Summary
I am a postdoc between the Yusuf Hamied Department of Chemistry at the University of Cambridge the Department of Chemical Engineering at Imperial College London working with Angelos Michaelides and Erich A. Müller. While my research focuses on the exploitation of machine learning to accurately mimic the atomic interactions of interfacial systems, I am also generally interested in various other fields ranging from fundamentals such as solid state physics and quantum chemistry to application-oriented research in the field of membranes and environmental engineering.
Biography
10/2018 - 03/2022 |
PhD in Physics University College London / University of Cambridge/ Imperial College London, UK. Topic: "Properties of Low-dimensional Materials Explored with Machine Learning Potentials". |
| 11/2017 - 05/2018 |
Visiting Researcher, Imperial College London, UK. Topic: "Modelling oxygenated compounds using the SAFT-γ Mie framework". |
| 05/2017 - 09/2017 |
Intern Reaction Engineering, BASF SE, Ludwigshafen, Germany. |
| 10/2015 - 05/2018 |
MSc in Process Engineering, University of Stuttgart, Germany. |
| 09/2013 - 02/2014 | Semester abroad, Tongji University, China. |
| 10/2011 - 09/2015 | BSc in Environ. Engineering, Technical University of Darmstadt, Germany. |
Publications
Journals
Muller E, Schran C, Thiemann F, et al., 2021, Machine learning potentials for complex aqueous systems made simple, Proceedings of the National Academy of Sciences of Usa, Vol:38, ISSN:0027-8424, Pages:1-8
Muller E, Thiemann F, Rowe P, et al., 2021, Defect-dependent corrugation in graphene, Acs Nano Letters, Vol:21, ISSN:1936-0851, Pages:8143-8150
Thiemann F, Rowe P, Muller E, et al., 2020, A machine learning potential for hexagonal boron nitride applied to thermally and mechanically induced rippling, The Journal of Physical Chemistry C: Energy Conversion and Storage, Optical and Electronic Devices, Interfaces, Nanomaterials, and Hard Matter, Vol:124, ISSN:1932-7447, Pages:22278-22290