Correlating electrochemical stimulus to structural change in liquid electron microscopy videos using the structural dissimilarity metric.

Autor: Mulvey JT; Department of Material Science and Engineering, University of California-Irvine, Irvine, CA 92697, USA. Electronic address: mulveyj@uci.edu., Iyer KP; Department of Material Science and Engineering, University of California-Irvine, Irvine, CA 92697, USA., Ortega T; Department of Electrical Engineering and Computer Science, University of California-Irvine, Irvine, CA 92697, USA., Merham JG; Department of Chemistry, University of California, California-Irvine, Irvine, CA 92697, USA., Pivak Y; DENSsolutions B.V., Informaticalaan 12, 2628 ZD Delft, the Netherlands., Sun H; DENSsolutions B.V., Informaticalaan 12, 2628 ZD Delft, the Netherlands., Hochbaum AI; Department of Material Science and Engineering, University of California-Irvine, Irvine, CA 92697, USA; Department of Chemistry, University of California, California-Irvine, Irvine, CA 92697, USA; Department of Chemical and Biomolecular Engineering, University of California, California-Irvine, Irvine, CA 92697, USA; Department of Molecular Biology and Biochemistry, University of California, California-Irvine, Irvine, CA 92697, USA., Patterson JP; Department of Material Science and Engineering, University of California-Irvine, Irvine, CA 92697, USA; Department of Chemistry, University of California, California-Irvine, Irvine, CA 92697, USA. Electronic address: patters3@uci.edu.
Jazyk: angličtina
Zdroj: Ultramicroscopy [Ultramicroscopy] 2024 Mar; Vol. 257, pp. 113894. Date of Electronic Publication: 2023 Nov 24.
DOI: 10.1016/j.ultramic.2023.113894
Abstrakt: In-situ liquid cell transmission electron microscopy (LCTEM) with electrical biasing capabilities has emerged as an invaluable tool for directly imaging electrode processes with high temporal and spatial resolution. However, accurately quantifying structural changes that occur on the electrode and subsequently correlating them to the applied stimulus remains challenging. Here, we present structural dissimilarity (DSSIM) analysis as segmentation-free video processing algorithm for locally detecting and quantifying structural change occurring in LCTEM videos. In this study, DSSIM analysis is applied to two in-situ LCTEM videos to demonstrate how to implement this algorithm and interpret the results. We show DSSIM analysis can be used as a visualization tool for qualitative data analysis by highlighting structural changes which are easily missed when viewing the raw data. Furthermore, we demonstrate how DSSIM analysis can serve as a quantitative metric and efficiently convert 3-dimensional microscopy videos to 1-dimenional plots which makes it easy to interpret and compare events occurring at different timepoints in a video. In the analyses presented here, DSSIM is used to directly correlate the magnitude and temporal scale of structural change to the features of the applied electrical bias. ImageJ, Python, and MATLAB programs, including a user-friendly interface and accompanying documentation, are published alongside this manuscript to make DSSIM analysis easily accessible to the scientific community.
Competing Interests: Declaration of Competing Interest Y. Pivak and H. Sun work for DENSsolutions B.V., a company manufacturing and marketing in-situ TEM systems. The remaining authors have no conflicts to declare.
(Copyright © 2023. Published by Elsevier B.V.)
Databáze: MEDLINE
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