论文标题
鞭毛锑薄膜的电子相的图案识别
Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films
论文作者
论文摘要
有许多应用涉及使用二晶型薄膜。但是，由于电子带边缘之间的晶体对称性低和强耦合，推断出这种材料的电子相一直是具有挑战性的。幸运的是，随着模式识别技术的发展，科学家可以构建许多黑框工具来预测各种材料特性。在目前的工作中，我们开发了几种模式识别工具，以预测二晶型薄膜的电子相。支持向量机，决策树和人工神经网络的预测准确性分别为〜90％，〜95％和〜100％。
There are many applications involving the use of bismuth antimony thin films. However, due to the low crystalline symmetry and strong coupling between the electronic band edges, it has always been challenging to infer the electronic phase of such a material. Fortunately, with the development of pattern recognition technology, scientists can build many black-box tools for predicting various materials properties. In this present work, we have developed several pattern recognition tools to predict the electronic phase of a bismuth antimony thin film. The support vector machine, the decision tree, and the artificial neural network are used to achieve a prediction accuracy of ~90%, ~95% and ~100%, respectively.
