用于神经形态应用的多孔纳米流体忆阻器的弛豫时间
Relaxation Time of Multipore Nanofluidic Memristors for Neuromorphic Applications
AI总结：
本文通过阻抗谱提取多孔纳米流体忆阻器的电压相关动力学弛豫时间，证明其行为与自然神经系统相当，为模拟神经元特性提供新途径。
摘要：
忆阻器一直处于开展神经形态计算用途的前沿。其可调电导特性使其能够模拟突触行为。多孔纳米流体忆阻器已展现出忆阻特性，是液态神经形态系统的候选器件。这类特性可通过电流-电压扫描中的感生迟滞观察到，随后又由阻抗谱测量中的感生特征得到证实。忆阻器的动态行为在很大程度上取决于电压相关的弛豫时间。本文中，我们通过多孔纳米流体忆阻器的阻抗谱获得其动力学弛豫时间。我们表明，忆阻器这一特征的行为可与自然神经系统相比拟。因此，我们通过寻找具有相同动力学时间的忆阻器，为研究神经元特征的模拟开辟了一条途径。
英文摘要：
Memristors have been positioned at the forefront of the purposes for carrying out neuromorphic computation. Their tuneable conductivity properties enable the imitation of synaptic behaviour. Multipore nanofluidic memristors have shown their memristic properties and are candidate devices for liquid neuromorphic systems. Such properties are visible through an inductive hysteresis in the current-voltage sweeps, which is then confirmed by the inductive characteristics in impedance spectroscopy measurements. The dynamic behaviour of memristors is largely determined by a voltage-dependent relaxation time. Here, we obtain the kinetic relaxation time of a multipore nanofluidic memristor via its impedance spectra. We show that the behaviour of this characteristic of memristors is comparable to that of natural neural systems. Hence, we open a way to study the mimic of neuron characteristics by searching for memristors with the same kinetic times.
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