Engineering Molecular Transformations for Sustainable Energy

Ind. Eng. Chem. Res. 2010, 49, 10183–10199

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Engineering Molecular Transformations for Sustainable Energy Conversion Matthew Neurock* Departments of Chemical Engineering and Chemistry, UniVersity of Virginia, CharlottesVille, Virginia 22904

Future strategies for sustainable energy production will undoubtedly require processes and materials that can efficiently convert renewable resources into fuels. Nature’s enzymes can exquisitely integrate highly active catalytic centers within flexible environments that can adaptively guide reactants to products with very high activities and selectivities. They are limited, however, by their stability and ability to integrate into large scale production processes. The design of more robust heterogeneous catalytic materials that mimic the performance of enzymes, however, has been hindered by our limited understanding of how such transformations proceed. The tremendous advances in ab initio quantum mechanical methods, atomistic simulations, and high performance computing that have occurred over the past two decades, however, provide unprecedented ability to track molecular transformations and how they proceed at specific sites and within particular environments. This information together with the advances in in situ spectroscopic methods that follow such transformations can begin to enable the design of atomic surface ensembles and nanoscale reaction environments. This paper provides the author’s perspective on how theory and simulation can be used to move from current onedimensional design efforts based on catalytic descriptors to the design of two-dimensional surfaces, threedimensional reaction environments, and proton-coupled electron transfer systems that mimic enzymes in the transformation of molecules. Introduction The sustainable production of energy presents one of the greatest societal challenges that we will face over the next few decades. Many of the proposed technologies to supply future energy demands are based on catalytic processes that convert renewable as well as nonrenewable resources into fuels.1-5 This includes catalytic conversion of natural gas, coal, and lignocellulose to fuels; electrocatalytic conversion of fuels to electrical energy; photocatalytic routes to split water to produce H2 and O2; and photo- or electrocatalytic processes to reduce of CO2 to fuels. Optimizing these processes will require integrated catalyst, reactor, and process design strategies and novel approaches that efficiently utilize light as well as electrons to selectively activate specific bonds and control molecular transformations. Such efforts will not be possible without the ability to elucidate the elementary bond-breaking and -making processes that must occur, establish the influence of the complex chemical environment on such steps, and follow these transformations as they proceed. Although there have been important advances in the development of novel processes and catalytic materials to carry out these conversions, their efficiencies are far too low to be viable strategies.1 The catalytic efficiencies of the materials used are governed by their ability to actively and selectively perform specific and precise molecular transformations. The challenges associated with each of these conversion strategies are rather unique and depend upon the molecules that make up the feedstock, the specific molecular transformations required, and the complex environments in which these reactions are carried out. In the conversion of fuel precursors or bio-oils derived from lignocellulose, the complex multicomponent nature of the feed streams, the multiple reaction sites on each molecule, the low hydrogen and high oxygen content, and the presence of solution and debris from the initial biological or chemical biomass deconstruction steps present significant challenges for the efficient catalytic conversion to fuels or chemicals. In the * E-mail: [email protected].

activation of methane, advanced catalytic materials are needed that can selectively activate a single C-H bond, functionalize the carbon center, and remove the more reactive product that forms to prevent subsequent unselective C-H bond activation steps from proceding. The efficiency of proton exchange membrane fuel cells is limited by the activity and durability of the catalysts at the anode and cathode that must activate specific C-H, O-H, or OdO bonds while simultaneously transferring protons to the polymer electrolytic and electrons to the support. The photocatalytic oxidation of water to O2 and H2 and photocatalytic reduction of CO2 present the added challenges of efficiently absorbing light, creating and separating electron-hole pairs, and utilizing the electrons or the holes to carry out catalytic oxidation or reduction. Whereas the design and synthesis of such active, selective, and robust heterogeneous catalytic materials and processes present significant challenges, nature has evolved enzymes that can efficiently catalyze such transformations.6-9 These are highly integrated systems consisting of molecular reaction centers embedded in unique reaction environments that can adaptively control specific bond-breaking and -forming steps together with proton-coupled electron transfer.7 Figure 1, for example, shows the binding of a methanol molecule to an active site in methanol dehydrogenase. The metal center and its unique ligand sphere (Figure 1A) dictate the electronic properties as well as the structural features of the active site and control which molecules adsorb, their mode and strength of adsorption, and their reactivity. The flexible protein backbone (Figure 1B) dynamically adjusts only to specific substrate molecules forming an active cavity around the reaction center that orients the substrate molecule into an active state through multiple point contacts and helps to guide the substrate along a low potential energy path through electrostatic stabilization, hydrogen-bonding, and weak van der Waal interactions.7-11 The protein cavity can also create local hydrophobic or hydrophilic environments to promote specific transformations. In addition, other reactive centers (Figure 1C) within the enzyme can cooperatively communicate with the active site

10.1021/ie101300c  2010 American Chemical Society Published on Web 10/11/2010

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Ind. Eng. Chem. Res., Vol. 49, No. 21, 2010

Figure 1. The structure of methanol dehydrogenase: (A) active center, (B) flexible protein cavity, and (C) other possible metal centers.

Figure 2. Schematic structure of the reaction environment for a carbonsupported bimetallic particle for aqueous phase electrocatalysis including the metal alloy, carbon support, solution phase, and polymer electrolyte.

through electron transfer. As such, enzymes provide adaptive reaction environments that allow for molecular recognition of the substrate and dynamically drive its transformation to product. Despite their unprecedented activities and selectivities, enzymes are limited by their stability and by difficulties associated with adopting them in large-scale energy production processes.5 This motivates the development of active, stable yet flexible catalytic materials that can result in activities and selectivities that rival enzymes but are durable enough to withstand the harsh operating environments for extended periods of operation. The supported metal, metal oxide, and metal sulfide catalysts that are currently used in many of the catalytic refining and chemical processes are quite different from enzymes in that they predominantly catalyze reactions on their external surfaces and lack the flexible three dimension cavities offered by the enzymes. Zeolites and other micro- and mesoporous materials are known exceptions; they offer well-defined 3D networks. Although these materials provide significant structural control, their inorganic frameworks are rather rigid, lacking the flexibility and the adaptive multipoint control of enzymes.6,12 Despite this lack of 3D control, conventional supported heterogeneous catalysts offer a number of features that can be tuned, however, to provide for efficient 2D control and in some cases begin to approach 3D control through the use of novel organic/inorganic hybrid materials, solvents, or well-controlled microporous systems. Our ability to tune these materials for the efficient conversion of renewable and nonrenewable sources will inevitably require more in-depth understanding of how the specific atomic structure influences catalytic activity, selectivity, and durability. Such knowledge will aid in the design of (1) particle size, morphology, and atomic structure; (2) alloy composition and spatial arrangement; (3) support properties and composition; (4) process conditions; (5) solvent effects and solution phase properties; and (6) electro- and photochemical promotion strategies for the complex catalytic materials, such as the supported metal particle shown schematically in Figure 2. Atomic Scale Insights into the Active Catalytic Sites. The tremendous advances in spectroscopy, characterization, and modeling that have occurred over the past two decades begin to provide insights in the atomic scale features of activate sites and local reaction environments under operating conditions and

elucidate how they control catalytic performance.1,6,13 In situ scanning tunneling microscopy, atomic force microscopy, and high-resolution transmission electron microscopy can currently be used to follow the dynamic changes in the atomic surface structure under working reaction conditions for ideal single crystal surfaces as well as for actual supported particles. These efforts, when coupled with in situ spectroscopic signatures derived from Raman, infrared, ultraviolet visible, and other spectroscopic probes, begin to establish the chemical signature of active sites.14 Such efforts have led to unprecedented advances in elucidating the nature of active sites and their environments for advanced catalytic materials. Over the past two decades we have also witnessed exponential advances in computing power, speed, and architectures that allow us to simulate much more realistic catalytic environments and catalytic systems. We have seen exponential increases in computing speeds as the fastest computers have exponentially increased from gigaflop (1.0 × 109 mathematical floating point operations per second) in 1982 for the Cray XMP, to petaflop (1.64 × 1012) for today’s fastest computer, the Jaguar CrayXT5 supercomputer at Oak Ridge National Laboratory.15 The recent invention of nanophotonic avalanche photodetectors by IBM16 is expected to result in microprocessor circuitry that will achieve exaflop (1.0 × 1018) speeds by 2015. The types of problems that we can solve today are tremendously more complex than what was possible in 1982. By 2015, it is likely that we will be able to follow the dynamic changes that result in making and breaking chemical bonds along with the atomic structure of the active site under much more realistic operating conditions and include the direct influence of working surface structure, adlayer composition, the support, and local reaction environment. In addition to the exponential increases in computing speed and memory, there have been tremendous advances in the development of ab initio-based methods to model the elementary bond-making and -breaking catalytic processes. Kohn17,18 and Pople,19 for example, shared the Nobel Prize in 1998 for their pioneering advances in the development of density functional theory and computational methods in quantum chemistry. These efforts have provided a strong foundation for modeling more complex systems, such as heterogeneous catalysis, and a sound and systematic framework for improving the accuracy and


reliability of the results. These developments have been followed by a number of other important advances that have enabled tremendous advances in the accuracy as well as the time and length scales of the problems that we can solve. They include more accurate functionals for density functional theory,8,20-24 fast ab initio molecular dynamics,25 linear scaling methods,26,27 ab initio-based kinetic Monte Carlo simulations,28-39 and novel coarse-graining40-42 and adaptive time-stepper approaches.43,44 The tremendous disparity in time scales that range from picoseconds for electron transfer events to months and years in terms of catalytic processes and length scales that range from angstroms to tens of meters for fixed-bed reactors undoubtably require the integration of numerous modeling approaches to capture elementary bond-making and -breaking processes that occur in complex reaction systems and realistic reactors. Ab initio quantum chemical calculations can, at best, simulate up to 1000 atoms and 100 ps in time. Such simulations, however, require thousands of processors and months of CPU time at national supercomputing centers. Although molecular dynamics simulations can handle millions of atoms and time scales of microseconds and ab initio based kinetic Monte Carlo simulations can follow time and length scales of seconds and micrometers, this still lies significantly short of the time and length scales of actual catalytic systems. Novel coarse graining algorithms40-42 based on the results of higher level simulations, theoretical model constructs, or empirical information can significantly minimize and even eliminate the upfront CPU intensive simulations, thus reducing months worth of ab intio calculations into a few seconds of simuation. In addition, the adaptive-time stepper approaches by Kevrekidis43,44 can use very short bursts of the microscopic KMC simulations to establish the important composition features to take much larger time steps in macroscopic numerical simulations, thus allowing one to move to the simulation of industrial scale reactors. The time and length scales from such simulations would not be possible with KMC simulations alone. Foundations of Computational Catalysis. The pioneering developments that gave rise to what we consider today as computational catalysis came from separate efforts out of the chemistry and solid state physics communities. Hoffmann,45 van Santen46 and Anderson47,48 who were some of the earliest pioneers from the chemistry community, used simple molecular orbital theory and Extended Hu¨ckel based methods in order to demonstrate the orbitals interactions and electronic structural features that control surface reactivity and catalysis. Despite the simplicity in the methods used, the insights and elegant treatments by these authors provided the foundation for understanding a number of important catalytic reactions and have stood the test of time. Newns and Anderson49 who pioneered some of the early developments out of the solid state physics community used band theory to provide a more rigorous treatment of the electronic structure of transition metals and the electronic features that control bonding on these surfaces. This work has provided the strong foundation and basis for many of the theories used today concerning chemisorption and reactivity. Hammer and Nørskov,50 for example, used a number of the guiding principles by Newns and Anderson in the development of the d-band center model which is the most widely used model for relating the electronic structure of solids to their reactivity. Computational Catalysis - Where Are We Today. The recent report “International Assessment of Research and Development in Catalysis by Nanostructured Materials” carried out by the World Technology Evaluation Center13 concluded

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that theory and simulation play an integral role in catalytic science and are successfully being used to: (1) Predict structure and properties of model catalytic systems, (2) Complement and resolve spectroscopic measurements by simulating the resulting spectra, (3) Elucidate catalytic reaction mechanisms, and (4) Begin to guide the search for new catalytic materials. The advances in theory coupled with the exponential increase in computing speed and memory have made it made it possible to calculate the structure, energies, and the resulting spectroscopic properties of molecules and intermediates bound to organometallic structures as well as model catalytic surfaces such as metals, oxides, sulfides, carbides, and nitrides. These results together with in situ spectroscopic analyses have been invaluable in identifying surface intermediates that form under reaction conditions and tracking their reactivity. It is now rather routine to calculate adsorption energies, reaction energies, and even activation barriers for simple elementary steps on well-defined organometallic clusters as well as model single crystal surfaces. Activation barriers for small molecules on ideal surfaces for example take only a day or two to calculate even on modest computing clusters. The ability to readily establish reaction intermediates and calculate their reaction energies and activation barriers has made it possible to construct overall potential energy reaction diagrams and elucidate catalytic reaction mechanisms. Although surface reaction chemistry and kinetics and mechanism will continue to dominate the focus of theory and simulation well into the future, there are a number of growing efforts aimed at using these methods toward the design of new materials.13,51,52 Catalyst Design. One of the most exciting findings from WTEC report on catalysis was the use of theory and simulation in aiding the design of catalytic materials. Catalyst discovery approaches in general tend to take on two characteristically different forms categorized by the balance between the knowledge sought and the speed at which it can be obtained. The slower knowledge-based approaches are often referred to as design, whereas rapid testing methods are referred to as highthroughput or combinatorial screening. Both approaches provide valuable guidance in the development of new materials. The use of theory and simulation in catalyst discovery has followed somewhat similar approaches. The elegant work from Nørskov and colleagues,52-59 Mavrikakis,60-62 and others have nicely demonstrated that theory can be used to identify relevant descriptors of the important attributes of the active catalytic surface. The changes in reactivity that result upon alloying the surface or changing the metal can then be used to screen a wide array of different materials to establish those that are most active and have the lowest cost. These efforts have led to the discovery of more active alloys to carry out specific catalytic reactions including ammonia synthesis,55,56 methanation,57 acetylene hydrogenation,63 and oxygen reduction.64 By way of example, I present some of their results for the hydrogenation of acetylene.63 The results from density functional theoretical calculations were used to show that the optimal metal surfaces should have strong acetylene adsorption energies to maintain high enough activities, yet weak ethylene adsorption energies to promote its desorption and prevent its overhydrogenation to ethane. The methyl binding energy was found to correlate directly with the acetylene heat of adsorption (the red line in Figure 3A) as well as the ethylene heat of adsorption (the blue line in Figure 3A). It was therefore used as a simple descriptor to identify an optimal region of phase space that would promote the adsorption of acetylene while enhancing

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Figure 3. Theory-guided predictions of promising acetylene hydrogenation catalysts. (A) DFT results correlate the methyl heats of adsorption with the ethylene and acteylene heats of adsorption. The region between the red (C2H2) and blue (C2H4) lines establishes alloys that are both active and selective. (B) The optimal methyl binding energies plotted against the price guide the prediction of possible new alloys such as NiZn. (C) A plot of experimental results comparing Pd, PdAg, and NiZn alloys indicates that NiZn alloys have comparably high selectivies at high conversions to PdAg.63 Copyright 2008 American Association for the Advancement of Science.

ethylene desorption. This is the region between the red and blue dotted lines shown in Figure 3A. The methyl binding energy was subsequently used to screen 70 different binary alloy compounds to determine possible candidates that would fall into an acceptable range of this performance criterion. A plot of the methyl binding energy verses the cost of the metals that make up the alloy (Figure 3B) reveals that whereas PdAg alloys provide optimal performance, NiZn alloys should be just as good, yet significantly cheaper. Experimental studies were then carried out to show that these materials indeed had performances that rivaled commercial PdAg catalysts (Figure 3C). Most of the initial efforts in catalyst design have focused on identifying appropriate “descriptors” that control catalytic reactions, such as the metal-adsorbate bond and computationally screening well-defined surfaces to identify new possible leads. Such descriptors focus solely on single point of contact between the adsorbate and the metal and, as such, can be considered one-dimensional design approaches. The Design of Surfaces and Reaction Environments. Many of the difficult reactions of interest discussed previously involve molecules with multiple functional groups that result in added complexity because they can interact with the surface as well as the local reaction environment in a number of ways. Although such complexity complicates the analysis, it also presents clear opportunities for the tailored design of novel 2D and 3D environments that can begin to mimic the multiple point contact and control of molecular transformations that has been the framework of biological systems. There are a growing number of efforts in computational catalysis that have begun to focus on modeling more realistic reaction environments that include the influence of the support, metal particle size and morphology, surface coverage effects, promoters, solution phase effects, and electric fields. Such efforts begin to provide the framework for extending design efforts to two-dimensional surfaces as well as complex three-dimensional environments.6,13,51 In the remainder of this paper, we will discuss various examples primarily from our own work to try to illustrate how theory

can be combined with molecular level simulations to track the transformation of molecules and aid in the design of model catalytic surfaces and systems with 2D and 3D control. Some of the examples are directly related to energy conversion; others do not, but were chosen to help illustrate important design strategies. Designing Alloy Configurations. Most of the previous design efforts discussed above and presented in the literature are based on the Sabatier principle, which suggests that there is an optimal metal-adsorbate bond strength that allows for both bondbreaking and -making processes to readily occur. Although this is an important principle that can be used to suggest active catalytic surfaces, it can significantly restrict the phase space available for design because it considers only one type of surface site and one type of interaction, thus missing out on the fact that different sites can provide unique functions and that the composition as well as the specific arrangement of such sites can enhance specific molecular transformations. By carefully monitoring the steps that control bond-breaking and -making, one can conceivably establish novel alloy surfaces that can carry out different reactions at different sites. This is illustrated in the following two example systems concerning NOx reduction and vinyl acetate synthesis. Two Dimensional Atomic Configurational Design: NO Decomposition. The current restrictions on acceptable levels of NOx from automotive exhaust as well as the strong incentive to commercialize direct-injection diesel and fuel efficient leanburn engines that operate at higher pressures of oxygen present significant challenges for the design of highly active and selective catalytic materials for the NOx reduction.65,66 Current three-way catalysts are typically ineffective under lean conditions because they are readily poisoned by oxygen. To understand the influence of the metal, metal surface structure, and alloying on catalytic performance, density functional theoretical calculations were carried and used to aid in the development of a kinetic database that was used in the development and


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Figure 4. Site specificity for the activation of NO over Pt. DFT-calculated transition states and NO dissociation barriers over (a) Pt(100) and (b) Pt(111) surfaces. The barrier for NO dissociation is 138 kJ/mol lower on the Pt(100) surface than the Pt(111) surface due to the removal of metal-atom-sharing in the transition state. Adapted from ref 29.

Figure 5. Comparison of DFT-calculated NO activation barriers and experimental results from ultrahigh-vacuum, single crystal surface science studies. Both show the unique reactivity of (410) and (210) sites that result from the corrugation of these surfaces, along with the presence of active (100) sites29 (also adapted from ref 115).

application ab initio-based kinetic Monte Carlo simulations for NO decomposition. The DFT results demonstrated that the (100) surface facets of Pt provide unique sites that can readily activate the NO bond.29 NO favorably adsorbs to the bridge sites on the (100) surface and can readily dissociate over the 4-fold site, resulting in a transition state in which the N* and O* atoms bind to two different Pt-Pt bridge sites (Figure 4A). This effectively eliminates metal-atom-sharing in the transition state and thus lowers the repulsion interactions associated with sharing. The dissociation of NO over Pt(111), on the other hand, requires sharing two Pt atoms in the transition state (Figure 4B), which leads to an increase of over 1.1 eV in the calculated activation barrier.29,67 As such, there appears to be significant structure sensitivity, at least at the elementary step level, which is consistent with results from ultrahigh-vacuum studies. This is illustrated in Figure 5, which shows the good agreement between the DFT and the experimental NO activation barriers and the high specificity (lowest barriers) for Pt(410) and in general the more open (100) sites.29 Whereas this structure sensitivity is interesting at vacuum conditions and at an elementary step level, its influence on actual catalytic performance may be quite small, though, since the coordinatively unsaturated sites may be poisoned by O* under lean conditions. To begin to understand the role of the metal, a series of calculations for NO* and O* binding energies as well as NO*

Figure 6. DFT-calculated NO* and O* binding energies and NO dissociation barriers over different transition metals. Results follow the Sabatier’s principle in that the NO activation barriers decrease with increasing oxygen binding energies.

activation energies on different closed packed surfaces of different metals were carried out. The resulting trends, which are shown in Figure 6, indicate that although metals on the lefthand side of the periodic table (Ru, Rh) can readily activate the NO bond, they are very likely poisoned by O*. Metals on the right (Pd, Pt), on the other hand, have significantly weaker M-O* bond strengths but cannot readily activate NO. Both NO* and O* effectively compete for the same bridging sites; thus, anything that is done to increase the adsorption and activation of NO will ultimately be poisoned by O*. A more detailed analysis of the literature shows that although Pt is one of the most active metals for NO decomposition, it is inhibited by oxygen carried out under lean conditions.68,69 Despite the higher intrinsic reactivity of Rh over Pt for NO dissociation, Rh is shut down because it is poisoned by the strongly bound O*. The classic concept of an ideal NO* or O* binding energy that is set by Sabatier’s principle would suggest that alloying Pt with a more noble Group IB metal such as Au, Ag, or Cu should help to weaken the O* binding energy without significant loss the activity of the surface to activate NO*. Ab initio kinetic Monte Carlo simulations were therefore carried out over Pt(100) as well as for a range of different PtxM1-x(100) surface alloys, where M ) Au, Ag, Cu.37,51,70,71 The intrinsic kinetics for these

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Figure 7. Snapshots of representative steady state surface coverages for the lean catalytic decomposition of NO over (a) Pt4Au4 and (b) Pt1Au1 surface alloys from ab initio-based kinetic Monte Carlo simulations. (PNO ) 0.47 Torr, PO2 ) 60.8 Torr, and T ) 713 K). Adapted from refs 51 and 71.

Figure 8. Influence of alloying the Pt(100) with different compositions of Au, Ag, and Cu on the relative steady state turnover frequencies (for the lean catalytic decomposition of NO reported with respect to the decomposition over Pt. (PNO ) 0.47 Torr, PO2 ) 60.8 Torr, and T ) 713 K) Adapted from ref 51.

simulations were determined from density functional theoretical calculations along with bond order conservation methods. The detailed calculations and results were discussed previously.29,37,71 Simulations carried out over ideal Pd4Au4(100) (well-ordered Pd4 and Au4 ensembles on the (100) surface) decreased the total oxygen surface coverage, since O* does not bind to the Au sites. The Pt-Pt bridge sites, however, are still present on the Pt4 ensembles and, as such, are still blocked by O*, as can be seen in the snapshot depicted in Figure 7A. If we adopt, instead, a well-dispersed Pd1Au1(100) ensemble (Pd0.5Au0.5 surface alloy) that removes all of the Pt bridging sites, we significantly weaken the O* binding energy and decrease the O* coverage (Figure 7B). This same substitution of Au for Pt, however, also significantly weakens the Pt-NO binding energy because it removes the favorable Pt bridge sites. As such, the Pt1Au1(100) ensembles are much less active for NO decomposition, but instead promote the NO2* formation because the Pt-O* and Pt-NO* bonds are now significantly weaker.51,71 As such, most of the guidance from the Sabatier’s principle would likely be ineffective, since the both NO* and O* compete for the same sites. The simulations were therefore used to analyze more closely how alloy composition and specific atomic arrangements (ensembles) of PtAu and PtAg, and PtCu (100) alloys influence

the simulated activities and selectivities.51,71 A comparison of the simulated turnover frequencies (TOF) for different alloy configurations of PtAu, PtAg, and PtCu surfaces is shown in Figure 8. The most active materials are those that contain between 30 and 50% of the secondary metal in the alloy. A closer examination of the actual atomic configuration of the two metals reveals that it is not the composition that results in higher TOF, but rather, the particular positioning or arrangements of the different metal atoms with respect to one another that is critical. The most active configurations for both PtAu and PtAg have the unique structural configuration of the alloy shown in Figure 9 which results in enhancements in the TOF by factors of 4 for the PtAu and 1.7 for the PtAg alloys. The active ensemble consists of a “+” configuration of Pt atoms surrounded by Au (or Ag). The “+” ensemble inhibits the dissociation of O2 on the surface and minimizes the amount of O* that can reside on the Pt bridge sites. Whereas O2 can dissociate at these “+” sites, the O* species that form spill over onto the surrounding Au sites so as to avoid the repulsive interactions that would result of sharing metal atoms. Since all of the bridging Pt sites are connected to the same central Pt atom, at least one of the O* products must spill over onto the rim of Au sites that surround the Pt ensemble to prevent metal atom sharing. Atomic


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Figure 9. KMC-predicted active “+” PtAu ensembles (Pt56.2%Au43.8%) for the lean catalytic decomposition of NO over Pt over Au (and PtAg) alloys. The unique Pt “+” allows O2 to dissociate but avoids poisoning the Pt-Pt sites for NO. (PNO ) 0.47 Torr, PO2 ) 60.8 Torr, and T ) 713 K) Adapted from ref 51.

oxygens at these Au perimeters readily combine and leave the surface as O2; thus, the surface coverage of oxygen is rather low. NO, on the other hand, can adsorb onto the Pt-Pt bridge sites and dissociate to form N* + O* or react with a second NO neighbor to form N2O* which readily goes on to form N2 + O*. The N* that forms from the dissociation of NO can react with a second N* to form N2(g) or recombine to give back NO*. The ab initio KMC simulations have allowed us to go beyond the 1D constraints imposed by the single average metaladsorbate bond strength that typically serves as the key feature of the Sabatier principle. The ensemble identified here specifically considers the unique atomic configuration necessary to carry out the competing steps, thus providing what might be considered a bifunctional surface consisting of Pt4 “+” sites necessary to activate NO surrounded by Au perimeters that promote the recombination and removal of 2O* from the surface and prevent O* poisoning. The results from these simulations suggest that if it were possible to control the specific structure of the alloy, one might be able to significantly advance design efforts beyond the simple one-dimensional screening and predictor approach. This would allow for the unique patterning and design of alloy surfaces that might separate specific structure-function relationships on the surface, thus enhancing both of these separately. This, of course, would be a considerable challenge because we do not know how to synthesize such specific ensembles and whether they would be stable under reaction conditions. Two Dimensional Surface Patterning for Self Assembly: Vinyl Acetate Synthesis. In a second example, we extend this idea of patterning the surface to allow for multifunctional sites but now take advantage of the effects of the atomic configuration of the alloy on surface coverage and adlayer composition along with their influence on the molecular interactions and reactivity on the surface. We do so by highlighting synthesis of vinyl acetate via the reaction of acetic acid, ethylene and oxygen, 1 CH3C(O)OH + CH2dCH2 + O2 f CH3(O)OCHdCH2 + 2 H2O (1)

over Pd and PdAu alloy surfaces.6,72-74 Two different mechanisms have been proposed to describe the reaction chemistry and are named after Samanos and Moiseev, who first proposed them. In the Samanos mechanism,6,72-74 the reaction proceeds via the direct coupling of ethylene with surface acetate species to form an acetoxyethyl intermediate that subsequently undergoes β-hydride elimination to form vinyl acetate, which can then desorb from the surface. In the Moiseev mechanism,6,75 ethylene first reacts with oxygen or the metal surface to form a surface vinyl intermediate, which subsequently combines with an adsorbed acetate species to form vinyl acetate. Both routes indicate that acetic acid and oxygen are readily activated on the vacant Pd sites to form acetate and atomic oxygen surface intermediates. The results from density functional theory calculations together with deuterium labeling experiments involving the titration of acetate with ethylene on acetatecovered Pd(111) surfaces indicate that the mechanism on Pd occurs via the Samanos route involving the direct coupling of ethylene and acetate.72-74 The adsorption energies, reaction energies, activation barriers, and lateral interactions were calculated with density functional theory and used to construct an intrinsic kinetic database to carry out ab initio-based kinetic Monte Carlo simulations.28,51,72 Simulations carried out over the ideal Pd(111) surface reveal that at steady state conditions (where T ) 200 °C, PAcOH ) 2 atm, PO2 ) 0.8 atm, and PC2H4 ) 5 atm), the surface is covered with acetate and oxygen, as can be seen in Figure 10A. These species block the adsorption of ethylene, which considerably lowers the rate. Although the rates can readily be increased by running at much higher partial pressures of ethylene and higher temperatures, there is a loss in selectivity as the open Pd sites that are created can ultimately lead to the formation of unreactive carbon intermediates. This process is carried out industrially over supported PdAu catalysts where the addition of Au significantly improves the selectivity, thus allowing for favorable yields at lower temperatures and ethylene partial pressures. To understand the role of Au, we systematically carried a number of DFT calculations over different PdAu surface and subsurface alloy configurations

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Figure 10. Snapshots from ab initio-based kinetic Monte Carlo simulations of the catalytic synthesis of vinyl acetate, which show the effect of alloying Au into Pd on the steady state surface coverages. Simulation carried out over (A) Pd(111) and (B) well-dispersed Pd50%Au50% alloys with T ) 473 K, PC2H4 ) 3800 Torr, PAcOH ) 1520 Torr, and PO2 ) 608 Torr. The introduction of Au increases the activity by a factor of 2 and selectivity by ∼5%. Adapted from refs 28 and 51.

to determine how alloy composition and configuration influence adsorption, reaction and activation energies. The results have been used to parametrize a more coarse-grained bond order conservation model to predict the energies required for a wide range of different PdAu alloy configurations. The DFT results together with the BOC model were then used to carry out simulations over model PdAu surfaces.30,33 The addition of uniformly dispersed Au atoms into the Pd surface indicates that Au opens up sites on the surface because neither atomic oxygen (O*) nor acetate (AcO*) will bind directly to any of the Au atoms. The adsorption of ethylene is significantly weaker than that of acetate or oxygen and will therefore indiscriminately adsorb at the Au sites to form a more weakly held surface intermediate that can subsequently react with neighboring acetate, as can be seen in the simulation snapshot depicted in Figure 10B. The addition of uniformly and atomically dispersed Au into the Pd(111) surface was found to increase the simulated TOF by a factor of 2 and the selectivity from 89% to 95%. The addition of Au increases the amount of ethylene on the surface, which leads to the marked improvement in activity, but it also acts to break up the larger Pd ensembles that catalyze unselective decomposition and oxidation reactions. The results are consistent with collaborative experiments carried out at DuPont that show improved activity and selectivity upon alloying.76 In moving to well-dispersed Au surface clusters, we find that the activity can be enhanced even further because there appears to be an optimal Au ensemble size. Whereas atomically dispersed Au helps to promote ethylene adsorption, the bulky acetate species bound to neighboring Pd sites still block access of the ethylene. Very large Au ensembles, on the other hand, are too big and thus, the ethylene begins to lose contact with the acetate, which thus lowers the activity. The most active Au ensembles are those consisting of 3-5 Au atoms. This allows ethylene to adsorb and provides for ideal contact with the neighboring acetate intermediates, thus significantly enhancing the catalytic activity. More recent results by Goodman indicate that very small concentrations of Pd in the Au(100) lattice can form unique discontiguous sites that are very active and selective for VAM synthesis.77 These alloys are currently being examined using theory and simulation. The results reported here for VAM synthesis are similar to those discussed above for NO decomposition in that alloying the surface provides specific adsorption and reaction sites that help to enhance surface reactivity. There are some subtle yet important differences, however, between the two. The addition

of Au to Pt for NO decomposition provided unique surface sites that would allow NO to dissociate and, in addition, promote O* recombinative desorption, thus preventing O* poisoning. The changes in the metal here directly influenced the reactive site. In VAM synthesis, the addition of Au influenced not only the nature of the site but, more importantly, the local coverage and proximity of the bulkier acetate intermediates. In VAM synthesis we are “patterning” the surface to allow for the selfassembly or the reactants. While the number of Au sites sets the number of vacancies, the size of the Au surface ensemble that forms controls the spatial topology of these vacancy sites. This ultimately dictates the specific contact (the number of contact points and their strength) between the ethylene and the neighboring acetate species and, hence, their reactivity. This can be thought of as a two-dimensional analogue of the unique reactivity of the enzyme in which the weak multiple-point interactions with the protein backbone help to lower the barrier and guide the reaction at a particular binding site. This concept is illustrated in Figure 11, which shows a vacant Au ensemble and the local “cavity” that is formed by the coadsorbed acetate molecules, thus allowing for contact with the adsorbed ethylene. The Au ensemble size controls the size of this cavity and the degree of contact with the acetate. In both of the previous examples, we naively assumed that one can synthesize specific alloy structures and that these structures would be stable under reaction conditions. These are obviously very idealized assumptions. The goal was simply to understand how such alloys work and identify potential new alloying strategies. We did not want to be limited by the current understanding of alloys, which is predominantly based on the stability of bulk alloys. Identifying possible new materials could help to encourage new synthetic routes and strategies. In the case of PdAu alloys for VAM synthesis, there are many possible alloy targets because the Au and Pd are rather miscible. In the PtAu alloys for NO decomposition, the bulk phase diagrams suggest that there is little miscibility. This, however, is based on bulk metal properties. There are a number of more recent experimental studies from the electrocatalysis community that suggest that one can begin to create nanometer-sized PtAu alloy clusters.78-81 We are currently analyzing the stability of such alloys under realistic reaction conditions. It is important to point out that although the ab initio kinetic simulations for both the NO decomposition and vinyl acetate synthesis examples discussed here directly connect atomic structure to function, they are rather CPU-intensive, and they require a comprehensive set of quantum mechanical calculations


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Figure 11. Alloying can be used to control the surface coverage and promote the specific contact between two coreactants. In this system, four-atom Au ensembles begin to provide optimal space within the actate-covered Pd surface for the adsorption of ethylene and its contact with the neighboring acetate in the transition state to enhance the reaction between the two. The Au ensembles also break up the larger Pd ensembles and help to control unselective reactions. The Au atoms can be used to optimally space the bulky acetate adlayer, allowing from multiple 2D point contacts, thus mimicking the 3D interactions that occur in enzymes.

to determine the intrinsic kinetic database along with coverage effects to simulate the intrinsic elementary kinetics. More coarsegrained models,40-42 such as bond order conservation approaches30,33 or classic and reactive force fields,82,83 are significantly advancing the field because they minimize the number of costly ab initio calculations required. In addition, the simulations discussed here provide information at only a particular point within a reactor. Although one could envision connecting a sequence of such simulations together to follow the conversion and selectivity down the length of a fixed-bed reactor, such simulations would require significant CPU resources. The coarse-graining approaches40-42,82,83 and the time-stepper approaches,43,44 however, offer significant advances because they would allow full-scale reactor simulations without any real sacrifice in the detailed kinetics. Moving to Three Dimensions. The previous two examples have shown that we can begin to move from the one-dimensional alloy design strategies based on Sabatier’s principle and simple descriptors to two-dimensional design of surface alloys that can take advantage of the unique atomic configuration of the surface structure to establish more active and selective catalytic materials. The latter example for VAM synthesis suggests that we can even begin to think of patterning the surface alloys in such a way as to encourage multiple-point contact between the reactants and adsorbed surface intermediates. Since most of the chemistry on metals, metal oxide, and metal sulfides is typically carried out on surfaces, regardless of the elegant threedimensional structures of the nanoparticles that form, we have very limited ability to control or “encourage” three-dimensional contact and, as such, are typically unable to carry out exquisite transformations that rival enzymes. There are, however, some ways in which this may be possible, and theory and simulation can be used to help take advantage of such systems. Microporous Cavity Control. The most obvious threedimensional heterogeneous catalytic systems involve microporous materials, such as zeolites, in which the pore size and pore dimensions can be tuned to control the activity and selectivity for specific reactions. While the more rigid inorganic silica framework of the zeolite prevent the flexibility offered by enzymes, they can be synthesized to create frameworks with different three-dimensional cages and channel sizes that can be used to help control specific molecular transformations. The design of the microporous framework provides many of the same opportunities that one has in enzymes in directing reactant,

product, and transition state selectivity. There are numerous studies that elegantly demonstrate reactant and product state selectivity, but there is only one study, at least that this author is aware of, that distinctively demonstrates transition state selectivity.84-87 Transition state selectivity involves the unique stabilization of the transition state over the reactant and product states at specific sites. The nanometer-sized cages and channels along with the unique intersections within the zeolite and other microporous materials can offer unique structural motifs that can provide for a unique stabilization of the transition state structures over their reactants via specific electrostatic and van der Waal interactions. In a recent study, Iglesia and colleagues84-87 elegantly demonstrated unique transition state selectivity for an 8-member ring (8-MR) containing zeolites for the carbonylation of methanol and dimethyl ether to methyl acetate. They showed that DME can be converted to methyl acetate at unprecedented rates and selectivities that exceed 99% when carried out within zeolites with 8-member rings. The significant increase in catalytic performance was shown to be the result of the unique structural and electronic topography of the 8-ring channels. The results in Figure 12A clearly show that only the 8-MR containing mordenite and ferierite zeolites result in any appreciable reactivity. The postulated reaction mechanism depicted schematically in Figure 12B indicates that the reaction proceeds via the acid catalyzed activation of methanol (or DME) to form stable methoxide intermediates that reside at the acid sites in the zeolite. Adsorbed methoxy intermediates subsequently react with CO in what is considered to be the rate-controlling step via a classic back-side attack of CO on the methoxy intermediate, which is shown in Figure 13.88 The resulting methyl carbenium ion transition state is stabilized via the interaction with the carbon end of the CdO and the ensuing negative charge on the zeolite framework. The calculations reveal the transition states are uniquely stabilized at the bottom of the 8 member ring channel as a result of the attractive Coulombic interactions between the carbenium ion that forms and the negative charge on the framework oxygen and the weak van der Waal interactions with the neighboring oxygen atoms within the 8-MR.88 The calculated activation barrier for the reaction of CO and surface methoxy intermediate agree quite well with the reported experimental value. The van der Waal interactions are critical in stabilizing this reaction in the 8-MR.88 The 8-MR cage

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Figure 12. The unique specificity of the carbonylation of DME to methyl acetate for the 8-member ring channels in zeolites. (A) Comparison of carbonylation rates on different zeolites consisting of different ring sizes. (B) The proposed reaction pathways for the carbonylation of DME over Brønsted acid sites in zeolites (copyright 2007 and 2008, The American Chemical Society84,85).

Figure 13. DFT-calculated reaction path and transition state for the carbonylation of an adsorbed methyl to form the methyl acetate intermediate. The acid sites at the bottom of the 8-MR channel show unique specificity because they can more effectively stabilize the transition state that forms over those at other sites88 as a result of the Coulombic and weak van der Waal interactions.

provides for the optimal weak multiple point contact analogous to that found in enzymes to drive the reaction. The results here

suggest that we can extend the two-dimensional contact discussed above for vinyl acetate synthesis to unique three-


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Figure 14. The structure of liquid methanol from A) neutron scattering studies by Dixit; copyright 2002, Nature;89 and (B) from ab initio molecular dynamics simulations that show the presence of three-dimensional hydrophilic and hydrophobic domains.

dimensional states that can be isolated within the pores of specific zeolites providing unique structure activation relationships. The Metal-Solution Interface. A second way in which to provide for three-dimensional contact with the reaction center for a supported catalyst is through the reaction medium. Many of the energy conversion processes discussed in the introduction are carried out in solution or in a solvent. The solution or solvent can be engineered to work with the metal or metal oxide surface to stabilize transition states and enhance catalytic activity and selectivity. The solution media can directly influence the surface kinetics via the stabilization of charged or polar transition states and intermediates, enabling heterolytic reactions to occur or directly participating in the catalytic sequence of events. To illustrate ideas, I present results on the selective hydrogenation of oxygenates because this is a critical step in many of the current renewable conversion strategies: hydrogen is required for the hydrogenolysis of carbon-carbon and carbonoxygen bonds contained in polyol intermediates. The presence of solution or polar solvents can greatly influence catalytic properties. At a molecular level, different solvents can lead to different degrees of stabilization as a result of their ability to stabilize both positive and negative charge, hydrogen bond, and provide multiple point contact. Many protic solvents, such as alcohols and amines, have both hydrophobic and hydrophilic functional groups that can orient in characteristic ways to provide unique domains in the liquid phase. Methanol in the liquid phase, for example, organizes itself into unique threedimensional hydrophilic domains consisting of hydrogen bonding networks and hydrophobic domains made up of the CH3 head groups. Dixit et al.89 used neutron scattering to show the presence of these 3D regions, as seen in Figure 14A. We demonstrate similar domain structures from ab initio molecular dynamic simulations, as can be seen in Figure 14B. The hydrophobic and hydrophilic domains that result can influence catalytic hydrogenation over supported metals in different ways as they stabilize the interactions and transition states in different ways. By way of example, I focus on methyl ethyl ketone (MEK) as a model for the selective hydrogenation of carbonyl containing oxygenates that result in the conversion of polyols to valueadded chemical intermediates. Aldehydes and ketones typically adsorb on metal surfaces in either a di-σ mode, in which both the carbon and the oxygen atoms of the carbonyl interact with metal atoms in the surface, or in an η1 mode, in which only the oxygen atom interacts with the surface through weak charge transfer.90 The hydrogenation of MEK and other ketones and

aldehydes proceeds on a number of different metals via the addition of hydrogen to the oxygen end of the adsorbed carbonyl to form an acetyl intermediate. The transition state for this reaction is a classic 3-center complex involving the insertion of the H into the metal-oxygen bond, as is shown in Figure 15A. The activation energy for the addition of hydrogen to the adsorbed oxygen atom for the vapor phase reaction over Ru(0001) was calculated to be 0.4 eV. The barrier, however, is considerably lower if the reaction is carried out in the presence of water. Water very effectively stabilizes the partially charged transition state through an extensive network of hydrogen bonds with the local water molecules. A detailed view of the transition state for this reaction carried out in water is shown in Figure 15B. The structure of the three center Ru-O-H transition state is essentially identical to that found in the vapor phase (Figure 15A), but the activation barrier (0.2 eV) is two times lower than that calculated in the vapor phase. This reduction is due to the stabilization of the O-H bond that forms in the transition state through hydrogen bonding with two of the vicinal water molecules on the Ru surface and one of the water molecules in the solution phase. If the reaction is carried out in methanol, the stabilization (over the vapor phase) is weaker because there is a much higher activation barrier than if it were carried out in water. This is rather intriguing because one might expect to see the same stabilization in all protic solvents. A detailed comparison of the transition state for the selective addition of hydrogen to the oxygen end of MEK reveals that the transition state is stabilized only by two vicinal coadsorbed methanol molecules on Ru. What is uniquely different in methanol is the loss of the hydrogen bonds that come directly from the solution phase. The local 3D hydrogen bonding network that forms at the at the water/metal interface provides for the full stabilization of hydrophilic reaction centers such as the Ru-O-H that form at the metal surface. In methanol, however there is loss in the 3D hydrogen bonding network at the reaction center at the metal interface. This is the result of the 2D ordering that results upon the adsorption of the functionalized molecules onto solid surfaces. The adsorption of methanol and other alcohols to metal surfaces proceeds via the formation of M-OH bonds, which organize the alcohol by creating planar 2D hydrophilic and hydrophilic domains as seen in Figure 15c. The M-O interactions that occur at the metal surface create an organized planar hydrophilic domain directly at the metal surface (region enclosed by the

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Figure 15. The effect of solvent on the hydrogenation of methyl ethyl ketone over Ru(0001). The transition state for the addition of hydrogen to the O end of the carbonyl to form the methyl ethyl acetyl intermediate carried out in (A) vapor phase, (B) water, and (C) methanol. The results show that Ea (vapor) > Ea (methanol) > Ea (water). The barriers decrease with the number of hydrogen bonds that can form in the transition state. Water provides nearly complete 3D hydrogen bonding with the solution phase. Methanol, on the other hand, organizes to form 2D hydrophilic and hydrophobic domains, thus resulting in a loss of hydrogen bonds with methanol in the solution phase. Only the coadsorbed methanol molecules on the surface provide the hydrogen bonding required to stabilize the transition state.

green box in Figure 15c). These metal-oxygen interactions align all of the adsorbed methanol molecules so as to orient the hydrophobic CH3 head groups away from the surface, thus creating a planar hydrophobic domain just above the surface (region enclosed in the blue box in Figure 15c). These two regions are clearly visible by examining the side view of the hydrogen addition reaction carried out in methanol (Figure 15c) and comparing the resulting structures and interfaces that form in methanol with those that form in water (Figure 15b). The metal-oxygen bonds that result from the adsorption of methanol onto the Ru(0001) surface are strong enough to rearrange the 3D hydrophilic and hydrophobic domains found in bulk methanol into 2D domains at the methanol/metal interface. The hydrophobic domain that forms just above the hydrophilic domain thus prevents the formation of hydrogen bonds between the surface and the solution phase. In the case of the hydrogenation of MEK, this leads to a loss of the hydrogen bond that orients out toward the solution phase. This loss in transition state stabilization increases the activation barrier by 0.13 eV. The results here suggest that solvents, metals, and supports may be chosen so as to control or organize 3D or 2D domains about the reaction centers that may enhance or impede certain reactions. This is similar to the 3D hydrophobic cavities that are formed in enzymes that can be used to exclude water from the reaction center even when the reactions occur in solution. Controlling Proton-Electron Transfer. In addition to the unique three-dimensional structural domains and topography, enzymes also provide for the exquisite control of coupled proton and electron transfer reactions that are important for efficiently carrying a number of reactions critical to energy conversion strategies, such as the oxidation of water, reduction CO2, and oxidation of alcohols. The development of inorganic catalytic

materials that can carry out these photo- and electrocatalytic processes has been met with a number of challenges as a result of the poor understanding of the interfaces where catalysis occurs.1,3,91,92 Modeling such systems poses a number of challenges because these reactions are typically carried out at a complex three-phase junction that requires optimal contact among the metal or metal oxide catalyst that carries out specific bond-breaking and -making steps, electron-conducting centers, and the substrate to efficiently transfer electrons and proton carriers to facilitate proton and electron transport.93-95 In addition to the challenges that result from the complex interfacial structure, there are a number of obstacles to modeling constant electrochemical systems. Traditional quantum mechanical methods are typically carried out within a canonical formalism whereby the number of electrons are held constant rather than the potential. We have recently developed an ab initio-based approach that can begin to simulate electrochemical and electrocatalytic systems.96,97 Although it is currently not possible to simulate a full electrochemical cell that would require two electrodes, the polymer electrolyte, and electron and proton conduction, we can mimic potentiostatically controlled half-cell experiments to determine the adsorption, reaction, and activation energies at applied (constant) potentials. By changing the potential, we can establish its influence on the governing surface chemistry and catalysis. This approach has been used to follow a range of different electrochemical and electrocatalytic phenomena, including the activation of water,96-101 the oxidation of methanol,93-95,100,102-105 the reduction of oxygen,106 the dissolution of metals,107,108 the absorption of hydrogen, and the embrittlement of metals.98,99,109 Some of the greatest technological hurdles to the deployment of fuel cells relate to their high costs due to the use of Pt and


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Figure 16. DFT-calculated path for the electrocatalytic reduction of O2 on Pt(111) indicates that the reaction proceeds via proton-coupled electron transfer to form a surface peroxo intermediate. (a) Separated H+ in solution and electron in the metal, (b) transition state to form the solvated H(H2O)3 · · · O2* system, and (c) OOH* surface intermediate. Adapted from ref 106.

their low efficiencies, which result from the high overpotentials.92 The latter is predominantly the result of the sluggish kinetics for the oxygen reduction reaction (ORR) which occurs at the cathode. ORR requires surfaces that can readily activate molecular oxygen without being poisoned by the OH* and O* surface intermediates that result. These reactions are limited by the high overpotentials required to produce current (0.9 V NHE) for most of today’s fuel cells.92,110 To understand the mechanistic factors that control ORR, we applied our ab initio double-reference approach discussed above to follow the reduction of O2*, OH*, and O* over ideal Pt(111) and Pt alloys in the presence of solution and electrolyte. The initial O2 reduction proceeds via the adsorption of O2 onto the Pt surface. At higher OH* surface coverages, this step alone can be quite difficult. ORR is thought to proceed via the single electron reduction of molecular oxygen (O2* + H+ + 1e-) at a constant potential. The reaction coordinate for this step involves the diffusion or shuttling of a proton from the solution along a conduit of hydrogen bonds to the adsorbed O2*, as is shown in Figure 16.106 As the proton moves to within a local hydration sphere of the adsorbed O2*, there is an important proton-coupled electron transfer event that occurs to form a hydrogen atom (H+ + e- f H) which can subsequently react with the adsorbed O2 to form the bound OOH* peroxy intermediate.106 This initial elementary O2 reduction reaction is thus controlled by the proton-coupled electron transfer process in which the reaction of O2* + H plays only a very minor role. The activation barrier for O2 reduction that is plotted as a function of potential in Figure 17 increases nearly linearly from 0.28 eV at 0.8 V to 0.95 eV at 1.2 V.106 The results are consistent with values determined experimentally by Markovic.111-112 Subsequent results for the reduction of OH* and O* indicate that at potentials above 0.8 V, the activation barriers for these steps significantly exceed the barriers for O2* reduction and are therefore likely to be the rate-controlling steps. As the potential drops below 0.8 V, the barriers for the reduction of OH* and O* drop significantly and begin to rival the initial O2 reduction step. The results indicate that ORR is limited by OH* and O* reduction at potentials >0.8 V and O2 reduction at potentials

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