Demonstration of a PECVD SiO x -Based RRAM Dendritic Device

Synaptic plasticity has been traditionally credited for learning in the brain. The prevalent view on learning through synapses forms the backbone behind all the significant developments in the area of artificial neural networks (ANN). However, more recent studies in Neuroscience reveal that dendritic junctions play a crucial role in the dynamics of learning, leading to increased efficiency and faster learning. Consequently, there is a need to implement dendritic computation/learning at a hardware level in ANNs. Resistive Random Access Memory (RRAM) devices have been frequently used as non-volatile synaptic elements for in-memory-computing (IMC) or neuromorphic computing applications. However, their usage in implementing dendritic dynamics has been rarely investigated. This work reports a SiOx-based RRAM device with gradual and volatile resistance switching behavior. We demonstrate that the switching dynamics of this device can be used to emulate the behavior of a dendritic junction. We also report robust endurance of this device up to 1 million cycles and investigate the transport mechanism responsible for the switching dynamics. The demonstrated dendritic devices makes room for the monolithic integration of all-SiOx neural networks in the future.