| Issue |
EPL
Volume 124, Number 5, December 2018
|
|
|---|---|---|
| Article Number | 56001 | |
| Number of page(s) | 5 | |
| Section | Condensed Matter: Structural, Mechanical and Thermal Properties | |
| DOI | https://doi.org/10.1209/0295-5075/124/56001 | |
| Published online | 27 December 2018 | |
Cation distribution of Mn-Zn ferrite nanoparticles using pair distribution function analysis and resonant X-ray scattering
1 Nuclear and Energy Research Institute, Materials Science and Technology Center(IPEN- CNEN) Av Lineu Prestes 2242, 05508-000 São Paulo-SP, Brazil
2 São Paulo State University, Institute of Biosciences(UNESP-IBB) - Via Domingos Sartor, Km 4, 18618-970, Botucatu- SP, Brazil
3 ALBA Synchrotron - Carrer de la Llum, 2-26, 08290 Cerdanyola del Vallès, Barcelona, Spain
4 Université du Luxembourg, Faculté des Sciences, de la Technologie et de la Communication 6 Rue Richard Coudenhove- Kalergi, 1359 Luxembourg, Luxembourg
5 Luxembourg Institute of Science and Technology - 5 Avenue des Hauts- Fourneaux, 4362 Esch-sur-Alzette, Luxembourg, Luxembourg
6 Institut de Ciència de Materials de Barcelona, Department of Crystallography (ICMAB-CSIC) Campus de la UAB 08193 Bellaterra, Spain, 08193 Bellaterra, Barcelona, Spain
(a) ichikawa@usp.br
Received: 15 August 2018
Accepted: 22 November 2018
Mn-Zn ferrite nanoparticles were synthesized by chemical co-precipitation method and analysed using X-ray synchrotron diffraction data. Pair distribution function (PDF) analysis was used to probe the local structure and revealed that the first-neighbour distances of Fe-Fe and Mn-Zn in the 3.0 up to 3.5 Å range are different from the ones usually reported in the literature. For the sample with the best magnetic behaviour, resonant X-ray scattering (RXS) using three energies close to the absorption edges of Mn, Zn and Fe was applied to determine the cation distribution which explained the previous result from PDF analysis.
PACS: 61.05.cp – X-ray diffraction / 61.46.Hk – Nanocrystals / 61.43.Bn – Structural modeling: serial-addition models, computer simulation
© EPLA, 2018
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