Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy
Abstract
To understand how hierarchically structured functional materials operate, analytical tools are needed that can reveal small structural and chemical details in large sample volumes. Often, a single method alone is not sufficient to get a complete picture of processes happening at multiple length scales. Here we present a correlative approach combining three-dimensional X-ray imaging techniques at different length scales for the analysis of metal poisoning of an individual catalyst particle. The correlative nature of the data allowed establishing a macro-pore network model that interprets metal accumulations as a resistance to mass transport and can, by tuning the effect of metal deposition, simulate the response of the network to a virtual ageing of the catalyst particle. In conclusion, the developed approach is generally applicable and provides an unprecedented view on dynamic changes in a material’s pore space, which is an essential factor in the rational design of functional porous materials.
- Authors:
-
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Utrecht Univ., Utrecht (The Netherlands)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1312961
- Grant/Contract Number:
- AC02-76SF00515
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Nature Communications
- Additional Journal Information:
- Journal Volume: 7; Journal ID: ISSN 2041-1723
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE
Citation Formats
Liu, Yijin, Meirer, Florian, Krest, Courtney M., Webb, Samuel, and Weckhuysen, Bert M. Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy. United States: N. p., 2016.
Web. doi:10.1038/ncomms12634.
Liu, Yijin, Meirer, Florian, Krest, Courtney M., Webb, Samuel, & Weckhuysen, Bert M. Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy. United States. https://doi.org/10.1038/ncomms12634
Liu, Yijin, Meirer, Florian, Krest, Courtney M., Webb, Samuel, and Weckhuysen, Bert M. Tue .
"Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy". United States. https://doi.org/10.1038/ncomms12634. https://www.osti.gov/servlets/purl/1312961.
@article{osti_1312961,
title = {Relating structure and composition with accessibility of a single catalyst particle using correlative 3-dimensional micro-spectroscopy},
author = {Liu, Yijin and Meirer, Florian and Krest, Courtney M. and Webb, Samuel and Weckhuysen, Bert M.},
abstractNote = {To understand how hierarchically structured functional materials operate, analytical tools are needed that can reveal small structural and chemical details in large sample volumes. Often, a single method alone is not sufficient to get a complete picture of processes happening at multiple length scales. Here we present a correlative approach combining three-dimensional X-ray imaging techniques at different length scales for the analysis of metal poisoning of an individual catalyst particle. The correlative nature of the data allowed establishing a macro-pore network model that interprets metal accumulations as a resistance to mass transport and can, by tuning the effect of metal deposition, simulate the response of the network to a virtual ageing of the catalyst particle. In conclusion, the developed approach is generally applicable and provides an unprecedented view on dynamic changes in a material’s pore space, which is an essential factor in the rational design of functional porous materials.},
doi = {10.1038/ncomms12634},
journal = {Nature Communications},
number = ,
volume = 7,
place = {United States},
year = {Tue Aug 30 00:00:00 EDT 2016},
month = {Tue Aug 30 00:00:00 EDT 2016}
}
Web of Science
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