Synaptic dynamics in complex self-assembled nanoparticle networks

Abstract

We report a detailed study of neuromorphic switching behaviour in inherently complex percolating networks of self-assembled metal nanoparticles. We show that variation of the strength and duration of the electric field applied to this network of synapse-like atomic switches allows us to control the switching dynamics. Switching is observed for voltages above a well-defined threshold, with higher voltages leading to increased switching rates. We demonstrate two behavioral archetypes and show how the switching dynamics change as a function of duration and amplitude of the voltage stimulus. We show that the state of each synapse can influence the activity of the other synapses, leading to complex switching dynamics. We further demonstrate the influence of the morphology of the network on the measured device properties, and the constraints imposed by the overall network conductance. The correlated switching dynamics, device stability over long periods, and the simplicity of the device fabrication provide an attractive pathway to practical implementation of on-chip neuromorphic computing. arXiv:1812.09865v1 [cond-mat.dis-nn]

Emergent dynamics of neuromorphic nanowire networks

“…The resistance model with dissolution threshold (or binary) combined with the observed decay traces (Fig. 3b), on the other hand, suggests that the different deactivation responses can be attributed to two effects: the stochastic nature of the filament-breaking junctions 28,46 and the potentiation of the backbone current pathways when very low voltage is present. This combined effect gives rise to the creation of multiple meta-stable states of the network, appearing as irregular plateaus at different conductances with different lifetimes.…”

“…The individual nanoparticle junctions show properties of metal oxide resistive switches, with tunneling and filament formation in the switches, conferring neuromorphic properties to the networks 26 . They also found some evidence of recurrent properties such as critical activation, memorization and stochastic-mediated dynamics 24,27,28 .…”

“…This length grows with electrical current, which promotes the development of the junction, and shrinks through an exponential decay term. This term is used to reproduce the inherent instability of atomic switches at room temperature 28,46 . The physical mechanism whereby Ag filaments decay could be related to spontaneous clustering of the Ag filament whenever voltage difference is absent, in order to minimize surface energy of the filaments 47 .…”

Non-ohmic behavior and resistive switching of Au cluster-assembled films beyond the percolation threshold

“…3 Networks based on nanoscale resistive switching (RS) junctions are currently investigated for the fabrication of neuromorphic computing architectures, where the processing of cognitive and distributed data intensive tasks is performed similarly to synapses networks. [4][5][6] RS refers to physical phenomena where the resistance of a dielectric material changes reversibly in response to the application of a strong external electric eld. RS has been reported in several systems including oxides, nitrides, chalcogenides, semiconductors, and organic materials.…”

Dynamic Electrical Pathway Tuning in Neuromorphic Nanowire Networks

“…The loss in controllability of synaptic weight at the level of individual memristors is offset by the gain in neuromorphic topology, with the connected network better resembling that of neurobiological systems. [23] Examples of such neuromorphic networks are those formed by atomic switches, [24][25][26][27] nanoparticles, [28][29][30][31][32] or nanowires. [33][34][35] Neuromorphic networks act also as resistive switching devices at the system-level, changing from a high resistance state (HRS) to a low resistance state (LRS) as a result of applying a voltage difference between two terminals across the network.…”