Interpretable machine learning-assisted discovery of BaTiO 3 -based ceramics with enhanced dielectric constant

Journal of Materials Chemistry C 2026

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Authors: J X Liu, Hua Hao, Xingzhong Liu, Jiahao Tian, Bangzhi Peng, Chunze Wei, Jinglong Fan, Hanxing Liu
DOI: 10.1039/d6tc00908e
Cited by: 1
References: 68

Abstract

We combined feature selection and SHAP analysis to identify promising composition ranges, then used EGO to guide synthesis. Four new compositions were prepared and characterized, yielding superior ε r25 in just one experimental round.

Fields of Study & Subjects

Machine Learning in Materials Science Ferroelectric and Piezoelectric Materials Ferroelectric and Negative Capacitance Devices

Publication details

Journal / source
Journal of Materials Chemistry C
Publisher
Royal Society of Chemistry (RSC)
Volume
14
Issue
26
Pages
11631–11641
Publication date
1 January 2026
Language
EN