Abstract
We present a strategy for the design of ferromagnetic materials with exceptionally low magnetic hysteresis, quantified by coercivity. In this strategy, we use a micromagnetic algorithm that we have developed in previous research and which has been validated by its success in solving the “Permalloy Problem”—the wellknown difficulty of predicting the composition 78.5% Ni of the lowest coercivity in the Fe–Ni system—and by the insight it provides into the “Coercivity Paradox” of W. F. Brown. Unexpectedly, the design strategy predicts that cubic materials with large saturation magnetization m_{s} and large magnetocrystalline anisotropy constant κ_{1} will have low coercivity on the order of that of Permalloy, as long as the magnetostriction constants λ_{100}, λ_{111} are tuned to special values. The explicit prediction for a cubic material with low coercivity is the dimensionless number \(({c}_{11}{c}_{12}){\lambda }_{100}^{2}/(2{\kappa }_{1})=81\) for 〈100〉 easy axes. The results would seem to have broad potential application, especially to magnetic materials of interest in energy research.
Introduction
A longstanding puzzle in materials science is understanding the origins of magnetic hysteresis in ferromagnetic materials. Hysteresis in this domain refers to the differing behaviors obtained when a demagnetized specimen is subject to an increasing magnetic field to saturation vs. that obtained when decreasing the field from saturation to zero. The effect is typically characterized by the final (absolute) value of the magnetic field after such a test, termed the coercivity. Informally, soft magnets have low coercivity. This paper is concerned with the prediction of coercivity from micromagnetic theory. An unexpected prediction of our study is that coercivity can be made very small even in materials with large magnetocrystalline anisotropy constant, as long as the magnetostrictive constants are tuned appropriately.
Aside from basic scientific interest on the origins of hysteresis and the traditional application to transformers, a strategy for the discovery of new soft magnetic materials is desirable for rapid powerconversion electronics, allelectric vehicles, and wind turbines, especially in cases where induction motors are favored. Magnetic hysteresis has also become critical to the adoption of proposed spintronic and storage devices, as requirements for limiting energy consumption have moved to the forefront^{1,2}. These requirements impact a wide range of applications, from hand held electronic devices to storage systems and servers at data centers. While our analysis is aimed primarily at bulk applications, the key idea that micromagnetic theory with magnetostriction, together with a wellchosen potent defect, can be used to predict hysteresis suggests a strategy for the lowering of coercivity also in these smallscale applications. In fact, in certain filmbased devices, the likely potent defects, such as threading dislocations in epitaxial films, are often better characterized than in bulk material.
Currently, a widely accepted strategy to lower the hysteresis in cubic ferromagnetic alloys is based on changing composition so as to reduce the magnitude of the anisotropy constant ∣κ_{1}∣. This has the effect of flattening the graph of magnetocrystalline anisotropy energy vs. magnetization and reducing the penalty associated with magnetization rotation. Intuitively, this makes sense, as it apparently makes available additional lowenergy pathways of an alloy in a metastable state on the shoulder of the hysteresis loop, as an applied field is being lowered. A related idea is the known strategy of tuning the composition so as to be precisely at the point where two different symmetries coincide, again leading to a flattening of the magnetocrystalline anisotropy energy vs. magnetization and the lowering of hysteresis. The latter is the strategy used by Clarke and collaborators^{3,4} that led to the particular composition of Terfenol: Tb_{x}Dy_{1−x}Fe_{2}, x = 0.3. We add that modern research on these RFe_{2} cubic Laves phase materials has focused on the benefits of exploiting a nearby morphotropicphase boundary in these systems to enhance magnetostrictive response under small fields^{5,6,7}.
However, these strategies cannot be the whole story behind coercivity. For example, in the iron–nickel system, a sharp drop in coercivity occurs at the Permalloy composition, at which κ_{1} = −161Jm^{−3}. Tuning the magnetocrystalline anisotropy constant to zero in ironnickel alloys in fact leads to an alloy composition with noticeably higher hysteresis^{8}. Similarly, in Sendust (Fe_{0.85}Si_{0.096}Al_{0.054} alloy), the hysteresis is minimum when the magnetocrystalline anisotropy and magnetostriction constants are close to zero, and not precisely at κ_{1} = 0^{9}. Finally, there are quite a few isolated examples of alloys that have very large magnetocrystalline anisotropy constants but low coercivity: an example is the uniaxial phase of Ni_{51.3}Mn_{24.0}Ga_{24.7} having a uniaxial magnetocrystalline anisotropy constant of 2.45 × 10^{5} Jm^{−3} and coercivity less than 1 kAm^{−1} in single crystals^{10}. Another example is the Galfenol alloys (Fe_{1−x}Ga_{x} for 0.13 ≤ x ≤ 0.24) that have small magnetic hysteresis, despite their very large magnetocrystalline anisotropy constants^{11,12}. These examples suggest that the magnetocrystalline anisotropy constant is not the only factor that governs hysteresis in magnetic alloys.
The precise role of magnetostriction constants on magnetic hysteresis is not well understood for two reasons: (a) prior research has typically ignored the contribution of magnetoelastic interactions on hysteresis, justified by the small values of the magnetostriction constants, and (b) mathematical methods, such as the linear stability analysis, overestimate the coercivity of bulk alloys—by over three orders of magnitude in some cases—as compared with measured experimental values^{13,14}. The latter is referred to as the “Coercivity Paradox”^{13,15}. These factors limit our understanding of how the balance between fundamental material constants—such as magnetocrystalline anisotropy and magnetostriction constants—affects magnetic coercivity.
In our recent work, we developed a computational tool based on micromagnetics, including magnetoelastic terms, that is adapted to the prediction of coercivity in bulk magnetic alloys^{16,17}. Micromagnetics, since its first postulation in 1963 by W.F.Brown Jr.^{13}, has been applied to a wide range of problems in ferromagnets and forms the basis to several computational frameworks^{18,19,20}. Our coercivity tool is based on the micromagnetics theory^{16}, but however differs from earlier works in the following ways: a key feature of this tool is that it uses a large but highly localized disturbance—in the form of a Néeltype spike domain—to predict magnetic coercivity. Néel spikelike domains are frequently observed to form around defects in various magnetic alloys (see^{21,22,23,24,25} for examples) and grow under an external field. In the absence of this spikedomain, the second variation of the micromagnetic energy misses the energy barrier for magnetization reversal^{13,26}. Instead, we model a large localized disturbance (i.e., compute a nonlinear stability analysis) to predict coercivity on the shoulder of the hysteresis curve, see Fig. 1. Other features of our coercivity tool are that we account for magnetoelastic interactions, however small, in estimating coercivity of bulk magnetic alloys; and we use the ellipsoid and reciprocal theorems to accelerate our coercivity calculations, see^{16}. Our computations are fully threedimensional with the magnetization evolving from (010) to (100) in all directions as one leaves the spike domain.
To arrive at the Néel spike as a reasonable description of a potent defect, we include in^{16} a study of alternative nuclei, including rotated spikes and multiple spikes. These spike domains serve as nuclei that grow during magnetization reversal. In this previous study^{16}, we investigated the role of defect geometry, defect orientation, and defect number on magnetic coercivity, and we found that these features did not significantly affect coercivity when compared with fundamental material constants. Mathematically, they can be interpreted as localized disturbances that, under the right combination of material constants and suitable applied field, are able to surmount an energy barrier^{27,28,29,30} Small, smooth disturbances of a homogeneous state are not able to surmount this barrier at realistic applied fields due to the dominance of domainwall energy at small scales, and, in our view, this is the essence of the Coercivity Paradox^{16,17}. Mathematically, the situation is that the study of the second variation of the micromagnetic energy misses the important energy barrier, while it is captured as a largeamplitude, but localized, disturbance.
Our viewpoint is consistent with the thesis of Pilet^{27} who examines the microscopic state on the shoulder of the hysteresis loop (far away from where coercivity is measured) using magnetic force microscopy, and finds good correlation with the presence of large localized disturbances. Another feature of our tool is that we account for the magnetoelastic interactions—however small—in estimating coercivity. Our results are in a form that is amenable to alloy development, as in related searches for low hysteresisphase transformations^{31}.
An alternative highly effective route to low hysteresis in magnetic materials is the synthesis of nanocrystalline material^{32}. For example, the powder synthesis and rapid solidification techniques have resulted in nanocrystalline and amorphous magnetic alloys that offer low hysteresis and enhanced permeability^{2,33,34}. Here we do not specifically analyze this situation, but we think this should be possible in the nanocrystalline case, though challenging due to the many grains that would likely have to be considered.
The aim of the present work is to identify combinations of material constants, including saturation magnetization (m_{s}), magnetocrystalline anisotropy constant (κ_{1}), elastic moduli (c_{11}, c_{12}, c_{44}), and magnetostriction constants (λ_{100}, λ_{111}) that give the lowest coercivity in a cubic material. We do not vary the exchange constant, which in practice does not vary much: we also give arguments why, when combined with the demagnetization energy, it should matter little. We find the striking result that magnetostriction plays a critical role, and more importantly, coercivities on the order of those found in very soft materials such as Permalloy are predicted to be possible in materials with large magnetocrystalline anisotropy constant, as long as the magnetostriction constants are tuned to special values. We find that magnetocrystalline anisotropy and magnetostriction constants play a particularly important role, but neither has to be small.
The simulations are carried out using our newly developed coercivity tool. Details on our micromagnetic algorithm are described in “Methods”. Specifically, we apply this tool in two studies: in Study 1, we test the hypothesis that the tuning of magnetostriction constants, in addition to the magnetocrystalline anisotropy constant, is necessary to reduce coercivity in magnetic alloys. Here we study how combinations of κ_{1} and λ_{100} affect coercivity, and ignore the contribution from λ_{111} = 0. In total, we compute coercivity values from N = 2, 163 independent simulations. In Study 2, we test our hypothesis that there exists a specific combination of material constants—κ_{1}, λ_{100}, λ_{111}—at which magnetic coercivity is the lowest. Here, we compute coercivity by systematically varying the magnetocrystalline anisotropy and the magnetostriction constants, in the ranges 0 ≤ κ_{1} ≤ 2000 J m^{−3}, −2000μϵ ≤ λ_{100} ≤ 2000μϵ, and 0 ≤ λ_{111} ≤ 600μϵ, respectively (N = 605). Overall, our computations from over 2500 independent simulations show that the lowest coercivity is attained when the dimensionless number \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\). Here, c_{11}, c_{12} are the elastic stiffness constants of the soft magnet assuming a linear cubic relation. To our knowledge, this discovery of the balance between material constants at which magnetic hysteresis is small has not been proposed before. A theoretical analysis supporting the importance of this dimensionless number is given below. This analysis further supports the idea that, in other situations, a second dimensionless number \(\frac{{c}_{12}{\lambda }_{100}^{2}}{2{\kappa }_{1}}\) may become important, and tuning the stiffness constants c_{11} and c_{12}, so that both of these dimensionless constants have particular values may be desirable^{35}.
Results
Computation of coercivity
In Study 1, we test our hypothesis that the magnetostriction constants, in addition to the magnetocrystalline anisotropy constant, are necessary to reduce coercivity in magnetic alloys. Figure 2(a) shows a heat map of coercivity values as a function of the magnetocrystalline anisotropy constant κ_{1} and the magnetostriction constant λ_{100}. A key feature of this plot is that the coercivity is minimum along a curve described by \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\). As expected, the coercivity is small when κ_{1} → 0 and the magnetostriction constant is small λ_{100} → 0, see Inset A. However, surprisingly, we find that the coercivity value is also small for nonzero magnetocrystalline anisotropy constants κ_{1} >> 0 with suitable combinations of the magnetostriction constant, see Inset B. Note the rather large magnetocrystalline anisotropy constants being considered, well outside the range associated with normal soft magnetism. Furthermore, the minimum coercivity valleys are symmetric about the λ_{100} = 0 axis. This symmetric response arises from the even terms \({\lambda }_{100}^{2}\) in the freeenergy expression. We observe a similar lowering of coercivity in magnetic alloys with κ_{1} < 0 at suitable values of λ_{111} magnetostriction constant (see Supplementary Fig. 2).
Figure 2(b–c) are 3D surface plots of the inset regions “A” and “B” respectively. The “wells” in these plots correspond to combinations of material constants at which coercivity is minimum. Figure 2(b) is a 3D plot of the inset region “A”—here, we note a discontinuity or a jump in coercivity values at κ_{1} = 0. This discontinuity is because of the change in easy axes for magnetic alloys with κ_{1} > 0 and κ_{1} < 0. For example, we compute coercivities along [100] and [111] crystallographic directions for magnetic alloys with κ_{1} > 0 and κ_{1} < 0, respectively. These alloys have different values of magnetostriction constants along their easy axes. We believe that the computed rapid change of coercivity at κ_{1} = 0 is real, and arises from the anisotropy of these magnetostriction constants. Figure 2(c) shows the 3D surface plot of the inset region B. Here, coercivities comparable to that of the permalloy composition are achieved at large magnetocrystalline anisotropy values κ_{1} ≈ 1700 J m^{−3} with suitable combinations of the magnetostriction constant λ_{100} ≈ 1200μϵ.
Overall, the findings from Study 1 contradict the general understanding of hysteresis in magnetism, i.e., the magnetocrystalline anisotropy constant needs to be near zero for small hysteresis. Our findings show that magnetic hysteresis (or coercivity value) is small not only when κ_{1} → 0 but also when κ_{1} >> 0, given suitable values of the magnetostriction constants. Figure 2 shows that the magnetostriction constant, λ_{100}, in addition to the magnetocrystalline anisotropy constant κ_{1} plays an important role in reducing coercivity in magnetic alloys.
Thus far, we investigated coercivity values by setting one of the magnetostriction constants λ_{111} to be zero. In Study 2, we test the hypothesis that there exists a specific combination of material constants, namely κ_{1}, λ_{100}, λ_{111}, at which magnetic coercivity is the lowest. We compute coercivities at every combination of κ_{1}, λ_{100}, and λ_{111} in the parameter space 0 ≤ κ_{1} ≤ 2000 J m^{−3} and −2000μϵ ≤ λ_{100} ≤ 2000μϵ and 0 ≤ λ_{111} ≤ 600μϵ.
Figure 3(a) shows the coercivity map as a function of κ_{1} and λ_{100} for increasing values of λ_{111}. A key feature here is that the minimum coercivity relationship \({\kappa }_{1}\propto {\lambda }_{100}^{2}\) is unique at each value of the λ_{111} magnetostriction constant. For example, the minimum coercivity valleys gradually widen and become asymmetric about λ_{100} = 0, with increasing value of the λ_{111} magnetostriction constant. We identify combinations of material constants at which minimum coercivity is achieved, and then plot a 3D surface through these points in the κ_{1}−λ_{100}−λ_{111} parameter space, see Fig. 3(b). This 3D plot represents a surface through the material parameter space on which coercivity is small.
Theoretical analysis
The results of our studies above can be understood in the following way. We begin from the free energy that we have used in the simulations of micromagnetics (see Figs. 4, 5) in dimensional form^{16},
where \({{{\bf{E}}}}=\frac{1}{2}(\nabla {{{\bf{u}}}}+{(\nabla {{{\bf{u}}}})}^{T})\) and the energy is to be minimized, or minimized locally, over the pair of functions u, m ∈ H^{1}(Ω). Here, m (with components on the cubic axes \({{{{\rm{{m}}}_{1},{m}_{2},\; m}}}_{{{{\rm{3}}}}}\)) has been previously nondimensionalized so m ⋅ m = 1, and the demagnetization field satisfies the magnetostatic equations H_{d} = −∇ζ_{m}, ∇ ⋅ (−∇ζ_{m} + m_{s}m) = 0 on all of space, so H_{d} has the dimensions of m_{s}, as does H_{ext}. Please note that m is extended to \({{\mathbb{R}}}^{3}\) by making it vanish outside Ω. Typical accepted values from a large compositional space appropriate to Fig. 3(a) including most of the Fe–Ni system, are
A nondimensional form is obtained by dividing the micromagnetic energy by \({\mu }_{0}{m}_{s}^{2} \sim 1{0}^{6}{{{{\rm{Nm}}}}}^{2}\), changing variables \({{{\bf{x}}}}^{\prime} =\frac{1}{\ell }\ {{{\bf{x}}}}\in {{\Omega }}^{\prime}\), where ℓ is a typical length scale and \({{{\bf{x}}}}^{\prime}\) is dimensionless. This gives a typical nondimensional value of the micromagnetic coefficients
The range of magnetostrictive coefficients is consistent with Fig. 3(a), and for material constants with a size range, we choose a typical intermediate value. A caveat with these numbers is the observation made by Brown^{26} (discussed also in^{21}) that the formal linearization of geometrically nonlinear micromagnetics that gives Eq. (1) implies a possible m dependence of the elastic moduli c_{11}, c_{12}, c_{44}. This dependence is usually neglected, as is done here. Note from Eq. (3) the wide ranging values of magnetostrictive energy and its relative importance generally.
It is seen from the nondimensionalized coefficient Eq. (3) that magnetostriction and demagnetization energy are dominant, but it is important to observe that each can be made negligible by suitable magnetization distributions. The magnetostrictive energy can be made to vanish by choosing a magnetization that satisfies curl\({({{{\rm{curl}}}}\,{{{{\bf{E}}}}}_{0}({{{\bf{m}}}}))}^{T}=0\), that is, \({{{{\bf{E}}}}}_{0}({{{\bf{m}}}}({{{\bf{x}}}}))=\frac{1}{2}(\nabla {{{\bf{u}}}}+{(\nabla {{{\bf{u}}}})}^{T})\) is the symmetric part of a gradient, while the demagnetization energy vanishes on divergencefree magnetizations. In addition, we note that the exchange energy is one of the smallest energy contributions and its contribution further decreases at increasing length scales. Although the exchange constant could be affected by temperature, composition, and presence of defects, its order of magnitude A ≈ 10^{−11} J m^{−1} does not significantly affect largescale micromagnetic simulations. Consequently, we do not vary the exchange constant in our calculations.
We first explain from a theoretical viewpoint why the Néel spike attached to a defect of the type we have chosen is a particularly potent perturbation. A key observation comes from symmetry and holds also in the more general case of a geometrically nonlinear magnetoelastic free energy (see Section 6 of^{36}). The observation is that domain walls involving a jump in the magnetization m^{+} − m^{−} ≠ 0, where m^{+} and m^{−} minimize the magnetocrystalline anisotropy energy density and satisfy the divergencefree condition (m^{+} − m^{−}) ⋅ n = 0 at an interface with normal n, have the property that they give rise to strains that are perfectly mechanically compatible in the sense that \({{{{\bf{E}}}}}_{0}({{{{\bf{m}}}}}^{+}){{{{\bf{E}}}}}_{0}({{{{\bf{m}}}}}^{})=\frac{1}{2}({{{\bf{a}}}}\otimes {{{\bf{n}}}}+{{{\bf{n}}}}\otimes {{{\bf{a}}}})\) for some vector a. The latter is the jump condition implying the existence of a continuous displacement across the interface. These conditions hold also for typical domainwall models with remote boundary conditions given by (m^{+}, E_{0}(m^{+})) and (m^{−}, E_{0}(m^{−})). This argument applies not only to materials with cubic symmetry but also to many lowersymmetry systems (see^{36} for the precise statement of this result).
To understand the relation between this symmetry argument and the Néel spike, we substitute the form of \({\mathbb{C}}\) and E_{0}(m) for cubic materials into Eq. (1). The latter is
in the orthonormal cubic basis. We consider only the case κ_{1} > 0 corresponding to 〈100〉 easy axes, for which we have the most data above. The case κ_{1} < 0 corresponding to 〈111〉 easy axes is handled similarly. Without loss of generality, we also divide the whole energy by the dimensionless number \({\kappa }_{1}/{\mu }_{0}{m}_{s}^{2}\). In addition, we define a new displacement \(\hat{{{{\bf{u}}}}}({{{\bf{x}}}})\) by \({{{\bf{u}}}}({{{\bf{x}}}})={\lambda }_{100}\hat{{{{\bf{u}}}}}({{{\bf{x}}}})\) with the corresponding strain tensor \({{{\bf{E}}}}={\lambda }_{100}\hat{{{{\bf{E}}}}}\). Minimization of energy using u is equivalent to the same using \(\hat{{{{\bf{u}}}}}\), and this equivalence applies also to local minimization or the relative height of an energy barrier. These changes give the explicit nondimensional form of the free energy
where we have used the magnetostatic equation to include the demagnetization term in the integrand. Also, \({\hat{\epsilon }}_{ij}=\frac{1}{2}({\hat{u}}_{i,j}+{\hat{u}}_{j,i})\), and for simplicity, we have dropped the prime on x. However, \({{\Omega }}^{\prime}\) remains dimensionless.
Now, we make an observation about the structure of Eq. (5) relating to the symmetry argument given above. With κ_{1} > 0 as assumed, the two magnetizations m^{−} = (1, 0, 0) and m^{+} = (0, 1, 0) satisfy (m^{+} − m^{−}) ⋅ n = 0, where \({{{\bf{n}}}}=\frac{1}{\sqrt{2}}(1,1,0)\). Therefore, by the symmetry argument described above, \({{{{\bf{E}}}}}_{0}({{{{\bf{m}}}}}^{+}){{{{\bf{E}}}}}_{0}({{{{\bf{m}}}}}^{})=\frac{1}{2}({{{\bf{a}}}}\otimes {{{\bf{n}}}}+{{{\bf{n}}}}\otimes {{{\bf{a}}}})\) and it is indeed verified that that this holds with \({{{\bf{a}}}}=\frac{3\sqrt{2}{\lambda }_{100}}{2}(1,1,0)\). The values of the strains are given in Fig. 6(c). Importantly, these choices of m^{+}, E_{0}(m^{+}), and m^{−}, E_{0}(m^{−}) make the magnetocrystalline anisotropy energy and all three magnetostrictive terms in Eq. (5) vanish, and also give a locally divergencefree magnetization. Recalling that the simulations are 3D (see Fig. 5), note that Fig. 6(c) can be confined to a slab between two surfaces parallel to the plane of the page and, if m(x) = m^{−} is assigned outside the slab, then these surfaces are also polefree. These facts support the potency (i.e., lowenergy barrier) provided by the Néel spikes.
At the transient state, the magnetic poles on the tips of the spike domains are far apart and the geometric features of the spike domain have evolved to compatible interfaces. Similar symmetry arguments can be made for transientstate microstructures with multiple Néel spikes and/or other defect geometries. In these cases, the magnetic material constants dominate the energy barrier, and the defect geometries appear to play a negligible role.
Thus, we arrive at the following scenario typical of nucleation. When the applied field is large, the magnetocrystalline anisotropy energy of a large spike is disfavored, and spike is small and collapsed near the defect, due to the dominating influence of (diffuse) domainwall energy at small scales. As the applied field is decreased, the magnetocrystalline anisotropy and demagnetization energies favor the growth of the spike. A local energy maximum is reached, beyond which an energydecreasing path is possible, leading to complete reversal of the magnetization.
The parabolic form of the locus of the lowest coercivity points in Figs. 3(a) and 2(a) can now be understood heuristically. The terms involving the very small nondimensional exchange constant and very large multiplier of the nondimensional demagnetization energy are the only terms that involve ∇m. These are expected to compete within the diffuse domain walls present in these simulations, but otherwise lead only to a neardivergencefree magnetization, as suggested by the inequality of arithmetic–geometric means in the form
which implies, using the magnetostatic equations H_{d} = − ∇ ζ_{m} and ∇ ⋅ (−∇ζ_{m} + m_{s}m) = 0, that
In the geometry being considered, the heuristic argument for the energy barrier suggests that the shear strains in this geometry play a minor role, and this is supported by typical measurements of the shear strains across the spike, Fig. 7(a–c), taken from the simulations. This observation, together with the fact that the magnetization is near the easy axes [100] or [010] in the region of the spikes (so that m_{i}m_{j} ≈ 0, i ≠ j), indicates that the constant \({c}_{44}{{\lambda }_{100}}^{2}/{\kappa }_{1}\) will play only a minor role in determining the energy barrier.
Granted these approximations, the height of the energy barrier must then be affected mainly by the remaining dimensionless constants
Again, from the simulations (Fig. 7(d–f)) tr E is quite small in comparison with the multiplier of \(({c}_{11}{c}_{12}){\lambda }_{100}^{2}/(2\kappa_1)\), and so we expect the latter, \(({c}_{11}{c}_{12}){\lambda }_{100}^{2}/(2{\kappa }_{1})\), to be the key dimensionless constant that governs the height of the barrier. In simulations, the term containing this constant accounted for up to 80% of the total magnetoelastic energy.
The value of this dimensionless constant giving the lowest energy barrier indicated by the simulations is
As we have noticed previously^{17}, 78.5% Ni Permalloy does not exactly fall on the computed parabola given by Eq. (9). This may indicate that there are opportunities for lowering the coercivity of permalloy. It is possible that favorable heat treatments of permalloy do just that by modifying the material constants present in Eq. (9). An alternative possibility is that, while Eq. (9) may be the primary dimensionless constant affecting coercivity, both constants given in Eq. (8) may play a role, indicating that the finetuning of elastic moduli according to their relative roles in the two constants of Eq. (8) may be a route to even lower coercivity.
Discussion
At present, the conventional approach to develop soft magnets is to reduce the magnetocrystalline anisotropy value to zero. Consequently, the search for soft magnets is concentrated around the κ_{1} → 0 region. Our theoryguided prediction suggests that in addition to the coercivity well at κ_{1} → 0 region, there exists other regions along \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\) at which coercivity is small. This analytical relation between material constants gives greater freedom for alloy development and increases the parameter space to discover novel soft magnets. In summary, our findings show that the magnetostriction constants, in addition to the magnetocrystalline anisotropy constant, play an important role in governing magnetic coercivity. This was the case in study 1 when coercivity was minimum along a parabolic relation given by \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\) with λ_{111} = 0 in magnetic alloys. In study 2, we identified a 3D surface topology on which the coercivity is small. Below, we discuss some limitations of our findings and then present its potential impact to the magnetic alloy development program.
Two features of this work limit the conclusions we can draw about the fundamental relationship between magnetic material constants. First, we compute coercivities assuming a simple defect structure (i.e., two spike domains formed around a nonmagnetic inclusion) in an oblate ellipsoid. While defect geometry has been shown to have surprisingly small effect on the coercivity values^{16}, it is not known whether and how different defect geometries, and crystallographic texture of the magnetic alloy would affect our predictions of the parabolic relation for minimum coercivity. Second, the presence of mechanical loads, such as residual strains or boundary loads, could affect the delicate balance between the magnetic material constants. The idealized stressfree conditions in our model are subject to the shortcomings associated with the presence of microstructural inhomogeneities and surface conditions in bulk materials. Whether accounting for these inhomogeneities would yield comparable results in experiments is an open question. With these reservations in mind, we next discuss the impact of our findings to the alloydevelopment program.
A key feature of our work is that we demonstrate that the magnetostriction constants play an important role in governing magnetic coercivity. These findings contrast with prior research in which the magnetocrystalline anisotropy constant has been regarded as the only material parameter that governs magnetic hysteresis, and the contribution from magnetostriction constants has been largely neglected. Consequently, the commonly accepted norm in the literature is that magnetic alloys with small magnetocrystalline anisotropy constant have small coercivity, and magnetic alloys with large magnetocrystalline anisotropy constant have large coercivity. However, by accounting for both magnetocrystalline anisotropy and magnetostriction constants, we show that magnetic alloys, despite their large κ_{1} values, have small coercivities at specific combinations of the magnetostriction constants.
Another significant feature of our work is that we identify a relationship \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\) between magnetic material constants at which the coercivity is small. This generic formula serves as a theoretical guide to the alloydevelopment program, by suggesting alternative combinations of material constants—beyond κ_{1} = 0—to develop soft magnets. While this relation is based on 〈100〉 easy axes and might differ for alloys with different easy axes, our work is intended to guide the search for soft magnetism in ordinary ferromagnets with large m_{s}. In future work, we intend to investigate other easy axes, elastic stiffness constants, to further lower coercivity in magnetic alloys^{35}. With the recent advances in atomicscale engineering, the compositions of magnetic alloys can be tuned atombyatom^{37,38}. For these experimental approaches, our prediction of the material constant formula could serve as a guiding principle, to engineer magnetic alloy compositions to small hysteresis. Overall, the fundamental relationship between material constants provides initial steps to experimentalists to discover soft magnets with high magnetocrystalline anisotropy constants.
In conclusion, the present findings contribute to a more nuanced understanding of how material constants, such as magnetocrystalline anisotropy and magnetostriction constants, affect magnetic hysteresis. Specifically, magnetoelastic interactions have been regarded to play a negligible role in lowering magnetic coercivity. Given the current findings, we quantitatively demonstrate that the delicate balance between magnetocrystalline anisotropy, magnetostriction constants, and the spikedomain microstructure (localized disturbance) is necessary to lower magnetic coercivity. We propose a mathematical relationship between material constants \(\frac{({c}_{11}{c}_{12}){\lambda }_{100}^{2}}{2{\kappa }_{1}}\approx 81\) at which minimum coercivity can be achieved in a material with 〈100〉 easy axes. More generally, our findings serve as a theoretical guide to discover novel combinations of material constants that lower coercivity in magnetic alloys.
Methods
Micromagnetics
In our coercivity tool, we use micromagnetics theory that describes the total free energy as a function of magnetization m, strain E, and magnetostatic field H_{d}:
The form of Eq. (10) is identical to that used in our previous work, in which we detail the meaning of the specific terms, material constants, and normalizations^{16}. For the present work, we note that the exchange energy ∇m ⋅ A∇m penalizes spatial gradients of magnetization. More generally, the anisotropy energy for cubic alloys would have contributions from higher order energy terms (e.g., \({\kappa }_{2}({{{{\rm{{m}}}_{1}^{2}\rm{{m}}_{2}^{2}\rm{{m}}_{3}^{2}}}})\)), and these additional anisotropy coefficients are likely in general to contribute to our coercivity calculations. Although including these higherorder anisotropy coefficients, e.g., κ_{2}, could affect the easy axes of magnetization of the material. For example at \({\kappa }_{1}\approx \frac{{\kappa }_{2}}{2}\) other crystallographic directions, such as [111], [110], and a family of irrational directions, would have similarly small magnetocrystalline anisotropy energy. This warrants a systematic investigation in a future study, especially with κ_{1}, κ_{2}, κ_{3} near actual measured values. However, we do not think that these higher order terms would significantly affect our coercivity calculations for the following reasons: first, in our computations, we model an oblate ellipsoid (pancakeshaped) that supports an inplane magnetization. This ellipsoid geometry and the defect shape penalizes outofplane magnetization and thus m_{3} ≈ 0 in our calculations of the magnetic hysteresis. Consequently, the energy contribution from the higherorder anisotropy term, \({\kappa }_{2}({{{{\rm{{m}}}_{1}^{2}\rm{{m}}_{2}^{2}\rm{{m}}_{3}^{2}}}})\), is negligible in our computations. Second, in the nondimensional form of the free energy (see Eq. (5)), the energy contribution from the higherorder anisotropy term would scale as \(\frac{{\kappa }_{2}}{{\kappa }_{1}}\!({{{{\rm{{m}}}_{1}^{2}\rm{{m}}_{2}^{2}\rm{{m}}_{3}^{2}}}})\) with ∣m∣ = 1. This sixthorder energy term is expected not to change the coercivity calculations significantly. We propose to investigate the precise role of the higherorder anisotropy terms in a future study, however, as a first step, we investigate coercivity as a function of magnetocrystalline anisotropy κ_{1} and magnetostriction constant λ_{100}. The elastic energy \(\frac{1}{2}[{{{\bf{E}}}}{{{{\bf{E}}}}}_{{{{\bf{0}}}}}({{{\bf{m}}}})]\cdot {\mathbb{C}}[{{{\bf{E}}}}{{{{\bf{E}}}}}_{{{{\bf{0}}}}}({{{\bf{m}}}})]\) penalizes mechanical deformation away from the preferred strains, and the external energy, μ_{0}H_{ext} ⋅ m accounts for the mutual interaction between magnetization moment and the applied field. Finally, the magnetostatic energy \(\frac{{\mu }_{0}}{2}{\left{{{{\bf{H}}}}}_{{{{\bf{d}}}}}\right}^{2}\) computed in all of space \({{\mathbb{R}}}^{3}\) penalizes the stray fields generated by the magnetic body in its surroundings.
We compute the evolution of the magnetization using an energyminimization technique, the generalized Landau–Lifshitz–Ginzburg equation, see Fig. 4:
Here, \({{{\mathcal{H}}}}=\frac{1}{{\mu }_{0}{m}_{s}^{2}}\frac{\delta {{\Psi }}}{\delta {{{\bf{m}}}}}\) is the effective field, τ = γm_{s}t is the dimensionless time step, γ is the gyromagnetic ratio, and α is the damping constant. We numerically solve Eq. (11) using the Gauss–Siedel projection method^{18}, and identify equilibrium states when the magnetization evolution converges, \(\left{{{{\bf{m}}}}}^{{{{\rm{n}}}}+1}{{{{\bf{m}}}}}^{{{{\rm{n}}}}}\right < 1{0}^{9}\). At each iteration we compute the magnetostatic field H_{d} = −∇ζ_{m} and the strain E by solving their respective equilibrium equations:
The magnetostatic equilibrium condition arises from the Maxwell equations, namely ∇ × H_{d} = 0 → H_{d} = −∇ ζ_{m} and ∇ ⋅ B = ∇ ⋅ (H_{d} + m_{s}m) = 0.
In our calculations, we model a finitesized domain Ω centered around a nonmagnetic defect Ω_{d}, see inset images in Fig. 4. This domain is several times smaller than the actual size of the ellipsoid \({{{\mathcal{E}}}},\) see Fig. 1. We define the total demagnetization field as a sum of the local \(\widetilde{{{{\bf{H}}}}}({{{\bf{x}}}})\) and nonlocal contributions \(\overline{{{{\bf{H}}}}}\). The local contribution \(\widetilde{{{{\bf{H}}}}}({{{\bf{x}}}})\) varies spatially and accounts for the magnetostatic fields generated from defects and other imperfections inside the body. We calculate this local contribution by solving \(\nabla \cdot (\widetilde{{{{\bf{H}}}}}+{m}_{s}\widetilde{{{{\bf{m}}}}})=0\) on Ω. The nonlocal contribution is computed as \(\overline{{{{\bf{H}}}}}={{{\bf{N}}}}{m}_{s}\overline{{{{\bf{m}}}}}\). Here, N is the demagnetizationfactor matrix that is a tabulated geometric property of the ellipsoid. We note, from the tabulated values in ref. ^{39}, the demagnetization factors for an oblate ellipsoid (pancakeshaped) are N_{11} = N_{22} = 0, N_{33} = 1. The \(\overline{{{{\bf{m}}}}}\) is the constant magnetization that is defined, such that ∫_{Ω}m(x)dx = 0. This decomposition simplifies our computational complexity, because we now model a local domain Ω that is much smaller than modeling a domain in \({{\mathbb{R}}}^{3}\), and yet account for the demagnetization contributions from both the body geometry and the local defects. This decomposition is justified in the appendix of our previous paper^{16}. Both the magnetostatic and mechanical equilibrium conditions in Eqs. (12)–(13) are solved in Fourier space, see refs. ^{16,19} for further details.
Numerical calculations
In the present work, we calibrate our micromagnetic model for the FeNi alloy with the following material constants: A = 10^{−11} J m^{−1}, m_{s} = 10^{6}Am^{−2}, μ_{0} = 1.3 × 10^{−6}NA^{−2}, c_{11} = 240.8GPa, c_{12} = 89.2GPa, and c_{44} = 75.8GPa. The values of κ_{1}, λ_{100}, λ_{111} are systematically varied as detailed in the “Results” section. Here, note that magnetic alloys with positive and negative magnetocrystalline anisotropy constants have their easy axes along 〈100〉 and 〈111〉 crystallographic directions, respectively. To accommodate this change of easy axes, we transform the energy potential from a cubic basis, and further details of this transformation are described in the appendix of^{16}.
We compute the coercivity of magnetic ellipsoids as a function of the magnetocrystalline anisotropy and magnetostriction material constants. In each computation, we model a domain of size 64 × 64 × 24 containing a defect with 16 × 16 × 6 grid points. We choose a grid size such that the domain walls span across 3–4 unit cells. We initialize the computational domain with a uniform magnetization m = m_{1}, and force the magnetization inside the defect to be zero throughout the computation, \(\left{{{\bf{m}}}}\right=0\), see Fig. 4. We apply a large external field along the easy axes, H_{ext} >> 0, and decrease it gradually in steps of δH = 0.25e_{1}Oe. As we decrease the applied field, a spike domain forms around the defect, see Fig. 1. This spike domain grows in size as the applied field is further lowered until a critical field value—known as the coercivity H_{c}—at which the magnetization vector reverses. We use this approach to predict the coercivity of the magnetic alloys at each combination of the magnetocrystalline anisotropy and magnetostriction constants.
Specifically, in Study 1 and Study 2 we carry out a total of n = 2163 and n = 605 computations respectively. In these computations, we systematically vary the material constants in the parameter space range of 0 ≤ κ_{1} ≤ 2000 J m^{−3}, −2000μϵ ≤ λ_{100} ≤ 2000μϵ, and 0 ≤ λ_{111} ≤ 600μϵ, respectively. Our investigation shows that the minimum coercivity is attained for a parabolic relation \({\kappa }_{1}\propto {\lambda }_{100}^{2}\), and a total of over 2500 computations are necessary to confirm this relationship.
Data availability
The authors declare that the data supporting the findings of this study are available within the paper and its supplementary information files. Furthermore, additional data that support the findings of this study are available from the corresponding author upon request.
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Acknowledgements
The authors acknowledge the Center for Advanced Research Computing at the University of Southern California and the Minnesota Supercomputing Institute at the University of Minnesota for providing resources that contributed to the research results reported within this paper. The authors would like to thank Anjanroop Singh (University of Minnesota) for help in checking some of the calculations. A.R.B acknowledges the support of a Provost Assistant Professor Fellowship, Gabilan WiSE fellowship, and USC’s startup funds. R.D.J acknowledges the support of a Vannevar Bush Faculty Fellowship. The authors thank NSF (DMREF1629026) and ONR (N000141812766) for partial support of this work.
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A.R.B. and R.D.J. conceptualized the project, designed the methodology, and procured funding. A.R.B. worked on model development, theoretical analysis, and visualization of data. R.D.J. worked on the theoretical calculations. Both authors were involved with the writing of the paper.
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Renuka Balakrishna, A., James, R.D. Design of soft magnetic materials. npj Comput Mater 8, 4 (2022). https://doi.org/10.1038/s41524021006827
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DOI: https://doi.org/10.1038/s41524021006827
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