Raman signatures of ferroic domain walls captured by principal component analysis

Area of Science:

• Materials Science
• Condensed Matter Physics
• Spectroscopy

Background:

• Ferroic domain walls (DWs) possess unique functional properties that are crucial for advanced materials.
• Current investigation of DWs relies on various sophisticated techniques to understand their behavior.
• Raman spectroscopy is a key tool for probing material properties at the nanoscale.

Purpose of the Study:

• To explore the application of principal component analysis (PCA) for analyzing Raman maps of ferroic domain walls.
• To demonstrate PCA's capability in identifying and quantifying spectral changes associated with domain walls.
• To establish a novel statistical approach for analyzing properties mapped across domain walls.

Main Methods:

• Application of principal component analysis (PCA) to Raman mapping data.
• Study of ferroelectric domain walls in Lithium Niobate (LiNbO₃).
• Investigation of ferroelastic domain walls in Neodymium Gallate (NdGaO₃).
• Utilizing a first-order Taylor expansion for spectral analysis.

Main Results:

• PCA enables rapid and reliable identification of small Raman peak variations at ferroelectric DWs.
• Accurate deduction of peak shift values without a priori assumptions is achieved through PCA and Taylor expansion.
• PCA effectively separates the spectral contributions of ferroelastic domains and domain walls.

Conclusions:

• Principal component analysis is a powerful tool for analyzing Raman spectroscopic data of ferroic domain walls.
• The developed method provides an accurate and assumption-free way to quantify domain wall properties.
• This work introduces a versatile statistical analysis framework applicable to various properties mapped across domain walls.