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RESEARCH PAPER · Materials Science and Engineering R Reports · 2026

Data-driven approaches for functional ceramics

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Data-driven approaches for functional ceramicsOriginalLinking the past and future of solid oxide cells: A bibliometric analysis based on recent articles from two premier review journals0Predicting dielectric constants of crystalline materials using explainable machine learning and composition-aware feature engineering0Composition-only machine-learning benchmark for three dielectric properties of single-phase ULTCC ceramics0

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  1. Linking the past and future of solid oxide cells: A bibliometric analysis based on recent articles from two premier review journals

    Materials Science and Engineering B · 2026-07-28

    Dmitry A. Medvedev

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  2. Predicting dielectric constants of crystalline materials using explainable machine learning and composition-aware feature engineering

    Applied Physics A · 2026-07-29

    Devbrat Pundhir, Ashok Kumar

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  3. Composition-only machine-learning benchmark for three dielectric properties of single-phase ULTCC ceramics

    Journal of Advanced Dielectrics · 2026-09-18

    Tao Zhou, Xuanrui Tu, Longyuan Zhao, Liangchen Fan, Huanhuan Wang, Yuanxun Li, Yulong Liao

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