A team involving UniSysCat group leader Tobias Gensch presents kraken, a new database employing machine learning methods to predict properties of new ligands for catalysis.
A UniSysCat team around Prof. Beatriz Roldan Cuenya applied electron microscopy to track the dynamic evolution of copper catalysts in real-time under reaction conditions.
Artificial Intelligence decodes catalyst performance based on "materials genes of catalysis" which encode crucial material properties. Researchers from NOMAD, FHI Berlin and BasCat have proposed a new approach for modeling…
With ultrashort X-ray laser pulses, a research team involving the UniSysCat groups of Athina Zouni & Holger Dobbek gained important new insights into the function of photosystem II, a key catalytic system in photosynthesis.
Two recent interdisciplinary UniSysCat publications shed light on the importance of protonation on the functionality and reactivity of molecular compounds relevant in chemistry and biology.
UniSysCat researchers Shuang Li and Arne Thomas present highly active single-atom catalysts based on inexpensive and durable materials. Their approach is a great step towards more efficient electrochemical water splitting.
The three top articles published in Angewandte Chemie report sophisticated studies of reaction intermediates important in biocatalytic processes involving metalloenzymes.
Four UniSysCat groups and one Einstein visiting fellow applied in a proof of concept study a new experimental setup for the characterization of reaction intermediates in [NiFe] hydrogenase, which was chosen as hot paper.
