Girls on Tour at the Long Night of Science: Be there!
Self-soldered Earrings © HZB
Are you a 10th to 13th grade student interested in mathematics and science? Then secure your free VIP ticket for a tour with exciting experiments and insights during the Long Night of Science! Meet female scientists who are passionate about making our world a better place! 17.06. , from 5.30 pm, Adlershof Research Campus.
Come along on a discovery tour and get to know interesting research labs that are otherwise closed. At the Helmholtz-Zentrum Berlin you will take part in a workshop and make earrings out of colourful LEDs with a soldering iron. You'll also learn why female mechatronics engineers should love one thing: tinkering and being creative.
The tour also takes you to Humboldt University and the Federal Institute for Materials Research and Testing. Learn about renewable energies and nano-optics or take a heat selfie. Join us and immerse yourself in the world of science for an evening!
When and Where?
- 17.06.2023, from 5:30p.m. to 9:30p.m.
- Adlershof Research Campus, Start: at HZB - End: IGAFA
- in German
- Participation is free of charge (ticket for the Long Night of Science is not required)
Register now!
Please register by 12 June 2023 at igafa@igafa.de
- 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.