Avalanches and criticality in self-organized nanoscale networks

Abstract

Current efforts to achieve neuromorphic computation are focused on highly organized architectures, such as integrated circuits and regular arrays of memristors, which lack the complex interconnectivity of the brain and so are unable to exhibit brain-like dynamics. New architectures are required, both to emulate the complexity of the brain and to achieve critical dynamics and consequent maximal computational performance. We show here that electrical signals from self-organized networks of nanoparticles exhibit brain-like spatiotemporal correlations and criticality when fabricated at a percolating phase transition. Specifically, the sizes and durations of avalanches of switching events are power law distributed, and the power law exponents satisfy rigorous criteria for criticality. These signals are therefore qualitatively and quantitatively similar to those measured in the cortex. Our self-organized networks provide a low-cost platform for computational approaches that rely on spatiotemporal correlations, such as reservoir computing, and are an important step toward creating neuromorphic device architectures.

Anomalous electrical conduction and negative temperature coefficient of resistance in nanostructured gold resistive switching films

“…Atomic rearrangement present under the application of high voltage bias contributes to the rearrangement of grain boundaries responsible for the switching events. The observed mechanism is substantially different from what observed in random networks of nanowires where ionic transport is involved 14 , 15 , 17 , 18 , 55 . In our case the highly correlated re-arrangement of grain boundaries changes the local conductivity as observed in single metallic nanowires 56 .…”

“…Random networks of metallic nanowires/nanoparticles in a polymeric matrix or passivated by shell of ligands or oxide layers have gained a renewed interest for the fabrication of non-linear circuital elements such as memristors and resistive switching devices for analog computing and neuromorphic data processing 14 – 18 . These systems are in the weak-coupling regime and their electrical behavior is determined by the formation/destruction of conducting junctions between isolated nanoparticles conferring neuromorphic properties to the networks 14 – 17 , 19 – 21 .…”

Neuromorphic nanowire networks: principles, progress and future prospects for neuro-inspired information processing

“…Similar self-assembled nanoparticle networks were shown to exhibit synapse-like resistive switching events near the electrical percolation threshold [28][29][30]. Subsequent studies by Brown and colleagues [31][32][33] revealed the neuromorphic nature of these switching events by demonstrating avalanche dynamics similar to that observed in cultured cortical neurons [34]. Other examples of low-dimensional neuromorphic nanomaterials include semiconducting quantum dots, carbon nanotubes [35,36] and other organic neuromorphic devices (see, e.g.…”

Avalanche criticality during ferroelectric/ferroelastic switching

“…In such ferroelectric avalanches, any switching event is likely to trigger subsequent switching, and anisotropic long-range interactions between local events are essential, in contrast with classical microscopic ferroelectric models 23 , 24 . This approach is particularly relevant for the development of neuromorphic computing architectures 25 where maximal computational performances are achieved through scale-invariant avalanches that develop at a critical point 26 , 27 , similar to neuronal avalanches observed in the brain 28 . The key question is whether this switching dynamics is a universal process in ferroelectrics with little or no influence from symmetry or structural features of domain walls.…”