Modeling and predicting the piezoelectric properties of (Ba,Ca)(Zr,Ti)O3 (BCTZ) combinatorial PLD sample doped with cerium 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)

Institutions

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

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2025-05-26
Primary Topic: Gas Sensing Nanomaterials and Sensors
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 (BCTZ) combinatorial PLD sample doped with cerium using machine learning

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

May 26, 2025

SPIRE - Sciences Po Institutional REpository

Gas Sensing Nanomaterials and Sensors

article

Modeling and predicting the piezoelectric properties of (Ba,Ca)(Zr,Ti)O3 (BCTZ) combinatorial PLD sample doped with cerium using machine learning

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

May 26, 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 73%

Gas Sensing Nanomaterials and Sensors

OpenAlex

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Modeling and predicting the piezoelectric properties of (Ba,Ca)(Zr,Ti)O3 (BCTZ) combinatorial PLD sample doped with cerium using machine learning — J. Wolfman, Hugo Kuentz, et al. · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS