NAT 03 - data processing

Understanding nanoscale dynamics under the STM by advanced data processing

NAT - Chemical Engineering

Physical Chemistry

Physical Chemistry

Chemical EngineeringChemistryComputer Science/ InformaticsPhysics

Participation also possible online only:

Planned project location:

Department of Chemistry, Garching

PD Dr.

Friedrich

Esch

friedrich.esch@tum.de

+498928913286

Prof. Dr.

Barbara

Lechner

bajlechner@tum.de

+498928913436

Our group investigates dynamic processes on surfaces of functional nanomaterials. In heterogeneous catalysis, for example, metallic clusters or nanoparticles as well as their oxide supports are typically highly dynamic during an ongoing chemical reaction: their structure and chemical composition change continuously during a reaction. Indeed, the high dynamic structural fluxionality of clusters is often what makes them such excellent catalysts, but dynamics can also decrease durability. We use state-of-the-art scanning tunneling microscopy (STM) to obtain video-rate movies of such dynamically changing surfaces, correlate structural changes with reactivity and even follow individual diffusing particles with sub-Å resolution. This is possible thanks to an electronics module which we have developed to speed up our (and other groups’) microscopes. These time-dependent measurements work in various reaction atmospheres, from gas phase to vacuum, from liquids to electrochemical conditions. The challenge lies in reconstructing the recorded data into high-quality movies, images and/or diffusion traces to answer scientific questions like: Do clusters diffuse by rolling, sliding or fluxional reconstruction? How can structural dynamics be controlled, e.g. by introducing specific surface defects or adapting the reaction environment? Can we observe catalytic reaction cycles on single active sites of model catalysts?

During your summer internship in our group, you will work on improving and expanding the existing Python software package PyfastSPM and be involved in analyzing newly measured dynamics data. This can involve writing new modules for a quantitative analysis of movies and tracked diffusion paths, to assign signal fluctuations to reaction intermediates, or to develop clever ways to extract hidden information with sub-Å structural precision by correcting for experimental artefacts. You will be integrated in the research group and discuss strategies and progress, while at the same time being responsible for your own project. You will further have the opportunity to participate in the STM measurements producing the data, so you get a full picture of the measurement and analysis challenges at hand.

40

3 years of bachelor studies completed

Programming skills in Python are required. Interest in state-of-the-art experiments at the boundary between chemistry and physics is advantageous.

Enthusiasm for working with experimental data by sophisticated data processing. Team player.