Collective capacitive and memristive responses in random nanowire networks: Emergence of critical connectivity pathways

Abstract

Random nanowire networks (NWNs) are promising synthetic architectures for non-volatile memory devices and hardware-based neuromorphic applications due to their history-dependent responses, recurrent connectivity, and neurosynaptic-like behaviors. Such brain-like functions occur due to emergent resistive switching phenomena taking place in the interwire junctions which are viewed as memristive systems; they operate as smart analogue switches whose resistance depends on the history of the input voltage/current. We successfully demonstrated that NWNs made with a particular class of memristive junctions can exhibit a highly-selective conduction mechanism which uses the lowest-energy connectivity path in the network identified as the “winner-takes-all” state. However, these complex networks do not always behave in the same fashion; in the limit of sufficiently low input currents (preceding this selective conduction regime), the system behaves as a leakage capacitive network and its electrical activation is driven by cascades of breakdown-based activation events involving binary capacitive transitions. Understanding these two regimes is crucial to establish the potential of these materials for neuromorphics, and for this, we present two computational modelling schemes designed to describe the capacitive and memristive responses of NWNs interrogated adiabatically by voltage/current sources. Our results are corroborated by experimental evidence that reveal the fine electrical properties of NWN materials in their respective formation (capacitive) and conducting (memristive) stages.