Analytical study of yttria based memristive system

Abstract

Before 1971, all the electronic circuits were based on three basic circuit elements. Until a professor from UC Berkeley reasoned that another basic circuit element exists, which he called memristor; characterized by the relationship between the charge and the flux-linkage. A memristor is essentially a resistor with memory. The resistance of a memristor (Memristance) depends on the amount of current that is passing through the device. In 2008, a research group at HP Labs succeeded to build an actual physical memristor. HP's memristor was a nanometer-scale titanium dioxide thin-film, composed of two doped and undoped regions, sandwiched between two platinum contacts. After this breakthrough, a considerable amount of research started with the aim of better realization of the device and discovering more possible applications of the memristor. Since the advent of the memristor as an actual basic element, a significant thrust of the research has been oriented to develop neuromorphic computing system based on memristor. Neuromorphic computing and learning behavior are among the most directly available applications of memristor due to its memory property. Here, an analytical model for Y2O3-based memristive system for synaptic learning behavior has been reported. In this analytical model, a new logarithmic window function is used along with modified IV relationship to show the asymmetric behavior in both positive and negative voltage biases and thus provides a good accuracy with the published experimental report.