Reduced Switching Threshold and Photo‐Modulated Dynamics in Self‐Organized Hybrid Ag/pV3D3 Nanoparticle Networks: Toward Photoresponsivity in Neural‐Like Networks

ABSTRACT Self‐organized neuromorphic nanogranular networks that mimic the switching dynamics of biological neural networks are promising for next‐generation brain‐inspired computing architectures. Despite recent advances, strategies to lower their switching threshold, and understanding of the influence of light on their switching dynamics, which are key aspects for energy‐efficient and multifunctional device operation, remains limited. Here, a strategy is introduced to lower the switching threshold, and the optical sensitivity of the nanoparticle networks (NPNs) is explored. Silver (Ag) NPNs are fabricated via surfactant‐free deposition from a gas aggregation cluster source. One network is coated with poly(1,3,5‐trivinyl‐1,3,5‐trimethyl‐cyclosiloxane) (pV3D3) using initiated chemical vapor deposition (iCVD), producing Ag/pV3D3 NPN with enhanced morphological stability and a significantly reduced switching threshold of 0.5 V compared to uncoated Ag NPNs (3 V). Time‐series measurements showed indications that the switching activity of Ag/pV3D3 NPNs can be modulated by visible light, with blue light irradiation showing the largest enhancement in switching events compared to the dark, unilluminated state. These findings establish a pathway toward low‐power, light‐tunable, self‐organized nanogranular networks for neuromorphic computing applications.