Importance of Angelica Lactone Formation in the Hydrodeoxygenation

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On the Importance of Angelica Lactone Formation in the Hydrodeoxygenation of Levulinic Acid to #-Valerolactone over a Ru(0001) Model Surface Osman Mamun, Mohammad Saleheen, Jesse Q. Bond, and Andreas Heyden J. Phys. Chem. C, Just Accepted Manuscript • DOI: 10.1021/acs.jpcc.7b06369 • Publication Date (Web): 03 Aug 2017 Downloaded from http://pubs.acs.org on August 8, 2017

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The Journal of Physical Chemistry

On the Importance of Angelica Lactone Formation in the Hydrodeoxygenation of Levulinic Acid to γ-Valerolactone over a Ru(0001) Model Surface Osman Mamun1, Mohammad Saleheen1, Jesse Q. Bond2, and Andreas Heyden1,* 1

Department of Chemical Engineering, University of South Carolina, 301 Main Street, Columbia, South Carolina 29208, USA

2

Department of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, USA

*Corresponding author: email: [email protected]

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Abstract Using mean-field microkinetic modeling with parameters derived from density functional theory calculations and harmonic transition state theory, we investigated the steady-state catalytic hydrodeoxygenation of levulinic acid (LA) to γ-valerolactone (GVL) on a Ru(0001) model surface. Focusing on the importance of intramolecular esterification of LA to its stable derivative α-angelica lactone (AGL) during the HDO to GVL, we studied various reaction pathways for GVL production that involve AGL and 4-hydroxypentanoic acid (HPA). We find that in a non-polar reaction environment these pathways are not kinetically relevant but that GVL can be produced from LA by a single hydrogenation step, followed by ring closure and C-OH bond cleavage. However, AGL reaction pathways lead to surface poisoning at temperatures above 423 K when these pathways become kinetically accessible.

As a result of surface

poisoning ─possibly at low temperatures by hydrogen and at high temperatures by AGL derivatives─ we observe two different activity regimes characterized by significantly different activation barriers. Overall, simulation results agree well with experimental observations except at low temperatures of 323 K where our model significantly underestimates the turnover frequency, questioning whether Ru(0001) sites are the active at these low temperatures.


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1. Introduction Efficient production of biomass derived second generation biofuels requires the development of active, selective, and stable catalytic materials for the reductive deoxygenation of platform chemicals such as levulinic acid (LA) and succinic acid (SA). One approach for the catalytic deoxygenation of biomass platform chemicals is the hydrodeoxygenation over supported transition metal catalysts. Levulinic acid (LA) hydrodeoxygenation (HDO), a crucial biomass conversion process to produce γ-valerolactone (GVL) that can be used as fuel additive, food ingredients, nylon intermediate, or renewable solvent, occurs in liquid phase environments (in both organic or aqueous solvents) in the presence of supported transition metal nanoparticles. Recent studies have shown1 that LA hydrodeoxygenation─ unlike petroleum refining where conventional hydrogenation catalysts such as palladium (Pd), rhodium (Rh), and nickel (Ni) are tailored to obtain high activities and selectivities─ is best performed with oxophillic ruthenium based mono- or bimetallic catalysts. Manzar et al. studied the hydrogenation of levulinic acid in dioxane with 800 psig (~55 bar) H2 pressure at 150 0C with several different carbon supported metal catalysts such as Ir, Rh, Pd, Ru, Pt, Re, and Ni. Their study shows superior activity and selectivity for the carbon supported Ru catalyst among all the catalysts screened for this conversion process.2 Another study also found at different reaction conditions (temperature of 130 0C, hydrogen pressure of 1.5 MPa, and methanol solvent) that the Ru/C catalyst performs superior in terms of activity and selectivity to, e.g., carbon supported palladium and nickel catalysts.3 Also, a comprehensive study by Dumesic and co-workers found that the Ru/C catalyst is the most active and selective monometallic catalyst in an aqueous phase environment.4 However, they also observed that a carbon supported bimetallic RuRe catalyst is more stable in water than the supported monometallic Ru catalyst. Next, Ftouni et al.5 compared the catalytic 3 ACS Paragon Plus Environment


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activity and selectivity of various supported Ru catalysts (ZrO2, TiO2, and carbon) at 423 K, 30 bar hydrogen, and 1,4-dioxane solvent conditions. They found that all supported Ru catalysts showed excellent yields; however, only ZrO2 was able to maintain these high yields after multiple regeneration steps. Finally, both Huber et al.6 and Michel et al.7 observed that Ru based catalysts are excellent carbonyl group hydrogenation catalysts in an aqueous reaction environment. To summarize, although the catalytic activity and in particular stability of the ruthenium surface is greatly influenced by the choice of the support, the catalytic performance of ruthenium nanoparticles was found to be superior to that of any other monometallic transition metal for the HDO of LA to GVL. In this paper, we use mean-field microkinetic modeling based on parameters obtained from DFT computations to describe the catalytic behavior of a Ru surface for the conversion of LA to GVL via intermediate production of both AGL and 4-hydroxypentanoic acid (HPA). We use no experimental data for fitting any parameters in our model and use a clean Ru(0001) slab to mimic the catalytic behavior of a carbon supported Ru catalyst. Considering the challenges in modeling liquid phase environments, we perform a computational vapor phase study at chemical potentials corresponding to liquid phase conditions which is likely characteristic of a non-polar aprotic solvent environment such as 1,4-dioxane. Our overall objectives are: (i) better understanding the reaction mechanism of the HDO of LA to GVL, (ii) understanding the kinetic relevance of AGL and HPA formation in the production of GVL, and (iii) investigating if Ru(0001) sites are possible active sites for the HDO of LA. In this way, this study is an extension of our previous study on the HDO of LA over Ru(0001) which did not consider any reaction pathways involving AGL8. In our prior study, we observed that the Ru(0001) surface is highly active for the HDO of LA to GVL at temperatures above 423 K and that at low 4 ACS Paragon Plus Environment

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temperatures below 373 K the Ru(0001) surface is not catalytically active; an observation that contradicts experimental observations of supported Ru catalysts. As a result, this study tests if the neglect of reaction pathways involving AGL and its derivatives are responsible for the low activity in our prior catalyst model. This article is organized as follows. In section 2, we briefly discuss the computational methodology and modeling strategy we adopted for the study of LA HDO over Ru(0001). Then, we present a detailed DFT analysis of the various pathways for LA conversion to GVL via intermediate formation of AGL. The results obtained from our microkinetic models and predictions regarding the dominant reaction mechanism, rate controlling steps, and reaction orders are analyzed in section 4. We conclude with a discussion on the detrimental effect of intramolecular esterification of LA to AGL for the HDO of LA to GVL. 2. Methods In this computational study the Vienna Ab initio Simulation Package (VASP) 9, 10 is used to perform periodic DFT calculations and the projector augmented wave method (PAW) is used to describe the ionic core potentials.11,

12

The Kohn-Sham one electron valance states are

expanded in a basis of plane waves with kinetic energies below 400 eV. The self-consistent field

calculations are converged with an energy cutoff of 1 × 10 eV, which is a standard SCF energy convergence criterion for computational studies of biomass molecules on model transition metal surfaces. The ionic cycle is converged using a force based criteria of 0.01 /Å

on each relaxed atom. The Methfessel-Paxton smearing scheme13 is used with a Fermi

population of the Kohn-Sham excited states at = 0.1 , and at the end of the optimization, the total energy is extrapolated to 0 K. To describe the exchange and correlation effects, we used

the PBE functional from Perdew, Burke, and Ernzerhof.14 The rationale behind choosing the 5 ACS Paragon Plus Environment


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GGA based PBE functional is: 1) it has been proven to be relatively accurate (both qualitatively and quantitatively) for describing transition metal-adsorbate (containing carbon, oxygen, and hydrogen) interactions, and 2) our gas phase thermodynamics with PBE-D3 returns a low error with respect to coupled cluster calculations at the CCSD(T) level of theory (which is often regarded as ‘gold standard’ for computational chemistry application15). We used Grimme’s D3 method16 to consider the long range dynamic correlation between fluctuating charge distributions. Though local environment dependent self-consistent dispersion inclusion is available,17 we used the non-self-consistent D3 method as it is well parameterized for the PBE functional and can be trusted to give reasonable energetics with no additional computational cost. A four layer, (4 × 4) slab is used as the surface model. The top two layers of the slab

are allowed to relax, while the bottom two layers are kept fixed in their bulk optimized position. A vacuum spacing of 15Å is used between two successive metal slabs. For the bulk Ru optimization, we used a 20 × 20 × 20 Monkhorst-Pack k-point mesh.18 The surface Brillouin

zone is sampled with a 4 × 4 × 1 k-point mesh and convergence with respect to k-point, cut-off

energy, and slab depth was tested for model reactions involving C, O, and H atom adsorption. For gas phase molecule optimizations, we used a box size of 20 Å × 20 Å × 20 Å with

1 × 1 × 1 Monkhorst-Pack k-point sampling technique. During gas phase molecule

optimizations, the electronic energy is optimized to 1 × 10 while the ion position is optimized to 0.005 eV/Å using a conjugate gradient algorithm.

To locate the transition state (TS) of each elementary reaction, we used a two-step procedure. First, an NEB19 calculation is carried out using the initial and final state conformations and 5-7 images along the reaction coordinate to scan the potential energy surface. Then, the image that represents the TS best (both geometrically and energetically) is chosen as 6 ACS Paragon Plus Environment

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the initial guess for a dimer20, 21 calculation. All transition states are optimized using the same 0.01 eV/Å force based criterion. Then, the Hessian matrix is calculated numerically with a 0.001 Å displacement to compute all frequencies and to ensure that the TS has an imaginary frequency along the reaction coordinate. Unfortunately, we were unable to converge the transition states for

six elementary reaction steps ( , , , , , and " ) with our target accuracy. All of

these elementary reactions are ring formation reactions and we used the BEP relations developed in our previous study8 for estimating the activation barriers for these processes. To confirm that the uncertainty in the BEP relations does not affect our conclusions of this paper, we performed a kinetic rate control analysis of all TSs. Our calculations indicate that our model results are robust

with respect to the uncertainty of these missing transition states, i.e., none of these transition states is rate controlling (see supplementary information for more details). 2.1 Microkinetic Model In the

microkinetic model, we used a hydrogen partial pressure of 4-40 bar which

corresponds to the pressure range used in the experimental studies by Dumesic et al.4 and Bond et al.22 As for the LA chemical potential, we used the LA partial pressure/fugacity equivalent to a 0.025M-1.5M LA solution in water computed using the modified Raoult’s law, & *+, #$% = '$% = ($% × )$% × '

%$(1)

*+, In Eq. 1 the activity coefficient, )$% , and saturation vapor pressure, '$% , were calculated using

the TURBOMOLE and COSMOtherm23,

24

program packages. All elementary reactions were

assumed to be reversible, which means no equilibrium and/or irreversibility assumptions were made in the microkinetic model. The rate of reaction for all intermediate reactions were calculated as



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- = -. / 013,4 − - / 06 7,4 2

1

2

6

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(2)

where . and are the forward and reverse rate constants, 81,- and 86,- are the stoichiometric coefficients, and 01 and 06 are the normalized surface coverages of reactants, m, and products,

n, i.e., the number of surface species on the surface relative to the number of surface sites (for

species that occupy more than one site the actual surface coverage is computed as 01 × number

of sites occupied per species m). Forward and backward rate constants were calculated using harmonic Transition State Theory (hTST) 9:; 0

−0.68 + 0.31 × θ + 3.99 × θ θ} θ # (θ} − 0.12) ≤ 0

E =-99Z;Z6,-+j (θ , θ} ) =

(13)

−2.994 + 2.014(θ − 0.07) + 0.31 × θ} + 3.99 × θ} θ θ} # (θ − 0.07) > 0

−2.994 + 0.31 × θ} + 3.99 × θ} θ θ} # (θ − 0.07) ≤ 0

All microkinetic modeling results presented in the next sections have been obtained using these lateral interaction parameters. 4.1 Reaction rates and dominant reaction mechanism At 323 K and typical reactant chemical potentials (0.45 M LA solution and 10 bar hydrogen pressure; see Table 3), our microkinetic 1-site model predicts an overall turnover

frequency (TOF) of 2.67 × 10" with a hydrogen coverage of roughly 100%. In contrast, the 2-site model predicts a TOF and hydrogen coverage at the same reaction condition of 2.23 × 10 and roughly 100% of ∆ sites, respectively. Although the 2-site model predicts a

TOF that is three orders of magnitude higher than the 1-site model, both microkinetic models

predict a TOF that is at least three orders of magnitude lower than the experimentally observed

TOF (2.00 × 10 ) by Abdelrahman et al.22 in liquid water. Considering that the 2-site model likely overestimates the actual TOF (as hydrogen should compete somewhat with other species), we conclude that the Ru(0001) surface is likely not the experimentally observed active



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site for the HDO of LA for the production of GVL in the low temperature region. Alternatively, solvent effects that are not considered explicitly in this study would have to be significant to lead to an increase in the TOF by 3-6 orders of magnitude. Interestingly, at moderate temperature (such as 423 K), both of our 1- and 2-site models predict reasonable TOFs of 3. 44 × 10

and 1.30 × 10 , respectively, which compare well to the experimentally observed TOF of 4.80 × 10 in liquid water at the same reaction temperature. This indicates that at moderate

temperatures (i.e. 423 K), Ru(0001) constitutes possibly the experimentally observed active site. We note that experimental Ru catalysts display various surface facets such as Ru(0001), Ru(100), Ru(101), etc. and it is possible that other facets dominate the experimentally observed kinetics; however, we conclude that at low temperatures our DFT data are not consistent with the experimental data while at higher temperatures our DFT data might be consistent with the experimental kinetic data. We are currently in the process of investigated the HDO of LA to GVL over various Ru surface facets and in various reaction environments. Our microkinetic models also suggest that the HDO pathways involving the formation of AGL intermediates are unfavorable. Pathways involving the formation of AGL and its derivatives are multiple orders of magnitude slower than the overall turnover frequency. For example, at 423 K, a hydrogen pressure of 10 bar and an LA chemical potential corresponding to

an aqueous 0.45 M LA solution, our 1-site model predicts an AGL formation rate of 6.49 ×

10 while the overall TOF is 3.44 × 10 for the production of GVL. Similarly, at a

temperature of 523 K, the AGL and GVL production rates are 6.40 × 10d and 3.37 ×

10 , respectively. The difference in experimental site time yield (STY) for AGL and GVL reported by Abdelrahman et al. are of somewhat similar order of magnitude.

22

For example, at

423 K they report a STY of 5 × 10 for AGL formation and a STY of 5 × 10 for


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GVL. In summary, we found that AGL formation pathways do not contribute to the overall GVL product yield. Furthermore, some of the AGL derivatives bind strongly to the metallic surface leading to surface poisoning which reduces the TOF at temperatures above 423 K. Simulation results for the 2-site model qualitatively agree with the 1-site model with regards to AGL formation pathways and surface poisoning at high temperatures. Figure 4 illustrates the dominant reaction mechanism as predicted by both of our 1- and 2-site models which follows a direct catalytic conversion pathway that does not involve either HPA or AGL formation. The dominant reaction mechanism includes the following elementary reaction steps: 1. LA hydrogenation towards surface alkoxy formation via a C-H bond formation step ( ), which is a thermoneutral process (0.06 eV) with an activation barrier of

0.67 eV.

2. C-O bond formation to yield I-80 from the alkoxy species via a ring closing reaction ( ). This step is slightly endothermic with a reaction energy and activation barrier of 0.22 eV and 0.33 eV, respectively.

3. Finally, a C-OH bond scission, "d , which is an exothermic process with a very small barrier leads to the formation of the final product GVL.

From the energetics of the dominant reaction pathway, we see that the potential energy surface followed by the dominant mechanism is mostly flat except for a 0.67 eV barrier for the first hydrogenation process. From this analysis, we can expect that the first LA hydrogenation is the rate controlling reaction for the HDO of LA. 4.2 Apparent activation barrier and reaction orders 21 ACS Paragon Plus Environment


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Figure 5 and 6 illustrate Arrhenius plots used for calculating apparent activation barriers of the 1- and 2-site models, respectively, at typical hydrogen and LA chemical potentials of 4 to 40 bar H2 and a 0.025 to 1.5 M LA solution. F+ = −

kLM (s) k (1a)

(14)

Both microkinetic models display a change in apparent activation barrier with temperature. For the 1-site model, at temperatures below 423 K the apparent activation barrier is nearly twice as high as at higher temperatures between 423 and 523 K. The change in apparent activation barrier can be understood by the catalyst surface being poisoned by surface hydrogen at low temperatures and an increase in temperature leads to both higher elementary rate constants and a larger free site coverage. Specifically, our 1-site model predicts an apparent activation barrier in the temperature range of 323 to 423 K of 1.5 to 1.8 eV, while the apparent activation barrier in the high temperature range of 423 to 523 K varies between 0.8 to 1.2 eV. As expected from our analysis above, higher activation barriers are observed for higher hydrogen partial pressures and lower concentrations of LA. In contrast, for the 2-site model the low temperature activation barrier is somewhat lower than the corresponding activation barrier in the 1-site model, mainly due to the non-competitive hydrogen adsorption mechanism and we observe an apparent activation barrier of 1 eV. Next, the high temperature apparent activation energy is relatively low due to an increased amount of surface poisoning by AGL derivatives with increasing temperature. Specifically, at temperatures above 473 K, the AGL derivatives I-20 and I-25 sweep off some reaction intermediates, e.g., Al and I-40, on the dominant reaction pathway for GVL production; thus, inhibiting reaction rate with increasing temperature. Specifically, we compute an apparent activation barrier between 22 ACS Paragon Plus Environment

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0.08 and 0.3 eV. Lange et al.31 also observed significant poisoning by carbonaceous species at high temperatures in their experimental study somewhat validating our computational prediction. As a word of caution, we note though that the PBE-D3 functional used in this study overestimates the hydrogen adsorption energy and likely the actual hydrogen reaction orders are higher, although still negative at low temperatures. In contrast, for the 2-site model, where hydrogen adsorption does not compete with hydrocarbon adsorption due to its small size, we observe a nearly temperature independent hydrogen reaction order between 0.33 and 0.47 which agrees quite well with the experimentally predicted hydrogen order of 0.5 in liquid water.22 Next, increasing the LA concentration / fugacity has a marked positive effect on the turnover frequency at all reaction temperatures. Our 1-site model predicts a decreasing LA reaction order from 1 at 323 K to 0.48 at 523 K (see Figure 7). In contrast, our 2-site model predicts a nearly temperature independent reaction order of LA between 0.33 and 0.46. The difference in LA reaction order in the two models can be understood by the hydrogen poisoning in the 1-site model and the lack thereof in the 2-site model. In liquid water, the experimental LA reaction order is approximately zero.22 4.3 Rate control analysis To identify rate controlling steps and intermediates in the reaction network and to study the sensitivity of the TOF with regards to the free energy of adsorbed species and TSs, we used Campbell’s degree of rate control analysis32 at a reaction temperature of 423 K and reactant fugacities corresponding to 10 bar hydrogen partial pressure and an aqueous 0.45 M LA solution. The kinetic degree of rate control is defined as,



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kLM (s) hn- = E-D k(− ) @QR

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(16)

,4 ,@7

where E-D and E6d are the free energy of activation of reaction step i and adsorbed species n,

respectively. Similarly, the thermodynamic degree of rate control is defined as kLM (s) n- = E-d k(− ) @

(17)

QR ,4 ,@7

Both the 1- and 2-site models suggest that LA adsorption (hn(1 − l) = 0.52, hn(2 −

l) = 0.26) and the first LA hydrogenation to an alkoxy intermediate (hn(1 − l) =

0.48, hn(2 − l) = 0.74) are the rate controlling elementary reaction steps. Next, our thermodynamic rate control analysis suggest for the 1-site model that a too strong hydrogen adsorption limits the overall reaction rate. In contrast, for the 2-site model we find both I-40, which is on the dominant reaction pathway, and I-20, which is a derivative of AGL, to bind too strongly to the Ru surface and are rate controlling. 5. Conclusion Various reaction pathways for the hydrodeoxygenation of levulinic acid to produce γ-

valerolactone have been studied on a Ru(0001) model catalyst surface using planewave density functional theory and mean-field microkinetic modeling at reaction conditions characteristic of a non-polar reaction environment. It is found that reaction pathways involving angelica-lactone and 4-hydroxypentanoic acid are not on the dominant reaction pathway. Instead, the dominant reaction pathway follows a hydrogenation step to an alkoxy intermediate followed by ring formation and C-OH bond cleavage. AGL reaction pathways lead to surface poisoning at higher 24 ACS Paragon Plus Environment

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temperatures when these pathways become kinetically accessible. As a result of possible hydrogen poisoning at low temperatures and AGL poisoning at high temperatures, we find two different activity regimes based on the operating temperature that lead to very different activation energies. Overall, when comparing our simulation results to experimental data, we observe good agreement at all reaction conditions except at low temperatures such as 323 K where our model significantly under-predicts the turnover frequency such that we conclude that Ru(0001) sites are likely not the active site at low temperatures although they might be the active site at higher temperatures. Associated content Supporting Information The supporting information is available free of charge on the ACS publication website at DOI: Optimized structures, equilibrium and rate constants, development of microkinetic model, steady state reaction rates and coverages, rate control analysis, and further discussion of reaction pathways of lesser importance are provided in the supporting information (PDF). Also, we list the coordinates of all gas phase molecules, surface species, and transition states in POSCAR format in three different text files (Molecules.txt, surface species.txt, and TS.txt). Notes The authors declare no competing financial interest. Acknowledgements We gratefully acknowledge financial support from the National Science Foundation (CBET1159863). M.S. acknowledges support from the U.S. Department of Energy, Office of Basic Energy Sciences, under contract DE-SC0007167. This research used resources of the National 25 ACS Paragon Plus Environment


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Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC0205CH11231. A portion of the research was performed using EMSL, a DOE Office of Science User Facility sponsored by the Office of Biological and Environmental Research.


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References 1. Luo, W.; Sankar, M.; Beale, A. M.; He, Q.; Kiely, C. J.; Bruijnincx, P. C. A.; Weckhuysen, B. M. High Performing and Stable Supported Nano-Alloys for the Catalytic Hydrogenation of Levulinic Acid to γValerolactone. Nat. Commun. 2015, 6, 6540. 2. Manzer, L. E. Catalytic Synthesis of Α-Methylene-γ-Valerolactone: A Biomass-Derived Acrylic Monomer. Appl. Catal., A 2004, 272, 249-256. 3. Yan, Z.-p.; Lin, L.; Liu, S. Synthesis of γ-Valerolactone by Hydrogenation of Biomass-Derived Levulinic Acid over Ru/C Catalyst. Energy Fuels 2009, 23, 3853-3858. 4. Braden, D. J.; Henao, C. A.; Heltzel, J.; Maravelias, C. C.; Dumesic, J. A. Production of Liquid Hydrocarbon Fuels by Catalytic Conversion of Biomass-Derived Levulinic Acid. Green Chem. 2011, 13, 1755-1765. 5. Ftouni, J.; Muñoz-Murillo, A.; Goryachev, A.; Hofmann, J. P.; Hensen, E. J. M.; Lu, L.; Kiely, C. J.; Bruijnincx, P. C. A.; Weckhuysen, B. M. ZrO2 Is Preferred over TiO2 as Support for the Ru-Catalyzed Hydrogenation of Levulinic Acid to γ-Valerolactone. ACS Catal. 2016, 6, 5462-5472. 6. Lee, J.; Xu, Y.; Huber, G. W. High-Throughput Screening of Monometallic Catalysts for AqueousPhase Hydrogenation of Biomass-Derived Oxygenates. Appl. Catal., B 2013, 140–141, 98-107. 7. Michel, C.; Zaffran, J.; Ruppert, A. M.; Matras-Michalska, J.; Jedrzejczyk, M.; Grams, J.; Sautet, P. Role of Water in Metal Catalyst Performance for Ketone Hydrogenation: A Joint Experimental and Theoretical Study on Levulinic Acid Conversion into Gamma-Valerolactone. Chem. Commun. 2014, 50, 12450-12453. 8. Mamun, O.; Walker, E.; Faheem, M.; Bond, J. Q.; Heyden, A. Theoretical Investigation of the Hydrodeoxygenation of Levulinic Acid to γ-Valerolactone over Ru(0001). ACS Catal. 2016, 215-228. 9. Kresse, G.; Furthmüller, J. Efficiency of Ab-Initio Total Energy Calculations for Metals and Semiconductors Using a Plane-Wave Basis Set. In Computational Materials Science, 1996; Vol. 6, pp 1550. 10. Kresse, G.; Hafner, J. Ab Initio Molecular Dynamics for Liquid Metals. Phys. Rev. B 1993, 47, 558561. 11. Kresse, G.; Joubert, D. From Ultrasoft Pseudopotentials to the Projector Augmented-Wave Method. Phys. Rev. B 1999, 59, 1758-1775. 12. Blöchl, P. E. Projector Augmented-Wave Method. Phys. Rev. B 1994, 50, 17953-17979. 13. Methfessel, M.; Paxton, A. T. High-Precision Sampling for Brillouin-Zone Integration in Metals. Phys. Rev. B 1989, 40, 3616-3621. 14. Perdew, J. P.; Burke, K.; Ernzerhof, M. Generalized Gradient Approximation Made Simple. Phys. Rev. Lett. 1996, 77, 3865-3868. 15. Řezáč, J.; Hobza, P. Describing Noncovalent Interactions Beyond the Common Approximations: How Accurate Is the “Gold Standard,” CCSD(T) at the Complete Basis Set Limit? J. Chem. Theory Comput. 2013, 9, 2151-2155. 16. Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. A Consistent and Accurate Ab Initio Parametrization of Density Functional Dispersion Correction (DFT-D) for the 94 Elements H-Pu. J. Chem. Phys. 2010, 132, 154104. 17. Tkatchenko, A.; Scheffler, M. Accurate Molecular Van Der Waals Interactions from Ground-State Electron Density and Free-Atom Reference Data. Phys. Rev. Lett. 2009, 102, 073005. 18. Monkhorst, H. J.; Pack, J. D. Special Points for Brillouin-Zone Integrations. Phys. Rev. B 1976, 13, 5188-5192. 19. Henkelman, G.; Uberuaga, B. P.; Jónsson, H. A Climbing Image Nudged Elastic Band Method for Finding Saddle Points and Minimum Energy Paths. J. Chem. Phys. 2000, 113, 9901-9904. 27 ACS Paragon Plus Environment


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20. Henkelman, G.; Jónsson, H. A Dimer Method for Finding Saddle Points on High Dimensional Potential Surfaces Using Only First Derivatives. J. Chem. Phys. 1999, 111, 7010-7022. 21. Heyden, A.; Bell, A. T.; Keil, F. J. Efficient Methods for Finding Transition States in Chemical Reactions: Comparison of Improved Dimer Method and Partitioned Rational Function Optimization Method. J. Chem. Phys. 2005, 123, 14. 22. Abdelrahman, O. A.; Heyden, A.; Bond, J. Q. Analysis of Kinetics and Reaction Pathways in the Aqueous-Phase Hydrogenation of Levulinic Acid to Form γ-Valerolactone over Ru/C. ACS Catal. 2014, 4, 1171-1181. 23. Ahlrichs, R.; Bär, M.; Häser, M.; Horn, H.; Kölmel, C. Electronic Structure Calculations on Workstation Computers: The Program System Turbomole. Chem. Phys. Lett. 1989, 162, 165-169. 24. Schafer, A.; Klamt, A.; Sattel, D.; Lohrenz, J. C. W.; Eckert, F. Cosmo Implementation in Turbomole: Extension of an Efficient Quantum Chemical Code Towards Liquid Systems. Phys. Chem. Chem. Phys. 2000, 2, 2187-2193. 25. Hindmarsh, A. C.; Brown, P. N.; Grant, K. E.; Lee, S. L.; Serban, R.; Shumaker, D. E.; Woodward, C. S. Sundials: Suite of Nonlinear and Differential/Algebraic Equation Solvers. ACM Trans. Math. Softw. 2005, 31, 363-396. 26. Serrano-Ruiz, J. C.; West, R. M.; Dumesic, J. A. Catalytic Conversion of Renewable Biomass Resources to Fuels and Chemicals. Annu. Rev. Chem. Biomol. Eng. 2010, 1, 79-100. 27. Lu, J.; Behtash, S.; Mamun, O.; Heyden, A. Theoretical Investigation of the Reaction Mechanism of the Guaiacol Hydrogenation over a Pt(111) Catalyst. ACS Catal. 2015, 2423-2435. 28. Lu, J.; Faheem, M.; Behtash, S.; Heyden, A. Theoretical Investigation of the Decarboxylation and Decarbonylation Mechanism of Propanoic Acid over a Ru(0 0 0 1) Model Surface. J. Catal. 2015, 324, 1424. 29. Faheem, M.; Saleheen, M.; Lu, J.; Heyden, A. Ethylene Glycol Reforming on Pt(111): FirstPrinciples Microkinetic Modeling in Vapor and Aqueous Phases. Catal. Sci. Technol. 2016, 6, 8242-8256. 30. Grabow, L.; Hvolbæk, B.; Nørskov, J. Understanding Trends in Catalytic Activity: The Effect of Adsorbate–Adsorbate Interactions for Co Oxidation over Transition Metals. Top. Catal. 2010, 53, 298310. 31. Lange, J.-P.; Price, R.; Ayoub, P. M.; Louis, J.; Petrus, L.; Clarke, L.; Gosselink, H. Valeric Biofuels: A Platform of Cellulosic Transportation Fuels. Angew. Chem. Int. Ed. 2010, 49, 4479-4483. 32. Stegelmann, C.; Andreasen, A.; Campbell, C. T. Degree of Rate Control: How Much the Energies of Intermediates and Transition States Control Rates. J. Am. Chem. Soc. 2009, 131, 8077-8082.


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Table 1: Species nomenclature, chemical formula, binding mode and number of adsorption sites of various surface species.

Species LA Al Hy HPA I-01 I-02 I-03 I-04 I-05 I-06 I-07 I-08 I-09 I-10 I-11 I-12 I-13 I-14 I-15 I-16 I-17 I-18 I-19 I-20 I-21 I-22 I-23 I-24 I-25 I-26 I-27 I-28 I-29 I-30 I-31 I-32 I-33

Chemical Formula

nr − ns − nr − nr − nssr nr − nrustv − nr − nr − nssr nr − nt (sr) − nr − nr − nssr nr − nr(sr) − nr − nr − nssr nr − ns − nt r − nr − nssr nr − ns − nt r − nr − nsst n sr (nr )(s)(s) n sr (nr )(sr)(s) nr − n sr (sr) = s nr − ns − nt r − nr − nt s nr − ns − nr − nr − nt s nr − n sr = s nr − nr(sr) − nt r − nr − nssr nr − nt r − nr − nr − nssr nr − nt (sr) − nt r − nr − nssr nr − nt r − nt r − nr − nssr nr − nr(sr) − nt r − nr − nt s nr − nt r − nr − nr − nsst nr − n − nr − nr − nssr nr − n sr − sr nr − n − nt r − nr − nssr nr − nr(st) − nt r − nr − nt s nr − nt (sr) − nt r − nr − nt s nr − nt r − nt r − nr − nsst nr − n − nr − nr − nsst nr − n sr − sr nr − n sr − sr nr − n sr = s nr − n − nt r − nr − nsst nr − nr(sr) − nr − nr − nt s nr − nt (sr) − nr − nr − nt s nr − nrustv − nr − nr − nt s nr − nt (sr) − nt r − nr − nsst nr (sr) − n sr − sr nr − nt (sr) − nr − nr − nsst nr (sr) − n sr = s nr − nr(sr) − nr − nr − nt (sr)

Binding mode

o p (s, s) o p (s, s) o p (s, n) o p (s, n, s) o p (s, n, s) o p (s, s, s, n) o p (n, s) o p (n, s) o p (s, s) o p (s, n, s) o p (s, n, s) o p (n, s) o p (s, n, n) o p (n, s) o p (n, n, s) o p (n, n, s) o p (n, n, s) o p (s, s, n) o p (n) o p (n, s) o p (s, n, n) o p (s, n, n) o p (s, n, n, n) o p (s, s) o p (s, s, n) o p (n, n) o p (n, n) o p (n, s) o p (s, s, n) o p (s, n, s) o p (n, n) o p (s, s, n) o p (s, s, n, n) o p (n, s) o p (s, s, n) o p (s, s) o p (s, n)

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No. of Adsorption site 2 2 2 3 3 4 2 2 2 3 3 2 3 2 3 3 3 3 2 2 3 3 3 2 3 2 2 2 3 3 2 3 4 2 3 2 2 29


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

I-34 I-35 I-36 I-37 I-38 I-39 I-40 AGL GVL OH H H2 O O

nr − nr(sr) − nr − nr − nt (sr) nr − nrustv − nr − nr − nt (sr) nr − nrustv − nr − nr − nt (sr) nr − ns − nr − nr − nsst nr − nr(st) − nr − nr − nsst n sr (nr )(st)(st) n sr (nr )(st)(sr) nr − n sr = s nr − n sr = s sr r H2O O

o p (n) o p (s, n) o p (s, n) o p (s, s, s) o p (s, s, s) o p (s, s) o p (s) o p (n, n) o p (s, s) o p (s) o p (r) o p (s) o p (s)

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1 2 2 3 3 2 1 2 2 1 1 1 1


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Table 2: Zero-point corrected reaction and activation energies, imaginary frequencies of the transition state structures, and free energies of reaction and activation for all elementary reactions at 423K.

Step ¢ £ ¤ ¦ § ¨ ª « ¢ £ ¤ ¦ § ¨ ª « ¢ ¢ ¢¢ ¢£ ¢¤ ¢¦ ¢§ ¢¨ ¢ª ¢« £ £ £¢ ££ £¤ £¦

Reaction

() + 2 ∗→ ∗ r () + 2 ∗→ 2r ∗ ∗ +r ∗→ L ∗ + ∗ ∗ +r ∗→ r¥ ∗ + ∗ L ∗ +r ∗→ r' ∗ r¥ ∗ +r ∗→ r' ∗ ∗ +2 ∗→ © − 1 ∗ +r ∗ ∗ +2 ∗→ © − 7 ∗ +sr ∗ © − 1 ∗ +2 ∗→ © − 2 ∗ +r ∗ © − 2 ∗→ © − 3 ∗ +2 ∗ © − 3 ∗ +r ∗→ © − 4 ∗ + ∗ © − 1 ∗ + ∗→ © − 6 ∗ +sr ∗ © − 1 ∗→ © − 5 ∗ + ∗ © − 5 ∗ + ∗→ E ∗ +sr ∗ © − 7 ∗ + ∗→ © − 6 ∗ +r ∗ © − 6 ∗→ E ∗ + ∗ © − 7 ∗→ © − 8 ∗ + ∗ E ∗ +r ∗→ © − 8 ∗ + ∗ © − 4 ∗ + ∗→ E ∗ +sr ∗ r' ∗ + ∗→ © − 9 ∗ +r ∗ r' ∗∗∗→ © − 10 ∗∗ +sr ∗ © − 9 ∗ + ∗→ © − 11 ∗ +r ∗ © − 9 ∗ + ∗→ © − 12 ∗ +sr ∗ © − 9 ∗ + ∗→ © − 13 ∗ +sr ∗ © − 10 ∗ +2 ∗→ © − 12 ∗ +r ∗ © − 10 ∗ +2 ∗→ © − 14 ∗ +r ∗ © − 10 ∗ + ∗→ © − 15 ∗ +r ∗ © − 10 ∗→ © − 16 ∗ © − 11 ∗ + ∗→ © − 17 ∗ +sr ∗ © − 11 ∗ + ∗→ © − 19 ∗ +sr ∗ © − 12 ∗ + ∗→ © − 17 ∗ +r ∗ © − 12 ∗→ © − 20 ∗ +r ∗ © − 13 ∗ + ∗→ © − 18 ∗ +r ∗ © − 13 ∗ + ∗→ © − 19 ∗ +r ∗ © − 14 ∗→ © − 20 ∗ +r ∗

∆ (eV)

∆‡ (eV)

-1.33 -1.30 0.06 0.88 0.76 -0.05 -0.47 -0.61 -0.94 0.85 0.74 -0.83 0.40 -0.38 -0.70 0.86 0.52 0.37 -0.62 -0.22 -0.34 -0.56 -0.82 -0.73 -0.71 -0.98 -0.23 0.28 -0.60 -0.73 -0.33 -0.58 -0.32 -0.55 -0.31

N/A N/A 0.67 1.36 1.29 0.76 0.21 0.71 0.32 2.07 0.90 0.81 0.93 0.24 0.54 1.08 0.87 0.70 0.51 0.51 0.99 0.29 0.44 0.44 0.30 0.34 0.06 0.81 1.03 0.37 0.19 0.40 0.42 0.74 1.09

∆(, ) ∆‡ (, ) ( ) N/A N/A 818 1249 1194 964 780 264 1090 375 1287 332 N/A 173 794 291 266 919 223 814 241 899 326 331 936 1277 796 N/A 413 319 814 1330 1121 879 880

-0.42 -0.82 0.09 0.87 0.78 0.00 -0.42 -0.54 -0.94 0.87 0.72 -0.87 0.39 -0.35 -0.75 0.90 0.49 0.33 -0.61 -0.23 -0.38 -0.57 -0.84 -0.71 -0.69 -0.93 -0.25 0.32 -0.65 -0.70 -0.37 -0.61 -0.33 -0.56 -0.37

N/A N/A 0.70 1.35 1.23 0.76 0.29 0.75 0.29 2.07 0.92 0.80 0.89 0.25 0.48 1.14 0.89 0.68 0.55 0.49 1.01 0.28 0.39 0.45 0.30 0.34 0.09 0.82 1.04 0.43 0.18 0.36 0.41 0.71 1.06



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

£§ £¨ £ª £« ¤ ¤ ¤¢ ¤£ ¤¤ ¤¦ ¤§ ¤¨ ¤ª ¤« ¦ ¦ ¦¢ ¦£ ¦¤ ¦¦ ¦§ ¦¨ ¦ª ¦« § § §¢ §£ §¤ §¦ §§ §¨ §ª §« ¨ ¨ ¨¢ ¨£ ¨¤ ¨¦ ¨§ ¨¨ ¨ª ¨«

© − 14 ∗ + ∗→ © − 21 ∗ +r ∗ © − 15 ∗ +2 ∗→ © − 17 ∗ +r ∗ © − 15 ∗ +2 ∗→ © − 21 ∗∗∗ +r ∗ © − 15 ∗∗→ © − 22 ∗∗ © − 16 ∗∗ + ∗→ © − 22 ∗ +r ∗ © − 17 ∗→ © − 23 ∗ + ∗ © − 17 ∗ + ∗→ © − 25 ∗ +r ∗ © − 18 ∗ + ∗→ © − 6 ∗ +r ∗ © − 18 ∗→ © − 24 ∗ + ∗ © − 19 ∗ + ∗→ © − 6 ∗ +r ∗ © − 20 ∗→ © − 24 ∗ © − 20 ∗ +2 ∗→ © − 25 ∗ +r ∗ © − 21 ∗ + ∗→ © − 25 ∗ +r ∗ © − 21 ∗→ © − 8 ∗ + ∗ © − 22 ∗ + ∗→ © − 8 ∗ +r ∗ © − 22 ∗ + ∗→ © − 23 ∗ +r ∗ © − 23 ∗ + ∗→ E ∗ +r ∗ © − 29 ∗→ © − 4 ∗ +2 ∗ E ∗ +r ∗→ © − 24 ∗ + ∗ © − 25 ∗→ E ∗ + ∗ © − 24 ∗ +r ∗→ E ∗ + ∗ r' ∗ + ∗→ © − 26 ∗ +sr ∗ © − 26 ∗→ © − 27 ∗ +r ∗ © − 26 ∗ + ∗→ © − 13 ∗ +r ∗ © − 26 ∗ + ∗→ © − 28 ∗ +r ∗ © − 27 ∗ +2 ∗→ © − 19 ∗ +r ∗ © − 27 ∗ +2 ∗→ © − 7 ∗ +r ∗ © − 28 ∗ + ∗→ © − 7 ∗ +r ∗ © − 28 ∗ + ∗→ © − 18 ∗ +r ∗ © − 8 ∗ +r ∗→ E ∗ + ∗ r¥ ∗→ © − 30 ∗ r¥ ∗ +2 ∗→ © − 11 ∗ +r ∗ r¥ ∗ + ∗→ © − 27 ∗ +sr ∗ r¥ ∗ + ∗→ © − 15 ∗ +sr ∗ r¥ ∗ +2 ∗→ © − 31 ∗ +r ∗ © − 30 ∗ + ∗→ © − 22 ∗ +sr ∗ © − 30 ∗ + ∗→ © − 32 ∗ +r ∗ © − 31 ∗ + ∗→ © − 21 ∗ +sr ∗ © − 31 ∗→ © − 32 ∗ + ∗ © − 31 ∗ +2 ∗→ © − 29 ∗ +r ∗ © − 32 ∗ + ∗→ © − 4 ∗ +r ∗ © − 29 ∗→ © − 25 ∗ +sr ∗ E ∗→ E () + 2 ∗ sr ∗ +r ∗→ r s ∗ + ∗

-0.36 -0.81 -1.11 0.16 -0.35 0.57 -1.02 -0.86 0.50 -0.63 0.85 -0.78 -0.73 0.76 -0.50 -0.40 -0.47 1.03 0.50 1.12 0.00 -0.66 -0.33 -0.30 -0.88 -0.52 -0.45 0.10 0.26 0.13 0.04 -0.83 -1.04 -0.62 -0.73 -0.42 -0.57 -1.00 0.12 -1.01 -0.10 -0.72 1.01 0.58

0.20 0.22 0.26 0.48 0.52 1.29 0.31 0.50 0.77 0.31 2.25 0.57 0.28 0.80 0.73 0.29 0.72 1.51 0.56 1.16 0.84 0.15 0.73 0.42 0.36 0.30 0.51 0.80 0.96 0.97 0.60 0.09 0.58 0.84 0.44 0.86 0.25 0.53 0.67 0.09 0.81 0.50 N/A 1.16

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804 938 1028 263 825 410 1137 560 265 1286 463 785 966 282 1216 721 1208 N/A 698 321 923 254 962 853 1237 435 1269 736 856 714 N/A 934 309 392 951 206 1297 405 N/A 949 876 281 N/A 1105

-0.35 -0.82 -1.03 0.24 -0.33 0.66 -0.93 -0.89 0.52 -0.66 0.95 -0.69 -0.71 0.74 -0.53 -0.40 -0.46 1.03 0.51 1.13 -0.03 -0.67 -0.32 -0.26 -0.83 -0.51 -0.42 0.10 0.24 0.15 0.13 -0.81 -1.01 -0.65 -0.67 -0.45 -0.63 -1.01 0.08 -1.01 -0.06 -0.71 0.07 0.52

0.21 0.26 0.30 0.60 0.54 1.41 0.36 0.48 0.80 0.30 2.27 0.64 0.28 0.82 0.75 0.30 0.69 1.59 0.56 1.17 0.85 0.14 0.72 0.42 0.37 0.33 0.52 0.76 0.95 0.97 0.61 0.12 0.60 0.84 0.42 0.83 0.26 0.52 0.56 0.10 0.84 0.52 N/A 1.13 32

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


ª ª ª¢ ª£ ª¤ ª¦ ª§ ª¨ ªª ª« « « «¢ «£ «¤ «¦ «§

r' ∗ +r ∗→ © − 33 ∗ +2 ∗ © − 39 ∗ +r ∗→ © − 40 ∗ +2 ∗ © − 26 ∗ +r ∗→ © − 34 ∗ +3 ∗ © − 33 ∗→ © − 34 ∗ +sr ∗ © − 33 ∗ + ∗→ © − 35 ∗ +r ∗ L ∗ +r ∗→ © − 35 ∗ + ∗ L ∗→ © − 40 ∗ + ∗ © − 34 ∗ +2 ∗→ © − 36 ∗ +r ∗ © − 35 ∗ + ∗→ © − 36 ∗ +sr ∗ © − 36 ∗→ © − 16 ∗ © − 40 ∗ +2 ∗→ E ∗ +sr ∗ ∗ +2 ∗→ © − 37 ∗ +r ∗ © − 37 ∗ +r ∗→ © − 38 ∗ © − 38 ∗→ © − 39 ∗ + ∗ r s ∗→ r s() +∗ sr ∗ + ∗→ r*+O* r' ∗→ r'() +∗

0.55 -0.04 0.83 -0.37 -0.25 1.06 0.22 -0.44 -0.56 0.21 -0.24 -1.13 0.45 1.01 0.55 -0.84 1.33

1.02 0.32 1.54 0.29 0.64 1.41 0.33 0.59 0.75 1.28 0.04 0.06 0.68 1.49 N/A 0.65 N/A

1311 1226 847 223 900 1350 138 1280 501 293 241 1045 486 N/A N/A 1310 N/A

0.56 -0.05 0.82 -0.41 -0.26 1.07 0.24 -0.44 -0.58 0.23 -0.24 -1.11 0.46 1.03 0.04 -0.82 0.41

1.03 0.32 1.49 0.25 0.65 1.44 0.37 0.60 0.78 1.31 0.05 0.04 0.71 1.59 N/A 0.66 N/A



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Table 3: Computed turnover frequencies at various reaction temperatures, hydrogen partial pressures, and 0.45 M LA solution. a) 1-site model TOF (s-1)

Temperature (K)

4 323 373 423 473 523

6.66 × 10-9 2.53 × 10-5 4.10 × 10-3 1.07 × 10-1 3.00 × 10-1

Hydrogen partial pressure (bar) 10 20 2.67 × 10-9 1.62 × 10-5 3.44 × 10-3 9.97 × 10-2 3.37 × 10-1

1.34 × 10-9 9.43 × 10-6 2.71 × 10-3 8.78 × 10-2 3.52 × 10-1

40 6.68 × 10-10 4.97 × 10-6 1.85 × 10-3 7.02 × 10-2 3.52 × 10-1

b) 2-site model TOF (s-1)

Temperature (K)

4 323 373 423 473 523

1.64 × 10-6 3.23 × 10-4 9.52 × 10-3 1.09 × 10-2 2.09 × 10-2

Hydrogen partial pressure (bar) 10 20 2.23 × 10-6 4.38 × 10-4 1.30 × 10-2 1.64 × 10-2 3.23 × 10-2

2.81 × 10-6 5.52 × 10-4 1.64 × 10-2 2.24 × 10-2 4.47 × 10-2

40 3.53 × 10-6 6.95 × 10-4 2.08 × 10-2 3.03 × 10-2 6.14 × 10-2


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 1: Possible reaction pathways for the hydrodeoxygenation (HDO) of levulinic acid (LA) to γ-valerolactone (GVL). Pathways involving the formation of angelica lactone (AGL) are displayed with red arrows. Zero-point corrected reaction energies for various gas phase reactions have been computed at the PBE-D3 level of theory.



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(A)

(B)


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2: Different pathways for LA hydrodeoxygenation to form GVL via LA hydrogenation to HPA, subsequent dehydration and dehydrogenation to form AGL, followed by hydrogenation of AGL to form GVL. A) Pathways leading to GVL formation via –OH group removal of HPA. B) Pathways for HPA to AGL formation via intermediate I-9 and I-10.



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(A)

(B) Figure 3: Different pathways for LA dehydration to form AGL. A) LA conversion to AGL via intermediate I-1 and I-7. B) Pathways for LA to AGL formation via intermediate Hy. 38 ACS Paragon Plus Environment

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Figure 4: Reaction pathways for the LA hydrodeoxygenation to GVL via direct catalytic conversion computed previously.8 The reaction pathway marked in green shows the dominant reaction mechanism when including all reaction pathways including those shown in Figure 2 and 3.



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(a)

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(b)

(c) Figure 5: Turnover frequencies for the HDO of LA predicted by the mean-field microkinetic model on Ru(0001) for 1-site competitive reaction mechanism at a) 0.025 M LA solution, b) 0.45 M LA solution, and c) 1.5 M LA solution. Apparent activation energies at both low temperature (323 - 423 K) and high temperature (423 - 523 K) regions are reported for varying hydrogen partial pressures.


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(a)

(b)

(c) Figure 6: Turnover frequencies for the HDO of LA predicted by the mean-field microkinetic model on Ru(0001) for the 2-site model at a) 0.025 M LA solution, b) 0.45 M LA solution, and c) 1.5 M LA solution. Apparent activation energies in both the low temperature (323 – 423 K) and high temperature (423 – 523 K) regions are reported for varying hydrogen partial pressures.



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(a)

(b)

(c)

(d)

Figure 7: Reaction orders calculated for the HDO of LA on Ru(0001). a) Reaction order of LA at various temperatures (323, 423 and 523 K) and 10 bar hydrogen partial pressure for a 1-site model, b) reaction order of hydrogen at various reaction temperatures (323, 423 and 523 K) and a fugacity of LA corresponding to a 0.45 M aqueous LA solution for a 1-site model, c) reaction order of LA at various temperatures (323, 423 and 523 K) and 10 bar hydrogen partial pressure for a 2-site model, and d) reaction order of hydrogen at various reaction temperatures (323, 423


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and 523 K) and a fugacity of LA corresponding to a 0.45 M aqueous LA solution for a 2-site model. TOC graphic


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