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Journal of Catalysis
Article . 2021
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Mimicking industrial aging in fluid catalytic cracking: A correlative microscopy approach to unravel inter-particle heterogeneities

A correlative microscopy approach to unravel inter-particle heterogeneities
Authors: M. Gambino; A.E. Nieuwelink; F. Reints; M. Veselý; M. Filez; D. Ferreira Sanchez; D. Grolimund; +4 Authors

Mimicking industrial aging in fluid catalytic cracking: A correlative microscopy approach to unravel inter-particle heterogeneities

Abstract

Artificially mimicking aging of an equilibrium catalyst (ECAT) is an effective strategy to model the deactivation of a Fluid Catalytic Cracking (FCC) catalyst during refinery operations. Herein, we have used a correlative microscopy approach to unravel inter-particle spatial heterogeneities in artificially deactivated catalysts (DCATs) and compared them with a real-life ECAT containing on average 3800 ppm of Ni and 2300 ppm of V, and a set of density separated ECAT fractions. By doing so we could rationalize the effect of metal contaminants on catalyst acidity and pore accessibility. More specifically, the Fe, Ni, and V distributions were obtained using X-Ray Fluorescence (XRF), while Confocal Fluorescence Microscopy (CFM) after thiophene and Nile Blue A staining, respectively provided a visualization of Brønsted acid sites and accessibility distribution. We found that not only the metal poisons distribution, but also hydrothermal degradation, that affects ECATs dealumination and related acidity drop, need to be properly reproduced by artificial catalyst deactivation protocols. Fe contamination must also be taken into account since it affects matrix accessibility.

Countries
Netherlands, Belgium
Related Organizations
Keywords

Microscopy, Artificial deactivation, ZEOLITES, Catalyst deactivation, INTEGRATED LASER, FCC CATALYSTS, ACCESSIBILITY, Catalysis, TIME, DIFFERENT LIFE STAGES, CONTAMINATION, Chemistry, VGO, Physics and Astronomy, Fluid catalytic cracking, DEACTIVATION, Physical and Theoretical Chemistry

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Top 10%
Average
Top 10%
Green
hybrid