While the working principle of MRAM memories is a well-established process, the development of the next generation of magnetic memories is driven by the selection of the right materials and the quality of their interfaces. Improvements are hence bound to the understanding of the fundamental aspects that define material interfaces and to the establishment of device design rules that allow an improved efficient spin manipulation. Unfortunately, little is known on the factors that are driving the global spin response at the device level. The main problem is that there is a missing link between the macroscopic device reality, governed by continuum formalisms, and atomistic realities dictated by local interactions. A proper connection of these theories then needs to be built to describe the physics that governs the full magnetic coupling of multi-scaled materials.
Through this Ph.D. proposal, we aim fulfilling this gap by building links between atomistic simulations and micromagnetic formalisms used to model magnetic devices to study fundamental relations between material, interface magnetic properties and device performances. For instance, the magnetic properties of nano-confined materials will be studied using atomistic simulations (such as density functional theory), deriving information of the impact of confinement of metals on properties such as the exchange coupling and the magnetic anisotropy. The output generated will then be coupled with micromagnetic techniques to build the insights needed into the engineering of interfaces for the development of new memories.
IMEC will provide training to both UNIX/Linux and to the material modeling techniques. A strong motivation, a good knowledge of solid-state physics and/or magnetism and of UNIX/LINUX are a plus. Excellent writing and oral communication skills are desired.
Required background: Material engineering or physics with strong interest in numerical analysis
Type of work: literature 10 % and 90 % modeling
Supervisor: Michel Houssa
Daily advisor: Kiroubanand Sankaran
The reference code for this position is 2020-018. Mention this reference code on your application form.
Chinese nationals who wish to apply for the CSC scholarship, should use the following code when applying for this topic: CSC2020-11.