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Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy

[Image: see text] Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resoluti...

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Autores principales: Yu, Haoran, Zachman, Michael J., Reeves, Kimberly S., Park, Jae Hyung, Kariuki, Nancy N., Hu, Leiming, Mukundan, Rangachary, Neyerlin, Kenneth C., Myers, Deborah J., Cullen, David A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413405/
https://www.ncbi.nlm.nih.gov/pubmed/35867353
http://dx.doi.org/10.1021/acsnano.2c02307
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author Yu, Haoran
Zachman, Michael J.
Reeves, Kimberly S.
Park, Jae Hyung
Kariuki, Nancy N.
Hu, Leiming
Mukundan, Rangachary
Neyerlin, Kenneth C.
Myers, Deborah J.
Cullen, David A.
author_facet Yu, Haoran
Zachman, Michael J.
Reeves, Kimberly S.
Park, Jae Hyung
Kariuki, Nancy N.
Hu, Leiming
Mukundan, Rangachary
Neyerlin, Kenneth C.
Myers, Deborah J.
Cullen, David A.
author_sort Yu, Haoran
collection PubMed
description [Image: see text] Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resolution, which allows direct visualization of composition and morphology with atomic precision. This typically comes at the cost of sample size, potentially limiting the accuracy and relevance of STEM results, as well as the ability to meaningfully track changes in properties that vary spatially. In this work, automated STEM data acquisition and analysis techniques are employed that enable physical and compositional properties of nanoparticles to be obtained at high resolution over length scales on the order of microns. This is demonstrated by studying the localized effects of potential cycling on electrocatalyst degradation across proton exchange membrane fuel cell cathodes. In contrast to conventional, manual STEM measurements, which produce particle size distributions representing hundreds of particles, these high-throughput automated methods capture tens of thousands of particles and enable nanoparticle size, number density, and composition to be measured as a function of position within the cathode. Comparing the properties of pristine and degraded fuel cells provides statistically robust evidence for the inhomogeneous nature of catalyst degradation across electrodes. These results demonstrate how high-throughput automated STEM techniques can be utilized to investigate local phenomena occurring in nanoparticle systems employed in practical devices.
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spelling pubmed-94134052022-08-27 Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy Yu, Haoran Zachman, Michael J. Reeves, Kimberly S. Park, Jae Hyung Kariuki, Nancy N. Hu, Leiming Mukundan, Rangachary Neyerlin, Kenneth C. Myers, Deborah J. Cullen, David A. ACS Nano [Image: see text] Nanoparticles are an important class of materials that exhibit special properties arising from their high surface area-to-volume ratio. Scanning transmission electron microscopy (STEM) has played an important role in nanoparticle characterization, owing to its high spatial resolution, which allows direct visualization of composition and morphology with atomic precision. This typically comes at the cost of sample size, potentially limiting the accuracy and relevance of STEM results, as well as the ability to meaningfully track changes in properties that vary spatially. In this work, automated STEM data acquisition and analysis techniques are employed that enable physical and compositional properties of nanoparticles to be obtained at high resolution over length scales on the order of microns. This is demonstrated by studying the localized effects of potential cycling on electrocatalyst degradation across proton exchange membrane fuel cell cathodes. In contrast to conventional, manual STEM measurements, which produce particle size distributions representing hundreds of particles, these high-throughput automated methods capture tens of thousands of particles and enable nanoparticle size, number density, and composition to be measured as a function of position within the cathode. Comparing the properties of pristine and degraded fuel cells provides statistically robust evidence for the inhomogeneous nature of catalyst degradation across electrodes. These results demonstrate how high-throughput automated STEM techniques can be utilized to investigate local phenomena occurring in nanoparticle systems employed in practical devices. American Chemical Society 2022-07-22 2022-08-23 /pmc/articles/PMC9413405/ /pubmed/35867353 http://dx.doi.org/10.1021/acsnano.2c02307 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Yu, Haoran
Zachman, Michael J.
Reeves, Kimberly S.
Park, Jae Hyung
Kariuki, Nancy N.
Hu, Leiming
Mukundan, Rangachary
Neyerlin, Kenneth C.
Myers, Deborah J.
Cullen, David A.
Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title_full Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title_fullStr Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title_full_unstemmed Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title_short Tracking Nanoparticle Degradation across Fuel Cell Electrodes by Automated Analytical Electron Microscopy
title_sort tracking nanoparticle degradation across fuel cell electrodes by automated analytical electron microscopy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9413405/
https://www.ncbi.nlm.nih.gov/pubmed/35867353
http://dx.doi.org/10.1021/acsnano.2c02307
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