Institute of Advanced Materials (INAM), Universitat Jaume I, 12006 Castelló, Spain.
J Phys Chem Lett. 2022 May 5;13(17):3789-3795. doi: 10.1021/acs.jpclett.2c00790. Epub 2022 Apr 22.
Memristors are candidate devices for constructing artificial neurons, synapses, and computational networks for brainlike information processing and sensory-motor autonomous systems. However, the dynamics of natural neurons and synapses are challenging and cannot be well reproduced with standard electronic components. Halide perovskite memristors operate by mixed ionic-electronic properties that may lead to replicate the live computation elements. Here we explore the dynamical behavior of a halide perovskite memristor model to evaluate the response to a step perturbation and the self-sustained oscillations that produce analog neuron spiking. As the system contains a capacitor and a voltage-dependent chemical inductor, it can mimic an action potential in response to a square current pulse. Furthermore, we discover a property that cannot occur in the standard two-dimensional model systems: a three-dimensional model shows a dynamical instability that produces a spiking regime without the need for an intrinsic negative resistance. These results open a new pathway to create spiking neurons without the support of electronic circuits.
忆阻器是构建人工神经元、突触和用于类脑信息处理和感觉运动自主系统的计算网络的候选器件。然而，自然神经元和突触的动态特性具有挑战性，无法用标准电子元件很好地再现。卤化物钙钛矿忆阻器通过混合离子-电子特性来工作，这可能导致复制活体计算元件。在这里，我们探索了卤化物钙钛矿忆阻器模型的动态行为，以评估对阶跃扰动的响应以及产生模拟神经元尖峰的自维持振荡。由于该系统包含一个电容器和一个电压相关的化学电感器，它可以模拟对方波电流脉冲的动作电位。此外，我们发现了一个在标准二维模型系统中不可能出现的特性：一个三维模型表现出动态不稳定性，产生尖峰状态，而不需要内在的负电阻。这些结果为创建无需电子电路支持的尖峰神经元开辟了一条新途径。
