Speaker
Description
Quantum corrals are of particular interest in surface science as they can be used to investigate quantum phenomena, such as quantum mirage (1) or function as quantum simulators that mirror the electronic properties of real atoms or molecules (2).
Currently, investigating these prominent structures requires researchers to manually assemble the objects on a surface using atomic manipulation techniques, a process that is extremely time-consuming. Our work aims to solve this critical bottleneck and save valuable research time.
A primary goal of our project is to create an instrument for automatic and autonomous atomic manipulation. We are developing this system using machine learning algorithms to enable the careful, precise positioning of atoms or molecules (3). This novel instrument will facilitate the assembly of large-scale objects or complex compositions of multiple smaller ones with high precision, thereby enabling the collection of significantly more data.
In this work, we our current status of assembled quantum corrals on noble metal surfaces. First results of manually assembled nanostructures will be presented together with the computational algorithm in the automated construction.
(1) Li, Q., Li, X., Miao, B. et al. Kondo-free mirages in elliptical quantum corrals. Nat Commun 11, 1400 (2020)
(2) E. Sierda et al., Quantum simulator to emulate lower-dimensional molecular structure. Science 380, 1048-1052 (2023)
(3) B. Ramsauer, G. J. Simpson, J. J. Cartus, A. Jeindl, V. García-López, J. M. Tour, L. Grill and O. T. Hofmann, Autonomous single-molecule manipulation based on reinforcement learning, Journal of Physical Chemistry A 127, 2041 (2023)