Modeling and Predicting the Piezoelectric Properties of (Ba,Ca)(Zr,Ti)O3 Films with Composition Gradient Using Machine Learning

Authors

J. Wolfman (ORCID: https://orcid.org/0000-0002-4786-2869)
Hugo Kuentz (ORCID: https://orcid.org/0000-0002-1086-2961)
Kevin Nadaud (ORCID: https://orcid.org/0000-0002-2969-1453)
B. Négulescu (ORCID: https://orcid.org/0000-0001-7218-9859)
K. Dey (ORCID: https://orcid.org/0000-0001-5502-8025)

Institutions

Centre National de la Recherche Scientifique (FR)
Thion Medical (France) (FR)

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2025-07-13
Primary Topic: Ferroelectric and Piezoelectric Materials
Type: article
Field-Weighted Citation Impact: 0.00

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article

Modeling and Predicting the Piezoelectric Properties of (Ba,Ca)(Zr,Ti)O3 Films with Composition Gradient Using Machine Learning

J. Wolfman, Hugo Kuentz, Kevin Nadaud, B. Négulescu et al.

Jul 13, 2025

SPIRE - Sciences Po Institutional REpository

Ferroelectric and Piezoelectric Materials

article

Modeling and Predicting the Piezoelectric Properties of (Ba,Ca)(Zr,Ti)O3 Films with Composition Gradient Using Machine Learning

J. Wolfman, Hugo Kuentz, Kevin Nadaud, B. Négulescu, K. Dey

July 13, 2025article en

Abstract

No abstract available for this paper.

SPIRE - Sciences Po Institutional REpository

Centre National de la Recherche Scientifique (FR), Thion Medical (France) (FR)

Openalex Percentile: Top 77%

Ferroelectric and Piezoelectric Materials

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Modeling and Predicting the Piezoelectric Properties of (Ba,Ca)(Zr,Ti)O3 Films with Composition Gradient Using Machine Learning — J. Wolfman, Hugo Kuentz, et al. · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS