Carbon monoxide (CO) adsorption on ultrathin fcc Fe films is known to result in the rotation of magnetization from out-of-plane to in-plane. By imaging in real time the magnetic domain structure of perpendicularly magnetized Fe/(2 ML)Ni/Cu(100) films during exposure to CO, we demonstrate that the effect of adsorption on the magnetic properties occurs in two distinct stages. Initially, when CO bonds preferentially on bridge sites, perpendicular magnetic anisotropy is enhanced. Later, when on-top adsorption dominates, magnetization rotates towards in-plane in agreement with previous studies. This CO-induced spin reorientation transition (SRT) is not reversible by annealing, as CO desorption would require high temperature cycles which yield permanent structural changes in the metal films. This study demonstrates the existence of a novel non-monotonic behavior of the magnetic anisotropy as a function of adsorbate coverage. The influence of CO on ultrathin film magnetism in real time near critical points, where the anisotropy balance is extremely sensitive to small variations, reveals the previously elusive complexity of this adsorbate induced SRT.

We present a joint experimental and theoretical study that demonstrates how to efficiently control a canted state of magnetization in Fe films grown on Ag(001) vicinal surface and precisely characterize it with the magneto-optical Kerr effect. It is shown that by employing different mechanisms to tune the magnetization tilting angle, any magnetization orientation within the plane perpendicular to the step edges can be achieved. In particular, increasing the Fe film thickness leads to continuous rotation of the magnetization easy axis toward the film surface and the sense of this rotation in uncovered films is opposite to that in films covered with Au. Another tuning mechanism is provided by oscillatory changes of the tilting angle at low temperatures due to formation of quantum well states in Fe films. The observed canting of magnetization is explained within a phenomenological model by an interplay of the shape anisotropy and two magnetocrystalline anisotropy terms, perpendicular and step-induced anisotropies, which results in an effective uniaxial magnetic anisotropy. The fitted thickness dependencies of the anisotropy constants accurately reproduce experimental variations of the tilting angle with both Fe and Au thicknesses as well as transient changes of the magnetization orientation in ultrathin Fe films upon submonolayer Au coverage, observed with spin-polarized low-energy electron microscopy.

The evolution of the domain structure with the thickness of bcc Fe films deposited on the Ag(116) vicinal surface is studied by spin-polarized low-energy electron microscopy. We show that a spin reorientation transition proceeds via two mechanisms: continuous rotation of magnetization within the vertical plane perpendicular to the steps and discontinuous reorientation of the in-plane component of magnetization, leading to splitting of the domains. In contrast to previously investigated systems with stripe domains, we reveal that in the case of a vicinal ferromagnetic surface, the domain width increases while changing the orientation of the magnetization from a canted out-of-plane state into an in-plane state. A theoretical model developed in this work successfully describes the domain structure behavior observed in our experiments and can be equally applied to other ferromagnetic films grown on vicinal surfaces.

Magnetic domain structure and spin-dependent reflectivity measurements on cobalt thin films intercalated at the graphene/Ir(111) interface are investigated using spin-polarised low-energy electron microscopy. We find that graphene-covered cobalt films have surprising magnetic properties. Vectorial imaging of magnetic domains reveals an unusually gradual thickness-dependent spin reorientation transition, in which magnetisation rotates from out-of-the-film plane to the in-plane direction by less than 10° per cobalt monolayer. During this transition, cobalt films have a meandering spin texture, characterised by a complex, three-dimensional, wavy magnetisation pattern. In addition, spectroscopy measurements suggest that the electronic band structure of the unoccupied states is essentially spin-independent already a few electron-Volts above the vacuum level. These properties strikingly differ from those of pristine cobalt films and could open new prospects in surface magnetism.

Understanding spin textures in magnetic systems is extremely important to the spintronics and it is vital to extrapolate the magnetic Hamiltonian parameters through the experimentally determined spin. It can provide a better complementary link between theories and experimental results. We demonstrate deep learning can quantify the magnetic Hamiltonian from magnetic domain images. To train the deep neural network, we generated domain configurations with Monte Carlo method. The errors from the estimations was analyzed with statistical methods and confirmed the network was successfully trained to relate the Hamiltonian parameters with magnetic structure characteristics. The network was applied to estimate experimentally observed domain images. The results are consistent with the reported results, which verifies the effectiveness of our methods. On the basis of our study, we anticipate that the deep learning techniques make a bridge to connect the experimental and theoretical approaches not only in magnetism but also throughout any scientific research.