Magnetic non-contact friction from domain wall dynamics actuated by oscillatory mechanical motion

Magnetic friction is a form of non-contact friction arising from the dissipation of energy in a magnet due to spin reorientation in a magnetic field. In this paper we study magnetic friction in the context of micromagnetics, using our recent implementation of smooth spring-driven motion [Phys. Rev. E. 97, 053301 (2018)] to simulate ring-down measurements in two setups where domain wall dynamics is induced by mechanical motion. These include a single thin film with a domain wall in an external field and a setup mimicking a magnetic cantilever tip and substrate, in which the two magnets interact through dipolar interactions. We investigate how various micromagnetic parameters influence the domain wall dynamics actuated by the oscillatory spring-driven mechanical motion and the resulting damping coefficient. Our simulations show that the magnitude of magnetic friction can be comparable to other forms of non-contact friction. For oscillation frequencies lower than those inducing excitations of the internal structure of the domain walls, the damping coefficient is found to be independent of frequency. Hence, our results obtained in the frequency range from 8 to 112 MHz are expected to be relevant also for typical experimental setups operating in the 100 kHz range.Comment: 19 pages, 8 figure

Domain walls within domain walls in wide ferromagnetic strips

We carry out large-scale micromagnetic simulations which demonstrate that due to topological constraints, internal domain walls (Bloch lines) within extended domain walls are more robust than domain walls in nanowires. Thus, the possibility of spintronics applications based on their motion channeled along domain walls emerges. Internal domain walls are nucleated within domain walls in perpendicularly magnetized media concurrent with a Walker breakdown-like abrupt reduction of the domain wall velocity above a threshold driving force, and may also be generated within pinned, localized domain walls. We observe fast field and current driven internal domain wall dynamics without a Walker breakdown along pinned domain walls, originating from topological protection of the internal domain wall structure due to the surrounding out-of-plane domains.Comment: 5 pages, 6 figure

Universality classes and crossover scaling of Barkhausen noise in thin films

We study the dynamics of head-to-head domain walls separating in-plane domains in a disordered ferromagnetic thin film. The competition between the domain wall surface tension and dipolar interactions induces a crossover between a rough domain wall phase at short length-scales and a large-scale phase where the walls display a zigzag morphology. The two phases are characterized by different critical exponents for Barkhausen avalanche dynamics that are in quantitative agreement with experimental measurements on MnAs thin films.Comment: 5 pages, 5 figure

Multistep Bloch-line-mediated Walker breakdown in ferromagnetic strips

A well-known feature of magnetic field driven dynamics of domain walls in ferromagnets is the existence of a threshold driving force at which the internal magnetization of the domain wall starts to precess -- a phenomenon known as the Walker breakdown -- resulting in an abrupt drop of the domain wall propagation velocity. Here, we report on micromagnetic simulations of magnetic field driven domain wall dynamics in thin ferromagnetic strips with perpendicular magnetic anisotropy which demonstrate that in wide enough strips Walker breakdown is a multistep process: It consists of several distinct velocity drops separated by short linear parts of the velocity vs field curve. These features originate from the repeated nucleation, propagation and annihilation of an increasing number of Bloch lines within the domain wall as the driving field magnitude is increased. This mechanism arises due to magnetostatic effects breaking the symmetry between the two ends of the domain wall.Comment: 6 pages, 4 figures, to appear in Phys. Rev.

Dynamic hysteresis in cyclic deformation of crystalline solids

The hysteresis or internal friction in the deformation of crystalline solids stressed cyclically is studied from the viewpoint of collective dislocation dynamics. Stress-controlled simulations of a dislocation dynamics model at various loading frequencies and amplitudes are performed to study the stress - strain rate hysteresis. The hysteresis loop areas exhibit a maximum at a characteristic frequency and a power law frequency dependence in the low frequency limit, with the power law exponent exhibiting two regimes, corresponding to the jammed and the yielding/moving phases of the system, respectively. The first of these phases exhibits non-trivial critical-like viscoelastic dynamics, crossing over to intermittent viscoplastic deformation for higher stress amplitudes.Comment: 5 pages, 4 figures, to appear in Physical Review Letter

Mimicking complex dislocation dynamics by interaction networks

Two-dimensional discrete dislocation models exhibit complex dynamics in relaxation and under external loading. This is manifested both in the time-dependent velocities of individual dislocations and in the ensemble response, the strain rate. Here we study how well this complexity may be reproduced using so-called Interaction Networks, an Artificial Intelligence method for learning the dynamics of complex interacting systems. We test how to learn such networks using creep data, and show results on reproducing individual and collective dislocation velocities. The quality of reproducing the interaction kernel is discussed

Predicting elastic and plastic properties of small iron polycrystals by machine learning

Deformation of crystalline materials is an interesting example of complex system behaviour. Small samples typically exhibit a stochastic-like, irregular response to externally applied stresses, manifested as significant sample-to-sample variation in their mechanical properties. In this work we study the predictability of the sample-dependent shear moduli and yield stresses of a large set of small cube-shaped iron polycrystals generated by Voronoi tesselation, by combining molecular dynamics simulations and machine learning. Training a convolutional neural network to infer the mapping between the initial polycrystalline structure of the samples and features of the ensuing stress-strain curves reveals that the shear modulus can be predicted better than the yield stress. We discuss our results in the context of the sensitivity of the system's response to small perturbations of its initial state

The effect of disorder on transverse domain wall dynamics in magnetic nanostrips

We study the effect of disorder on the dynamics of a transverse domain wall in ferromagnetic nanostrips, driven either by magnetic fields or spin-polarized currents, by performing a large ensemble of GPU-accelerated micromagnetic simulations. Disorder is modeled by including small, randomly distributed non-magnetic voids in the system. Studying the domain wall velocity as a function of the applied field and current density reveals fundamental differences in the domain wall dynamics induced by these two modes of driving: For the field-driven case, we identify two different domain wall pinning mechanisms, operating below and above the Walker breakdown, respectively, whereas for the current-driven case pinning is absent above the Walker breakdown. Increasing the disorder strength induces a larger Walker breakdown field and current, and leads to decreased and increased domain wall velocities at the breakdown field and current, respectively. Furthermore, for adiabatic spin transfer torque, the intrinsic pinning mechanism is found to be suppressed by disorder. We explain these findings within the one-dimensional model in terms of an effective damping parameter $\alpha^*$ increasing with the disorder strength.Comment: 5 pages, 3 figure

Barkhausen noise from formation of 360∘^{\circ} domain walls in disordered permalloy thin films

Barkhausen noise in disordered ferromagnets is typically understood to originate primarily from jerky field-driven motion of domain walls. We study the magnetization reversal process in disordered permalloy thin films using micromagnetic simulations, and find that the magnetization reversal process consists of the gradual formation of immobile 360$^{\circ}$ domain walls via a sequence of localized magnetization rotation events. The density of 360$^{\circ}$ domain walls formed within the sample as well as the statistical properties of the Barkhausen jumps are controlled by the disorder strength