Liu Wenhao, Wang Jihong, Guo Jiahao, Wang Lin, Gu Zhen, Wang Huifeng, Fang Haiping
Haiping Fang, School of Physics, East China University of Science and Technology, Shanghai, 20023, China.
Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education, East China University of Science and Technology, Shanghai, 200237, China.
Adv Sci (Weinh). 2025 Mar;12(11):e2414319. doi: 10.1002/advs.202414319. Epub 2025 Jan 22.
The human visual nervous system excels at recognizing and processing external stimuli, essential for various physiological functions. Biomimetic visual systems leverage biological synapse properties to improve memory encoding and perception. Optoelectronic devices mimicking these synapses can enhance wearable electronics, with layered heterojunction materials being ideal materials for optoelectronic synapses due to their tunable properties and biocompatibility. However, conventional synthesis methods are complex and environmentally harmful, leading to issues such as poor stability and low charge transfer efficiency. Therefore, it is imperative to develop a more efficient, convenient, and eco-friendly method for preparing layered heterojunction materials. Here, a one-step ultrasonic method is employed to mix fullerene (C60) with graphene oxide (GO), yielding a homogeneous layered heterojunction composite film via self-assembly. The biomimetic optoelectronic synapse based on this film achieves 97.3% accuracy in dynamic visual recognition tasks and exhibits capabilities such as synaptic plasticity. Experiments utilizing X-ray photoelectron spectroscopy (XPS), X-ray diffraction spectroscopy (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-vis), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) confirms stable π-π interactions between GO and C60, facilitating electron transfer and prolonging carrier recombination times. The novel approach leveraging high-density π electron materials advances artificial intelligence and neuromorphic systems.
人类视觉神经系统擅长识别和处理外部刺激，这对各种生理功能至关重要。仿生视觉系统利用生物突触特性来改善记忆编码和感知。模仿这些突触的光电器件可以增强可穿戴电子产品，由于其可调谐特性和生物相容性，层状异质结材料是光电子突触的理想材料。然而，传统的合成方法复杂且对环境有害，导致稳定性差和电荷转移效率低等问题。因此，开发一种更高效、便捷且环保的层状异质结材料制备方法势在必行。在此，采用一步超声法将富勒烯（C60）与氧化石墨烯（GO）混合，通过自组装得到均匀的层状异质结复合膜。基于该膜的仿生光电子突触在动态视觉识别任务中实现了97.3%的准确率，并展现出诸如突触可塑性等能力。利用X射线光电子能谱（XPS）、X射线衍射光谱（XRD）、傅里叶变换红外光谱（FTIR）、紫外可见光谱（UV-vis）、扫描电子显微镜（SEM）和透射电子显微镜（TEM）进行的实验证实了GO和C60之间稳定的π-π相互作用，促进了电子转移并延长了载流子复合时间。这种利用高密度π电子材料的新方法推动了人工智能和神经形态系统的发展。
