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Machine learning has shown its great potential in the accelerated discovery of advanced materials in the field of computational molecular design. High-temperature polymer dielectrics are urgently required with the emerging applications of energy-storage dielectric film capacitors under high-temperature conditions. Here, we demonstrate the successful prediction of polymers with a high dielectric constant (ɛ) and high glass transition temperature (Tg) using a Bayesian molecular design model. The model is trained on a joint data set containing 382 computed ɛ values using density functional perturbation theory and experimentally measured Tg values of ∼7000 polymers to build relative quantitative structure–property relationships and identify the promising polymers with specific desired range of dielectric constant and glass transition temperature. From the hypothetical polymer candidates, ten promising polymers are proposed based on their predicted properties and synthetic accessibility score for high-temperature dielectric film capacitors' application. Moreover, 250k novel polymer structures are generated with the model to support future polymer informatics research. This work contributes to the successful prediction of high-temperature polymer dielectrics using machine learning models. [ABSTRACT FROM AUTHOR]

Superconducting MgB2–MgO composite with about 75% mole concentration of MgO was synthesized in situ by a single-replacement reaction. The resistance versus temperature curve shows that the composite has a high superconducting transition temperature to 38.0 K and metallic transport behavior with low resistivity and highly residual resistance ratio comparable to a pure MgB2 sample. These characteristics are explained by using the statistical percolation model and a conductivity expression with temperature for the metal–insulator MgB2 composite is given in this paper. The results indicate that MgB2 superconductor can tolerance a high content of insulating contamination and this metal–insulator MgB2–MgO composite can be utilized for the superconducting fault current limiter. [ABSTRACT FROM AUTHOR]

Superconducting Mg[B.sub.2]-MgO composite with 75% mole concentration of MgO is prepared in situ by a single-replacement reaction. The results have shown that Mg[B.sub.2] superconductor can tolerate a high content of insulating contamination and the metal-insulator Mg[B.sub.2]-MgO composite is used for the superconducting fault current limiter.