Effective Model of NOx Adsorption and Desorption on PtPd/CeO2-ZrO2 Passive NOx Adsorber

• Published in: Catalysis letters Vol. 150; no. 11; pp. 3223 - 3233
• Main Authors: Kvasničková, Anežka, Kočí, Petr, Ji, Yaying, Crocker, Mark
• Format: Journal Article
• Language: English
• Published: New York Springer US 01-11-2020; Springer Nature B.V
• Subjects: Adsorption; Catalysis; Cerium oxides; Chemistry; Chemistry and Materials Science; Computer simulation; Desorption; Industrial Chemistry/Chemical Engineering; Low temperature; Nanoparticles; Nitrates; Nitrites; Organometallic Chemistry; Palladium; Physical Chemistry; Platinum; Reducing agents; Temperature dependence; Thermal decomposition; Zirconium dioxide; PNA; catalyst; ZrO; Automotive exhaust gas aftertreatment; PtPd/CeO; Mathematical modeling; NOx adsorption
• ISSN: 1011-372X; 1572-879X
• DOI: 10.1007/s10562-020-03186-z

An effective model for describing NO
x
adsorption and desorption on a PtPd/CeO
2
-ZrO
2
passive NO
x
adsorber is presented. The kinetic parameters are evaluated from the available experimental data obtained during NO
x
adsorption/desorption experiments including CO
2
and H
2
O in the feed, performed at 80, 120 and 160 °C both in the presence and in the absence of reducing agents (CO or C
2
H
4
). The model describes the temperature dependence of the NO
x
adsorption rate and capacity, the impact of CO, and dynamics of the NO
x
desorption events. The model predicts formation of nitrites, nitrates, and additional storage enabled in the presence of CO. Thermal decomposition of the stored NO
x
species results in two main desorption peaks. Nitrites are desorbed at lower temperatures while nitrates are thermally more stable. The evolution of nitrite and nitrate species in the model corresponds with the measured DRIFTS spectra of the catalyst surface. The presence of CO significantly improves the rate of NO
x
adsorption and storage efficiency at low temperatures, most probably due to reduction of oxidic Pt and Pd nanoparticles. The developed model captures well the observed trends and can be utilized for simulations of PNA performance under real operating conditions.