MULTIFERROIC DEVICES: MODELING, ANALYSIS, AND APPLICATIONS

Recently, multiferroic-based devices have gained significant spotlight in the literature due to its non-volatility and high on/off current ratio. In order to analyze such devices and to have an insightful understanding of their characteristics, there is a need for developing a multi-physics modeling and simulation framework. The simulation framework discussed in this study is motivated by the scarcity of such multi-physics studies in the literature. In this thesis, a theoretical analysis of multiferroic tunnel junctions (MFTJs) is demonstrated using self-consistent analysis of spin-based non-equilibrium Green’s function (NEGF) method to estimate the tunneling current, Landau-Khalatnikov (LK) equation to model the ferroelectric polarization dynamics, together with landau-Lifshitz-Gilbert’s (LLG) equations to capture the magnetization dynamics. The spin-based NEGF method is equipped with a magnetization dependent Hamiltonian that eases the modeling of the tunneling electroresistance (TER), tunneling magneto-resistance (TMR), and the magnetoelectric effect (ME) in MFTJs. Moreover, we apply the first principle calculations to estimate the screening lengths of the MFTJ electrodes that are necessary for the estimation of tunneling current. These multiferroic-based devices show significant performance improvement in many applications. In this study, we demonstrate the use of these multiferroic-based devices for in-memory computing and combinatorial optimization problems. The simulation results of these applications show significant performance improvement compared to conventional computing schema.