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Leonhard Grill

Leonhard Grill

University of Graz, Austria

Title: Manipulation of single molecules at surfaces: switches, wires and motors

Biography

Biography: Leonhard Grill

Abstract

Molecular nanotechnology aims to use functional molecules as individual machines or electronic devices. Hence, their selfassembly into pre-defined architectures and the full control over each individual molecule are key objectives. Various examples of functional molecules, ranging from molecular wires to molecular switches and machines that are studied and manipulated at the single-molecule level by scanning tunneling microscopy (STM) under ultrahigh vacuum conditions, will be discussed in this presentation. Molecular wires or molecular nodes with different conjugation pathways can be fabricated from specifically designed molecular building blocks that are connected to two-dimensional networks or one-dimensional chains. In the case of molecular switches, the switching rate can be tuned up and down by only one single atom in the vicinity of the molecule. The same effect is then extended to molecular assemblies where cooperative effects in single molecules are directly observed. The switching process can also be used to trigger a molecular motor where the lateral translation of molecular machines on a surface can be enhanced by light of specific wavelengths that match the absorption properties of the molecule. By comparing molecules with and without a motor unit, the enhanced motion can be directly assigned to the motor that is incorporated in the molecules. STM manipulation gives detailed insight into the physical and chemical processes at the single-molecule level by varying the relevant parameters as tip height over the surface, bias voltage or tunneling current. While the speed is typically of minor importance in these experiments, it becomes crucial when studying so-called nanocars. By implementing a dipole moment into the molecular structure, we could show that very efficient and therefore fast manipulation can be realized. The key property is that no continuous imaging is required, rendering the manipulation fast enough to win the first nanocars race.