Silicon Oxide-based CBRAM Memory and Neuromorphic Properties

Abstract

The constant scaling of the conventional field-effect transistors (FETs) over the last half century has permitted the development of memory elements with enhanced density. However, since continuous miniaturization is practically impossible, novel device architectures have been proposed. Among them, resistive switching memories (RRAMs) emerge as quite promising candidates due to their simple structure, which permits aggressive scaling, and inherent stochastic performance, which is leveraged for the implementation of neuromorphic functionalities. Along these lines, a detailed analysis from a material point of view is presented, as far as the fabrication of SiO2-based resistive switching elements is concerned. The incorporation of metal nanoparticles (NPs) with various surface densities, as well as the employment of bilayer configurations, is thoroughly investigated in enhancing the total memory performance. More specifically, low-power operation (∼ 200 mV), enhanced variability (σ/μ < 0.2) and multibit capabilities (4 bits) were demonstrated. Moreover, the manifestation of two switching modes (bipolar and threshold) was leveraged to emulate artificial neuron and synaptic functionalities. As a result, integrate and fire (IF) properties were produced from single memristive cells, whereas enhanced analog synaptic weight modulation was also recorded. Physics-driven device engineering is thus of great importance for attaining reconfigurable memory and neuromorphic properties.