Electropolymerized dopamine-based memristors using threshold switching behaviors for artificial current-activated spiking neurons

作者：Bowen Zhong, Xiaokun Qin, Zhexin Li, Yiqiang Zheng, Lingchen Liu, Zheng Lou, Lili Wang · 发表于：Journal of Semiconductors · 年份：2025 · DOI：10.1088/1674-4926/24070007 · 被引用次数：10 · 研究领域：Advanced Memory and Neural Computing、Neuroscience and Neural Engineering、Conducting polymers and applications

Abstract Memristors have a synapse-like two-terminal structure and electrical properties, which are widely used in the construction of artificial synapses. However, compared to inorganic materials, organic materials are rarely used for artificial spiking synapses due to their relatively poor memrisitve performance. Here, for the first time, we present an organic memristor based on an electropolymerized dopamine-based memristive layer. This polydopamine-based memristor demonstrates the improvements in key performance, including a low threshold voltage of 0.3 V, a thin thickness of 16 nm, and a high parasitic capacitance of about 1 μ F∙mm −2 . By leveraging these properties in combination with its stable threshold switching behavior, we construct a capacitor-free and low-power artificial spiking neuron capable of outputting the oscillation voltage, whose spiking frequency increases with the increase of current stimulation analogous to a biological neuron. The experimental results indicate that our artificial spiking neuron holds potential for applications in neuromorphic computing and systems.