Understanding Electron Density

This lecture delves into the concept of electron density in chemistry, starting from the Bohr atomic model to the more accurate Balanced Shell model. It explores how machine learning is applied to predict electron density, the challenges in representing it, and the implications for understanding molecular properties, drug design, and diffraction patterns. The discussion also covers a paper that uses kernel methods to predict electron density in chemical environments, showcasing its effectiveness in predicting non-covalent interactions and generalizing to larger molecules like peptides.