Journal of Austrian Chemistry

Journal for the Chemical Industry in Austria

Publication

Chemical data mining boosts search for new organic semiconductors

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Organic semiconductors are lightweight, flexible and easy to manufacture. But they often fail to meet expectations regarding efficiency and stability. Researchers at the Technical University of Munich (TUM) are now deploying data mining approaches to identify promising organic compounds for the electronics of the future.

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.

Both the carbon-based molecular frameworks and the functional groups decisively influence the conductivity of organic semiconductors. | Credit: C. Kunkel / TUM

Together with his team, Karsten Reuter, Professor of Theoretical Chemistry at the Technical University of Munich, is looking for novel substances for photovoltaics applications, as well as for displays and light-emitting diodes – OLEDs. The researchers have set their sights on organic compounds that build on frameworks of carbon atoms.

CONTENDERS FOR THE ELECTRONICS OF TOMORROW

Depending on their structure and composition, these molecules, and the materials formed from them, display a wide variety of physical properties, providing a host of promising candidates for the electronics of the future.

“To date, a major problem has been tracking them down: It takes weeks to months to synthesize, test and optimize new materials in the laboratory,” says Reuter. “Using computational screening, we can accelerate this process immensely.”

COMPUTERS INSTEAD OF TEST TUBES

The researcher needs neither test tubes nor Bunsen burners to search for promising organic semiconductors. Using a powerful computer, he and his team analyze 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.”

ALGORITHMS IDENTIFY KEY PARAMETERS

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 “reorganization 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 analyzed 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.

IDENTIFYING MOLECULES USING ARTIFICIAL INTELLIGENCE

The clusters highlight structural frameworks and functional groups that facilitate favorable 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 Reuter.

Publication

Christian Kunkel, Christoph Schober, Johannes T. Margraf, Karsten Reuter, Harald Oberhofer. Finding the Right Bricks for Molecular Lego: A Data Mining Approach to Organic Semiconductor Design.
in Chem. Mater. 2019, 31, 3, 969-978. DOI: 10.1021/acs.chemmater.8b04436

Scientific Contact

Prof. Dr. Karsten Reuter
Chair of Theoretical Chemistry
Technical University of Munich

Header-Image: First author Christian Kunkel, PD Dr. Harald Oberhofer and Prof. Karsten Reuter (fltr). Credit: A. Battenberg / TUM

Cut flowers: HHU biologists increase longevity

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Valentine’s Day is just around the corner, and 14 February will see huge quantities of cut flowers being bought as a gift. However, not only on this occasion, but also anytime of the year flowers will bring joy into our homes and offices. According to a statistic from the United Nations on imports, the world trade value of cut flowers is roughly USD 4 billion. The main purchasers are Europe (66.7%), the USA (19.3%) and Japan (10.7%). In Germany alone, the average per capita spending on cut flowers and decorative plants amounts to roughly EUR 100 per year.

So it’s important for traders and consumers that these flowers – which are often transported over long distances from where they are grown in Africa and South America – stay fresh for a long time and don’t start to wilt after a few days. The research team of Prof. Dr. Georg Groth from the Institute of Biochemical Plant Physiology at HHU has developed an efficient method for slowing down the wilting process of cut flowers. In the current edition of the journal Scientific Reports, the scientists describe how a synthetic peptide can be used to alter the response of cut flowers to the gaseous plant hormone ethylene substantially.

In recent years, several international research teams have identified the major elements of the ethylene signalling pathway and have determined their molecular functions and downstream interactions. These studies showed that each plant cell perceives the hormone via special receptors. From the receptors the signal is then transmitted via different protein molecules into the cell nucleus, where it triggers the wilting process, known as ‘senescence’. Interaction between the hormone receptors and the downstream ethylene pathway protein EIN2 is essential for the ethylene signalling process. By closing off this interaction signal transfer to the nucleus is disrupted and the wilting process can be delayed.

The research team of Prof. Groth made use of this finding and copied a short sequence from the EIN2 protein consisting of just eight consecutive amino acids. They introduced this sequence to the plant as a synthetic peptide called NOP-1. This peptide blocks the interaction of receptors and EIN2, which ultimately interrupts the transfer of the ethylene signal.
Experiments on different cut flower varieties such as roses and carnations demonstrated the simplicity, effectiveness and sustainability of this approach. NOP-1 is absorbed by the cut flower from the vase water. The biologists in Düsseldorf provide clear evidence on the NOP-1effect to extend the vase life of cut flowers.

Influencing senescence in cut flowers in a targeted manner is not the only application area for NOP-1. Prof. Groth and his group had previously demonstrated that NOP-1 can also inhibit fruit ripening in tomatoes and apples.

The next step now is to identify partners in industry to exploit a potential commercial use of NOP-1. This includes further studies to confirm non-toxicity as well as process development for cost-effective and economic production of NOP-1.

Publication

Claudia Hoppen, Lena Müller, Anna Christina Albrecht and Georg Groth.
The NOP-1 peptide derived from the central regulator of ethylene signaling EIN2 delays floral senescence in cut flowers.
Scientific Reports 9, 1287 (2019). DOI: 10.1038/s41598-018-37571-x

Scientific Contact

Prof. Dr. Georg Groth
Institut für Biochemische Pflanzenphysiologie
Heinrich-Heine-Universität Düsseldorf