V. Zaverkin, D. Holzmüller, L. Bonfirraro, and J. Kästner. Dataset, (2023)Related to: Viktor Zaverkin, David Holzmüller, Luca Bonfirraro, Johannes Kästner. Transfer learning for chemically accurate interatomic neural network potentials, Phys. Chem. Chem. Phys., 2023, 25, 5383-5396. doi: 10.1039/D2CP05793J.
S. Klostermann, and J. Kästner. Dataset, (2023)Related to: Marc Schnierle, Sina Klostermann, Elif Kaya, Zheng Li, Daniel Dittmann, Carolin Rieg, Deven P. Estes, Johannes Kästner, Mark R. Ringenberg, and Michael Dyballa. How Solid Surfaces Control Stability and Interactions of Supported Cationic Cu^I(dppf) Complexes - A Solid-State NMR Study. Inorg. Chem. 2023, 62, 19, 7283-7295. doi: 10.1021/acs.inorgchem.3c00351.
D. Holzmüller, V. Zaverkin, J. Kästner, and I. Steinwart. Software, (2023)Related to: David Holzmüller, Viktor Zaverkin, Johannes Kästner, and Ingo Steinwart. A Framework and Benchmark for Deep Batch Active Learning for Regression, 2023. arXiv: 2203.09410.
K. Gugeler, and J. Kästner. Dataset, (2023)Related to: Carolin Rieg, Manuel Kirchhof, Katrin Gugeler, Ann-Katrin Beurer, Lukas Stein, Klaus Dirnberger, Wolfgang Frey, Johanna R. Bruckner, Yvonne Traa, Johannes Kästner, Sabine Ludwigs, Sabine Laschat and Michael Dyballa. Determination of accessibility and spatial distribution of chiral Rh diene complexes immobilized on SBA-15 via phosphine-based solid-state NMR probe molecules. Catal. Sci. Technol. 13, 410-425, 2023. doi: 10.1039/d2cy01578a.