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• W2562474887 abstract "The control and understanding of magnetization reversal mechanisms and magnetostatic interactions in nanomagnet arrays is a critical point that has to be overcome in order to reach industrial applications. However, usual magnetic characterization techniques can only provide information on the overall array behaviour and are not able to discriminate relevant local properties. In this work, we show that the first-order reversal curve (FORC) method is a unique tool to identify weakly-interacting uniaxial single domain (SD) particles in systems with complex mixed magnetic states. We compare the FORC diagrams of two sets of Ni nanowire (NW) arrays electrodeposited in hexagonally ordered nanoporous alumina templates: A) with a uniform length distribution (interacting SD particles), and B) with a non-uniform length distribution. For non-uniform length distributions, regions of isolated NWs occur in the array, creating a complex mixture of strongly and weakly-interacting SD particles. These weakly-interacting NWs are here identified by a characteristic ridge along the coercive field axis of the FORC diagram. Micromagnetic simulations confirmed the presence of this weakly-interacting magnetic behaviour in the array with non-uniform length distributions. Combining FORC results with micromagnetic simulations, we show that the magnetization reversal of interacting wires occurs by the nucleation of transverse domain walls at the NWs' ends, while isolated wires nucleate vortex domain walls. This work thus highlights the importance of the FORC method for the accurate identification and understanding of local magnetic behaviours in nanomagnet arrays." @default.
• W2562474887 created "2017-01-06" @default.
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• W2562474887 date "2017-03-01" @default.
• W2562474887 modified "2023-10-01" @default.
• W2562474887 title "Identifying weakly-interacting single domain states in Ni nanowire arrays by FORC" @default.
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• W2562474887 doi "https://doi.org/10.1016/j.jallcom.2016.12.340" @default.
• W2562474887 hasPublicationYear "2017" @default.
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