Dresden 2026 – scientific programme

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O: Fachverband Oberflächenphysik

O 61: Organic molecules on inorganic substrates: electronic, optical and other properties II

O 61.10: Talk

Wednesday, March 11, 2026, 17:15–17:30, HSZ/0201

Unveiling the precise configuration of a molecular junction — Joshua Scheidt^1,3, Jonas Lederer³, Mong-Wen Gu^1,2, Hadi Arefi^1,2, Jose M. Guevara^1,2, Amin Karimi^1,2, Rustem Bolat^1,2, Marvin Knol^1,2, Klaus-Robert Müller³, F. Stefan Tautz^1,2, and •Christian Wagner^1,2 — ¹PGI-3, Forschungszentrum Jülich, Germany — ²JARA, Fundamentals of Future Information Technology, Germany — ³Institut für Softwaretechnik und Theoretische Informatik, Technische Universität Berlin, Germany

Exploring structure-property relationships of molecular junctions is crucial for future single-molecule applications. While, e.g., a strong scattering of conductance values is found in break-junctions, the responsible structural variations cannot be identified. Here, we describe NC-AFM/STM-based two-contact manipulation experiments on PTCDA (3,4,9,10-perylene-tetracarboxylic dianhydride) on Ag(111) and analyze them using a DFT-based machine learning model of the junction. Our approach allows solving the inverse problem of configuration identification from force gradient data[1] and reveals the origin of the 3-4 fold conductance variations observed upon sub-Angstrom changes in the junction geometry.

[1] J. Scheidt et al., J. Phys. Chem. C 127, 13817 (2023)

Keywords: STM; molecular manipulation; PTCDA; machine learning; molecular electronics