In Situ Imaging of Dynamic Current Paths in a Neuromorphic Nanoparticle Network with Critical Spiking Behavior

In the strive for energy efficient computing, many different neuromorphic computing and engineering schemes have been introduced. Nanoparticle networks (NPNs) at the percolation threshold have been established as one of the promising candidates, e.g., for reservoir computing because among other useful properties they show self-organization and brain-like avalanche dynamics. The dynamic resistance changes trace back to spatio-temporal reconfigurations in the connectivity upon resistive switching in distributed memristive nano-junctions and nano-gaps between neighboring nanoparticles. Until now, however, there has not yet been any direct imaging or monitoring of current paths in NPN. In this study, an NPN comprising of Ag/CxOyHz core/shell and Ag nanoparticles at the percolation threshold is reported. It is shown that this NPN is within a critical regime, exhibiting avalanche dynamics. To monitor in situ the evolving current paths in this NPN, active voltage contrast and resistive contrast imaging are used complementarily. Including simulations, the results provide experimental insight toward understanding the complex current response of the memristive NPN. As such, this study paves the way toward an experimental characterization of dynamic reorganizations in current paths inside NPN, which is highly relevant for validating and improving simulations and finally establishing a deeper understanding of switching dynamics in NPNs. Silver-based nanoparticle networks poised at the percolation threshold show brain-like dynamics and critical behavior. Reconfigurable current paths through the network are monitored via in situ and in operando experiments in the scanning electron microscope, combined with simulations. This proposed experimental platform for current path imaging may lead to knowledge-driven improvements of such neuromorphic nanoparticle networks. image