Advanced Analysis Using Deep Learning Method

Abstract

X-ray Photoelectron Spectroscopy (XPS) is an important analytical method utilized to determine not only the electronic structure of a material, but also the elemental content of the material. However, it requires a high level of expertise to interpret XPS data, and the reliability of XPS analysis depends on the competence of the expert. To overcome these challenges, this article introduces the process of developing a deep learning model that can automatically interpret XPS data without human intervention. Furthermore, by understanding how a deep learning model can quantify elemental content in a spectrum, we provide insights into XPS analysis methods and the interpretation of the spectrum itself.