Open Access Conference Proceedings

Neuromorphic engineering is a rapidly developing branch of science that aims to implement the unique attributes of biological neural networks in artificial devices. Most neuromorphic devices are based on the resistive switching effect, which involves changing the device’s conductivity in response to an external electric field. For instance, percolating nanoparticle (NP) networks produced by gas aggregation cluster sources (GAS) show collective spiking behavior in conductivity reminiscent of brain-like dynamics. Nevertheless, the problem of dynamic spatial reconfiguration in solid-state neuromorphic systems remains unsolved. Herein, novel nanofluids with resistive switching properties are proposed as neuromorphic media. They are produced by depositing silver NPs from GAS into vacuum-compatible liquids (paraffin, silicon oil, and PEG) without the use of surfactants or other chemicals. When the electric field is applied between two electrodes, the migration of NPs toward biased electrode is detected in all liquids. The electrophoretic nature of the NP movement was proved by means of ζ-potential measurements. Such movement led to the self-assembly of NPs in conductive paths connecting the electrodes and, as a result, to resistive switching. The electrical response was strongly dependent on the dielectric constant of the base liquid. The Ag-PEG nanofluid demonstrated the best switching performance reproducible during several tens of current-voltage cycles. The growth of flexible and reconfigurable conductive filaments in nanofluids makes them suitable media for potential realization of 3D neural networks.

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