Machine learning-based design of electrocatalytic materials towards high-energy lithium

Summary

The article discusses designing electrocatalysts for lithium-sulfur batteries using machine learning to uncover complex features influencing catalytic activity. Fourier transformation in spectroscopy aids in characterizing catalyst structures like transition metals and iron, enhancing understanding of their mechanisms. Key topics include transition metals, catalysis, iron, and Mössbauer spectroscopy.