Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films

Shuang Tang,1,*Email

Lucy Dow1 

Emmanuel Ojukwu1

1College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA

Abstract

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.

Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films