Introduction to Computational Chemistry

Computational chemistry methods have become an important tool for solving chemical problems. But a chemical computational program is not a "black box", any more than an NMR spectrometer; rather, it must be used properly to provide reliable results. The course will describe and explain, from a distinct user perspective, how computational chemistry can contribute to everything from the analysis and explanation of reaction mechanisms, the interpretation of measured IR or NMR spectra to the description of complex systems such as electrolytes, nanoparticles, proteins, DNA and ligand-receptor complexes under realistic conditions (aqueous solution, room temperature). We will discuss both quantum chemical methods, with a focus on the "workhorse" of modern quantum chemistry - density functional theory (DFT) - and molecular mechanics in combination with molecular dynamics and Monte-Carlo methods. Here, we will discuss the basic ideas, strengths and weaknesses, and potential pitfalls for the different methods. We will also discuss how artificial intelligence (AI) influences computational chemistry and its application. The methods and concepts will be illustrated by extensive computer exercises.