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Title: Nanoscale tomography reveals the deactivation of automotive copper-exchanged zeolite catalysts

Abstract

Copper-exchanged zeolite chabazite (Cu-SSZ-13) was recently commercialized for the selective catalytic reduction of NOX with ammonia in vehicle emissions as it exhibits superior reaction performance and stability compared to all other catalysts, notably Cu-ZSM-5. Herein, the 3D distributions of Cu as well as framework elements (Al, O, Si) in both fresh and aged Cu-SSZ-13 and Cu-ZSM-5 are determined with nanometer resolution using atom probe tomography (APT), and correlated with catalytic activity and other characterizations. Both fresh catalysts contain a heterogeneous Cu distribution, which is only identified due to the single atom sensitivity of APT. After the industry standard 135,000 mile simulation, Cu-SSZ-13 shows Cu and Al clustering, whereas Cu-ZSM-5 is characterized by severe Cu and Al aggregation into a copper aluminate phase (CuAl2O4 spinel). The application of APT as a sensitive and local characterization method provides identification of nanometer scale heterogeneities that lead to catalytic activity and material deactivation.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1]; ORCiD logo [2]
  1. Univ. of Utrecht (Netherlands)
  2. Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Publication Date:
Research Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1474499
Grant/Contract Number:  
AC05-00OR22725
Resource Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY

Citation Formats

Schmidt, Joel E., Oord, Ramon, Guo, Wei, Poplawsky, Jonathan D., and Weckhuysen, Bert M. Nanoscale tomography reveals the deactivation of automotive copper-exchanged zeolite catalysts. United States: N. p., 2017. Web. doi:10.1038/s41467-017-01765-0.
Schmidt, Joel E., Oord, Ramon, Guo, Wei, Poplawsky, Jonathan D., & Weckhuysen, Bert M. Nanoscale tomography reveals the deactivation of automotive copper-exchanged zeolite catalysts. United States. https://doi.org/10.1038/s41467-017-01765-0
Schmidt, Joel E., Oord, Ramon, Guo, Wei, Poplawsky, Jonathan D., and Weckhuysen, Bert M. Tue . "Nanoscale tomography reveals the deactivation of automotive copper-exchanged zeolite catalysts". United States. https://doi.org/10.1038/s41467-017-01765-0. https://www.osti.gov/servlets/purl/1474499.
@article{osti_1474499,
title = {Nanoscale tomography reveals the deactivation of automotive copper-exchanged zeolite catalysts},
author = {Schmidt, Joel E. and Oord, Ramon and Guo, Wei and Poplawsky, Jonathan D. and Weckhuysen, Bert M.},
abstractNote = {Copper-exchanged zeolite chabazite (Cu-SSZ-13) was recently commercialized for the selective catalytic reduction of NOX with ammonia in vehicle emissions as it exhibits superior reaction performance and stability compared to all other catalysts, notably Cu-ZSM-5. Herein, the 3D distributions of Cu as well as framework elements (Al, O, Si) in both fresh and aged Cu-SSZ-13 and Cu-ZSM-5 are determined with nanometer resolution using atom probe tomography (APT), and correlated with catalytic activity and other characterizations. Both fresh catalysts contain a heterogeneous Cu distribution, which is only identified due to the single atom sensitivity of APT. After the industry standard 135,000 mile simulation, Cu-SSZ-13 shows Cu and Al clustering, whereas Cu-ZSM-5 is characterized by severe Cu and Al aggregation into a copper aluminate phase (CuAl2O4 spinel). The application of APT as a sensitive and local characterization method provides identification of nanometer scale heterogeneities that lead to catalytic activity and material deactivation.},
doi = {10.1038/s41467-017-01765-0},
journal = {Nature Communications},
number = 1,
volume = 8,
place = {United States},
year = {Tue Nov 21 00:00:00 EST 2017},
month = {Tue Nov 21 00:00:00 EST 2017}
}

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