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Omnidirectional Control of Large Electrical Output in a Topological Antiferromagnet

Tomoya Higo, Yufan Li, Kouta Kondou, Danru Qu, Muhammad Ikhlas, Ryota Uesugi, Daisuke Nishio‐Hamane, C. L. Chien, Y. Otani, Satoru Nakatsuji

2021Advanced Functional Materials48 citationsDOI

Abstract

Abstract Control of magnetization direction is essential for the wide application of ferromagnets; it defines the signal size of memory and sensor. However, the magnetization itself causes a dilemma. While its size matters to obtain strong responses upon its reversal, the large magnetization concomitantly suppresses the range of its directional control because of the demagnetizing field. On the other hand, realization of the desired magnetic anisotropy requires careful engineering of crystalline and interfacial effects to overcome the demagnetization barrier. Thus, it would be ideal if one could find alternative magnets that carry no magnetization but strong responses. The discovery of a topological metallic state in the antiferromagnet Mn 3 Sn is significant; they host a large Berry curvature in momentum space, enabling the observation of disproportionately large transverse responses such as anomalous Hall and Nernst effects, the key functionalities for replacing ferromagnets in the magnetic devices. Here, the experimental realization of omnidirectional control of the large responses in an antiferromagnet is reported. In particular, it is demonstrated that the absence of shape anisotropy enables the omnidirectional control, and lifts the shape constraint in designing the magnetic devices. This work lays the technological foundation for developing simple‐structured high‐performance devices including multi‐level memory and heat flux sensor.

Topics & Concepts

MagnetizationCondensed matter physicsDemagnetizing fieldMaterials scienceFerromagnetismAntiferromagnetismTopology (electrical circuits)MagnetRealization (probability)Berry connection and curvatureNanomagnetPhysicsMagnetic fieldElectrical engineeringQuantum mechanicsGeometric phaseEngineeringStatisticsMathematicsTopological Materials and PhenomenaAdvanced Memory and Neural ComputingAdvanced Condensed Matter Physics
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