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In a new article published in Computer Physics Communications, the team of the Open Software Services for Classrooms and Research project (OSSCAR) describes how to create custom widgets and extensions that can be used in interactive notebooks to teach computational materials science. The article also introduces two new entries in OSSCAR: a widget to display an interactive periodic table that allows users to group elements into different states, and one to plot and visualize electronic band structures and density of states.

The conversion of solar energy into chemical energy, stored in the form of hydrogen, bears enormous potential as a sustainable fuel for powering emerging technologies. Photoactive oxynitrides are promising materials for splitting water into molecular oxygen and hydrogen. However, one of the issues limiting widespread commercial use of oxynitrides is degradation during operation. While recent studies have shown the loss of nitrogen, its relation to reduced efficiency has not been directly and systematically addressed with experiments. In this study, we demonstrate the impact of the anionic stoichiometry of BaTaO_xN_y on its electronic structure and functional properties. Through experimental ion scattering, electron microscopy, and photoelectron spectroscopy investigations, we determine the anionic composition ranging from the bulk toward the surface of BaTaO_xN_y thin films. This further serves as input for band structure computations modeling the substitutional disorder of the anion sites. Combining our experimental and computational approaches, we reveal the depth-dependent elemental composition of oxynitride films, resulting in downward band bending and the loss of semiconducting character toward the surface. Extending beyond idealized systems, we demonstrate the relation between the electronic properties of real oxynitride photoanodes and their performance, providing guidelines for engineering highly efficient photoelectrodes and photocatalysts for clean hydrogen production.

In a collaboration between PSI and the Zurich University of Applied Sciences, a sample position tracking setup based on a computer vision algorithm was developed to automatically track the sample position. A factor of ten improvement on the overlap between consecutive x-ray absorption spectra was obtained when the automatic sample tracking was used.

Artificial intelligence (AI) is accelerating the development of new materials. A prerequisite for AI in materials research is large-scale use and exchange of data on materials, which is facilitated by a broad international standard. A major international collaboration including researchers from the LMS laboratory now presents an extended version of the OPTIMADE standard.