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RUI: Magnetic interactions in nanoparticle systems Yumi Ijiri, Oberlin College, DMR 0704178. Context: Magnetic nanoparticles are of interest for many applications from data storage to magnetic refrigeration to biosensors.
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RUI: Magnetic interactions in nanoparticle systemsYumi Ijiri, Oberlin College, DMR 0704178 Context: Magnetic nanoparticles are of interest for many applications from data storage to magnetic refrigeration to biosensors. Results: Working with collaborators at Carnegie Mellon, NIST, and Los Alamos, we have probed magnetic interactions in magnetic nanoparticles using an unusual polarization analyzed small angle neutron scattering (PASANS) method. •For Mn3O4/MnO nanoparticles, we have been measuring ordered crystals of 27 nm diameter particles and correlating to behavior observed by other methods. • With Fe3O4 nanoparticles, we have explored the robustness of the PASANS approach, with a manuscript submitted to J. Appl. Cryst. Significance:Our work is important in 1) quantifying magnetic interactions and spin arrangements in technologically interesting nanoparticles and 2) developing polarized SANS methods for separating magnetic components. Structural signal Magnetic signal SANS data on manganese oxide nanoparticle crystals, showing structural and significantly weaker and different magnetic features. Inset shows microscopy image of a single nanoparticle crystal.
RUI: Magnetic interactions in nanoparticle systems Yumi Ijiri, Oberlin College, DMR 0704178 Educational impact: In this past year of funding, four undergraduate physics and/or chemistry majors have worked on this project, either during the summer and/or school year: Robert Bond ’11 (PHY) Matthew Chaves ’11(CHE) Liv Dedon ’12 (PHY/CHE) Kathryn Hasz ’14 (PHYS) Seniors Rob Bond and Matt Chaves have graduated, now both interning in the Boston area. Kathryn Hasz, a first year student, began working in Jan. on the project, her first research experience. Rob Bond, working on the Rigaku x-ray diffractometer obtained via NSF DMR Award #0922588. LivDedon, analyzing SANS data.