AI 中文总结
该研究针对1T-TaS₂的近公度电荷密度波噪声，建立介观模型解释其与漏极积分放电神经元动力学的相似性，证实其可作为室温脉冲神经模拟器的非线性元件，助力器件小型化。
AI 中文摘要
低维材料是类神经元放电模拟的极具潜力材料，对该行为原子尺度起源的理解可助力其集成至神经形态硬件。利用扫描隧道显微镜（STM）作为电荷密度波（CDW）关联的高局域探针，我们在室温下研究1T-TaS₂的原子尺度CDW噪声。我们对隧道结噪声进行统计分析，为解释时间关联的电流爆发，引入介观模型，其中CDW公度错的分形结构与重组存在关联。该噪声模拟漏极积分放电神经元动力学。我们的结果表明，隧道结中的原子尺度电流爆发可作为脉冲神经模拟器中的有效非线性元件，在室温下通过丰富的CDW动力学实现仿生处理，并支持脉冲器件的小型化。
英文摘要
Low-dimensional materials are promising materials for emulating neuron-like firing were understanding of the atomic-scale origin of this behavior can benefit integration into neurormophic hardware. Using scanning tunneling microscopy (STM) as a highly local probe of correlations in the charge density wave (CDW), we study atomic-scale CDW noise in $1T\text{-}\mathrm{TaS}_2$ at room temperature. We statistically analyze the tunnel-junction noise and, to explain the temporally correlated current bursts, introduce a mesoscopic model in which the fractal structure and reorganization of CDW discommensurations are related. This noise mimics leaky-integrate-and-fire neuron dynamics. Our results show that atomic-scale current bursts in the tunnel junction can act as effective nonlinear elements in spiking neural emulators, enabling bioinspired processing through rich CDW dynamics at room temperature and supporting the miniaturization of spiking devices.
Comments20 pages, 5 figures
