Jang, K.; Kim, M.-Y.; Jung, C.; Kim, S.-H.; Choi, D.; Park, S.-C.; Scheu, C.; Choi, P.-P.: Direct Observation of Trace Elements in Barium Titanate of Multilayer Ceramic Capacitors Using Atom Probe Tomography. Microscopy and Microanalysis 30 (6), pp. 1047 - 1056 (2024)
Cheraparambil, H.; Vega-Paredes, M.; Scheu, C.; Weidenthaler, C.: Unraveling the Evolution of Dynamic Active Sites of LaNixFe1-xO3 Catalysts During OER. ACS Applied Materials & Interfaces 16 (17), pp. 21997 - 22006 (2024)
Knezevic, M.; Hoang, T.-H.; Wang, C.; Johar, M.; Manjón, A. G.; Rauret, D. L.; Scheu, C.; Erard, M.; Berardan, D.; Arbiol, J.et al.; Colbeau-Justin, C.; Ghazzal, M. N.: Amplified Photoluminescence of CsPbX3 Perovskites Confined in Silica Film with a Chiral Nematic Structure. Advanced Materials Interfaces 11 (3), 2300636 (2024)
Vega-Paredes, M.; Scheu, C.; Aymerich Armengol, R.: Expanding the Potential of Identical Location Scanning Transmission Electron Microscopy for Gas Evolving Reactions: Stability of Rhenium Molybdenum Disulfide Nanocatalysts for Hydrogen Evolution Reaction. ACS Applied Materials and Interfaces 15 (40), pp. 46895 - 46901 (2023)
Jung, C.; Zhang, S.; Cheng, N.; Scheu, C.; Yi, S.-H.; Choi, P.-P.: Effect of Heat Treatment Temperature on the Crystallization Behavior and Microstructural Evolution of Amorphous NbCo1.1Sn. ACS Applied Materials and Interfaces 15 (39), pp. 46064 - 46073 (2023)
New machine learning framework makes metal recycling more sustainable without compromising on mechanical properties. Results now published in journal Science Advances.
Scientists of the Max-Planck-Institut für Eisenforschung pioneer new machine learning model for corrosion-resistant alloy design. Their results are now published in the journal Science Advances
In order to prepare raw data from scanning transmission electron microscopy for analysis, pattern detection algorithms are developed that allow to identify automatically higher-order feature such as crystalline grains, lattice defects, etc. from atomically resolved measurements.
The general success of large language models (LLM) raises the question if they could be applied to accelerate materials science research and to discover novel sustainable materials. Especially, interdisciplinary research fields including materials science benefit from the LLMs capability to construct a tokenized vector representation of a large…