(561d) Mitigating the Oxidative Deactivation on a Multi-Faceted Fe Catalyst: A Multi-Scale Model from First Principles
promising method for addressing the growing need for diverse, sustainable
energy sources is bio-oil produced via the fast-pyrolysis of biomass. However,
these bio-oils have high concentrations of oxygenated compounds, resulting in fuel
quality issues1 that require catalytic hydrodeoxygenation (HDO),
thereby reducing the overall oxygen content and improving fuel quality.
Bimetallic, doped iron, catalysts have demonstrated synergistic behavior that
contributes to a more cost-effective and longer-lasting HDO catalyst2-6.
In order to improve the performance of such bimetallic iron catalysts, the oxidative
deactivation mechanism that limits these catalysts must be determined.
the addition of dopants to Fe catalysts exhibits an overall synergistic
interaction, further investigation into the behavior of oxygen on a doped catalytic
Fe grain is required to minimize the use of precious metals while maximizing
its synergistic properties2,4,7. Here, we model the oxidative deactivation of a full
catalytic Fe grain by exposure to O2 as well as taking into account both
coverage and facet effects on the kinetic behavior. Additionally, as the
application of external electric fields has demonstrated favorable effects on
other catalytic processes, such as methane steam reforming, the effect of a
range of electric fields were also investigated8-11. Such a realistic,
multi-faceted model of a doped Fe grain is an effective tool for optimizing the
use of precious metal dopants and taking advantage of the effect of an electric
field. These realistic, predictive models help to bridge the gap between
experiment and theory, streamlining research efforts and accelerating progress.
order to build the multi-faceted catalytic Fe grain model, the adsorption of
oxygen was calculated on both clean and doped Fe(100), Fe(110), and Fe(111)
over a range of surface coverages. The effect of an electric field on oxygen
adsorption on these three Fe facets was studied over a range of ±1.0 V/Å,
examining each available adsorption site over a range of coverages. Surprisingly,
we found that the undoped Fe(111) facet favors a high oxygen coverage even
under low O2 exposure and all electric field strengths (see Figure
1). Results indicate that the undoped Fe(110) surface is the most strongly
affected by the electric field over the coverage range, while the undoped Fe(100)
surface is the least effected. As seen in Figure 1, the undoped Fe(100) and
Fe(111) surfaces have the strongest adsorption energy, resulting in high oxygen
coverage upon exposure to O2. Preliminary work on Pd doped Fe(100) with
varying Pd concentration has shown that increasing the surface concentration of
Pd significantly decreased the adsorption strength of oxygen, which is
consistent with other studies on the adsorption of benzene and phenol on Fe
doped surfaces12,13. These results suggest that the primary function of
Pd is the disruption of oxide formation due to the aversion that oxygen has for
Pd on the Pd/Fe(100) surfaces. Consequently, the degree of catalyst deactivation
due to the formation of a surface oxide likely decreases with the addition of
Pd to an Fe surface, thereby promoting HDO with minimal deactivation of the
active Fe surface.
three Fe facets studied here were then used to construct a model of a multi-faceted
grain surface, incorporating the anisotropic effects of the surface orientation
on kinetic characteristics14. Such a model accounts for the effect of pressure,
temperature, electric field, dopants, and surface orientation on the
adsorption/desorption and oxidative deactivation behavior. This doped Fe
catalytic grain model can be used as an experimentally predictive, useful tool
for optimizing methods in which HDO catalysts are designed to reduce oxidative
deactivation while minimizing the use of costly precious metals.
Equilibrium oxygen coverage on a multi-faceted catalytic iron grain at 500 K,1.5
Pa, and an electric field of -1.0 V/Å.
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