Producing traditional solar cells made of silicon is very energy intensive. On top of that, they are rigid and brittle. Organic semiconductor materials, on the other hand, are flexible and lightweight. They would be a promising alternative, if only their efficiency and stability were on par with traditional cells.
The researchers have set their sights on organic compounds that build on frameworks of carbon atoms.
Depending on their structure and composition, these molecules, and the materials formed from them, display a variety of physical properties that are promising candidates for the electronics of the future.
"To date, a major problem has been tracking them down: It takes weeks to months to synthesise, test and optimise new materials in the laboratory," says Prof Reuter. "Using computational screening, we can accelerate this process immensely."
The researcher needs neither test tubes nor Bunsen burners to search for promising organic semiconductors. Using a powerful computer, he and his team analyse existing databases. This virtual search for relationships and patterns is known as data mining.
"Knowing what you are looking for is crucial in data mining," says PD Dr. Harald Oberhofer, who heads the project. "In our case, it is electrical conductivity. High conductivity ensures, for example, that a lot of current flows in photovoltaic cells when sunlight excites the molecules."
Using his algorithms, he can search for very specific physical parameters: An important one is, for example, the "coupling parameter." The larger it is, the faster electrons move from one molecule to the next.
A further parameter is the "reorganisation energy": It defines how costly it is for a molecule to adapt its structure to the new charge following a charge transfer - the less energy required, the better the conductivity.
The research team analysed the structural data of 64,000 organic compounds using the algorithms and grouped them into clusters. The result: Both the carbon-based molecular frameworks and the "functional groups", i.e. the compounds attached laterally to the central framework, decisively influence the conductivity.
The clusters highlight structural frameworks and functional groups that facilitate favourable charge transport, making them particularly suitable for the development of electronic components.
"We can now use this to not only predict the properties of a molecule, but using artificial intelligence we can also design new compounds in which both the structural framework and the functional groups promise very good conductivity," explains Prof. Reuter.