Researchers used a hierarchical machine learning strategy to identify tungsten bronze oxides and guide bismuth and germanium substitutions that improved permittivity and thermal stability. The resulting Ba4(Nd0.5Bi0.5)9.33(Ti0.99Ge0.01)18O54 ceramic combined high permittivity, very low dielectric loss, and near-zero temperature dependence, and was used to make compact prototype chip capacitors.
Machine Learning Guides New High-Permittivity Ceramic for Smaller, Temperature-Stable Capacitors
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