Introduction to Computational Chemistry

Education facts

Code: KEM322

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.

Entry requirements

For admission to the course, passed courses in science comprising 90 credits (or, alternatively, passed courses in pharmacy/medicine comprising 120 credits) are required, which must include course KEM040 Physical chemistry (15 credits), alternatively course FYP203, Quantum Physics A, or equivalent knowledge. Knowledge in mathematics corresponding to course MMGK11, Mathematics for Science (15 credits) is recommended.

Education offerings

Each offering has its own dates and conditions. Closed offerings are retained as history and do not mean that a new application is open.

• Introduction to Computational Chemistry

  University of Gothenburg

  GÖTEBORG

  Start date: 4 November 2026

  End date: 17 January 2027

  Pace of study: 100 %