The role of areal mass density on spatiotemporal dynamics of multiterminal memristive nanowire networks

Self-organizing memristive nanowire networks are promising substrates for physical reservoir computing because their computational properties emerge from complex spatiotemporal dynamics distributed across the network. However, how these dynamics rely on material-level parameters set during self-assembly remains insufficiently understood. Here, we investigate the impact of nanowire (NW) areal mass density (AMD) on the spatiotemporal response and computing-related properties of multiterminal Ag-PVP NW networks. We analyze the dependence of spatiotemporal dynamics on areal mass density by combining correlation analyses, temporal network response, and the impact of local properties on computational capabilities evaluated on computational benchmarks. Results show that lower-density networks exhibit weaker global correlation, slower average dynamics, longer autocorrelation times, and a broader spatial distribution of electrodes contributing to memory capacity. In contrast, denser networks show faster and more predictable responses with reduced fading memory. These findings indicate that nanowire AMD does not simply tune the overall conductance of the network, but also controls the balance between connectivity, temporal persistence, and synchronization. AMD therefore emerges as a key experimental parameter for designing multiterminal NW networks with targeted dynamical regimes for neuromorphic and reservoir-computing applications.