Confined-hydrogel fluidic memristor crossbar array for neuromorphic computing.

Guo, Guangguo; Xiong, Tianyi; Xie, Boyang; Zhang, Jianping; Zhang, Jin; Lu, Yinghai; Zhao, Yueru; Ma, Wenjie et al. · Nat Commun · 2026

basic_science · Level V

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Abstract

Replicating brain-like computation with fluidic memristors offers advantages in energy efficiency and chemical responsiveness over solid-state devices, yet scaling remains challenging due to complex fabrication and their amorphous nature. Herein, we developed a confined hydrogel fluidic memristor by forming a gel-gel interface at the micropore orifice. This design with confined hydrogel enables scalable fabrication of a 10×10 fluidic memristor array (FMA) on polyimide micropores. FMA exhibits fundamental neuromorphic behaviors like paired-pulse facilitation/depression, spike-rate-dependent plasticity, and chemical-regulated plasticity. We also used reservoir computing algorithms with FMA to recognize both computer-generated black-and-white digit images and handwritten digits, achieving a classification accuracy of 89.5% on the Modified National Institute of Standards and Technology dataset. This study demonstrates a hydrogel confined fluidic memristor array, paving an avenue for creating large-scale fluidic memristor arrays and hardware intelligence with ions.