National Research Centre "Kurchatov Institute", 123182, Moscow, Russia.
Moscow Institute of Physics and Technology, 141700, Dolgoprudny, Moscow Region, Russia.
Sci Rep. 2019 Jul 25;9(1):10800. doi: 10.1038/s41598-019-47263-9.
In this paper, the resistive switching and neuromorphic behaviour of memristive devices based on parylene, a polymer both low-cost and safe for the human body, is comprehensively studied. The Metal/Parylene/ITO sandwich structures were prepared by means of the standard gas phase surface polymerization method with different top active metal electrodes (Ag, Al, Cu or Ti of ~500 nm thickness). These organic memristive devices exhibit excellent performance: low switching voltage (down to 1 V), large OFF/ON resistance ratio (up to 10), retention (≥10 s) and high multilevel resistance switching (at least 16 stable resistive states in the case of Cu electrodes). We have experimentally shown that parylene-based memristive elements can be trained by a biologically inspired spike-timing-dependent plasticity (STDP) mechanism. The obtained results have been used to implement a simple neuromorphic network model of classical conditioning. The described advantages allow considering parylene-based organic memristors as prospective devices for hardware realization of spiking artificial neuron networks capable of supervised and unsupervised learning and suitable for biomedical applications.
本文全面研究了基于聚对二甲苯的忆阻器的电阻开关和神经形态行为,聚对二甲苯是一种低成本且对人体安全的聚合物。采用标准气相表面聚合方法,通过不同的顶部活性金属电极(约 500nm 厚的 Ag、Al、Cu 或 Ti)制备了金属/聚对二甲苯/ITO 三明治结构。这些有机忆阻器具有优异的性能:低开关电压(低至 1V)、大的 OFF/ON 电阻比(高达 10)、保持性(≥10s)和高的多级电阻开关(在 Cu 电极的情况下至少有 16 个稳定的电阻状态)。我们已经通过实验证明,基于聚对二甲苯的忆阻器元件可以通过生物启发的尖峰时间依赖可塑性(STDP)机制进行训练。所获得的结果已用于实现经典条件反射的简单神经形态网络模型。所描述的优点使得基于聚对二甲苯的有机忆阻器成为用于实现能够进行监督和无监督学习的尖峰人工神经元网络的硬件的有前途的器件,并且适用于生物医学应用。