Recently it has become evident that as the dimensions of magnetic systems shrink, certain interactions that are normally neglected are actually of great importance for the magnetic ordering and the dynamics of these systems. Of particular interest is the chiral, anti-symmetric Dzyaloshinskii-Moriya interactions (DMI) which occurs in systems lacking inversion symmetries and is thus present at surfaces as well as in many heterostructures. DMI introduces a chirality to the system and it has been shown that DMI can stabilize exotic, collective yet particle like, magnetic configurations known as Skyrmions which have have not only very interesting fundamental physical properties but they also exhibit very suitable properties for future information processing and storage applications. For other technologically relevant systems that can be used for magnetic RAM and race-track memories, it has also been shown that the time scale for their dynamics is actually determined by the strength of the DMI.
In this project we will examine both the microscopic origin of the DMI as well as its effects on relevant systems with the purpose of obtaining a deepened understanding on if and how the DMI can be tuned by geometrical and chemical constraints which will allow for tailoring novel materials suitable for information processing applications. We will also put effort in studying the fundamental and materials specific properties of a selection of Skyrmion systems.
For our studies we will employ a combination of first-principles electronic structure calculations with atomistic spin dynamics simulations to obtain an efficient yet reliable, materials specific description of the magnetization dynamics at play in the systems of interest. This theoretical approach has successfully been applied to several similar problems earlier and the methods are known to work and scale well on the proposed computing platforms. The spin dynamics method is also under continuous development aimed at increased versatility, multi-scale capabilities and improved numerical efficiency.