FURI | Spring 2025
Improving Event Detection of Pt Nanoparticle Surfaces Through the Quantification of Fluxionality Using Image Processing

Characterizing surface dynamic behavior of Pt nanoparticles may be important for understanding catalytic performance because atomic-level structural fluctuations at the surface may impact the reaction process. Such events can be observed by recording nanoparticle movies with a transmission electron microscope (TEM). By applying a computer vision technique called blob detection, it is possible to characterize surface dynamics by detecting and counting the number of atomic columns through time, giving a quantitative metric on surface fluxionality. Further data normalization techniques provide an interpretation of how the Pt particle surface fluctuates and a more comprehensive view of Pt nanoparticle structural dynamics.
Student researcher
Lucas Anton Hardesty
Materials science and engineering
Hometown: Prescott Valley, Arizona, United States
Graduation date: Spring 2027