Phase Identification of La-Doped Hard Magnetic Barium Ferrite Using Artificial Neural Network

Date

2011-01-01

Author

Sozeri, Huseyin
KÜÇÜK, İLKER
Ozkan, Husnu

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A model based on an artificial neural network (ANN) was designed for the simulation and estimation of 2 theta and intensity values obtained by X-Ray Diffraction (XRD) of pure and La-doped barium ferrite powders which have been synthesized in ammonium nitrate melt. Its performance is evaluated by the influences of different La content, sintering temperature, Fe/Ba ratio, and washed in HCl (or not washed in HCl) samples. The XRD patterns of samples estimated by the ANN agree well with the experimental values, indicating that the model is reliable and adequate.

Subject Keywords

Electronic, Optical and Magnetic Materials, Condensed Matter Physics

URI

https://hdl.handle.net/11511/66253

Journal

JOURNAL OF SUPERCONDUCTIVITY AND NOVEL MAGNETISM

DOI

https://doi.org/10.1007/s10948-010-0937-z

Collections

Department of Physics, Article

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Citation Formats

H. Sozeri, İ. KÜÇÜK, and H. Ozkan, “Phase Identification of La-Doped Hard Magnetic Barium Ferrite Using Artificial Neural Network,” JOURNAL OF SUPERCONDUCTIVITY AND NOVEL MAGNETISM, pp. 683–687, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66253.