Dresden 2026 – wissenschaftliches Programm

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CPP: Fachverband Chemische Physik und Polymerphysik

CPP 9: French-German Session: Simulation Methods and Modeling of Soft Matter I

CPP 9.3: Vortrag

Montag, 9. März 2026, 15:45–16:00, ZEU/LICH

Fluctuating Solvent Fields and Vibrational Shifts Revealed by Machine Learned Force Fields — •Florian Brünig and Alexandre Tkatchenko — Department of Physics and Materials Science, University of Luxembourg, Luxembourg

Fluctuating solvent fields is one of the driving mechanism behind vibrational shifts observed in solvatochromic experiments [1]. Previously, experimental infrared spectra have been correlated with mean electric fields obtained from empirical force field molecular dynamics simulations [2]. However, vibrational dynamics of these force fields are insufficient to reproduce the experimental line shape properties.

Here, machine learned force fields (MLFFs) offer multiple opportunities: they are highly accurate, efficient, and can be interpretable if based on physical models. We explore the capabilities of modeling solvatochromism of vibrational probes in solvent and protein environments employing the SO3LR [3] MLFF. SO3LR combines the SO3krates architecture with pairwise analytical electrostatic and dispersion potentials in the long range, and was pretrained on a diverse data set of molecular complexes. We show how fluctuating solvent electrostatic and dispersion fields can be related to vibrational bands in a self consistent manner due to the versatility of MLFFs.

[1] Brünig, FN, Netz, RR, et al. JPCB 126, 1579 (2022).

[2] Weaver, JB, Kozuch, J, Kirsh, JM & Boxer, SG. JACS 144, 7562 (2022).

[3] Kabylda, A, Frank, JT, Müller, KR, Tkatchenko A, et al. JACS 147, 33723 (2025).

Keywords: Infrared Spectroscopy; Liquids; Machine Learned Force Fields; Molecular Dynamics; Electric Fields