(561d) Mitigating the Oxidative Deactivation on a Multi-Faceted Fe Catalyst: A Multi-Scale Model from First Principles

One
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 catalyst^2-6.
In order to improve the performance of such bimetallic iron catalysts, the oxidative
deactivation mechanism that limits these catalysts must be determined.

While
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 properties^2,4,7. 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 investigated^8-11. 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.

In
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 surfaces^12,13. 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.

The
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.

Figure 1: 
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.

References:

1.       Wang, H., Male, J. & Wang,
Y. Recent Advances in Hydrotreating of Pyrolysis Bio-Oil and Its
Oxygen-Containing Model Compounds. ACS Catal. 3, 1047–1070
(2013).

2.       Hong, Y., Zhang, H., Sun, J.,
Ayman, K. M. & Hensley, A. Synergistic catalysis between Pd and Fe in gas
phase hydrodeoxygenation of m-cresol. ACS Catalysis (2014).
doi:10.1021/cs500578g

3.       Nie, L., de Souza, P. M.,
Noronha, F. B. & An, W. Selective conversion of m-cresol to toluene over
bimetallic Ni–Fe catalysts. Journal of Molecular … (2014).
doi:10.1016/j.molcata.2013.09.029

4.       Sun, J. et al.
Carbon-supported bimetallic Pd–Fe catalysts for vapor-phase
hydrodeoxygenation of guaiacol. Journal of Catalysis 306,
47–57 (2013).

5.       Sitthisa, S., An, W. &
Resasco, D. E. Selective conversion of furfural to methylfuran over
silica-supported Ni Fe bimetallic catalysts. Journal of Catalysis
(2011). doi:10.1016/j.jcat.2011.09.005

6.       González-Borja, M. Á. &
Resasco, D. E. Anisole and guaiacol hydrodeoxygenation over monolithic
Pt–Sn catalysts. Energy & Fuels (2011). doi:10.1021/ef200728r

7.       Hensley, A. J. R. et al.
Enhanced Fe 2O 3Reducibility via Surface Modification with Pd: Characterizing
the Synergy within Pd/Fe Catalysts for Hydrodeoxygenation Reactions. ACS
Catal. 4, 3381–3392 (2014).

8.       Che, F., Ha, S., McEwen, J. S.,
Hensley, A. J. & Zhang, R. Elucidating the field influence on the
energetics of the methane steam reforming reaction: A density functional theory
study. ‘Applied Catalysis B, Environmental’ (2016).
doi:10.1016/j.apcatb.2016.04.026

9.       Che, F., Gray, J. T., Ha, S.
& McEwen, J.-S. Improving Ni Catalysts Using Electric Fields: A DFT and
Experimental Study of the Methane Steam Reforming Reaction. ACS Catal.
(2016). doi:10.1021/acscatal.6b02318

10.     Che, F., Ha, S. & McEwen, J.
S. Hydrogen Oxidation and Water Dissociation over an Oxygen-Enriched Ni/YSZ
Electrode in the Presence of an Electric Field: A First Principles-Based
Microkinetic …. Industrial & Engineering Chemistry … (2017).
doi:10.1021/acs.iecr.6b04028

11.     Che, F., Gray, J. T., Ha, S.
& McEwen, J. S. Catalytic water dehydrogenation and formation on nickel:
Dual path mechanism in high electric fields. Journal of Catalysis
(2015). doi:10.1016/j.jcat.2015.09.010

12.     Hensley, A. J. R., Zhang, R.,
Wang, Y. & McEwen, J.-S. Tailoring the Adsorption of Benzene on PdFe
Surfaces: A Density Functional Theory Study. J. Phys. Chem. C 117,
24317–24328 (2013).

13.     Hensley, A., Schneider, S., Wang,
Y. & McEwen, J. S. Adsorption of aromatics on the (111) surface of PtM and
PtM 3 (M= Fe, Ni) alloys. RSC Adv. (2015). doi:10.1039/C5RA13578H

14.     McEwen, J. S., Gaspard, P., de
Bocarmé, T. V. & Kruse, N. Oscillations and Bistability in the Catalytic
Formation of Water on Rhodium in High Electric Fields. J. Phys. Chem. C 113,
17045–17058 (2009).