利用材料信息学预测β-(AlxGa1-x)2O3的光学带隙

Edward Swinnich, Yash Jayeshbhai Dave, E. Bruce Pitman, Scott Broderick, Baishakhi Mazumder, Jung-Hun Seo
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引用次数: 15

摘要

在本研究中,使用主成分回归和高斯随机过程预测了β-(AlxGa1-x)2O3的光学带隙与Al组成x的关系。特性来源于其他成熟的铝合金化合物半导体,以形成带隙模型。研究发现,电子带隙、热导率和Al成分对光学带隙的影响最大。最后的关系是由混合信息学方法产生的,该方法结合了从多个模型获得的信息。预测了β-(AlxGa1-x)2O3的光学带隙与Al组成的关系,并与测量的光学带间隙吻合良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Prediction of optical band gap of β-(AlxGa1-x)2O3 using material informatics

In this study, the optical band gap of β-(AlxGa1-x)2O3 versus the Al composition x is predicted using principal component regression and a Gaussian stochastic process. Properties were sourced from other mature Al-alloyed compound semiconductors to form a band gap model. It is found that the electronic band gap, the thermal conductivity, and the Al composition have the greatest influences on the optical band gap. A final relation is generated from a hybrid informatics approach combining information gained from multiple models. The optical band gap of β-(AlxGa1-x)2O3 versus the Al composition is predicted and agrees well with measured optical band gap.

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