Raman signatures of ferroic domain walls captured by principal component analysis

Guillaume F. Nataf (1, 2, 3) , Nicholas Barrett (1) , J. Kreisel (2) , M. Guennou (2)

1 LENSIS - Laboratoire d'Etude des NanoStructures et Imagerie de Surface
2 LIST - Luxembourg Institute of Science and Technology
3 DMSM - Department of Materials Science and Metallurgy [Cambridge University]

Ferroic domain walls are currently investigated by several state-of-the art techniques in order to get a better understanding of their distinct, functional properties. Here, principal component analysis (PCA) of Raman maps is used to study ferroelectric domain walls (DWs) in LiNbO$_3$ and ferroelastic DWs in NdGaO$_3$. It is shown that PCA allows us to quickly and reliably identify small Raman peak variations at ferroelectric DWs and that the value of a peak shift can be deduced (accurately and without a priori) from a rst order Taylor expansion of the spectra. The ability of PCA to separate the contribution of ferroelastic domains and DWs to Raman spectra is emphasized. More generally, our results provide a novel route for the statistical analysis of any property mapped across a DW.

Mots clés: domain wall; multivariate statistical analysis; Raman

Domaines: Physique [physics]

Guillaume F. Nataf, Nicholas Barrett, J. Kreisel, M. Guennou. Raman signatures of ferroic domain walls captured by principal component analysis. Journal of Physics: Condensed Matter, 2018, 30, pp.035902. ⟨10.1088/1361-648X/aa9778⟩. ⟨cea-01687736⟩