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O: Fachverband Oberflächenphysik

O 8: Focus Session Molecular Nanostructures on Surfaces: On-Surface Synthesis and Single-Molecule Manipulation I

O 8.1: Hauptvortrag

Montag, 17. März 2025, 10:30–11:00, H24

Chiral reactions at surfaces elucidated by machine learning and enhanced sampling — Raymond Amador¹, Enrico Trizio², Peilin Kang², Umberto Raucci², Hannah Bertschi¹, Marcella Iannuzzi³, Jacob Wright¹, Roland Widmer¹, Oliver Gröning¹, Michele Parrinello², and •Daniele Passerone¹ — ¹Empa, Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, Switzerland — ²Italian Institute of Technology, Genova, Italy — ³Department of Chemistry, University of Zurich, Switzerland

Experiments performed at the surface of the chiral intermetallic compound PdGa unleash a fascinating surface chemistry phenomenology including regioselectivity and enantioselectivity, in which the energetics is dominated by mid-range dispersive molecular interactions with the substrate. The corresponding modelling of chiral and prochiral adsorption and reactions requires both a high level of electronic structure theory and an appropriate statistical sampling of the reactants, transition state and products ensemble. We show that machine learning potentials based on DFT molecular dynamics trajectories and recently introduced enhanced sampling techniques allow to describe both the thermodynamics and the kinetics of reactions investigated in the laboratories next-door, such as an Orito-like reaction catalysed by PdGa. Moreover, we study a chirality switching of a bianthracene molecule by applying a method introduced by some of us, based on the committor function and the variational principle that it obeys: its minimum uses a self-consistent procedure that starts from information limited to the initial and final states and reveals the transition state ensemble.

Keywords: Enhanced sampling; Machine learning potentials; Molecular dynamics; Enantioselectivity