Visualizing nanoparticle surface dynamics and instabilities enabled by deep denoising

Peter A. Crozier(Arizona State University), Matan Leibovich(Courant Institute of Mathematical Sciences), Piyush Haluai(Arizona State University), Mai Tan(Arizona State University), Andrew M. Thomas(University of Iowa), Joshua Vincent(Arizona State University), Sreyas Mohan(New York University), Adrià Marcos Morales(New York University), Shreyas A. Kulkarni(New York University), David S. Matteson(Cornell University), Yifan Wang(Arizona State University), Carlos Fernandez‐Granda(Courant Institute of Mathematical Sciences)
Science
February 27, 2025
Cited by 28

Abstract

Materials functionalities may be associated with atomic-level structural dynamics occurring on the millisecond timescale. However, the capability of electron microscopy to image structures with high spatial resolution and millisecond temporal resolution is often limited by poor signal-to-noise ratios. With an unsupervised deep denoising framework, we observed metal nanoparticle surfaces (platinum nanoparticles on cerium oxide) in a gas environment with time resolutions down to 10 milliseconds at a moderate electron dose. On this timescale, many nanoparticle surfaces continuously transition between ordered and disordered configurations. Stress fields can penetrate below the surface, leading to defect formation and destabilization, thus making the nanoparticle fluxional. Combining this unsupervised denoiser with in situ electron microscopy greatly improves spatiotemporal characterization, opening a new window for the exploration of atomic-level structural dynamics in materials.


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