Computer vision in fast scanning probe microscopy
|Betreuer||Dr.-Ing. Mohammadreza Babaee
Tel.: +49 (0)89 289-28543
Dr. Barbara Lechner & PD Dr. Friedrich Esch, Dept. Chemistry, TUM
|Beschreibung||We recently achieved scan frequencies in scanning probe microscopes (SPM) two to three orders of magnitude higher than in conventional experiments, allowing us to follow surface diffusion, adsorption and reactions in situ with atomic resolution. Detecting different chemical species and tracking their motion between frames is key to analyzing the movies quantitatively, e.g. to extract diffusion constants, activation barriers and diffusion traces.
We are interested in tracking particles observed in the images of recent and ongoing experiments of reactions on Pt clusters on magnetite (our model catalyst surface). Particular challenges involve: identifying particles of different shape which cannot be separated by apparent height (see Figure); detecting them under measurement noise (‘streaks’); tracking motion of particles that can cross paths and appear and disappear (e.g. by exchange with the bulk); and overlaying the motion onto a grid representing the atomic structure of the surface. You will create a modular, easily expandable and well-documented data analysis software package.
|Voraussetzung||Knowledge of Python 3, computer vision and machine learning is a prerequisite.|
|Bewerbung||If you are interested in this topic, we welcome the applications via the email address above. Please set the email subject to “<Type of application> application for topic 'XYZ'”, ex. “Master’s thesis application for topic 'XYZ'”, while clearly specifying why are you interested in the topic in the text of the message. Also make sure to attach your most recent CV (if you have one) and grade report.|