ABSTRACT
The use of low-dimensional materials is a promising approach to improve the key characteristics of memristors. The development process includes modeling, but the question of the most common compact model applicability to the modeling of device characteristics with the inclusion of low-dimensional materials remains open. In this paper, a comparative analysis of linear and nonlinear drift as well as threshold models was conducted. For this purpose, the assumption of the relationship between the results of the optimization of the volt-ampere characteristic loop and the descriptive ability of the model was used. A global random search algorithm was used to solve the optimization problem, and an error function with the inclusion of a regularizer was developed to estimate the loop features. Based on the characteristic features derived through meta-analysis, synthetic volt-ampere characteristic contours were built and the results of their approximation by different models were compared. For every model, the quality of the threshold voltage estimation was evaluated, the forms of the memristor potential functions and dynamic attractors associated with experimental contours on graphene oxide were calculated.
ABSTRACT
Memristors are among the most promising devices for building neural processors and non-volatile memory. One circuit design stage involves modeling, which includes the option of memristor models. The most common approach is the use of compact models, the accuracy of which is often determined by the accuracy of their parameter extraction from experiment results. In this paper, a review of existing extraction methods was performed and new parameter extraction algorithms for an adaptive compact model were proposed. The effectiveness of the developed methods was confirmed for the volt-ampere characteristic of a memristor with a vertical structure: TiN/HfxAl1-xOy/HfO2/TiN.
