纳米银基神经形态网络的制备与应用研究进展

doi:10.11896/cldb.24070124

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Abstract The rapid advancement of big data and artificial intelligence has heightened the demand for improved data processing efficiency. Beyond optimizing algorithms, developing new computing elements based on physical morphology offers an alternative to reduce algorithm iteration. Nanosilver-based neuromorphic networks, utilizing silver nanomaterials as structural units, can mimic the information processing capabilities of the human nervous system, making them promising for neuromorphic and brain-inspired computing applications. To ensure stable operation and ease of fabrication, researchers have implemented various improvements to the material system and fabrication processes. This paper reviews recent progress in nanosilver-based neuromorphic networks, focusing on preparation methods such as drop-casting, random copper seed-induced self-assembly, and patterned copper seed self-assembly across different material systems. Additionally, it summarizes current applications and discusses future development and applicative prospects of this technology.

Key words： nano-silver neuromorphic networks self-organization nonlinear mapping inorganic synapses memristors atomic switch

Published: 10 October 2025 Online: 2025-09-24

CLC number:

TB31

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	Articles by authors
	HAN Kunyuan
	LIU Fengqi
	YE Yicong

Cite this article:

HAN Kunyuan,LIU Fengqi,YE Yicong. Research Progress on the Formulation and Application of Nanosilver-based Neuromorphic Networks[J]. Materials Reports, 2025, 39(19): 24070124-11.

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https://www.mater-rep.com/EN/10.11896/cldb.24070124 OR https://www.mater-rep.com/EN/Y2025/V39/I19/24070124

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