Voltage Control of Magnetism in Nanoscale Artificial Multiferroics

In this work, voltage control of magnetism in nanoscale artificial multiferroic structures was demonstrated through numerical simulation and measurement. The multiferroic nanostructures studied in this dissertation were modeled using two methods. The first approach relies solely on the Landau-Lifshitz-Gilbert (LLG) equation and incorporates the effects of strain through an effective magnetic field term that only accounts for spatially-uniform strain distributions. The second-modeling technique couples the LLG equation with the elastodynamics and piezoelectric constitutive equations by using an innovative weak-formulation. In contrast to the purely micromagnetic model, the coupled solution can account for nonuniform distributions of strain and magnetization within nanostructures. Here, these simulation tools were used to understand the effects of strain on magnetoelastic nanodots and to investigate new coupling phenomena. Regarding strain effects, the innovative magnetic measurement technique of Scanning Electron Microscopy with Polarization Analysis (SEMPA) was used to observe strain-induced changes from vortex to antiparallel bidomain states in submicron Ni disks. This data was then used to validate the modeling methods of this dissertation. Consequently, the SEMPA study represents an advancement in terms of magnetic characterization and experimental model validation. Following this work, a design that leverages shape anisotropy, magnetic dipole coupling, and strain effects to achieve transitions between artificial antiferromagnetic and artificial ferromagnetic ordering is presented. Specifically, the micromagnetic models demonstrate voltage-induced transitions between these artificial magnetic states, but there are discrepancies with the measured data. To account for this, geometric defects are added to the models, thus dramatically improving the correlation between experiment and simulation. Importantly, this specific study demonstrates novel device behavior and