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Revision 3867 by jmichalk, Tue Mar 5 00:18:33 2013 UTC

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1 < \documentclass[a4paper,12pt]{article}
2 <
1 > \documentclass[11pt]{article}
2 > \usepackage{amsmath}
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4 > \usepackage{times}
5 > \usepackage{mathptm}
6   \usepackage{setspace}
7 < \usepackage{float}
8 < \usepackage{cite}
9 < \usepackage[pdftex]{graphicx}
10 < \usepackage[font=small,labelfont=bf]{caption}
7 > \usepackage{endfloat}
8 > \usepackage{caption}
9 > %\usepackage{tabularx}
10 > \usepackage{graphicx}
11 > \usepackage{multirow}
12 > %\usepackage{booktabs}
13 > %\usepackage{bibentry}
14 > %\usepackage{mathrsfs}
15 > \usepackage[square, comma, sort&compress]{natbib}
16 > \usepackage{url}
17 > \pagestyle{plain} \pagenumbering{arabic} \oddsidemargin 0.0cm
18 > \evensidemargin 0.0cm \topmargin -21pt \headsep 10pt \textheight
19 > 9.0in \textwidth 6.5in \brokenpenalty=10000
20  
21 + % double space list of tables and figures
22 + %\AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
23 + \setlength{\abovecaptionskip}{20 pt}
24 + \setlength{\belowcaptionskip}{30 pt}
25 +
26 + \bibpunct{}{}{,}{s}{}{;}
27 + \bibliographystyle{achemso}
28 +
29 + \begin{document}
30 +
31 +
32   %%
33   %Introduction
34   %       Experimental observations
# Line 24 | Line 47
47   %Summary
48   %%
49  
50 + %Title
51 + \title{Molecular Dynamics simulations of the surface reconstructions
52 +  of Pt(557) and Au(557) under exposure to CO}
53  
54 + \author{Joseph R. Michalka, Patrick W. McIntyre and J. Daniel
55 + Gezelter\footnote{Corresponding author. \ Electronic mail: gezelter@nd.edu} \\
56 + Department of Chemistry and Biochemistry,\\
57 + University of Notre Dame\\
58 + Notre Dame, Indiana 46556}
59  
29 \begin{document}
30 %Title
31 \title{Investigation of the Pt and Au 557 Surface Reconstructions under a CO Atmosphere}
60   %Date
61 < \date{Dec 15,  2012}
61 > \date{Mar 4, 2013}
62 >
63   %authors
64 < \author{Joseph R.~Michalka, Patrick W. McIntyre, \& J.~Daniel Gezelter}
64 >
65   % make the title
66   \maketitle
67  
68 < \doublespacing
68 > \begin{doublespace}
69  
70 + \begin{abstract}
71 + We examine potential surface reconstructions of Pt and Au(557)
72 + under various CO coverages using molecular dynamics in order
73 + to explore possible mechanisms for any observed reconstructions and their dynamics.
74 + The metal-CO interactions were parameterized as part of this
75 + work so that an efficient large-scale treatment of this system could be
76 + undertaken. The relative binding strengths of the metal-CO
77 + interactions were found to play a large role with regards to
78 + step-edge stability and adatom diffusion. A small correlation
79 + between coverage and the size of the diffusion constant was
80 + also determined. An in-depth examination of the energetics of CO
81 + adsorbed to the surface provides results that appear sufficient to explain the
82 + reconstructions observed on the Pt systems and the corresponding lack  
83 + on the Au systems.
84 + \end{abstract}
85  
86 + \newpage
87  
88 +
89   \section{Introduction}
90   % Importance: catalytically active metals are important
91   %       Sub: Knowledge of how their surface structure affects their ability to catalytically facilitate certain reactions is growing, but is more reactionary than predictive
# Line 48 | Line 94
94   %       Sub: Also, easier to observe what is going on and provide reasons and explanations
95   %
96  
97 + Industrial catalysts usually consist of small particles that exhibit a
98 + high concentration of steps, kink sites, and vacancies at the edges of
99 + the facets.  These sites are thought to be the locations of catalytic
100 + activity.\cite{ISI:000083038000001,ISI:000083924800001} There is now
101 + significant evidence that solid surfaces are often structurally,
102 + compositionally, and chemically modified by reactants under operating
103 + conditions.\cite{Tao2008,Tao:2010,Tao2011} The coupling between
104 + surface oxidation states and catalytic activity for CO oxidation on
105 + Pt, for instance, is widely documented.\cite{Ertl08,Hendriksen:2002}
106 + Despite the well-documented role of these effects on reactivity, the
107 + ability to capture or predict them in atomistic models is somewhat
108 + limited.  While these effects are perhaps unsurprising on the highly
109 + disperse, multi-faceted nanoscale particles that characterize
110 + industrial catalysts, they are manifest even on ordered, well-defined
111 + surfaces. The Pt(557) surface, for example, exhibits substantial and
112 + reversible restructuring under exposure to moderate pressures of
113 + carbon monoxide.\cite{Tao:2010}
114  
115 < High-index surfaces of catalytically active metals are an important area of exploration because they are typically more reactive than an ideal surface of the same metal. The greater number of low-coordinated surface atoms is likely responsible for this increased reactivity \cite{}. Additionally, the activity and specificity of many metals towards certain chemical processes has been shown to strongly depend on the structure of the surface \cite{}. Prior work has also shown that reaction conditions: high pressures, temperatures, etc. are able to cause reconstructions of the surface, either through changing the displayed surface facets or by changing the number and types of high-index sites available for reactions \cite{doi:10.1126/science.1197461,doi:10.1021/nn3015322, doi:10.1021/jp302379x}. A greater understanding of these high-index surfaces and the restructuring processes they undergo is needed as a prerequisite for more intelligent catalyst design. While current experimental work has started exploring systems at \emph{in situ} conditions, for a long time such experiments were limited to ideal surfaces in high vacuum. New techniques, such as ambient pressure XPS (AP-XPS) \cite{}, high-pressure XPS (HP-XPS) \cite{}, high-pressure STM \cite{}, environmental transmission electron microscopy (E-TEM) \cite{} and many others, are giving a clearer picture of what processes are occurring on metal surfaces when exposed to \emph{in situ} conditions. But all of these techniques still have difficulties, especially in observing what is occurring on the surfaces at an atomic level. Theoretical models and simulations in combination with experiment have proven their worth in explaining the underlying reasons for some of these reconstructions \cite{}.
116 < \\
117 < By examining two different metal-CO systems the effect the metal and the metal-CO interaction plays can be elucidated. Our first system is composed of Platinum and CO and has been the subject of many experimental and theoretical studies primarily because of Platinum's strong reactivity toward CO oxidation. The focus has primarily been on absorption energies, preferred absorption sites, and catalytic activities. The second system we examined is composed of Gold and CO. The Gold-CO interaction is much weaker than the Platinum-CO interaction and it seems likely that this difference in attraction would lead to differences in any potential surface reconstructions.
118 < %It has also been a good test for new quantum methods because of the difficulty with modeling the preference CO has for the atop binding site \cite{doi:10.1021/jp002302t}.
119 < %Now that dynamic surface events are known to play a role in many catalytic systems, additional research is being done to more closely examine many systems. Recent work by Tao et al. \cite{doi:10.1126/science.1182122} shows that a high-index platinum surface will undergo surface reconstructions when exposed to a small amount of CO, $\sim$~1 torr. Unexpectedly,  the reconstruction was metastable and reverted upon removal of the CO. Work by McCarthy et al. \cite{doi:10.1021/jp302379x} examined temperature programmed desorption's of CO from various Platinum samples and saw that species which had large amounts of low-coordinated surface atoms, highly sputtered surfaces or small nano particles, developed a higher temperature desorption peak, suggesting that binding of CO to the Platinum surface is strongly dependent on local geometry.
115 > This work is an attempt to understand the mechanism and timescale for
116 > surface restructuring using molecular simulations.  Since the dynamics
117 > of the process are of particular interest, we employ classical force
118 > fields that represent a compromise between chemical accuracy and the
119 > computational efficiency necessary to simulate the process of interest.
120 > Restructuring can occur as a result of specific interactions of the
121 > catalyst with adsorbates. In this work, two metal systems exposed
122 > to carbon monoxide were examined. The Pt(557) surface has already been shown
123 > to reconstruct under certain conditions. The Au(557) surface, because
124 > of a weaker interaction with CO, is less likely to undergo this kind
125 > of reconstruction.  MORE HERE ON PT AND AU PREVIOUS WORK.
126  
127 + %Platinum molecular dynamics
128 + %gold molecular dynamics
129  
130 + \section{Simulation Methods}
131 + The challenge in modeling any solid/gas interface problem is the
132 + development of a sufficiently general yet computationally tractable
133 + model of the chemical interactions between the surface atoms and
134 + adsorbates.  Since the interfaces involved are quite large (10$^3$ -
135 + 10$^6$ atoms) and respond slowly to perturbations, {\it ab initio}
136 + molecular dynamics
137 + (AIMD),\cite{KRESSE:1993ve,KRESSE:1993qf,KRESSE:1994ul} Car-Parrinello
138 + methods,\cite{CAR:1985bh,Izvekov:2000fv,Guidelli:2000fy} and quantum
139 + mechanical potential energy surfaces remain out of reach.
140 + Additionally, the ``bonds'' between metal atoms at a surface are
141 + typically not well represented in terms of classical pairwise
142 + interactions in the same way that bonds in a molecular material are,
143 + nor are they captured by simple non-directional interactions like the
144 + Coulomb potential.  For this work, we have used classical molecular
145 + dynamics with potential energy surfaces that are specifically tuned
146 + for transition metals.  In particular, we used the EAM potential for
147 + Au-Au and Pt-Pt interactions\cite{EAM}, while modeling the CO using a rigid
148 + three-site model developed by Straub and Karplus for studying
149 + photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and
150 + Pt-CO cross interactions were parameterized as part of this work.
151 +  
152 + \subsection{Metal-metal interactions}
153 + Many of the potentials used for modeling transition metals are based
154 + on a non-pairwise additive functional of the local electron
155 + density. The embedded atom method (EAM) is perhaps the best known of
156 + these
157 + methods,\cite{Daw84,Foiles86,Johnson89,Daw89,Plimpton93,Voter95a,Lu97,Alemany98}
158 + but other models like the Finnis-Sinclair\cite{Finnis84,Chen90} and
159 + the quantum-corrected Sutton-Chen method\cite{QSC,Qi99} have simpler
160 + parameter sets. The glue model of Ercolessi et al. is among the
161 + fastest of these density functional approaches.\cite{Ercolessi88} In
162 + all of these models, atoms are conceptualized as a positively charged
163 + core with a radially-decaying valence electron distribution. To
164 + calculate the energy for embedding the core at a particular location,
165 + the electron density due to the valence electrons at all of the other
166 + atomic sites is computed at atom $i$'s location,
167 + \begin{equation*}
168 + \bar{\rho}_i = \sum_{j\neq i} \rho_j(r_{ij})
169 + \end{equation*}
170 + Here, $\rho_j(r_{ij})$ is the function that describes the distance
171 + dependence of the valence electron distribution of atom $j$. The
172 + contribution to the potential that comes from placing atom $i$ at that
173 + location is then
174 + \begin{equation*}
175 + V_i =  F[ \bar{\rho}_i ]  + \sum_{j \neq i} \phi_{ij}(r_{ij})
176 + \end{equation*}
177 + where $F[ \bar{\rho}_i ]$ is an energy embedding functional, and
178 + $\phi_{ij}(r_{ij})$ is a pairwise term that is meant to represent the
179 + repulsive overlap of the two positively charged cores.  
180  
181 + % The {\it modified} embedded atom method (MEAM) adds angular terms to
182 + % the electron density functions and an angular screening factor to the
183 + % pairwise interaction between two
184 + % atoms.\cite{BASKES:1994fk,Lee:2000vn,Thijsse:2002ly,Timonova:2011ve}
185 + % MEAM has become widely used to simulate systems in which angular
186 + % interactions are important (e.g. silicon,\cite{Timonova:2011ve} bcc
187 + % metals,\cite{Lee:2001qf} and also interfaces.\cite{Beurden:2002ys})
188 + % MEAM presents significant additional computational costs, however.
189  
190 + The EAM, Finnis-Sinclair, and the Quantum Sutton-Chen (QSC) potentials
191 + have all been widely used by the materials simulation community for
192 + simulations of bulk and nanoparticle
193 + properties,\cite{Chui:2003fk,Wang:2005qy,Medasani:2007uq}
194 + melting,\cite{Belonoshko00,sankaranarayanan:155441,Sankaranarayanan:2005lr}
195 + fracture,\cite{Shastry:1996qg,Shastry:1998dx} crack
196 + propagation,\cite{BECQUART:1993rg} and alloying
197 + dynamics.\cite{Shibata:2002hh} All of these potentials have their
198 + strengths and weaknesses.  One of the strengths common to all of the
199 + methods is the relatively large library of metals for which these
200 + potentials have been
201 + parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}  
202  
203 < \section{Simulation Methods}
204 < Our model systems are composed of nearly 4000 metal atoms cut along the 557 plane. This cut creates a stepped surface of 6x(111) surface plateaus separated by a single (100) atomic step height. The large number of low-coordination atoms along the step edges provide a suitable model for industrial catalysts which tend to have a prevalence of lower CN, i.e. more reactive, sites. Drawing from experimental conclusions, the reconstructions seen for the Pt 557 surface involve doubling of the step height and the formation of triangular motifs along the steps \cite{doi:10.1126/science.1182122}. To properly observe these changes, our system size need to be greater than the periodic phenomena we are examining. The large size and the long time scales needed precluded us from using expensive quantum approaches. Thus, a forcefield describing the Metal-Metal, CO-CO, and CO-Metal interactions was parameterized.
205 < %Metal
206 < \subsection{Metal}
207 < Recent metallic forcefields, inspired by density-functional theory, including EAM\cite{doi:10.1103/PhysRevB.29.6443, doi:10.1103/PhysRevB.33.7983} and QSC\cite{} have become very popular for modeling novel metallic systems.  What makes these forcefields more suitable for metals than their pair-wise predecessors is that they work with the total electron density of the system in a manner akin to DFT. The energy contributed by a single atom is a function of the total background electron density at the point where the atom is to be embedded. The density at any given point is well-approximated by a linear superposition of the electron density as contributed by all the other atoms in the system. This description of the embedding energy allows this method to more accurately treat surfaces, alloys, and other non-bulk systems. The function describing the energy as related to the density is parameterized for each element, rather than by solving the Kohn-Sham equations which is what allows this method to be used for large systems. The embedding energy is completely enclosed within the functional $F_i[\rho_{h,i}]$ which is dependent on the host density $\rho_{h}$ at atom $i$. The density at $i$ is the sum of the density as generated by the rest of the metal. The $\phi_{ij}$ term is a purely repulsive pair-pair interaction parameterized from effective charge repulsions.
208 < %Can I increase the \sum size, not sure how...
209 < \begin{equation}
210 < E_{tot} = \sum_i F_i[\rho_{h,i}] + \frac{1}{2}\sum_i\sum_{j(\ne i)} \phi_{ij}(R_{ij})
211 < \end{equation}
212 < \begin{equation}
213 < \rho_{h,i} = \sum_{j (\ne i)} \rho_j^a(R_{ij})
214 < \end{equation}
215 < The EAM functional forms are used to model the Au and Pt self-interactions in all of our simulations.
75 < %CO
76 < \subsection{CO}
77 < Our CO model was obtained from work done by Karplus and Straub\cite{}. In their description of the biological importance of CO they developed an accurate quadrupolar model of CO which we make use of in this work. It has been suggested that the strong electrostatic repulsion that arises from this linear quadrupole may play an important role in the restructuring of metal surfaces to which CO is bound\cite{}.
203 > \subsection{Carbon Monoxide model}
204 > Previous explanations for the surface rearrangements center on
205 > the large linear quadrupole moment of carbon monoxide.  
206 > We used a model first proposed by Karplus and Straub to study
207 > the photodissociation of CO from myoglobin because it reproduces
208 > the quadrupole moment well.\cite{Straub} The Straub and
209 > Karplus model, treats CO as a rigid three site molecule which places a massless M
210 > site at the center of mass position along the CO bond.  The geometry used along
211 > with the interaction parameters are reproduced in Table~\ref{tab:CO}. The effective
212 > dipole moment, calculated from the assigned charges, is still
213 > small (0.35 D) while the linear quadrupole (-2.40 D~\AA) is close
214 > to the experimental (-2.63 D~\AA)\cite{QuadrupoleCO} and quantum
215 > mechanical predictions (-2.46 D~\AA)\cite{QuadrupoleCOCalc}.
216   %CO Table
217   \begin{table}[H]
218 < \caption{$\sigma$, $\epsilon$ and charges for CO self-interactions\cite{}. Distances are in \AA~, energies are in kcal/mol, and charges are in $e$.}
218 >  \caption{Positions, Lennard-Jones parameters ($\sigma$ and
219 >    $\epsilon$), and charges for the CO-CO
220 >    interactions borrowed from Ref.\bibpunct{}{}{,}{n}{}{,} \protect\cite{Straub}. Distances are in \AA, energies are
221 >    in kcal/mol, and charges are in atomic units.}
222   \centering
223 < \begin{tabular}{| c | ccc |}
223 > \begin{tabular}{| c | c | ccc |}
224   \hline
225 < \multicolumn{4}{|c|}{\textbf{Self-Interactions}}\\
225 > &  {\it z} & $\sigma$ & $\epsilon$ & q\\
226   \hline
227 < &  $\sigma$ & $\epsilon$ & q\\
227 > \textbf{C} & -0.6457 &  0.0262  & 3.83   &   -0.75 \\
228 > \textbf{O} &  0.4843 &   0.1591 &   3.12 &   -0.85 \\
229 > \textbf{M} & 0.0 & -  &  -  &    1.6 \\
230   \hline
88 \textbf{C} &  0.0262  & 3.83   &   -0.75 \\
89 \textbf{O} &   0.1591 &   3.12 &   -0.85 \\
90 \textbf{M} & -  &  -  &    1.6 \\
91 \hline
231   \end{tabular}
232 + \label{tab:CO}
233   \end{table}
94 %Cross
95 \subsection{Cross-Interactions}
96 To finish the forcefield, the cross-interactions between the metals and the CO needed to be parameterized. Previous attempts at parameterization have used two different functional forms to model these interactions\cite{}. A LJ model was fit for the Metal-Carbon interaction and a Morse potential was parameterized for the Metal-Oxygen interaction. The parameter sets chosen, as shown in Table 2, did a suitable job at reproducing experimental adsorption energies as shown in Table 3, but more importantly, they were able to capture the binding site preference. The Pt-CO parameters show a slight preference for the atop binding site which matches the experimental observations.
234  
235 + \subsection{Cross-Interactions between the metals and carbon monoxide}
236  
237 + Since the adsorption of CO onto a Pt surface has been the focus
238 + of much experimental \cite{Yeo, Hopster:1978, Ertl:1977, Kelemen:1979}
239 + and theoretical work
240 + \cite{Beurden:2002ys,Pons:1986,Deshlahra:2009,Feibelman:2001,Mason:2004}
241 + there is a significant amount of data on adsorption energies for CO on
242 + clean metal surfaces. Parameters reported by Korzeniewski {\it et
243 +  al.}\cite{Pons:1986} were a starting point for our fits, which were
244 + modified to ensure that the Pt-CO interaction favored the atop binding
245 + position on Pt(111). These parameters are reproduced in Table~\ref{tab:co_parameters}
246 + This resulted in binding energies that are slightly higher
247 + than the experimentally-reported values as shown in Table~\ref{tab:co_energies}. Following Korzeniewski
248 + et al.,\cite{Pons:1986} the Pt-C interaction was fit to a deep
249 + Lennard-Jones interaction to mimic strong, but short-ranged partial
250 + binding between the Pt $d$ orbitals and the $\pi^*$ orbital on CO. The
251 + Pt-O interaction was parameterized to a Morse potential at a larger
252 + minimum distance, ($r_o$).  This was chosen so that the C would be preferred
253 + over O as the binder to the surface. In most cases, this parameterization contributes a weak
254 + repulsion which favors the atop site.  The resulting potential-energy
255 + surface suitably recovers the calculated Pt-C separation length
256 + (1.6~\AA)\cite{Beurden:2002ys} and affinity for the atop binding
257 + position.\cite{Deshlahra:2012, Hopster:1978}
258  
259 + %where did you actually get the functionals for citation?
260 + %scf calculations, so initial relaxation was of the four layers, but two layers weren't kept fixed, I don't think
261 + %same cutoff for slab and slab + CO ? seems low, although feibelmen had values around there...
262 + The Au-C and Au-O cross-interactions were also fit using Lennard-Jones and
263 + Morse potentials, respectively, to reproduce Au-CO binding energies.
264 + The limited experimental data for CO adsorption on Au lead us to refine our fits against DFT.
265 + Adsorption energies were obtained from gas-surface DFT calculations with a
266 + periodic supercell plane-wave basis approach, as implemented in the
267 + {\sc Quantum ESPRESSO} package.\cite{QE-2009} Electron cores are
268 + described with the projector augmented-wave (PAW)
269 + method,\cite{PhysRevB.50.17953,PhysRevB.59.1758} with plane waves
270 + included to an energy cutoff of 20 Ry. Electronic energies are
271 + computed with the PBE implementation of the generalized gradient
272 + approximation (GGA) for gold, carbon, and oxygen that was constructed
273 + by Rappe, Rabe, Kaxiras, and Joannopoulos.\cite{Perdew_GGA,RRKJ_PP}
274 + In testing the Au-CO interaction, Au(111) supercells were constructed of four layers of 4
275 + Au x 2 Au surface planes and separated from vertical images by six
276 + layers of vacuum space. The surface atoms were all allowed to relax
277 + before CO was added to the system. Electronic relaxations were
278 + performed until the energy difference between subsequent steps
279 + was less than $10^{-8}$ Ry.   Nonspin-polarized supercell calculations
280 + were performed with a 4~x~4~x~4 Monkhorst-Pack {\bf k}-point sampling of the first Brillouin
281 + zone.\cite{Monkhorst:1976,PhysRevB.13.5188} The relaxed gold slab was
282 + then used in numerous single point calculations with CO at various
283 + heights (and angles relative to the surface) to allow fitting of the
284 + empirical force field.
285  
286 < %\subsection{System}
287 < %Once equilibration was reached, the systems were exposed to various sub-monolayer coverage of CO: $0, \frac{1}{10}, \frac{1}{4}, \frac{1}{3},\frac{1}{2}$. The CO was started many \AA~above the surface with random velocity and rotational velocity vectors sampling from a Gaussian distribution centered on the temperature of the equilibrated metal block.  Full adsorption occurred over the period of approximately 10 ps for Pt, while the binding energy between Au and CO is smaller and led to an incomplete adsorption. The metal-metal interactions were treated using the Embedded Atom Method while the Pt-CO and Au-CO interactions were fit to experimental data and quantum calculations. The raised temperature helped shorten the length of the simulations by allowing the activation barrier of reconstruction to be more easily overcome. A few runs at lower temperatures showed the very beginnings of reconstructions, but their simulation lengths limited their usefulness.
286 > %Hint at future work
287 > The parameters employed for the metal-CO cross-interactions in this work
288 > are shown in Table~\ref{co_parameters} and the binding energies on the
289 > (111) surfaces are displayed in Table~\ref{co_energies}.  Charge transfer
290 > and polarization are neglected in this model, although these effects are likely to
291 > affect binding energies and binding site preferences, and will be added in
292 > a future work.\cite{Deshlahra:2012,StreitzMintmire:1994}
293  
104
294   %Table  of Parameters
295   %Pt Parameter Set 9
296   %Au Parameter Set 35
297   \begin{table}[H]
298 < \caption{Best fit parameters for metal-adsorbate interactions. Distances are in \AA~and energies are in kcal/mol}
298 >  \caption{Best fit parameters for metal-CO cross-interactions. Metal-C
299 >    interactions are modeled with Lennard-Jones potential, while the
300 >    metal-O interactions were fit to Morse
301 >    potentials.  Distances are given in \AA~and energies in kcal/mol. }
302   \centering
303   \begin{tabular}{| c | cc | c | ccc |}
304   \hline
305 < \multicolumn{7}{| c |}{\textbf{Cross-Interactions} }\\
305 > &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ (\AA$^{-1}$) \\
306   \hline
115 &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ \\
116 \hline
307   \textbf{Pt-C} & 1.3 & 15  & \textbf{Pt-O} & 3.8 & 3.0 & 1 \\
308   \textbf{Au-C} & 1.9 & 6.5  & \textbf{Au-O} & 3.8 & 0.37 & 0.9\\
309  
310   \hline
311   \end{tabular}
312 + \label{tab:co_parameters}
313   \end{table}
314  
315   %Table of energies
316   \begin{table}[H]
317 < \caption{Absorption energies in eV}
317 >  \caption{Adsorption energies for CO on M(111) at the atop site using the potentials
318 >    described in this work.  All values are in eV.}
319   \centering
320   \begin{tabular}{| c | cc |}
321 < \hline
322 < & Calc. & Exp. \\
323 < \hline
324 < \textbf{Pt-CO} & -1.9 & -1.4~\cite{Kelemen}-- -1.9~\cite{Yeo} \\
325 < \textbf{Au-CO} & -0.39 & -0.44~\cite{TPD_Gold_CO} \\
326 < \hline
321 >  \hline
322 >  & Calculated & Experimental \\
323 >  \hline
324 >  \multirow{2}{*}{\textbf{Pt-CO}} & \multirow{2}{*}{-1.9} & -1.4 \bibpunct{}{}{,}{n}{}{,}
325 >  (Ref. \protect\cite{Kelemen:1979}) \\
326 > & &  -1.9 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{Yeo}) \\ \hline
327 >  \textbf{Au-CO} & -0.39 & -0.40 \bibpunct{}{}{,}{n}{}{,}  (Ref. \protect\cite{TPD_Gold}) \\
328 >  \hline
329   \end{tabular}
330 + \label{tab:co_energies}
331   \end{table}
332  
333 + \subsection{Pt(557) and Au(557) metal interfaces}
334  
335 + Our model systems are composed of 3888 Pt atoms and 3384 Au atoms in a
336 + FCC crystal that have been cut along the (557) plane so that they are
337 + periodic in the {\it x} and {\it y} directions, and have been oriented
338 + to expose two aligned (557) cuts along the extended {\it
339 +  z}-axis.  Simulations of the bare metal interfaces at temperatures
340 + ranging from 300~K to 1200~K were performed to observe the relative
341 + stability of the surfaces without a CO overlayer.  
342  
343 <
344 <
343 > The different bulk (and surface) melting temperatures (1337~K for Au
344 > and 2045~K for Pt) suggest that any possible reconstruction may happen at
345 > different temperatures for the two metals.  The bare Au and Pt surfaces were
346 > initially run in the canonical (NVT) ensemble at 800~K and 1000~K
347 > respectively for 100 ps. These temperatures were chosen because the
348 > surfaces were relatively stable at these temperatures when no CO was
349 > present, but experienced additional instability upon addition of CO in the time
350 > frames we were examining. Each surface was exposed to a range of CO
351 > that was initially placed in the vacuum region.  Upon full adsorption,
352 > these amounts correspond to 0\%, 5\%, 25\%, 33\%, and 50\% surface
353 > coverage. Higher coverages were tried, but the CO-CO repulsion was preventing
354 > a higher amount of adsorption.  Because of the difference in binding energies, the Pt
355 > systems very rarely had CO that was not bound to the surface, while
356 > the Au surfaces often had a significant CO population in the gas
357 > phase.  These systems were allowed to reach thermal equilibrium (over
358 > 5 ns) before being run in the microcanonical (NVE) ensemble for
359 > data collection. All of the systems examined had at least 40 ns in the
360 > data collection stage, although simulation times for some of the
361 > systems exceeded 200ns.  All simulations were run using the open
362 > source molecular dynamics package, OpenMD.\cite{Ewald,OOPSE}
363  
364   % Just results, leave discussion for discussion section
365 + % structure
366 + %       Pt: step wandering, double layers, no triangular motifs
367 + %       Au: step wandering, no double layers
368 + % dynamics
369 + %       diffusion
370 + %       time scale, formation, breakage
371   \section{Results}
372 < \subsection{Diffusion}
373 < While an ideal metallic surface is unlikely to experience much surface diffusion, high-index surfaces have large numbers of low-coordinated atoms which have a much easier time overcoming the energetic barriers limiting diffusion, leading to easier surface reconstructions. Surface movement was divided between the parallel ($\parallel$) and perpendicular ($\perp$) directions relative to the step edge. We were then able to calculate diffusion constants as a function of CO coverage. As can be seen in Table 4, the presence and amount of CO directly affects the diffusion constants of surface Platinum atoms. The presence of two 50\% coverage systems is to show how the diffusion process is affected by time. The majority of the systems were run for approximately 50 ns while the half monolayer system been running continuously. The lowered diffusion constant at longer run times will be examined in-depth in the discussion section.
372 > \subsection{Structural remodeling}
373 > Tao et al. showed experimentally that the Pt(557) surface
374 > undergoes two separate reconstructions upon CO
375 > adsorption.\cite{Tao:2010} The first involves a doubling of
376 > the step height and plateau length. Similar behavior has been
377 > seen to occur on numerous surfaces at varying conditions (Ni 977, Si 111, etc).
378 > \cite{Williams:1994,Williams:1991,Pearl} Of the two systems
379 > we examined, the Pt system showed a larger amount of
380 > reconstruction when compared to the Au system. The amount
381 > of reconstruction appears to be correlated to the amount of CO
382 > adsorbed upon the surface.  We believe this is related to the
383 > effect that adsorbate coverage has on edge breakup and surface
384 > diffusion of adatoms. While both systems displayed step-edge
385 > wandering, only the Pt surface underwent the doubling seen by
386 > Tao et al., within the time scales we were modeling. Specifically,
387 > only the 50~\% coverage Pt system was observed to have a
388 > step-edge undergo a complete doubling in the time scales we
389 > were able to monitor. This event encouraged us to allow that
390 > specific system to run for much longer periods during which two
391 > more double layers were created. The other systems, not displaying
392 > any large scale changes of interest, were all stopped after running
393 > for 40 ns in the microcanonical ensemble. Despite no observation
394 > of double layer formation, the other Pt systems tended to show
395 > more cumulative lateral movement of the step-edges when
396 > compared to the Au systems. The 50\% Pt system is highlighted
397 > in Figure \ref{fig:reconstruct} at various times along the simulation
398 > showing the evolution of the system.
399  
400 < %Table of Diffusion Constants
401 < %Add gold?M
402 < \begin{table}[H]
403 < \caption{Platinum diffusion constants parallel and perpendicular to the 557 step edge. As the coverage increases, the diffusion constants parallel and  perpendicular to the step edge both initially increase and then decrease slightly. There were two approaches of analysis. One looking at the surface atoms that had moved more than a prescribed amount over the run time and the other looking at all surface atoms. Units are \AA\textsuperscript{2}/ns}
404 < \centering
405 < \begin{tabular}{| c | ccc | ccc | c |}
154 < \hline
155 < \textbf{System Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & \textbf{Atoms} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & \textbf{Atoms} & \textbf{Time (ns)}\\
156 < \hline
157 < &\multicolumn{3}{c|}{\textbf{Mobile}}&\multicolumn{3}{c|}{\textbf{Surface Atoms}} & \\
158 < \hline
159 < 50\% & 3.74 & 0.89 & 497 & 2.05 & 0.49 & 912 & 116 \\
160 < 50\% & 5.81 & 1.59 & 365 & 2.41 & 0.68 & 912 & 46   \\
161 < 33\% & 6.73 & 2.47 & 332 & 2.51 & 0.93 & 912 & 46   \\
162 < 25\% & 5.38 & 2.04 & 361 & 2.18 & 0.84 & 912 & 46  \\
163 < 5\% & 5.54 & 0.63 & 230 & 1.44 & 0.19 & 912 & 46  \\
164 < 0\% & 3.53 & 0.61 & 282 & 1.11 & 0.22 & 912 & 56  \\
165 < \hline
166 < 50\%-r & 6.91 & 2.00 & 198 & 2.23 & 0.68  & 925 & 25\\
167 < 0\%-r  & 4.73 & 0.27 & 128 & 0.72 & 0.05 & 925 & 43\\
168 < \hline
169 < \end{tabular}
170 < \end{table}
400 > The second reconstruction on the Pt(557) surface observed by
401 > Tao involved the formation of triangular clusters that stretched
402 > across the plateau between two step-edges. Neither system, within
403 > our simulated time scales, experiences this reconstruction. A constructed
404 > system in which the triangular motifs were constructed on the surface
405 > will be explored in future work and is shown in the supporting information.
406  
407 + \subsection{Dynamics}
408 + While atomistic-like simulations of stepped surfaces have been
409 + performed before, they tend to be performed using Monte Carlo
410 + techniques\cite{Williams:1991,Williams:1994}. This allows them
411 + to efficiently sample the equilibrium thermodynamic landscape
412 + but at the expense of ignoring the dynamics of the system. Previous
413 + work by Pearl and Sibener\cite{Pearl}, using STM, has been able to
414 + visualize the coalescing of steps of Ni(977). The time scale of the image
415 + acquisition, $\sim$70 s/image provides an upper bounds for the time
416 + required for the doubling to actually occur. Statistical treatments of step-edges
417 + are adept at analyzing such systems. However, in a system where
418 + the number of steps is limited, examining the individual atoms that make
419 + up the steps can provide useful information as well.
420  
421  
422 + \subsubsection{Transport of surface metal atoms}
423 + %forcedSystems/stepSeparation
424 + The movement or wandering of a step-edge is a cooperative effect
425 + arising from the individual movements, primarily through surface
426 + diffusion, of the atoms making up the step. An ideal metal surface
427 + displaying a low index facet, (111) or (100) is unlikely to experience
428 + much surface diffusion because of the large energetic barrier that must
429 + be overcome to lift an atom out of the surface. The presence of step-edges
430 + on higher-index surfaces provide a source for mobile metal atoms.
431 + Breaking away from the step-edge on a clean surface still imposes an
432 + energetic penalty around $\sim$~40 kcal/mole, but is much less than lifting
433 + the same metal atom out from the surface,  \textgreater~60 kcal/mole, and
434 + the penalty lowers even further when CO is present in sufficient quantities
435 + on the surface. For certain tested distributions of CO, the penalty was lowered
436 + to $\sim$~20 kcal/mole. Once an adatom exists on the surface, its barrier for
437 + diffusion is negligible ( \textless~4 kcal/mole) and is well able to explore the
438 + terrace before potentially rejoining its original step-edge or becoming a part
439 + of a different edge. Atoms traversing separate terraces is a more difficult
440 + process, but can be overcome through a joining and lifting stage which is
441 + examined in the discussion section. By tracking the mobility of individual
442 + metal atoms on the Pt and Au surfaces we were able to determine the relative
443 + diffusion rates and how varying coverages of CO affected the rates. Close
444 + observation of the mobile metal atoms showed that they were typically in
445 + equilibrium with the step-edges, constantly breaking apart and rejoining.
446 + At times their motion was concerted and two or more adatoms would be
447 + observed moving together across the surfaces. The primary challenge in
448 + quantifying the overall surface mobility was in defining ``mobile" vs. ``static" atoms.
449 +
450 + A particle was considered mobile once it had traveled more than 2~\AA~
451 + between saved configurations of the system (10-100 ps). An atom that was
452 + truly mobile would typically travel much greater than this, but the 2~\AA~ cutoff
453 + was to prevent the in-place vibrational movement of non-surface atoms from
454 + being included in the analysis. Diffusion on  a surface is strongly affected by
455 + local structures and in this work the presence of single and double layer
456 + step-edges causes the diffusion parallel to the step-edges to be different
457 + from the diffusion perpendicular to these edges. This led us to compute
458 + those diffusions separately as seen in Figure \ref{fig:diff}.
459 +
460 + \subsubsection{Double layer formation}
461 + The increased amounts of diffusion on Pt at the higher CO coverages appears
462 + to play a primary role in the formation of double layers, although this conclusion
463 + does not explain the 33\% coverage Pt system. On the 50\% system, three
464 + separate layers were formed over the extended run time of this system. As
465 + mentioned earlier, previous experimental work has given some insight into the
466 + upper bounds of the time required for enough atoms to move around to allow two
467 + steps to coalesce\cite{Williams:1991,Pearl}. As seen in Figure \ref{fig:reconstruct},
468 + the first appearance of a double layer, a nodal site, appears at 19 ns into the
469 + simulation. Within 12 ns, nearly half of the step has formed the double layer and
470 + by 86 ns, a smooth complete layer has formed. The double layer is ``complete" by
471 + 37 ns but is a bit rough. From the appearance of the first node to the initial doubling
472 + of the layers ignoring their roughness took $\sim$~20 ns. Another ~40 ns was
473 + necessary for the layer to completely straighten. The other two layers in this
474 + simulation form over a period of 22 ns and 42 ns respectively. Comparing this to
475 + the upper bounds of the image scan, it is likely that aspects of this reconstruction
476 + occur very quickly.
477 +
478 + %Evolution of surface
479 + \begin{figure}[H]
480 + \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
481 + \caption{The Pt(557) / 50\% CO system at a sequence of times after
482 +  initial exposure to the CO: (a) 258 ps, (b) 19 ns, (c) 31.2 ns, and
483 +  (d) 86.1 ns. Disruption of the (557) step-edges occurs quickly.  The
484 +  doubling of the layers appears only after two adjacent step-edges
485 +  touch.  The circled spot in (b) nucleated the growth of the double
486 +  step observed in the later configurations.}
487 +  \label{fig:reconstruct}
488 + \end{figure}
489 +
490 + \begin{figure}[H]
491 + \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
492 + \caption{Diffusion constants for mobile surface atoms along directions
493 +  parallel ($\mathbf{D}_{\parallel}$) and perpendicular
494 +  ($\mathbf{D}_{\perp}$) to the (557) step-edges as a function of CO
495 +  surface coverage.  Diffusion parallel to the step-edge is higher
496 +  than that perpendicular to the edge because of the lower energy
497 +  barrier associated with traversing along the edge as compared to
498 +  completely breaking away. Additionally, the observed
499 +  maximum and subsequent decrease for the Pt system suggests that the
500 +  CO self-interactions are playing a significant role with regards to
501 +  movement of the Pt atoms around and across the surface. }
502 + \label{fig:diff}
503 + \end{figure}
504 +
505 +
506 +
507 +
508   %Discussion
509   \section{Discussion}
510 < Comparing the results from simulation to those reported previously by Tao et al. the similarities in the Platinum and CO system are quite strong. As shown in figure 1, the simulated platinum system under a CO atmosphere will restructure slightly by doubling the terrace heights. The restructuring appears to occur slowly, one to two Platinum atoms at a time. Looking at individual snapshots, these adatoms tend to either rise on top of the plateau or break away from the step edge and then diffuse perpendicularly to the step direction until reaching another step edge. This combination of growth and decay of the step edges appears to be in somewhat of a state of dynamic equilibrium. However, once two previously separated edges meet as shown in figure 1.B, this point tends to act as a focus or growth point for the rest of the edge to meet up, akin to that of a zipper. From the handful of cases where a double layer was formed during the simulation. Measuring from the initial appearance of a growth point, the double layer tends to be fully formed within $\sim$~35 ns.
510 > In this paper we have shown that we were able to accurately model the initial reconstruction of the
511 > Pt(557) surface upon CO adsorption as shown by Tao et al. \cite{Tao:2010}. More importantly, we
512 > were able to observe the dynamic processes necessary for this reconstruction.
513  
514 + \subsection{Mechanism for restructuring}
515 + Comparing the results from simulation to those reported previously by
516 + Tao et al.\cite{Tao:2010} the similarities in the Pt-CO system are quite
517 + strong. As shown in Figure \ref{fig:reconstruct}, the simulated Pt
518 + system under a CO atmosphere will restructure by doubling the terrace
519 + heights. The restructuring occurs slowly, one to two Pt atoms at a time.
520 + Looking at individual configurations of the system, the adatoms either
521 + break away from the step-edge and stay on the lower terrace or they lift
522 + up onto the higher terrace. Once ``free'' they will diffuse on the terrace
523 + until reaching another step-edge or coming back to their original edge.  
524 + This combination of growth and decay of the step-edges is in a state of
525 + dynamic equilibrium. However, once two previously separated edges
526 + meet as shown in Figure 1.B, this meeting point tends to act as a focus
527 + or growth point for the rest of the edge to meet up, akin to that of a zipper.
528 + From the handful of cases where a double layer was formed during the
529 + simulation, measuring from the initial appearance of a growth point, the
530 + double layer tends to be fully formed within $\sim$~35 ns.
531 +
532 + A number of possible mechanisms exist to explain the role of adsorbed
533 + CO in restructuring the Pt surface. Quadrupolar repulsion between adjacent
534 + CO molecules adsorbed on the surface is one likely possibility.  However,
535 + the quadrupole-quadrupole interaction is short-ranged and is attractive for
536 + some orientations.  If the CO molecules are ``locked'' in a specific orientation
537 + relative to each other, through atop adsorption perhaps, this explanation
538 + gains some weight.  The energetic repulsion between two CO located a
539 + distance of 2.77~\AA~apart (nearest-neighbor distance of Pt) with both in
540 + a  vertical orientation is 8.62 kcal/mole. Moving the CO apart to the second
541 + nearest-neighbor distance of 4.8~\AA~or 5.54~\AA~drops the repulsion to
542 + nearly 0 kcal/mole. Allowing the CO's to leave a purely vertical orientation
543 + also quickly drops the repulsion, a minimum is reached at $\sim$24 degrees
544 + of 6.2 kcal/mole. As mentioned above, the energy barrier for surface diffusion
545 + of a Pt adatom is only 4 kcal/mole. So this repulsion between CO can help
546 + increase the surface diffusion. However, the residence time of CO was
547 + examined and while the majority of the CO is on or near the surface throughout
548 + the run, it is extremely mobile. This mobility suggests that the CO are more
549 + likely to shift their positions without necessarily dragging the Pt along with them.
550 +
551 + Another possible and more likely mechanism for the restructuring is in the
552 + destabilization of strong Pt-Pt interactions by CO adsorbed on surface
553 + Pt atoms.  This would then have the effect of increasing surface mobility
554 + of these atoms.  To test this hypothesis, numerous configurations of
555 + CO in varying quantities were arranged on the higher and lower plateaus
556 + around a step on a otherwise clean Pt(557) surface. One representative
557 + configuration is displayed in Figure \ref{fig:lambda}. Single or concerted movement
558 + of Pt atoms was then examined to determine possible barriers. Because
559 + the movement was forced along a pre-defined reaction coordinate that may differ
560 + from the true minimum of this path, only the beginning and ending energies
561 + are displayed in Table \ref{tab:energies}. These values suggest that the presence of CO at suitable
562 + locations can lead to lowered barriers for Pt breaking apart from the step-edge.
563 + Additionally, as highlighted in Figure \ref{fig:lambda}, the presence of CO makes the
564 + burrowing and lifting of adatoms favorable, whereas without CO, the process is neutral
565 + in terms of energetics.
566 +
567 + %lambda progression of Pt -> shoving its way into the step
568 + \begin{figure}[H]
569 + \includegraphics[width=\linewidth]{lambdaProgression_atopCO.png}
570 + \caption{A model system of the Pt(557) surface was used as the framework
571 + for exploring energy barriers along a reaction coordinate. Various numbers,
572 + placements, and rotations of CO were examined as they affect Pt movement.
573 + The coordinate displayed in this Figure was a representative run. As shown
574 + in Table \ref{tab:rxcoord}, relative to the energy of the system at 0\%, there
575 + is a slight decrease upon insertion of the Pt atom into the step-edge along
576 + with the resultant lifting of the other Pt atom when CO is present at certain positions.}
577 + \label{fig:lambda}
578 + \end{figure}
579 +
580 +
581 +
582   \subsection{Diffusion}
583 < As shown in the results section, the diffusion parallel to the step edge tends to be much faster than that perpendicular to the step edge. Additionally, the coverage of CO appears to play a slight role in relative rates of diffusion, as shown in Table 4. Thus, the bottleneck of the double layer formation appears to be the initial formation of this growth point, which seems to be somewhat of a stochastic event. Once it appears, parallel diffusion, along the now slightly angled step edge, will allow for a faster formation of the double layer than if the entire process were dependent on only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the more likely a growth point is to be formed. One driving force behind this reconstruction appears to be the lowering of surface energy that occurs by doubling the terrace widths. (I'm not really proving this... I have the surface flatness to show it, but surface energy?)
583 > As shown in the results section, the diffusion parallel to the step-edge tends to be
584 > much larger than that perpendicular to the step-edge, likely because of the dynamic
585 > equilibrium that is established between the step-edge and adatom interface. The coverage
586 > of CO also appears to play a slight role in relative rates of diffusion, as shown in Figure \ref{fig:diff}.
587 > The
588 > Thus, the bottleneck of the double layer formation appears to be the initial formation
589 > of this growth point, which seems to be somewhat of a stochastic event. Once it
590 > appears, parallel diffusion, along the now slightly angled step-edge, will allow for
591 > a faster formation of the double layer than if the entire process were dependent on
592 > only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the
593 > more likely a growth point is to be formed.
594   \\
595 < \\
596 < %Evolution of surface
595 >
596 >
597 > %breaking of the double layer upon removal of CO
598   \begin{figure}[H]
599 < \includegraphics[scale=0.5]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
600 < \caption{Four snapshots at various times a) 258 ps b) 19 ns c) 31.2 ns d) 86.1 ns. Slight disruption of the surface occurs fairly quickly. However, the doubling of the layers seems to be very dependent on the initial linking of two separate step edges. The focal point in b, appears to be a growth spot for the rest of the double layer.}
599 > \includegraphics[width=\linewidth]{doubleLayerBreaking_greenBlue_whiteLetters.png}
600 > %:
601 > \caption{(A)  0 ps, (B) 100 ps, (C) 1 ns, after the removal of CO. The presence of the CO
602 > helped maintain the stability of the double layer and upon removal the two layers break
603 > and begin separating. The separation is not a simple pulling apart however, rather
604 > there is a mixing of the lower and upper atoms at the edge.}
605 > \label{fig:breaking}
606   \end{figure}
607  
608  
609  
610  
611   %Peaks!
612 < \includegraphics[scale=0.25]{doublePeaks_noCO.png}
613 < \section{Conclusion}
612 > \begin{figure}[H]
613 > \includegraphics[width=\linewidth]{doublePeaks_noCO.png}
614 > \caption{At the initial formation of this double layer  ( $\sim$ 37 ns) there is a degree
615 > of roughness inherent to the edge. The next $\sim$ 40 ns show the edge with
616 > aspects of waviness and by 80 ns the double layer is completely formed and smooth. }
617 > \label{fig:peaks}
618 > \end{figure}
619  
620  
621 + %Don't think I need this
622 + %clean surface...
623 + %\begin{figure}[H]
624 + %\includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
625 + %\caption{}
626  
627 + %\end{figure}
628 + %\label{fig:clean}
629  
630  
631 + \section{Conclusion}
632 + In this work we have shown the reconstruction of the Pt(557) crystalline surface upon adsorption of CO in < $\mu s$. Only the highest coverage Pt system showed this initial reconstruction similar to that seen previously. The strong interaction between Pt and CO and the limited interaction between Au and CO helps explain the differences between the two systems.
633  
634 + %Things I am not ready to remove yet
635  
636 + %Table of Diffusion Constants
637 + %Add gold?M
638 + % \begin{table}[H]
639 + %   \caption{}
640 + %   \centering
641 + % \begin{tabular}{| c | cc | cc | }
642 + %   \hline
643 + %   &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
644 + %   \hline
645 + %   \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$  \\
646 + %   \hline
647 + %   50\% & 4.32(2) & 1.185(8)  & 1.72(2) & 0.455(6) \\
648 + %   33\% & 5.18(3)  & 1.999(5)  & 1.95(2) & 0.337(4)   \\
649 + %   25\% & 5.01(2)  & 1.574(4)  & 1.26(3) & 0.377(6) \\
650 + %   5\%   & 3.61(2)  & 0.355(2)  & 1.84(3)  & 0.169(4)  \\
651 + %   0\%   & 3.27(2)  & 0.147(4)  & 1.50(2)  & 0.194(2)   \\
652 + %   \hline
653 + % \end{tabular}
654 + % \end{table}
655  
656 + \section{Acknowledgments}
657 + Support for this project was provided by the National Science
658 + Foundation under grant CHE-0848243 and by the Center for Sustainable
659 + Energy at Notre Dame (cSEND). Computational time was provided by the
660 + Center for Research Computing (CRC) at the University of Notre Dame.
661  
662 <
663 <
664 < \end{document}
662 > \newpage
663 > \bibliography{firstTryBibliography}
664 > \end{doublespace}
665 > \end{document}

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