Quantitative Mapping of Nanoscale Chemical Dynamics in Sub‐Sampled Operando (S)TEM Images using Spatio‐Temporal Analytics. Issue 14 (15th May 2018)

• Record Type: Journal Article
• Authors: Stanfill, Bryan A.; Reehl, Sarah M.; Johnson, Margaret C.; Browning, Nigel D.; Mehdi, B. Layla; Caragea, Petruta C.; Bramer, Lisa M.
• Is Part Of: ChemCatChem. Volume 10:Issue 14(2018)
• Page Start: 3115
• Page End: 3120
• Publication Date: 2018-05-15
• Subjects: batteries -- Gaussian mixture model -- lithium -- nanoparticles -- silver; Catalysis -- Periodicals; 541.39505
• DOI: 10.1002/cctc.201800333
• Languages: English
• ISSNs: 1867-3880

Abstract

Abstract: One of the main limitations in the use of operando scanning transmission electron microscopes to study dynamic chemical processes is the effect of the electron beam on the kinetics of the reaction being observed. Here we demonstrate that a flexible Gaussian mixture model can be used to extract quantitative information directly from sub‐sampled images, that is, images in which not all the pixels in the image are illuminated with the beam. The use of this method is demonstrated on the growth of silver (Ag) nanoparticles in an aqueous solution and the charge/discharge cycle of a lithium battery. In both videos, the imaged chemical reactions can be accurately quantified for sub‐sampling levels down to 1 %. In addition, our analysis of the Ag nucleation video sheds new light on the interplay between heterogeneous and homogeneous nucleation dynamics. Performing operando imaging using a small fraction of the pixels means that the observations can significantly reduce the effect of the beam, automatically increase the imaging speed and decrease the total data transfer rate required. Such new software capabilities offer the potential to significantly widen the application of operando hardware approaches to study nanoscale dynamics in materials. Abstract : Getting a lot of out a little : A major limitation of using operando (S)TEM to study dynamic chemical processes is the effect of the electron beam on the kinetics of the reaction being observed. We propose a new analytics method that can accurately quantify chemical reactions when as little as 1 % of image is sampled. This new software capability offers the potential to significantly widen the application of operando hardware approaches to study nanoscale dynamics in materials.