Predictive Model for Tunneling Magnetoresistance in 2D Material Magnetic Tunnel Junctions Utilizing Bulk Properties

Recently, magnetic tunnel junctions (MTJs) have been formed using two-dimensional materials (2DM) heterostructures, leading to increased attention regarding the spin transport of these layered systems. The large number of possible MTJs that can be formed using this expanding family of 2D magnetic materials poses an exhaustive challenge for both experimental and computational efforts. Hence, alternative search methods are required for the realization of 2DM MTJs with exceptional tunneling magnetoresistance (TMR) values. In this work, we developed a model based on the readily obtained physical properties of bulk constituents to estimate the TMR in the full junctions as well as identify materials that yield positive response. We characterize the properties of multilayer junctions formed with transition metal chalcogenides and halides using density functional theory and ballistic transport. Our model shows agreement with sample structures and further predicts multiple MTJs with TMR values greater than 1,000%. From the comparison against full quantum transport calculations, we discuss virtues and limitations of our model.  This work serves to create a data driven design of complex 2DM MTJs which will guide experimental studies as to realize their use for applications in spintronics.