| 2022 | Richard Beckmann, Fabien Brieuc, Christoph Schran, Dominik Marx: Infrared Spectra at Coupled Cluster Accuracy from Neural Network Representations. In: J. Chem. Theory Comput., 18, 2022, 5492–5501 |
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| 2022 | Laura DuránCaballero, Christoph Schran, Fabien Brieuc, Dominik Marx: Neural network interaction potentials for para-hydrogen with flexible molecules. In: The Journal of Chemical Physics, 7, 2022, 074302 |
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| 2022 | Venkat Kapil, Christoph Schran, Andrea Zen, Ji Chen, Chris J Pickard, Angelos Michaelides: The first-principles phase diagram of monolayer nanoconfined water. In: Nature, 609, 2022, 512–516 |
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| 2022 | Nick Clark, Daniel J. Kelly, Mingwei Zhou, Yi-Chao Zou, Chang Woo Myung, David G. Hopkinson, Christoph Schran, Angelos Michaelides, Roman Gorbachev, Sarah J. Haigh: Tracking single adatoms in liquid in a Transmission Electron Microscope. In: Nature, 2022, |
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| 2022 | Fabian L. Thiemann, Christoph Schran, Patrick Rowe, Erich A. Müller, and Angelos Michaelides: Water Flow in Single-Wall Nanotubes: Oxygen Makes It Slip, Hydrogen Makes It Stick. In: ACS Nano, 16, 2022, 10775–10782 |
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| 2021 | Schran, Christoph and Thiemann, Fabian L. and Rowe, Patrick and Müller, Erich A. and Marsalek, Ondrej and Michaelides, Angelos: Machine learning potentials for complex aqueous systems made simple. In: Proc. Natl. Acad. Sci., 118, 2021, e2110077118 |
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| 2021 | Schran, Christoph and Brieuc, Fabien and Marx, Dominik: Transferability of machine learning potentials: Protonated water neural network potential applied to the protonated water hexamer. In: J. Chem. Phys., 154, 2021, 051101 |
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| 2020 | Schran, Christoph and Brezina, Krystof and Marsalek, Ondrej: Committee neural network potentials control generalization errors and enable active learning. In: J. Chem. Phys., 153, 2020, 104105 |
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