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The crystal structure of polycrystalline PbBaSrPrCu 3 O 8 was studied using high resolution neutron diffraction. Rietveld refinement of the diffraction pattern shows that the compound crystallizes into the Tl 2 Ba 2 YCu 2 O 8 2212-type structure. The Pb and Cu atoms in the two ͑Pb,Cu͒O layers are randomly mixed to form two ͑Pb 0.5 Cu 0.5 ͒O layers, and the Ba and Sr atoms are also randomly mixed to form two ͑Ba 0.5 Sr 0.5 ͒O layers, resulting in ͑Pb 0.5 Cu 0.5 ͒ 2 ͑Ba 0.5 Sr 0.5 ͒ 2 PrCu 2 O 8 . The magnetic ordering of the Pr ions was also studied using magnetic neutron diffraction and ac susceptibility measurements. At low temperatures, magnetic peaks presumably originating from the Pr spin ordering were observed at the ͕1/2 1/2 1/2 1/2͖, ͕1/2 1/2 3/2͖, and ͕1/2 1/2 5/2͖ positions. The Pr spins order at T N Ϸ 9 K with the moment direction along the c axis and the nearest-neighbor spins coupled antiferromagnetically. A cusp associated with the antiferromagnetic ordering at T N is also clearly observed in ac susceptibility measurements.

Ferromagnetic resonance (FMR) and the measurement of magnetization dynamics in general have become sophisticated tools for the study of magnetic systems at the nanoscale. Nanosystems, such as the nanodots of this study, are technologically important structures, which find applications in a number of devices, such as magnetic storage and spintronic systems. In this work, we describe the detailed investigation of cobalt nanodots with a 200 nm diameter arranged in a square pitch array with a periodicity of 400 nm. Due to their size, such structures can support standing spinwave modes, which can have complex spectral responses. To interpret the experimentally measured broadband FMR, we are comparing the spectra of the nanoarray structure with the unpatterned film of identical thickness. This allows us to obtain the general magnetic properties of the system, such as the magnetization, g-factor and magnetic anisotropy. We then use state-of-the-art simulations of the dynamic response to identify the nature of the excitation modes. This allows us to assess the boundary conditions for the system. We then proceed to calculate the spectral response of our system, for which we obtained good agreement. Indeed, our procedure provides a high degree of confidence, since we have interpreted all the experimental data to a good degree of accuracy. In presenting this work, we provide a full description of the theoretical framework and its application to our system, and we also describe in detail the novel simulation method used.

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