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Phase Identification of La-Doped Hard Magnetic Barium Ferrite Using Artificial Neural Network
Date
2011-01-01
Author
Sozeri, Huseyin
KÜÇÜK, İLKER
Ozkan, Husnu
Metadata
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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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BibTeX
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.