Three-way catalysts,
which typically include Rh, are used to treat
automotive exhaust and reduce nitric oxide (NO) with a combination
of CO and H2, although few kinetic and theoretical investigations
have studied NO–H2 reactions on Rh. Here, we examine
NO activation, which is believed to control the rate of NO reduction,
through direct, NO-assisted, and H2-assisted dissociation
pathways on NO*-covered Rh(111) surfaces and Rh nanoparticle models
using density functional theory (DFT) and contrast these results with
previously reported data on Pt(111) surfaces. Saturation coveragesdetermined
by incrementally adsorbing NO*were determined to be 5/9 ML
NO* on Pt(111), 6/9 ML on Rh(111), and 1.38 ML on a 201-atom Rh nanoparticle
(∼2 nm). Free energies of activation and reaction were calculated
by DFT for the pathways at these coverages and interpreted through
maximum rate analyses over a wide range of NO and H2 pressures
to predict NO activation mechanisms and kinetics. Rates are inhibited
by NO at all relevant NO pressures and to similar extents on all catalyst
models. On Pt(111) surfaces, NO is activated through NOH* formation
and dissociation (to N* and OH*) at low H2 pressures (<0.5
bar) and through HNOH* (to HN* and OH*) at high H2 pressures
(>0.5 bar), resulting in a shift in the H2 dependency
from
half order to first order. NO is activated through NOH* formation
and dissociation on Rh(111) at all relevant H2 pressures,
with all other pathways being >1000 times slower. NO activation
occurs
with similar rates through either NOH* or HNO* on Rh particles at
1.38 ML NO*, indicating that these high coverages can shift mechanistic
preferences. Predicted NO consumption rates are half order in H2 on Rh particles and surfaces and are similar in magnitude
to one another, despite shifts in the mechanism; these rates on Rh
are 106 times slower than Pt, consistent with the prior
reports that demonstrate that equal turnover rates for Pt at 60 °C
occur for Rh at 200 °C. This work demonstrates that strong NO
bonds activate through bimolecular (assisted) pathways and that particle
models of catalysts enable high coverages of strongly bound species,
which can then influence relative rates and mechanistic predictions.