LAUSR

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, we experimentally demonstrate that a Fe3 O4 water-based Ferrofluid (FF) can perform electrical analogue computing and be programmed using quasi DC signals and read at Radio Frequency (RF) mode. We have observed features in all respects attributable to a memristive behaviour, featuring both short and long-term information storage capacity and plasticity. The colloid was capable of classifying digits of a 8 × 8 pixel dataset using a custom in-memory signal processing scheme, and through Physical Reservoir Computing (PRC) 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. This article is protected by copyright. All rights reserved.