Choosing a computer modelling method to predict chemical behaviour

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Quantum dots enlarged to macroscopic proportions and plunged into a tank of water,

Scientists use density functional theory to model molecular behaviour, such as how semiconductor particles called quantum dots can convert light into electricity.

Computer modelling methods based on density functional theory predict how molecules will behave. New tools help researchers choose the best method.

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Density functional theory (DFT) is a computer modelling technique that uses the mathematics of quantum mechanics to predict how electrons – the negatively charged particles in atoms and molecules – behave under different conditions.

Modelling this behaviour using other techniques requires prohibitive amounts of computer power. This is a barrier to advances in fields like materials science. DFT methods are popular because the computational costs are lower.

Computational chemists have developed hundreds of DFT methods, but there were no clear guidelines on how to select the best one. Dr Lars Goerigk and his team from the School of Chemistry at the University of Melbourne have developed guidelines that help users to identify the most appropriate DFT method for their needs.

For example, they recommend using DFT methods that take into account the London-dispersion force – a weak force between atoms and molecules. Although the force between individual atoms is negligible, the total forces within molecules can be strong enough to influence their structure, thermochemical properties and how they react with other substances. Many DFT methods that neglect the treatment of such forces remain popular today. The new guidelines help improve on common practice.

The pharmaceutical, energy and manufacturing industries use DFT to understand the chemistry of living things, design efficient ways to make energy, and create new materials. For example, DFT methods are used to predict whether molecules degrade at high temperatures, react with one another, interact with light, or conduct electricity.

The Goerigk group, with Professor Stefan Grimme’s group from the University of Bonn, Germany, has also created a database of reference values for testing the accuracy of DFT methods as they are developed.

Called the GMTKN55 database, it includes reference values for 55 sets of chemical properties and reactions. It is used by research groups worldwide to develop new computational methods.

Next steps

Dr Goerigk’s research group is developing improved DFT methods for predicting how light excites electrons. These methods could be used in photovoltaics – for example, to design more efficient solar cells. They could also be used to discover new organic dyes and light-absorbing materials for industry.


ARC Discovery Early Career Researcher Award

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Goerigk L et al (2017) A look at the Density Functional Theory zoo with the advanced GMTKN55 database for general main group thermochemistry, kinetics and noncovalent interactions. Physical Chemistry Chemical Physics 19: 32184–32215. doi: 10.1039/C7CP04913G

Image: Nbrawand CC BY 4.0

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