Computational Design of Rare-Earth Reduced Permanent Magnets

Multiscale simulation is a key research tool in the quest for new permanent magnets.Starting with first principles methods,a sequence of simulation methods can be applied to calculate the maximum possible coercive field and expected energy density product of a magnet made from a novel magnetic material composition.Iron(Fe)-rich magnetic phases suitable for permanent magnets can be found by means of adaptive genetic algorithms.The intrinsic properties computed by ab initio simulations are used as input for micromagnetic simulations of the hysteresis properties of permanent magnets with a realistic structure.Using machine learning techniques,the magnet’s structure can be optimized so that the upper limits for coercivity and energy density product for a given phase can be estimated.Structure property relations of synthetic permanent magnets were computed for several candidate hard magnetic phases.The following pairs(coercive field(T),energy density product(kJ·m^-3))were obtained for iron-tin-antimony(Fe3Sn0.75Sb0.25):(0.49,290),L10-ordered iron-nickel(L10 FeNi):(1,400),cobalt-iron-tantalum(CoFe6Ta):(0.87,425),and manganese-aluminum(MnAl):(0.53,80).

Nanoscale chemical segregation to twin interfaces in τ-MnAl-C and resulting effects on the magnetic properties

In this study,aberration-corrected scanning transmission electron microscopy coupled with electron energy-loss spectroscopy(STEM-EELS)was used to investigate the atomistic structure and chemical com-position of true twin and order twin boundaries in ferromagneticτ-MnAl-C.True twins and order twins were distinguished based on the diffraction patterns using TEM.No elemental segregation was observed at the coherent true twin boundary but some Mn enrichment within a region of about 1.5-2 nm was found at the incoherent true twin boundary.A transition region with Mn enrichment about 4-6 nm wide was found at the order twin boundary.A carbon cluster with a size of around 5 nm was also found at the twin boundary.Micromagnetic simulations were conducted to study the effect of this chemical seg-regation at twin interfaces on the magnetic properties.The results showed that the coercivity tends to increase with increasing structural and chemical disorder at the interface.

Full-spin-wave-scaled stochastic micromagnetism for mesh-independent simulations of ferromagnetic resonance and reversal

In this paper,we address the problem that standard stochastic Landau-Lifshitz-Gilbert(sLLG)simulations typically produce results that show unphysical mesh-size dependence.The root cause of this problem is that the effects of spin-wave fluctuations are ignored in sLLG.We propose to represent the effect of these fluctuations by a full-spin-wave-scaled stochastic LLG,or FUSSS LLG method.In FUSSS LLG,the intrinsic parameters of the sLLG simulations are first scaled by scaling factors that integrate out the spin-wave fluctuations up to the mesh size,and the sLLG simulation is then performed with these scaled parameters.We developed FUSSS LLG by studying the Ferromagnetic Resonance(FMR)in Nd_(2)Fe_(14)B cubes.The nominal scaling greatly reduced the mesh size dependence relative to sLLG.We then performed three tests and validations of our FUSSS LLG with this modified scaling.(1)We studied the same FMR but with magnetostatic fields included.(2)We simulated the total magnetization of the Nd_(2)Fe_(14)B cube.(3)We studied the effective,temperature-and sweeping rate-dependent coercive field of the cubes.In all three cases,we found that FUSSS LLG delivered essentially mesh-size-independent results,which tracked the theoretical expectations better than unscaled sLLG.Motivated by these successful validations,we propose that FUSSS LLG provides marked,qualitative progress towards accurate,high precision modeling of micromagnetics in hard,permanent magnets.

Extracting local nucleation fields in permanent magnets using machine learning

Microstructural features play an important role in the quality of permanent magnets.The coercivity is greatly influenced by crystallographic defects,like twin boundaries,as is well known for MnAl-C.It would be very useful to be able to predict the macroscopic coercivity from microstructure imaging.Although this is not possible now,in the present work we examine a related question,namely the prediction of simulated nucleation fields of a quasi-three-dimensional(rescaled and extruded)system constructed from a two-dimensional image.