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Magnetic materials are essential for energy generation and information devices, and they play an important role in advanced technologies and green energy economies. Currently, the most widely used magnets contain rare earth (RE) elements. An outstanding challenge of notable scientific interest is the discovery and synthesis of novel magnetic materials without RE elements that meet the performance and cost goals for advanced electromagnetic devices. Here, we report our discovery and synthesis of an RE-free magnetic compound, Fe 3 CoB 2 , through an efficient feedback framework by integrating machine learning (ML), an adaptive genetic algorithm, first-principles calculations, and experimental synthesis. Magnetic measurements show that Fe 3 CoB 2 exhibits a high magnetic anisotropy ( K 1 = 1.2 MJ/m 3 ) and saturation magnetic polarization ( J s = 1.39 T), which is suitable for RE-free permanent-magnet applications. Our ML-guided approach presents a promising paradigm for efficient materials design and discovery and can also be applied to the search for other functional materials. 

Neutron powder diffraction (NPD) and x-ray magnetic circular dichroism (XMCD) spectroscopy are employed to investigate the magnetism and spin structure in single-phase B20 Co 1.043 Si 0.957 . The magnetic contributions to the NPD data measured in zero fields are consistent with the helical order among the allowed spin structures derived from group theory. The magnitude of the magnetic moment is (0.3 ± 0.1) μ B /Co according to NPD, while the surface magnetization probed by XMCD at 3 kOe is (0.18–0.31) μ B /Co. Both values are substantially larger than the bulk magnetization of 0.11 μ B /Co determined from magnetometry at 70 kOe and 2 K. These experimental data indicate the formation of a helical spin phase and the associated conical states in high magnetic fields. 

The spin structure and transport behavior of B20-ordered CoSi nanomagnets are investigated experimentally and by theoretical calculations. B20 materials are of interest in spin electronics because their noncentrosymmetric crystal structure favors noncoplanar spin structures that yield a contribution to the Hall effect. However, stoichiometric bulk CoSi is nonmagnetic, and combining magnetic order at and above room temperature with small feature sizes has remained a general challenge. Our CoSi nanoclusters have an average size of 11.6 nm and a magnetic ordering temperature of 330 K. First-principle calculations and x-ray circular dichroism experiments show that the magnetic moment is predominantly confined to the shells of the clusters. The CoSi nanocluster ensemble exhibits a topological Hall effect, which is explained by an analytical model and by micromagnetic simulations on the basis of competing Dzyaloshinskii-Moriya and intra- and intercluster exchange interactions. The topological Hall effect is caused by formation of chiral spin textures in the shells of the clusters, which exhibit fractional skyrmion number and are therefore termed as paraskyrmions (closely related to skyrmion spin structures). This research shows how nanostructuring of a chiral atomic structure can create a spin-textured material with a topological Hall effect and a magnetic ordering temperature above room temperature. 

Magnetotransport and ferromagnetism in thin films of Co2Si nanoclusters are investigated experimentally and theoretically. The nanoclusters are fabricated by an inert-gas condensation-type cluster-deposition method and have an average size of 11.3 nm. Unlike the bulk Co2Si that exhibits a very weak net magnetic moment only below 10 K, the nanoclusters exhibit room-temperature ferromagnetism with a substantial saturation magnetization. Key features of the system are its closeness to the Stoner transition, magnetic moments induced by spin polarization starting from surface atoms, and nonuniaxial anisotropy associated with the orthorhombic crystal structure of Co2Si. A method is introduced to determine the effective anisotropy using the experimental magnetization data of this complex system and its relationship with the two lowest-order nonuniaxial anisotropy constants. On decreasing temperature from 300 K, the nanoclusters show electron-transport properties unusual for a ferromagnetic metal, including an increase of Hall resistivity and a nonmonotonic change of negative magnetoresistance with a peak at around 100 K. The underlying physics is explained on the basis of the large polarization of surface spins and variation in the degree of their misalignments due to temperature-dependent effective anisotropy. 

Heusler compounds and alloys based on them are of great recent interest because they exhibit a wide variety of spin structures, magnetic properties, and electron-transport phenomena. Their properties are tunable by alloying and we have investigated L21-orderd compound Ru2MnSn and its alloys by varying the atomic Mn:Sn composition. While antiferromagnetic ordering with a Néel temperature of 361 K was observed in Ru2MnSn, the Mn-poor Ru2Mn0.8Sn1.2 alloy exhibits properties of a diluted antiferromagnet in which there are localized regions of uncompensated Mn spins. Furthermore, a noncoplanar spin structure, evident from a topological Hall-effect contribution to the room-temperature Hall resistivity, is realized in Ru2Mn0.8Sn1.2. Our combined experimental and theoretical analysis shows that in the Ru2Mn0.8Sn1.2 alloy, the magnetic properties can be explained in terms of a noncoplanar antiferromagnetic scissor mode, which creates a small net magnetization in a magnetic field and subsequently yields a Berry curvature with a strong topological Hall effect. 

New magnetic materials for energy and information-processing applications are of paramount importance in view of significant global challenges in environmental and information security. The discovery and design of materials requires efficient computational and experimental approaches for high throughput and efficiency. When increasingly powerful computational techniques are combined with special non-equilibrium fabrication methods, the search can uncover metastable compounds with desired magnetic properties. Here we review recent results on novel Fe-, Co- and Mn-rich magnetic compounds with high magnetocrystalline anisotropy, saturation magnetization, and Curie temperature created by combining experiments, adaptive genetic algorithm searches, and advanced electronic-structure computational methods. We discuss structural and magnetic properties of such materials including Co– and/or Fe–X compounds (X = N, Si, Sn, Zr, Hf, Y, C, S, Ti, or Mn), and their prospects for practical applications. 

We develop an open-access database that provides a large array of datasets specialized for magnetic compounds as well as magnetic clusters. Our focus is on rare-earth-free magnets. Available datasets include (i) crystallography, (ii) thermodynamic properties, such as the formation energy, and (iii) magnetic properties that are essential for magnetic-material design. Our database features a large number of stable and metastable structures discovered through our adaptive genetic algorithm (AGA) searches. Many of these AGA structures have better magnetic properties when compared to those of the existing rare-earth-free magnets and the theoretical structures in other databases. Our database places particular emphasis on site-specific magnetic data, which are obtained by high-throughput first-principles calculations. Such site-resolved data are indispensable for machine-learning modeling. We illustrate how our data-intensive methods promote efficiency of the experimental discovery of new magnetic materials. Our database provides massive datasets that will facilitate an efficient computational screening, machine-learning-assisted design, and the experimental fabrication of new promising magnets.