218 resultados para Magnetic adsorbates


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We have fabricated using high-resolution electron beam lithography circular magnetic particles (nanomagnets) of diameter 60 nm and thickness 7 nm out of the common magnetic alloy supermalloy. The nanomagnets were arranged on rectangular lattices of different periods. A high-sensitivity magneto-optical method was used to measure the magnetic properties of each lattice. We show experimentally how the magnetic properties of a lattice of nanomagnets can be profoundly changed by the magnetostatic interactions between nanomagnets within the lattice. We find that simply reducing the lattice spacing in one direction from 180 nm down to 80 nm (leaving a gap of only 20 nm between edges) causes the lattice to change from a magnetically disordered state to an ordered state. The change in state is accompanied by a peak in the magnetic susceptibility. We show that this is analogous to the paramagnetic-ferromagnetic phase transition which occurs in conventional magnetic materials, although low-dimensionality and kinetic effects must also be considered.

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This paper proposes an analytical approach that is generalized for the design of various types of electric machines based on a physical magnetic circuit model. Conventional approaches have been used to predict the behavior of electric machines but have limitations in accurate flux saturation analysis and hence machine dimensioning at the initial design stage. In particular, magnetic saturation is generally ignored or compensated by correction factors in simplified models since it is difficult to determine the flux in each stator tooth for machines with any slot-pole combinations. In this paper, the flux produced by stator winding currents can be calculated accurately and rapidly for each stator tooth using the developed model, taking saturation into account. This aids machine dimensioning without the need for a computationally expensive finite element analysis (FEA). A 48-slot machine operated in induction and doubly-fed modes is used to demonstrate the proposed model. FEA is employed for verification.

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