University of Freiburg
Institute of Physics
Statistical Physics of Soft Matter and Complex Systems
Numerical search for free energy minima of acene clusters
This research project is about the exploration of different computational optimization techniques. We tackle the minimization problems in two complementary ways: The first method is to perform basin-hopping Monte Carlo simulations in which local minimizations and Monte Carlo steps are alternating. In the second approach we use Bayesian optimization based on Gaussian Process regression. The goal of this is not only to find minima in the potentials but to speed up the Monte Carlo simulations as well.
The systems that we look into are clusters of Acene molecules, chains of merged benzene rings. These molecules are considered as promising materials for high performance organic semiconductors, solar cells and light emitting diodes. To describe these systems we use classical force fields.
The research is done in a collaboration between the groups of Prof. T. Schilling and
Prof. R. Krems.
• Force Fields: C. Pramanik et al., ACS Nano, 11 (12), 12805–12816 (2017)
• Basin-hopping: D. Wales., Ann. Rev. Phys. Chem. 69, 401-425 (2018)
• Molecular clusters: M. Mravlak et al., J. Chem. Phys. 145 (2), 024302 (2016)
• Spectroscopy of tetracene clusters: M. Mitsui et al., J. Phys. Chem. A 111 (39),
• Machine learning on improving force fields: K. Asnaashari and R. Krems, Mach.
Learn.: Sci. & Technol. 3 (1), 015005 (2021)