Two‐Junction Model in Different Percolation Regimes of Silver Nanowires Networks

Random networks offer fertile ground for achieving complexity and criticality,both crucial for an unconventional computing paradigm inspired by biologicalbrains’ features. In this work, characterizing and modeling different electrical transport regimes of self-assemblies of silver nanowires (AgNWs) are focused. As percolation plays an essential role in such a scenario, a broad range of a real density coverage is examined. Close-to-percolation realizations (usually used to demonstrate neuromorphic computing capabilities) have high pristine resistance and require an electrical activation. Until now, highly conductiveover-percolated systems (commonly used in electrode fabrication technology)have not been thoroughly considered for hardware-based neuromorphic applications, even though biological systems exhibit such an extremely high degree of interconnections. Here, it is shown that high current densities in over-percolated low-resistance AgNW networks induce a fuse-type process, allowing a switching operation. Such electro-fusing discriminates between weak and robust NW-to-NW links and enhances the role of filamentary junctions. Their reversible resistive switching enable different conductive paths exhibiting linear I–V features. Both percolation regimes are experimentally studied and proposed a model comprising two types of junctions that can describe, through numerical simulations, the overall behavior and observed phenomenology. These findings reveal a potential interplay of functionalities of neuromorphic systems and transparent electrodes.