Biography
Raised in the Ruhr area in the western part of Germany, Christoph studied Chemistry in Bochum obtaining his PhD in 2019. He got around a bit during that time for various exchanges and research visits to Glasgow, Stanford University, and the ENS in Paris.
After completing his PhD, he moved to London as a post-doctoral research fellow in 2020 before transitioning to Cambridge working on machine learning to understand complex aqueous systems.
He is an active member of the management team of the Lennard-Jones Centre, which brings together the molecular and materials modelling community in Cambridge.
In his spare time he enjoys brewing coffee and beer as well as getting beaten by 11-year-olds in Parkruns.
CV Positions:
- University Assistant Professor, Department of Physics, University of Cambridge
- Postdoctoral Research Fellow in the group of Prof. Angelos Michaelides, University of Cambridge & University College London (2020-2023)
- Postdoctoral Researcher in the group of Dr. Ondrej Marsalek, Charles University Prague (2019)
- PhD in Theoretical Chemistry, Ruhr-University Bochum in the group of Prof. Dominik Marx (2016-2019)
- Bachelor (2013) & Master (2015) of Science in Chemistry, Ruhr-University Bochum, Germany
Research
We are a group of computational scientists fascinated by the study of challenging materials, mostly involving water, by means of computational methods. In recent time, we primarily focus on developing machine learning potentials in order to provide insight into complex aqueous systems, for which accurate and efficient representations of potential energy surfaces are urgently needed. Examples of this are the exploration of the behaviour of water at interfaces, or confined in nanotubes and nanochannels, the mechanistic details of ion dissolution and proton transfer in water, as well as the interplay of CO2 and aqueous solutions.
Publications
- V. Kapil, C. Schran, A. Zen, J. Chen, C. J. Pickard, A. Michaelides. The first-principles phase diagram of monolayer nanoconfined water. Nature, 2022, 609, 512-516
- F. L. Thiemann, C. Schran, P. Rowe, E. A. Müller, A. Michaelides. Water Flow in Single-Wall Nanotubes: Oxygen Makes It Slip, Hydrogen Makes It Stick. ACS Nano, 2022, 16 (7), 10775-10782
- C. Schran, F. L. Thiemann*, P. Rowe*, E. A. Müller, O. Marsalek, A. Michaelides. Machine learning potentials for complex aqueous systems made simple. Proc. Nat. Acad. Sci., 2021, 118 (38), e2110077118
- C. Schran, K. Brezina, O. Marsalek. Committee neural network potentials control generalization errors and enable active learning. J. Chem. Phys., 2020, 153 (10), 104105
- C. Schran, J. Behler, D. Marx. Automated Fitting of Neural Network Potentials at Coupled Cluster Accuracy: Protonated Water Clusters as Testing Ground. J. Chem. Theory Comput., 2020, 16 (1), 88-99
