In-Situ Nanoindentation Surface Topography of Lead-Free Piezoelectric Thin Films

Surface roughness significantly affects the performance of microelectromechanical systems (MEMS) and piezoelectric films. This study investigates the impact of surface roughness on the mechanical properties of thin piezoelectric films using nanoindentation and scanning probe microscopy (SPM). Four piezoelectric films with different thicknesses (220, 350, and 450 nm) and substrate configurations (LNO/SiO2/Si or LNO/Si) were analyzed. A discriminant analysis revealed that the fractal dimension is more effective than the arithmetic mean height (Sa) for distinguishing surfaces, with only 2% misclassification versus 25% for Sa. A multiscale analysis identified the Smr2 parameter with low-pass filtering at 140 nm as highly effective for surface discrimination, achieving only 0.1% misclassification. The analysis of the roughness parameter Sa at various scales showed that band-pass filtering at 500 nm yielded a 0.7% misclassification rate, indicating its relevance for fractal roughness characterization. Most relevant roughness parameters for mechanical property correlation were found: Smr2 with low-pass filtering at 500 nm correlated best with hardness (R2 = 0.82), and Vvc with low-pass filtering at 2 nm correlated best with reduced elastic modulus (R2 = 0.84). These results demonstrate that surface roughness features like valley volume and voids significantly impact the apparent mechanical properties of piezoelectric films.

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Publication Details

Journal
Applied Sciences
Published
2024-12-18
DOI
https://doi.org/10.3390/app142411849
Citations
1
Primary Topic
Adhesion, Friction, and Surface Interactions
Type
article
Field-Weighted Citation Impact
0.27

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article

In-Situ Nanoindentation Surface Topography of Lead-Free Piezoelectric Thin Films

Maxence Bigerelle, Alex Montagne, Denis Rémiens, Julie Lemesle
1 citations
Applied Sciences
Adhesion, Friction, and Surface Interactions
0.27
article

In-Situ Nanoindentation Surface Topography of Lead-Free Piezoelectric Thin Films

Maxence Bigerelle, Alex Montagne, Denis Rémiens, Julie Lemesle
article en
1 citations

Abstract

Surface roughness significantly affects the performance of microelectromechanical systems (MEMS) and piezoelectric films. This study investigates the impact of surface roughness on the mechanical properties of thin piezoelectric films using nanoindentation and scanning probe microscopy (SPM). Four piezoelectric films with different thicknesses (220, 350, and 450 nm) and substrate configurations (LNO/SiO2/Si or LNO/Si) were analyzed. A discriminant analysis revealed that the fractal dimension is more effective than the arithmetic mean height (Sa) for distinguishing surfaces, with only 2% misclassification versus 25% for Sa. A multiscale analysis identified the Smr2 parameter with low-pass filtering at 140 nm as highly effective for surface discrimination, achieving only 0.1% misclassification. The analysis of the roughness parameter Sa at various scales showed that band-pass filtering at 500 nm yielded a 0.7% misclassification rate, indicating its relevance for fractal roughness characterization. Most relevant roughness parameters for mechanical property correlation were found: Smr2 with low-pass filtering at 500 nm correlated best with hardness (R2 = 0.82), and Vvc with low-pass filtering at 2 nm correlated best with reduced elastic modulus (R2 = 0.84). These results demonstrate that surface roughness features like valley volume and voids significantly impact the apparent mechanical properties of piezoelectric films.

Applied SciencesVol. 14(24)
Centre National de la Recherche Scientifique (FR), Laboratoire d'Automatique, de Mécanique et d'Informatique Industrielles et Humaines (FR), Institut d'Electronique, de Microélectronique et de Nanotechnologie (FR), Université Polytechnique Hauts-de-France (FR)
Agence Nationale de la Recherche, Centre National de la Recherche Scientifique, Université Polytechnique Hauts-de-France
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 47%
Adhesion, Friction, and Surface Interactions
0.27
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