Unveiling the Fundamental Principles of Reconfigurable Resistance States in Silver/Poly(Ethylene Glycol) Nanofluids.

Developing novel memristive systems aims to implement key principles of biological neuron assemblies - plasticity, adaptivity, and self-organization - into artificial devices for parallel, energy-efficient computing. Solid-state memristive devices, such as crossbar arrays and percolated nanoparticle (NP) networks, already demonstrate these properties. However, closer similarity to neural networks is expected from liquid-state systems, including polymer melts, which remain largely unexplored. Here, the resistive switching in silver/poly(ethylene glycol) (Ag/PEG) nanofluids, prepared by depositing gas-aggregated Ag NPs into PEGs of varying molecular mass, is investigated. These systems form long-range conductive NP bridges with reconfigurable resistance states in response to an electric field. The zeta-potential of Ag NPs and molecular mobility of PEG determine the prevalence of low resistance (ohmic) state, high resistance states (poor conductance) or intermediate transition states governed by space-charge-limited conduction or electron tunneling. The occurrence of these states is given by the interparticle gaps, which are determined by the conformation of PEG molecules adsorbed on the NPs. It is presented, for the first time, an equivalent circuit model for the Ag/PEG system. These findings pave the way to adopt polymer melts as matrices for neuromorphic engineering and bio-inspired electronics.