Author

Hong-Yu Yang

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Aug 2026

Machine-Learning-Guided Polarization-Lattice Decoupling Enables Ultrahigh Energy Storage in Lead-Free Dielectric Ceramics.

Achieving ultrahigh energy storage in lead-free dielectric ceramics is fundamentally constrained by the intrinsic trade-off between large polarization and high dielectric breakdown strength. Here, we establish an interpretable machine-learning-guided design framework that quantitatively links ionic descriptors with pol...

Zi-Xiong Sun, Yao Li, Hong-Yu Yang et al. · Advances in Materials · 2 citations

Open access Aug 2026

Machine Learning-Guided Electronic Configuration Design for Dielectrics With High Energy Storage Performance.

An interpretable machine learning framework based on Shapley Additive exPlanations is developed to guide the compositional design of K0.5Na0.5NbO3-based relaxor ferroelectrics, leading to Sc as the optimal dopant, outperforming the Bi5/6In0.5Sn0.5O3-doped system.

Liang-Zhe Chen, Lei Cao, Zishan Jin et al. · Small · 0 citations