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Simultaneous characterization of operando multi-material distribution via high-contrast correlative tomographic microscopy

Published

Author(s)

Pranay Shrestha, Jacob LaManna, Kieran Fahy, Pascal Kim, ChungHyuk Lee, Jason Lee, Elias Baltic, David Jacobson, Daniel Hussey, Aimy Bazylak

Abstract

High-contrast tomographic microscopy of evolving multi-material systems, such as electrochemical devices, offers a unique and often exclusive perspective into inner workings of these complex systems. Here, we characterize the operando spatiotemporal distribution of six interacting fuel cell components simultaneously in high contrast using a combination of dual-modality neutron and X-ray tomography (NeXT) and advanced image processing, achieving the highest reported pairwise contrast between these materials (average and median pairwise contrast-to-noise ratio of 9.5). Signal and contrast enhancements of up to 48 times and 10 times, respectively, are achieved when adopting the proposed methodology over single-modality imaging with conventional image processing. These drastic contrast enhancements reveal subtle variation in operando microstructural morphology of the catalyst coated membrane and liquid water distribution with respect to flow-field land-channel patterns in fuel cells. Such high-contrast NeXT imaging sets the stage for the establishment of a new gold-standard for operando tomographic characterization of electrochemical devices.
Citation
Nature Communications

Keywords

neutron and X-ray tomography, operando imaging, iterative reconstruction, fuel cells, tomographic microscopy, multi-material characterization

Citation

Shrestha, P. , LaManna, J. , Fahy, K. , Kim, P. , Lee, C. , Lee, J. , Baltic, E. , Jacobson, D. , Hussey, D. and Bazylak, A. (2023), Simultaneous characterization of operando multi-material distribution via high-contrast correlative tomographic microscopy, Nature Communications, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935631 (Accessed March 21, 2025)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created November 8, 2023, Updated March 12, 2025