Advanced Simulation Techniques for Evaluating Emerging Magnetoresistive Random Access Memory Technologies for Next Generation Non-Volatile Memory

Abstract

Magnetoresistive random access memory (MRAM) has various features such as nonvolatility, zero static power consumption, CMOS compatibility, and high endurance, which enable it to be a potential candidate for the next generation non-volatile memory (NVM) technology. The MRAM basically stores the data in a magnetic tunnel junction (MTJ) device which consists of a free ferromagnetic layer, an oxide barrier, and a fixed ferromagnetic layer, and the intrinsic properties of MTJ device have critical roles in write and read operations considering thermal fluctuation. Due to the importance of the MTJ device, the academic and industrial groups have researched the MTJ device models for reliable MRAM applications, however, there is still no standard model to be commonly utilized in design process. Moreover, diverse types of MRAM have been researched for the last few decades. For example, spin-transfer torque (STT)-MRAM, voltage-controlled magnetic anisotropy (VCMA)-MRAM, and spin-Hall effect (SHE)-MRAM have been evaluated in order to commercialize more effective MRAM application. STT-MRAM, which utilizes bidirectional current flow for switching, has almost reached commercialization with mass production. SHE-MRAM consists of MTJ with spin Hall metal (SHM) to generate efficient spin current, whereas the VCMA MRAM utilizes a VCMA effect to lower the energy barrier of magnetization for faster switching and lower energy consumption. This thesis has focused on different modeling approaches such as a SPICE-based compact model and a Fokker-Planck model for representative MRAM types. Using the simulation models, we provide practical analyses of the MRAM applications as well as comparison of the models. Firstly, SPICE-based MTJ compact model is introduced for the VCMA-MRAM application. For this study, we developed a physics-based SPICE model that includes various VCMA parameters such as VCMA coefficient, energy barrier time constant, and external magnetic field. Using realistic material and device parameters, we evaluate the operating margin and switching probability of the VCMA-MRAM. Based on the Monte-Carlo simulation, the highest switching probabilities were 94.9, 84.8, and 53.5 %, for VCMA coefficient values of 33, 105, and 290 fJ·V-1·m-1, respectively. For the practical memory applications, their switching probability must be improved by incorporating different physics. Secondly, the Fokker-Planck (FP) numerical model is utilized for an efficient analysis of STT-MRAM application, which allows for parametric variation and evaluates its impact on switching. We analyzes the impact of MTJ material and geometric parameter variations such as saturation magnetization (MS), magnetic anisotropy (HK), damping factor (α), spin polarization efficiency factor (η), oxide thickness (tOX), free layer thickness (tF), tunnel magnetoresistance (TMR), and cross-sectional area of free layer (AF) variations on Write Error Rate (WER) and Read Disturbance Rate (RDR) for reliable write and read operations. Both WER and RDR are analyzed with a wide range of MTJ diameters between 90nm and 30nm to evaluate the scalability of MRAM devices. Even though the effect of material and geometric parameter variations on WER is decreased as MTJ scales down, the variation effect can be still considerable with small MTJ diameter and the most significant influential variation is η, MS, HK, and α in that order. On the other hand, the impact of the parameter variations on RDR increases in MTJ scaling, and the negative variations of HK and MS could be major problems in 30nm and 40nm MTJ diameters. The efficient FP numerical model-based study puts emphasis on the need of WER and RDR analyses by considering the parameter variations in MTJ scaling for practical STT-MRAM development. Thirdly, MRAM applications have been also expected to replace embedded cache memories in the near future. For the MRAM-based embedded cache memory, precedent research considering MRAM’s high write current, scaling challenges, and variation issues should be studied. In this work, a physics based MTJ model are utilized to evaluate the scalability and variability of the MRAM based cache memory. Through the studies, we investigate STT and SHE MRAM based cache memory applications considering device, circuit, layout, and architecture level details.