 | Brigitta Bachmair University of Vienna Institute of Theoretical Chemistry Währinger Str. 17 1090 Vienna Austria brigitta.bachmair@univie.ac.at +43 1 4277 52767 / 73290 ORCID: 0000-0002-2346-7995 |
| Focus Area |
| In our research, we develop methods for sampling pathways of chemical reactions that are initiated by the absorption of light. In particular, we investigate reactions that include rare events, which makes them occur infrequently on microscopic scale and thus it is challenging to simulate them. Our work aims at overcoming this issue by efficiently combining path sampling techniques for excited states and machine learning approaches with nonadiabatic chemical dynamics simulations. This project is part of the research platform ViRAPID. |
| Publications |
Excited-state Nonadiabatic Dynamics in Explicit Solvent Using Machine Learned Interatomic Potentials Digital Discovery 4, 1478-1491, (2025), DOI: 10.1039/D5DD00044K M. Tiefenbacher, B. Bachmair, C. Cheng-Giuseppe, J. Westermayr, P. Marquetand, J. Dietschreit, L. González Revisiting the Intricate Photodissociation Mechanism of Ammonia along the Minor NH + H2 Pathway Phys. Chem. Chem. Phys. 27, 8212-8220, (2025), DOI: 10.1039/D4CP04834B 3. S. Polonius, O. Zhuravel, B. Bachmair, S. Mai LVC/MM: A Hybrid Linear Vibronic Coupling/Molecular Mechanics Model with Distributed Multipole Electrostatic Embedding for Highly Efficient Surface Hopping Dynamics in Solution J. Chem. Theory Comput. 19, 7171-7186, (2023), DOI: 10.1021/acs.jctc.3c00805 2. M. M. Reiner, B. Bachmair, M. Tiefenbacher, S. Mai, L. González, P. Marquetand, C. Dellago Nonadiabatic Forward Flux Sampling for Excited-State Rare Events J. Chem. Theory Comput. 19, 1657–1671, (2023), DOI: 10.1021/acs.jctc.2c01088 M. M. Reiner, B. Bachmair, M. Tiefenbacher, S. Mai, L. González, P. Marquetand, C. Dellago
Recent Advances in Machine Learning for Electronic Excited State Molecular Dynamics Simulations SPR Chemical Modelling 17, 178-200, (2022), DOI: 10.1039/9781839169342-00178 |