Electrodeposition of magnetic nanonetworks featuring triangular motifs and parallel ridges on a macroscopic scale

Fei Chen, Junkang Shan, Xi Wang, Jingning Li, Fei Jia, Fan Wang, Zihao Yang, Kai Liu, Ru-Wen Peng () and Mu Wang ()
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Fei Chen: Nanjing University
Junkang Shan: Nanjing University
Xi Wang: Nanjing University
Jingning Li: Nanjing University
Fei Jia: Nanjing University
Fan Wang: Nanjing University
Zihao Yang: Nanjing University
Kai Liu: Georgetown University
Ru-Wen Peng: Nanjing University
Mu Wang: Nanjing University

Nature Communications, 2025, vol. 16, issue 1, 1-11

Abstract: Abstract 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.

Date: 2025
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DOI: 10.1038/s41467-025-65589-z

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