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Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films

Shuang Tang, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, Lucy Dow, Emmanuel Ojukwu, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA
2022 ES Materials & Manufacturing  

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There are many applications involving the use of bismuth antimony thin films. However, due to the low crystalline symmetry and the 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 work, we have developed several pattern recognition tools to predict the
more » ... 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.
doi:10.30919/esmm5f661 fatcat:5ied4fvfs5epjexrie2wq3vx5a
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Shuang Tang, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, Lucy Dow, Emmanuel Ojukwu, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA, College of Engineering, State University of New York Polytechnic Institute, Albany, NY, 12203, USA. "Pattern Recognition for the Electronic Phase of Bismuth Antimony Thin Films." ES Materials & Manufacturing (2022)