Synaptic plasticity features and neuromorphic system simulation in AlN-based memristor devices

In this paper, we show various memory characteristics of the Ag/AlN/TiN devices for neuromorphic systems. We verified the thickness and the components of the device stack by transmission electron microscopy (TEM) and energy-dispersive X-ray spectroscopy (EDS). We investigated the long-term memory (LTM) characteristics, and short-term memory (STM) characteristics can be determined by compliance current (CC). It shows LTM characteristics when CC is high and STM characteristics when CC is low. I-V curves for each characteristic were investigated, and potentiation and depression for LTM characteristics. The switching and conduction mechanisms of Ni/Ag/AlN/TiN devices are studied using the schematic drawing of the conducting filament and the energy band diagram, including the work function, electron affinity, and bandgap energy of each layer. The linearity of potentiation and depression was compared for an identical pulse and an incremental pulse. Finally, we investigated Modified National Institute of Standards and Technology (MNIST) pattern accuracy depending on the linearity of potentiation and depression. • AlN based device is proposed to implement synaptic properties. • TEM and EDS analysis provide the chemical and material information of device. • The improved synaptic properties are achieved by controlling pulse scheme. • Neuromorphic system simulation is conducted to evaluate the conductance update.