Nanoparticle Networks for Neuromorphic Computing
Physical computing leverages complex dynamical systems for energy-efficient data processing. In this work, we present a neuromorphic architecture based on metallic nanoparticles interconnected by molecular junctions on a $\text{SiO}_2$/Si substrate. We demonstrate that surrounding static control electrodes transform this nanoparticle network from a passive reservoir into a tunable nonlinear dynamical system. By analyzing how these electrodes route simple one-dimensional voltage inputs into multidimensional signal responses, we establish three core design rules to maximize computational performance. First, operating near the system's cutoff frequency achieves an optimal balance between non...
| Authors | Jonas Mensing, Wilfred G. van der Wiel, Andreas Heuer |
|---|---|
| Primary category | cs.ET |
| Published | 30 July 2026 |
| Last updated at source | 30 July 2026 |
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