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Experimental study demonstrates template-free electrodeposition of macroscopic magnetic nanonetworks, highlighting a scalable pathway for neuromorphic computing physical reservoirs.
Ordered nanostructured magnetic networks offer a versatile platform for studying magnetic frustration, reconfigurable magnonics, and neuromorphic computing. Their fabrication, however, often relies on complicated and expensive nanolithography. Here, we demonstrate an electrochemical strategy for growing large-area magnetic networks composed of self-organized triangular motifs separated by periodic parallel ridges. The ridges arise deterministically from voltage-controlled electrodeposition, while the regions between them undergo self-organization: cobalt nucleates, bifurcates, and assembles into either solid or hollow triangular units depending on the growth conditions. The global network morphology is dictated by the waveform of the applied voltage. These triangular structures host diverse magnetic states, including vortex-like and macro-spin-like configurations, and exhibit nonlinear responses to external magnetic fields. Our approach combines macroscopically controlled, deterministic growth and microscopic self-organization, providing a scalable pathway for fabricating complex nanostructures. The resulting magnetic networks show potential as physical reservoirs for neuromorphic computing. Self-organized growth often suffers from a lack of long-range order in preparing large-area nanostructures. Here, the authors develop a direct electrochemical growth technique for preparing ordered magnetic networks without the use of templates.
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Chen et al. (2025) studied this question.
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