical analogue computing and be programmed using quasi direct current (DC) signals and read at radio frequency (RF) mode. Features have been observed in all respects attributable to a memristive behavior, featuring both short and long‐term information storage capacity and plasticity. The colloid is capable of classifying digits of a 8 × 8 pixel dataset using a custom in‐memory signal processing scheme, and through physical reservoir computing by training a readout layer. These findings demonstrate the feasibility of in‐memory computing using an amorphous FF system in a liquid aggregation state. This work poses the basis for the exploitation of a FF colloid as both an in‐memory computing device and as a full‐electric liquid computer thanks to its fluidity and the reported complex dynamics, via probing read‐out and programming ports.

Logical circuits in colloids

“…Our experiments conducted in controlled laboratory conditions also revealed the potential of ZnO colloid mixtures to function as electrical analogue neurons, successfully implementing synaptic-like learning as described in [ 10 , 11 ], as well as demonstrating the manifestation of Pavlovian reflexes [ 12 ]. The experimental study presented in [ 13 ] showcases the classification capabilities of a Fe 3 O 4 water-based ferrofluid for digit recognition within an 8 8-pixel dataset. Additionally, we demonstrated that this ferrofluid could be programmed using quasi-direct current signals and read in radio frequency mode.…”

Robot locomotion by fluid–fluid interaction

“…Researchers have demonstrated movement and manipulation of a liquid cluster based on ferrofluids [2][3][4] and liquid metals [5][6][7][8][9] . Furthermore, ferrofluids have also been reported to enable in-memory computation 10 . These robotic systems usually move by applying external electromagnetic fields.…”