Multivariate data analysis approach to understand magnetic properties of perovskite manganese oxides
✍ Scribed by N. Imamura; T. Mizoguchi; H. Yamauchi; M. Karppinen
- Publisher
- Elsevier Science
- Year
- 2008
- Tongue
- English
- Weight
- 609 KB
- Volume
- 181
- Category
- Article
- ISSN
- 0022-4596
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✦ Synopsis
Here we apply statistical multivariate data analysis techniques to obtain some insights into the complex structure-property relations in antiferromagnetic (AFM) and ferromagnetic (FM) manganese perovskite systems, AMnO 3 . The 131 samples included in the present analyses are described by 21 crystal-structure or crystal-chemical (CS/CC) parameters. Principal component analysis (PCA), carried out separately for the AFM and FM compounds, is used to model and evaluate the various relationships among the magnetic properties and the various CS/CC parameters. Moreover, for the AFM compounds, PLS (partial least squares projections to latent structures) analysis is performed so as to predict the magnitude of the Ne´el temperature on the bases of the CS/CC parameters. Finally, so-called PLS-DA (PLS discriminant analysis) method is employed to find out the most influential/characteristic CS/CC parameters that differentiate the two classes of compounds from each other.