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1 < \documentclass[a4paper,12pt]{article}
2 <
1 > \documentclass[11pt]{article}
2 > \usepackage{amsmath}
3 > \usepackage{amssymb}
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 5, 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 surface reconstructions of Pt and Au(557) under
72 + various CO coverages using molecular dynamics in order to
73 + explore possible mechanisms for any observed reconstructions
74 + and their dynamics. The metal-CO interactions were parameterized
75 + as part of this work so that an efficient large-scale treatment of
76 + this system could be undertaken. The large difference in binding
77 + strengths of the metal-CO interactions was found to play a significant
78 + role with regards to step-edge stability and adatom diffusion. A
79 + small correlation between coverage and the diffusion constant
80 + was also determined. The energetics of CO adsorbed to the surface
81 + is sufficient to explain the reconstructions observed on the Pt
82 + systems and the lack  of reconstruction of the Au systems.
83  
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 investigation into 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 > Since restructuring typically occurs 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 undergo a large scale reconstruction under certain conditions.\cite{Tao:2010}
124 > The Au(557) surface, because of a weaker interaction with CO, is seen as less
125 > likely to undergo this kind of reconstruction. However, Peters et al.\cite{Peters:2000}
126 > and Piccolo et al.\cite{Piccolo:2004} have both observed CO-induced
127 > reconstruction of a Au(111) surface. Peters et al. saw a relaxation to the
128 > 22 x $\sqrt{3}$ cell. They argued that only a few Au atoms
129 > become adatoms, limiting the stress of this reconstruction while
130 > allowing the rest to relax and approach the ideal (111)
131 > configuration. They did not see the usual herringbone pattern being greatly
132 > affected by this relaxation. Piccolo et al. on the other hand, did see a
133 > disruption of the herringbone pattern as CO was adsorbed to the
134 > surface. Both groups suggested that the preference CO shows for
135 > low-coordinated Au atoms was the primary driving force for the reconstruction.
136  
137  
138  
139 + %Platinum molecular dynamics
140 + %gold molecular dynamics
141  
61
142   \section{Simulation Methods}
143 < 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.
144 < %Metal
145 < \subsection{Metal}
146 < 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.
147 < %Can I increase the \sum size, not sure how...
148 < \begin{equation}
149 < E_{tot} = \sum_i F_i[\rho_{h,i}] + \frac{1}{2}\sum_i\sum_{j(\ne i)} \phi_{ij}(R_{ij})
150 < \end{equation}
151 < \begin{equation}
152 < \rho_{h,i} = \sum_{j (\ne i)} \rho_j^a(R_{ij})
153 < \end{equation}
154 < The EAM functional forms are used to model the Au and Pt self-interactions in all of our simulations.
155 < %CO
156 < \subsection{CO}
157 < 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{}.
143 > The challenge in modeling any solid/gas interface is the
144 > development of a sufficiently general yet computationally tractable
145 > model of the chemical interactions between the surface atoms and
146 > adsorbates.  Since the interfaces involved are quite large (10$^3$ -
147 > 10$^6$ atoms) and respond slowly to perturbations, {\it ab initio}
148 > molecular dynamics
149 > (AIMD),\cite{KRESSE:1993ve,KRESSE:1993qf,KRESSE:1994ul} Car-Parrinello
150 > methods,\cite{CAR:1985bh,Izvekov:2000fv,Guidelli:2000fy} and quantum
151 > mechanical potential energy surfaces remain out of reach.
152 > Additionally, the ``bonds'' between metal atoms at a surface are
153 > typically not well represented in terms of classical pairwise
154 > interactions in the same way that bonds in a molecular material are,
155 > nor are they captured by simple non-directional interactions like the
156 > Coulomb potential.  For this work, we have used classical molecular
157 > dynamics with potential energy surfaces that are specifically tuned
158 > for transition metals.  In particular, we used the EAM potential for
159 > Au-Au and Pt-Pt interactions\cite{EAM}. The CO was modeled using a rigid
160 > three-site model developed by Straub and Karplus for studying
161 > photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and
162 > Pt-CO cross interactions were parameterized as part of this work.
163 >  
164 > \subsection{Metal-metal interactions}
165 > Many of the potentials used for modeling transition metals are based
166 > on a non-pairwise additive functional of the local electron
167 > density. The embedded atom method (EAM) is perhaps the best known of
168 > these
169 > methods,\cite{Daw84,Foiles86,Johnson89,Daw89,Plimpton93,Voter95a,Lu97,Alemany98}
170 > but other models like the Finnis-Sinclair\cite{Finnis84,Chen90} and
171 > the quantum-corrected Sutton-Chen method\cite{QSC,Qi99} have simpler
172 > parameter sets. The glue model of Ercolessi et al. is among the
173 > fastest of these density functional approaches.\cite{Ercolessi88} In
174 > all of these models, atoms are conceptualized as a positively charged
175 > core with a radially-decaying valence electron distribution. To
176 > calculate the energy for embedding the core at a particular location,
177 > the electron density due to the valence electrons at all of the other
178 > atomic sites is computed at atom $i$'s location,
179 > \begin{equation*}
180 > \bar{\rho}_i = \sum_{j\neq i} \rho_j(r_{ij})
181 > \end{equation*}
182 > Here, $\rho_j(r_{ij})$ is the function that describes the distance
183 > dependence of the valence electron distribution of atom $j$. The
184 > contribution to the potential that comes from placing atom $i$ at that
185 > location is then
186 > \begin{equation*}
187 > V_i =  F[ \bar{\rho}_i ]  + \sum_{j \neq i} \phi_{ij}(r_{ij})
188 > \end{equation*}
189 > where $F[ \bar{\rho}_i ]$ is an energy embedding functional, and
190 > $\phi_{ij}(r_{ij})$ is a pairwise term that is meant to represent the
191 > repulsive overlap of the two positively charged cores.  
192 >
193 > % The {\it modified} embedded atom method (MEAM) adds angular terms to
194 > % the electron density functions and an angular screening factor to the
195 > % pairwise interaction between two
196 > % atoms.\cite{BASKES:1994fk,Lee:2000vn,Thijsse:2002ly,Timonova:2011ve}
197 > % MEAM has become widely used to simulate systems in which angular
198 > % interactions are important (e.g. silicon,\cite{Timonova:2011ve} bcc
199 > % metals,\cite{Lee:2001qf} and also interfaces.\cite{Beurden:2002ys})
200 > % MEAM presents significant additional computational costs, however.
201 >
202 > The EAM, Finnis-Sinclair, and the Quantum Sutton-Chen (QSC) potentials
203 > have all been widely used by the materials simulation community for
204 > simulations of bulk and nanoparticle
205 > properties,\cite{Chui:2003fk,Wang:2005qy,Medasani:2007uq}
206 > melting,\cite{Belonoshko00,sankaranarayanan:155441,Sankaranarayanan:2005lr}
207 > fracture,\cite{Shastry:1996qg,Shastry:1998dx} crack
208 > propagation,\cite{BECQUART:1993rg} and alloying
209 > dynamics.\cite{Shibata:2002hh} One of EAM's strengths
210 > is its sensitivity to small changes in structure. This arises
211 > from the original parameterization, where the interactions
212 > up to the third nearest neighbor were taken into account.\cite{Voter95a}
213 > Comparing that to the glue model of Ercolessi et al.\cite{Ercolessi88}
214 > which is only parameterized up to the nearest-neighbor
215 > interactions, EAM is a suitable choice for systems where
216 > the bulk properties are of secondary importance to low-index
217 > surface structures. Additionally, the similarity of EAMs functional
218 > treatment of the embedding energy to standard density functional
219 > theory (DFT) makes fitting DFT-derived cross potentials with adsorbates somewhat easier.
220 > \cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}  
221 >
222 >
223 >
224 >
225 > \subsection{Carbon Monoxide model}
226 > Previous explanations for the surface rearrangements center on
227 > the large linear quadrupole moment of carbon monoxide.\cite{Tao:2010}  
228 > We used a model first proposed by Karplus and Straub to study
229 > the photodissociation of CO from myoglobin because it reproduces
230 > the quadrupole moment well.\cite{Straub} The Straub and
231 > Karplus model treats CO as a rigid three site molecule with a massless M
232 > site at the molecular center of mass. The geometry and interaction
233 > parameters are reproduced in Table~\ref{tab:CO}. The effective
234 > dipole moment, calculated from the assigned charges, is still
235 > small (0.35 D) while the linear quadrupole (-2.40 D~\AA) is close
236 > to the experimental (-2.63 D~\AA)\cite{QuadrupoleCO} and quantum
237 > mechanical predictions (-2.46 D~\AA)\cite{QuadrupoleCOCalc}.
238   %CO Table
239   \begin{table}[H]
240 < \caption{$\sigma$, $\epsilon$ and charges for CO self-interactions\cite{}. Distances are in \AA~, energies are in kcal/mol, and charges are in $e$.}
240 >  \caption{Positions, Lennard-Jones parameters ($\sigma$ and
241 >    $\epsilon$), and charges for the CO-CO
242 >    interactions in Ref.\bibpunct{}{}{,}{n}{}{,} \protect\cite{Straub}. Distances are in \AA, energies are
243 >    in kcal/mol, and charges are in atomic units.}
244   \centering
245 < \begin{tabular}{| c | ccc |}
245 > \begin{tabular}{| c | c | ccc |}
246   \hline
247 < \multicolumn{4}{|c|}{\textbf{Self-Interactions}}\\
247 > &  {\it z} & $\sigma$ & $\epsilon$ & q\\
248   \hline
249 < &  $\sigma$ & $\epsilon$ & q\\
249 > \textbf{C} & -0.6457 &  3.83 & 0.0262   &   -0.75 \\
250 > \textbf{O} &  0.4843 &  3.12 &  0.1591  &   -0.85 \\
251 > \textbf{M} & 0.0 & -  &  -  &    1.6 \\
252   \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
253   \end{tabular}
254 + \label{tab:CO}
255   \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.
256  
257 + \subsection{Cross-Interactions between the metals and carbon monoxide}
258  
259 + Since the adsorption of CO onto a Pt surface has been the focus
260 + of much experimental \cite{Yeo, Hopster:1978, Ertl:1977, Kelemen:1979}
261 + and theoretical work
262 + \cite{Beurden:2002ys,Pons:1986,Deshlahra:2009,Feibelman:2001,Mason:2004}
263 + there is a significant amount of data on adsorption energies for CO on
264 + clean metal surfaces. An earlier model by Korzeniewski {\it et
265 +  al.}\cite{Pons:1986} served as a starting point for our fits. The parameters were
266 + modified to ensure that the Pt-CO interaction favored the atop binding
267 + position on Pt(111). These parameters are reproduced in Table~\ref{tab:co_parameters}.
268 + The modified parameters yield binding energies that are slightly higher
269 + than the experimentally-reported values as shown in Table~\ref{tab:co_energies}. Following Korzeniewski
270 + et al.,\cite{Pons:1986} the Pt-C interaction was fit to a deep
271 + Lennard-Jones interaction to mimic strong, but short-ranged partial
272 + binding between the Pt $d$ orbitals and the $\pi^*$ orbital on CO. The
273 + Pt-O interaction was modeled with a Morse potential with a large
274 + equilibrium distance, ($r_o$).  These choices ensure that the C is preferred
275 + over O as the surface-binding atom. In most cases, the Pt-O parameterization contributes a weak
276 + repulsion which favors the atop site.  The resulting potential-energy
277 + surface suitably recovers the calculated Pt-C separation length
278 + (1.6~\AA)\cite{Beurden:2002ys} and affinity for the atop binding
279 + position.\cite{Deshlahra:2012, Hopster:1978}
280  
281 + %where did you actually get the functionals for citation?
282 + %scf calculations, so initial relaxation was of the four layers, but two layers weren't kept fixed, I don't think
283 + %same cutoff for slab and slab + CO ? seems low, although feibelmen had values around there...
284 + The Au-C and Au-O cross-interactions were also fit using Lennard-Jones and
285 + Morse potentials, respectively, to reproduce Au-CO binding energies.
286 + The limited experimental data for CO adsorption on Au required refining the fits against plane-wave DFT calculations.
287 + Adsorption energies were obtained from gas-surface DFT calculations with a
288 + periodic supercell plane-wave basis approach, as implemented in the
289 + {\sc Quantum ESPRESSO} package.\cite{QE-2009} Electron cores were
290 + described with the projector augmented-wave (PAW)
291 + method,\cite{PhysRevB.50.17953,PhysRevB.59.1758} with plane waves
292 + included to an energy cutoff of 20 Ry. Electronic energies are
293 + computed with the PBE implementation of the generalized gradient
294 + approximation (GGA) for gold, carbon, and oxygen that was constructed
295 + by Rappe, Rabe, Kaxiras, and Joannopoulos.\cite{Perdew_GGA,RRKJ_PP}
296 + In testing the Au-CO interaction, Au(111) supercells were constructed of four layers of 4
297 + Au x 2 Au surface planes and separated from vertical images by six
298 + layers of vacuum space. The surface atoms were all allowed to relax
299 + before CO was added to the system. Electronic relaxations were
300 + performed until the energy difference between subsequent steps
301 + was less than $10^{-8}$ Ry.   Nonspin-polarized supercell calculations
302 + were performed with a 4~x~4~x~4 Monkhorst-Pack {\bf k}-point sampling of the first Brillouin
303 + zone.\cite{Monkhorst:1976,PhysRevB.13.5188} The relaxed gold slab was
304 + then used in numerous single point calculations with CO at various
305 + heights (and angles relative to the surface) to allow fitting of the
306 + empirical force field.
307  
308 < %\subsection{System}
309 < %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.
308 > %Hint at future work
309 > The parameters employed for the metal-CO cross-interactions in this work
310 > are shown in Table~\ref{tab:co_parameters} and the binding energies on the
311 > (111) surfaces are displayed in Table~\ref{tab:co_energies}.  Charge transfer
312 > and polarization are neglected in this model, although these effects are likely to
313 > affect binding energies and binding site preferences, and will be addressed in
314 > future work.
315  
104
316   %Table  of Parameters
317   %Pt Parameter Set 9
318   %Au Parameter Set 35
319   \begin{table}[H]
320 < \caption{Best fit parameters for metal-adsorbate interactions. Distances are in \AA~and energies are in kcal/mol}
320 >  \caption{Best fit parameters for metal-CO cross-interactions. Metal-C
321 >    interactions are modeled with Lennard-Jones potentials. While the
322 >    metal-O interactions were fit to Morse
323 >    potentials.  Distances are given in \AA~and energies in kcal/mol. }
324   \centering
325   \begin{tabular}{| c | cc | c | ccc |}
326   \hline
327 < \multicolumn{7}{| c |}{\textbf{Cross-Interactions} }\\
327 > &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ (\AA$^{-1}$) \\
328   \hline
115 &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ \\
116 \hline
329   \textbf{Pt-C} & 1.3 & 15  & \textbf{Pt-O} & 3.8 & 3.0 & 1 \\
330   \textbf{Au-C} & 1.9 & 6.5  & \textbf{Au-O} & 3.8 & 0.37 & 0.9\\
331  
332   \hline
333   \end{tabular}
334 + \label{tab:co_parameters}
335   \end{table}
336  
337   %Table of energies
338   \begin{table}[H]
339 < \caption{Absorption energies in eV}
339 >  \caption{Adsorption energies for a single CO at the atop site on M(111) at the atop site using the potentials
340 >    described in this work.  All values are in eV.}
341   \centering
342   \begin{tabular}{| c | cc |}
343 < \hline
344 < & Calc. & Exp. \\
345 < \hline
346 < \textbf{Pt-CO} & -1.9 & -1.4~\cite{Kelemen}-- -1.9~\cite{Yeo} \\
347 < \textbf{Au-CO} & -0.39 & -0.44~\cite{TPD_Gold_CO} \\
348 < \hline
343 >  \hline
344 >  & Calculated & Experimental \\
345 >  \hline
346 >  \multirow{2}{*}{\textbf{Pt-CO}} & \multirow{2}{*}{-1.9} & -1.4 \bibpunct{}{}{,}{n}{}{,}
347 >  (Ref. \protect\cite{Kelemen:1979}) \\
348 > & &  -1.9 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{Yeo}) \\ \hline
349 >  \textbf{Au-CO} & -0.39 & -0.40 \bibpunct{}{}{,}{n}{}{,}  (Ref. \protect\cite{TPD_Gold}) \\
350 >  \hline
351   \end{tabular}
352 + \label{tab:co_energies}
353   \end{table}
354  
355 + \subsection{Pt(557) and Au(557) metal interfaces}
356 + Our Pt system is an orthorhombic periodic box of dimensions
357 + 54.482~x~50.046~x~120.88~\AA~while our Au system has
358 + dimensions of 57.4~x~51.9285~x~100~\AA.
359 + The systems are arranged in a FCC crystal that have been cut
360 + along the (557) plane so that they are periodic in the {\it x} and
361 + {\it y} directions, and have been oriented to expose two aligned
362 + (557) cuts along the extended {\it z}-axis.  Simulations of the
363 + bare metal interfaces at temperatures ranging from 300~K to
364 + 1200~K were performed to confirm the relative
365 + stability of the surfaces without a CO overlayer.  
366  
367 + The different bulk melting temperatures (1337~K for Au
368 + and 2045~K for Pt) suggest that any possible reconstruction should happen at
369 + different temperatures for the two metals.  The bare Au and Pt surfaces were
370 + initially run in the canonical (NVT) ensemble at 800~K and 1000~K
371 + respectively for 100 ps. The two surfaces were relatively stable at these
372 + temperatures when no CO was present, but experienced increased surface
373 + mobility on addition of CO. Each surface was then dosed with different concentrations of CO
374 + that was initially placed in the vacuum region.  Upon full adsorption,
375 + these concentrations correspond to 0\%, 5\%, 25\%, 33\%, and 50\% surface
376 + coverage. Higher coverages resulted in the formation of a double layer of CO,
377 + which introduces artifacts that are not relevant to (557) reconstruction.
378 + Because of the difference in binding energies, nearly all of the CO was bound to the Pt surface, while
379 + the Au surfaces often had a significant CO population in the gas
380 + phase.  These systems were allowed to reach thermal equilibrium (over
381 + 5 ns) before being run in the microcanonical (NVE) ensemble for
382 + data collection. All of the systems examined had at least 40 ns in the
383 + data collection stage, although simulation times for some Pt of the
384 + systems exceeded 200~ns.  Simulations were carried out using the open
385 + source molecular dynamics package, OpenMD.\cite{Ewald,OOPSE}
386  
387  
388  
389  
390 < % Just results, leave discussion for discussion section
390 > % RESULTS
391 > %
392   \section{Results}
393 < \subsection{Diffusion}
394 < 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.
393 > \subsection{Structural remodeling}
394 > The surfaces of both systems, upon dosage of CO, began
395 > to undergo remodeling that was not observed in the bare
396 > metal system. The surfaces to which no CO was exposed
397 > did experience minor roughening of the step-edge, but the
398 > (557) lattice was well-maintained throughout the simulation
399 > time. The Au systems were limited to greater amounts of
400 > roughening, i.e. breakup of the step-edge, and some step
401 > wandering. The lower coverage Pt systems experienced
402 > similar restructuring but to a greater extent when
403 > compared to the Au systems. The 50\% coverage
404 > Pt system formed double layers at numerous spots upon its surface.
405  
148 %Table of Diffusion Constants
149 %Add gold?M
150 \begin{table}[H]
151 \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}
152 \centering
153 \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}
406  
407 + \subsubsection{Step wandering}
408 + The 0\% coverage surfaces for both metals showed
409 + minimal movement at their respective run temperatures.
410 + As the coverage increased, the mobility of the surface
411 + also increased. Additionally, at the higher coverages
412 + on both metals, there was a large increase in the amount
413 + of observed step-wandering. Previous work by
414 + Williams\cite{Williams:1993} highlighted the entropic
415 + contribution to the repulsion felt between step-edges,
416 + and situations were that repulsion could be negated, or
417 + overcome, to allow for step coalescence or facet formation.
418  
419 + \subsubsection{Double layers}
420 + Tao et al. have shown experimentally that the Pt(557) surface
421 + undergoes two separate reconstructions upon CO
422 + adsorption.\cite{Tao:2010} The first involves a doubling of
423 + the step height and plateau length. Similar behavior has been
424 + seen to occur on numerous surfaces at varying conditions: Ni(977), Si(111).
425 + \cite{Williams:1994,Williams:1991,Pearl} Of the two systems
426 + we examined, the Pt system showed a greater propensity for
427 + reconstruction when compared to the Au system. The amount
428 + of reconstruction is correlated to the amount of CO
429 + adsorbed upon the surface.  This appears to be related to the
430 + effect that adsorbate coverage has on edge breakup and on the surface
431 + diffusion of metal adatoms. While both systems displayed step-edge
432 + wandering, only the Pt surface underwent the doubling seen by
433 + Tao et al. within the time scales studied here.  
434 + Only the 50\% coverage Pt system exhibited
435 + a complete doubling in the time scales we
436 + were able to monitor. Over longer periods (150~ns) two more double layers formed on this interface.
437 + Although double layer formation did not occur in the other Pt systems, they show
438 + more lateral movement of the step-edges
439 + compared to their Au counterparts. The 50\% Pt system is highlighted
440 + in Figure \ref{fig:reconstruct} at various times along the simulation
441 + showing the evolution of a step-edge.
442  
443 + The second reconstruction on the Pt(557) surface observed by
444 + Tao involved the formation of triangular clusters that stretched
445 + across the plateau between two step-edges. Neither system, within
446 + the 40~ns time scale, experienced this reconstruction.
447 +
448 + \subsection{Dynamics}
449 + Previous atomistic simulations of stepped surfaces dealt largely
450 + with the energetics and structures at different conditions
451 + \cite{Williams:1991,Williams:1994}. Consequently, the most common
452 + technique utilized to date has been Monte Carlo sampling. Monte Carlo gives an efficient
453 + sampling of the equilibrium thermodynamic landscape at the expense
454 + of ignoring the dynamics of the system. Previous work by Pearl and
455 + Sibener\cite{Pearl}, using STM, has been able to show the coalescing
456 + of steps on Ni(977). The time scale of the image acquisition,
457 + $\sim$70 s/image provides an upper bound for the time required for
458 + the doubling to occur. In this section we give data on dynamic and
459 + transport properties, e.g. diffusion, layer formation time, etc.
460 +
461 +
462 + \subsubsection{Transport of surface metal atoms}
463 + %forcedSystems/stepSeparation
464 + The movement or wandering of a step-edge is a cooperative effect
465 + arising from the individual movements, primarily through surface
466 + diffusion, of the atoms making up the steps. An ideal metal surface
467 + displaying a low index facet, (111) or (100), is unlikely to experience
468 + much surface diffusion because of the large energetic barrier that must
469 + be overcome to lift an atom out of the surface. The presence of step-edges
470 + on higher-index surfaces provide a source for mobile metal atoms.
471 + Breaking away from the step-edge on a clean surface still imposes an
472 + energetic penalty around $\sim$~40 kcal/mol, but this is significantly easier than lifting
473 + the same metal atom vertically out of the surface,  \textgreater~60 kcal/mol.
474 + The penalty lowers significantly when CO is present in sufficient quantities
475 + on the surface. For certain distributions of CO, the penalty can fall as low as
476 + $\sim$~20 kcal/mol. Once an adatom exists on the surface, the barrier for
477 + diffusion is negligible ( \textless~4 kcal/mol) and these adatoms are
478 + able to explore the terrace before rejoining either the original step-edge or
479 + becoming a part of a different edge. It is a more difficult process for an atom
480 + to traverse to a separate terrace although the presence of CO can lower the
481 + energy barrier required to lift or lower the adatom. By tracking the mobility of individual
482 + metal atoms on the Pt and Au surfaces we were able to determine the relative
483 + diffusion constants, as well as how varying coverages of CO affect the diffusion. Close
484 + observation of the mobile metal atoms showed that they were typically in
485 + equilibrium with the step-edges, dynamically breaking apart and rejoining the edges.
486 + At times, their motion was concerted and two or more adatoms would be
487 + observed moving together across the surfaces.
488 +
489 + A particle was considered ``mobile'' once it had traveled more than 2~\AA~
490 + between saved configurations of the system (typically 10-100 ps). An atom that was
491 + truly mobile would typically travel much greater distances than this, but the 2~\AA~cutoff
492 + was used to prevent swamping the diffusion data with the in-place vibrational
493 + movement of buried atoms. Diffusion on  a surface is strongly affected by
494 + local structures and in this work, the presence of single and double layer
495 + step-edges causes the diffusion parallel to the step-edges to be different
496 + from the diffusion perpendicular to these edges. Parallel and perpendicular
497 + diffusion constants are shown in Figure \ref{fig:diff}.
498 +
499 + \subsubsection{Dynamics of double layer formation}
500 + The increased diffusion on Pt at the higher
501 + CO coverages plays a primary role in double layer formation. However, this is not
502 + a complete explanation -- the 33\%~Pt system
503 + has higher diffusion constants but did not show
504 + any signs of edge doubling. On the
505 + 50\%~Pt system, three separate layers were formed over
506 + 150~ns of simulation time. Previous experimental
507 + work gives insight into the upper bounds of the
508 + time required for step coalescence.\cite{Williams:1991,Pearl}
509 + In this system, as seen in Figure \ref{fig:reconstruct}, the first
510 + appearance of a double layer, appears at 19~ns
511 + into the simulation. Within 12~ns of this nucleation event, nearly half of the step has
512 + formed the double layer and by 86 ns, the complete layer
513 + has been flattened out. The double layer could be considered
514 + ``complete" by 37~ns but remains a bit rough. From the
515 + appearance of the first nucleation event to the first observed double layer, the process took $\sim$20~ns. Another
516 + $\sim$40~ns was necessary for the layer to completely straighten.
517 + The other two layers in this simulation formed over periods of
518 + 22~ns and 42~ns respectively. Comparing this to the upper
519 + bounds of the image scan, it is likely that most aspects of this
520 + reconstruction occur very rapidly. A possible explanation
521 + for this rapid reconstruction is the elevated temperatures
522 + under which our systems were simulated. It is probable that the process would
523 + take longer at lower temperatures.
524 +
525 + %Evolution of surface
526 + \begin{figure}[H]
527 + \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
528 + \caption{The Pt(557) / 50\% CO system at a sequence of times after
529 +  initial exposure to the CO: (a) 258 ps, (b) 19 ns, (c) 31.2 ns, and
530 +  (d) 86.1 ns. Disruption of the (557) step-edges occurs quickly.  The
531 +  doubling of the layers appears only after two adjacent step-edges
532 +  touch.  The circled spot in (b) nucleated the growth of the double
533 +  step observed in the later configurations.}
534 +  \label{fig:reconstruct}
535 + \end{figure}
536 +
537 + \begin{figure}[H]
538 + \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
539 + \caption{Diffusion constants for mobile surface atoms along directions
540 +  parallel ($\mathbf{D}_{\parallel}$) and perpendicular
541 +  ($\mathbf{D}_{\perp}$) to the (557) step-edges as a function of CO
542 +  surface coverage.  Diffusion parallel to the step-edge is higher
543 +  than that perpendicular to the edge because of the lower energy
544 +  barrier associated with traversing along the edge as compared to
545 +  completely breaking away. Additionally, the observed
546 +  maximum and subsequent decrease for the Pt system suggests that the
547 +  CO self-interactions are playing a significant role with regards to
548 +  movement of the Pt atoms around and across the surface. }
549 + \label{fig:diff}
550 + \end{figure}
551 +
552 +
553 +
554 +
555   %Discussion
556   \section{Discussion}
557 < 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.
557 > We have shown that the classical potential models are able to model the initial reconstruction of the
558 > Pt(557) surface upon CO adsorption as shown by Tao et al. \cite{Tao:2010}. More importantly, we
559 > were able to observe features of the dynamic processes necessary for this reconstruction.
560  
561 + \subsection{Mechanism for restructuring}
562 + Since the Au surface showed no large scale restructuring throughout
563 + our simulation time our discussion will focus on the 50\% Pt-CO system
564 + which did undergo the doubling featured in Figure \ref{fig:reconstruct}.
565 + Similarities of our results to those reported previously by
566 + Tao et al.\cite{Tao:2010} are quite
567 + strong. The simulated Pt
568 + system exposed to a large dosage of CO readily restructures by doubling the terrace
569 + widths and step heights. The restructuring occurs in a piecemeal fashion, one to two Pt atoms at a time, but is rapid on experimental timescales.
570 + The adatoms either
571 + break away from the step-edge and stay on the lower terrace or they lift
572 + up onto a higher terrace. Once ``free'', they diffuse on the terrace
573 + until reaching another step-edge or rejoining their original edge.  
574 + This combination of growth and decay of the step-edges is in a state of
575 + dynamic equilibrium. However, once two previously separated edges
576 + meet as shown in Figure 1.B, this nucleates the rest of the edge to meet up, forming a double layer.
577 + From simulations which exhibit a double layer, the time delay from the initial appearance of a nucleation point to a fully formed double layer is $\sim$35 ns.
578 +
579 + A number of possible mechanisms exist to explain the role of adsorbed
580 + CO in restructuring the Pt surface. Quadrupolar repulsion between adjacent
581 + CO molecules adsorbed on the surface is one possibility.  However,
582 + the quadrupole-quadrupole interaction is short-ranged and is attractive for
583 + some orientations.  If the CO molecules are ``locked'' in a specific orientation
584 + relative to each other, through atop adsorption for example, this explanation
585 + gains some credence.  The energetic repulsion between two CO located a
586 + distance of 2.77~\AA~apart (nearest-neighbor distance of Pt) and both in
587 + a  vertical orientation, is 8.62 kcal/mol. Moving the CO apart to the second
588 + nearest-neighbor distance of 4.8~\AA~or 5.54~\AA~drops the repulsion to
589 + nearly 0 kcal/mol. Allowing the CO's to leave a purely vertical orientation
590 + also quickly drops the repulsion, a minimum of 6.2 kcal/mol is reached at $\sim$24 degrees between the 2 CO when the carbons are locked at a distance of 2.77 \AA apart.
591 + As mentioned above, the energy barrier for surface diffusion
592 + of a Pt adatom is only 4 kcal/mol. So this repulsion between neighboring CO molecules can
593 + increase the surface diffusion. However, the residence time of CO on Pt was
594 + examined and while the majority of the CO is on or near the surface throughout
595 + the run, most molecules are mobile. This mobility suggests that the CO are more
596 + likely to shift their positions without necessarily the Pt along with them.
597 +
598 + Another possible and more likely mechanism for the restructuring is in the
599 + destabilization of strong Pt-Pt interactions by CO adsorbed on surface
600 + Pt atoms.  This would then have the effect of increasing surface mobility
601 + of these atoms.  To test this hypothesis, numerous configurations of
602 + CO in varying quantities were arranged on the higher and lower plateaus
603 + around a step on a otherwise clean Pt(557) surface. One representative
604 + configuration is displayed in Figure \ref{fig:lambda}. Single or concerted movement
605 + of Pt atoms was then examined to determine possible barriers. Because
606 + the movement was forced along a pre-defined reaction coordinate that may differ
607 + from the true minimum of this path, only the beginning and ending energies
608 + are displayed in Table \ref{tab:energies}. These values suggest that the presence of CO at suitable
609 + locations can lead to lowered barriers for Pt breaking apart from the step-edge.
610 + Additionally, as highlighted in Figure \ref{fig:lambda}, the presence of CO makes the
611 + burrowing and lifting of adatoms favorable, whereas without CO, the process is neutral
612 + in terms of energetics.
613 +
614 + %lambda progression of Pt -> shoving its way into the step
615 + \begin{figure}[H]
616 + \includegraphics[width=\linewidth]{lambdaProgression_atopCO.png}
617 + \caption{A model system of the Pt(557) surface was used as the framework
618 + for exploring energy barriers along a reaction coordinate. Various numbers,
619 + placements, and rotations of CO were examined as they affect Pt movement.
620 + The coordinate displayed in this Figure was a representative run. As shown
621 + in Table \ref{tab:rxcoord}, relative to the energy of the system at 0\%, there
622 + is a slight decrease upon insertion of the Pt atom into the step-edge along
623 + with the resultant lifting of the other Pt atom when CO is present at certain positions.}
624 + \label{fig:lambda}
625 + \end{figure}
626 +
627 +
628 +
629   \subsection{Diffusion}
630 < 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?)
630 > The diffusion parallel to the step-edge tends to be
631 > much larger than that perpendicular to the step-edge. The dynamic
632 > equilibrium that is established between the step-edge and adatom interface. The coverage
633 > of CO also appears to play a slight role in relative rates of diffusion, as shown in Figure \ref{fig:diff}.
634 > The
635 > Thus, the bottleneck of the double layer formation appears to be the initial formation
636 > of this growth point, which seems to be somewhat of a stochastic event. Once it
637 > appears, parallel diffusion, along the now slightly angled step-edge, will allow for
638 > a faster formation of the double layer than if the entire process were dependent on
639 > only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the
640 > more likely a growth point is to be formed.
641   \\
642 < \\
643 < %Evolution of surface
642 >
643 >
644 > %breaking of the double layer upon removal of CO
645   \begin{figure}[H]
646 < \includegraphics[scale=0.5]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
647 < \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.}
646 > \includegraphics[width=\linewidth]{doubleLayerBreaking_greenBlue_whiteLetters.png}
647 > %:
648 > \caption{(A)  0 ps, (B) 100 ps, (C) 1 ns, after the removal of CO. The presence of the CO
649 > helped maintain the stability of the double layer and upon removal the two layers break
650 > and begin separating. The separation is not a simple pulling apart however, rather
651 > there is a mixing of the lower and upper atoms at the edge.}
652 > \label{fig:breaking}
653   \end{figure}
654  
655  
656  
657  
658   %Peaks!
659 < \includegraphics[scale=0.25]{doublePeaks_noCO.png}
660 < \section{Conclusion}
659 > %\begin{figure}[H]
660 > %\includegraphics[width=\linewidth]{doublePeaks_noCO.png}
661 > %\caption{At the initial formation of this double layer  ( $\sim$ 37 ns) there is a degree
662 > %of roughness inherent to the edge. The next $\sim$ 40 ns show the edge with
663 > %aspects of waviness and by 80 ns the double layer is completely formed and smooth. }
664 > %\label{fig:peaks}
665 > %\end{figure}
666  
667  
668 + %Don't think I need this
669 + %clean surface...
670 + %\begin{figure}[H]
671 + %\includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
672 + %\caption{}
673  
674 + %\end{figure}
675 + %\label{fig:clean}
676  
677  
678 + \section{Conclusion}
679 + In this work we have shown the reconstruction of the Pt(557) crystalline surface upon adsorption of CO in less than a $\mu s$. 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.
680  
681 + %Things I am not ready to remove yet
682  
683 + %Table of Diffusion Constants
684 + %Add gold?M
685 + % \begin{table}[H]
686 + %   \caption{}
687 + %   \centering
688 + % \begin{tabular}{| c | cc | cc | }
689 + %   \hline
690 + %   &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
691 + %   \hline
692 + %   \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$  \\
693 + %   \hline
694 + %   50\% & 4.32(2) & 1.185(8)  & 1.72(2) & 0.455(6) \\
695 + %   33\% & 5.18(3)  & 1.999(5)  & 1.95(2) & 0.337(4)   \\
696 + %   25\% & 5.01(2)  & 1.574(4)  & 1.26(3) & 0.377(6) \\
697 + %   5\%   & 3.61(2)  & 0.355(2)  & 1.84(3)  & 0.169(4)  \\
698 + %   0\%   & 3.27(2)  & 0.147(4)  & 1.50(2)  & 0.194(2)   \\
699 + %   \hline
700 + % \end{tabular}
701 + % \end{table}
702  
703 + \section{Acknowledgments}
704 + Support for this project was provided by the National Science
705 + Foundation under grant CHE-0848243 and by the Center for Sustainable
706 + Energy at Notre Dame (cSEND). Computational time was provided by the
707 + Center for Research Computing (CRC) at the University of Notre Dame.
708  
709 <
710 <
711 < \end{document}
709 > \newpage
710 > \bibliography{firstTryBibliography}
711 > \end{doublespace}
712 > \end{document}

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