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

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.

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