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Modeling the Dielectric Constant of Silicon-Based Nanocomposites Using Machine Learning

机译:使用机器学习对硅基纳米复合材料的介电常数建模

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In this work, we solve the problem of predicting the dielectric constant of silicon-based nanocomposites using machine learning methods. Mathematical models and programs have been developed to predict the electrophysical properties of new materials, as well as to select the optimal composition. The results obtained will be useful for faster and cheaper creation of new functional composites.
机译:在这项工作中,通过机器学习方法解决了预测基于硅基纳米复合材料的介电常数的问题。已经开发了数学模型和程序以预测新材料的电神法性质,以及选择最佳组合物。获得的结果对于更快和更便宜地创建新功能复合材料。

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