Machine Learning-Assisted Materials Design and Discovery of Low-Melting-Point Inorganic Oxides for Low-Temperature Cofired Ceramic Applications
收藏Figshare2022-01-20 更新2026-04-28 收录
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https://figshare.com/articles/dataset/Machine_Learning-Assisted_Materials_Design_and_Discovery_of_Low-Melting-Point_Inorganic_Oxides_for_Low-Temperature_Cofired_Ceramic_Applications/18779666
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The fabrication of low-temperature cofired ceramics (LTCCs) densified at a low sintering temperature (R2 = 0.7968 and root-mean-square error = 247.4 (K). Three features, including formation energy per atom (fepa), theoretical density (d), and number of atoms (na), were extracted as the decisive characteristics of inorganic oxides. The melting point demonstrates positive correlations with the absolute value of fepa and d. The na acts as a “recessive gene” because its contribution is indirect but necessary. The physical relationships between features and the melting point were also discussed. Furthermore, the LTCC inorganic oxides often have melting points lower than 1400 °C statistically. This criterion was verified by the reported LTCC/ultra-LTCC materials. The melting points of materials in the prediction set consisting of ∼3600 inorganic oxides were calculated by the ML model, and thus, the underlying LTCC materials could be screened out efficiently.
创建时间:
2022-01-20



