Priority programme for topological insulators begins second funding period
Applicants for support funds to conduct research on topological insulators met at HZB Adlershof on February 15th and 16th. This meeting dealt with the second period of funding for the SPP 1666 Priority programme of the German Research Foundation (DFG) that runs from mid-2016 to 2019. Researchers from across Germany contribute their specific expertise and work together in these Priority programmes (SPPs).
Germany holds a very strong position in the field, in particular through the pioneering work of Laurens Molenkamp from Universität Würzburg, considered by a number of experts in this field as a candidate for the Nobel Prize. Research teams presented a total of 56 projects, of which 37 were recommended for approval. The selection was made by a review committee of international experts.
We are pleased about numerous approved projects on the dynamics of topological insulators – an important area of work at HZB.
For further information: www.helmholtz-berlin.de/topins
- Ultrafast demagnetisation - Thinner iron, stronger effectThe thinner an iron film, the more easily it can be demagnetised by a laser pulse. Researchers at the University of Duisburg-Essen, working with Helmholtz-Zentrum Berlin and other partners, have discovered why: the key lies in the magnetic order at the material's interfaces. In the long term, these findings could contribute to the development of new technologies for magnetic data storage. The results have been published in the scientific journal Advanced Science.
- Blind spot for the arrangement of atomsArtificial intelligence is increasingly being used to predict the properties of new materials. A research team from Jena and the United States now shows in a study published in the journal Nature Computational Science that when language models are used for this purpose, they reliably identify which types of atoms a material contains. However, they make insufficient use of information about how those atoms are arranged in space. Neither larger models nor additional training data resolve this weakness. For material properties that depend strongly on structure, AI models specifically designed to process spatial relationships are therefore the more reliable choice. (DOI: 10.1038/s43588-026-01045-2)
- Patterns of polar vortices in lead-free superlattices on siliconA team at HZB has, for the first time, reported polar vortices in (BaTiO3/SrTiO3)10 superlattices on silicon. These results expand the range of materials and substrates on which polar topological textures can occur and open up new options for incorporating complex ferroelectric states into silicon-based technologies.