ViewVC Help
View File | Revision Log | Show Annotations | View Changeset | Root Listing
root/group/trunk/COonPt/COonPtAu.tex
(Generate patch)

Comparing trunk/COonPt/firstTry.tex (file contents):
Revision 3820 by gezelter, Mon Dec 17 18:45:57 2012 UTC vs.
Revision 3874 by jmichalk, Wed Mar 13 14:57:09 2013 UTC

# Line 4 | Line 4
4   \usepackage{times}
5   \usepackage{mathptm}
6   \usepackage{setspace}
7 < \usepackage{float}
7 > \usepackage{endfloat}
8   \usepackage{caption}
9
9   %\usepackage{tabularx}
10   \usepackage{graphicx}
11   \usepackage{multirow}
# Line 59 | Line 58 | Notre Dame, Indiana 46556}
58   Notre Dame, Indiana 46556}
59  
60   %Date
61 < \date{Dec 15, 2012}
61 > \date{Mar 5, 2013}
62  
63   %authors
64  
# Line 69 | Line 68 | Notre Dame, Indiana 46556}
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  
# Line 83 | Line 94 | Industrial catalysts usually consist of small particle
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 exposing
98 < different atomic terminations that exhibit a high concentration of
99 < step, kink sites, and vacancies at the edges of the facets.  These
89 < sites are thought to be the locations of catalytic
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 to demonstrate that solid surfaces are often
102 < structurally, compositionally, and chemically {\it modified} by
103 < reactants under operating conditions.\cite{Tao2008,Tao:2010,Tao2011}
104 < The coupling between surface oxidation state and catalytic activity
105 < for CO oxidation on Pt, for instance, is widely
106 < documented.\cite{Ertl08,Hendriksen:2002} Despite the well-documented
107 < role of these effects on reactivity, the ability to capture or predict
108 < them in atomistic models is currently somewhat limited.  While these
109 < effects are perhaps unsurprising on the highly disperse, multi-faceted
110 < nanoscale particles that characterize industrial catalysts, they are
111 < manifest even on ordered, well-defined surfaces. The Pt(557) surface,
112 < for example, exhibits substantial and reversible restructuring under
113 < exposure to moderate pressures of carbon monoxide.\cite{Tao:2010}
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 < This work is part of an ongoing effort to understand the causes,
116 < mechanisms and timescales for surface restructuring using molecular
117 < simulation methods.  Since the dynamics of the process is of
118 < particular interest, we utilize classical molecular dynamic methods
119 < with force fields that represent a compromise between chemical
120 < accuracy and the computational efficiency necessary to observe the
121 < process of interest.
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 < Since restructuring occurs as a result of specific interactions of the catalyst
138 < with adsorbates, two metals systems exposed to the same adsorbate, CO,
115 < were examined in this work. The Pt(557) surface has already been shown to
116 < reconstruct under certain conditions. The Au(557) surface, because of gold's
117 < weaker interaction with CO, is less likely to undergo such a large reconstruction.
137 >
138 >
139   %Platinum molecular dynamics
140   %gold molecular dynamics
141  
121
122
142   \section{Simulation Methods}
143 < The challenge in modeling any solid/gas interface problem is the
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$^3$ -
# Line 134 | Line 153 | Coulomb potential.  For this work, we have been using
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 been using classical
157 < molecular dynamics with potential energy surfaces that are
158 < specifically tuned for transition metals.  In particular, we use the
159 < EAM potential for Au-Au and Pt-Pt interactions, while modeling the CO
160 < using a model developed by Straub and Karplus for studying
161 < photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and Pt-CO
162 < cross interactions were parameterized as part of this work.
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 classical simulation of transition
166 < metals are based on a non-pairwise additive functional of the local
167 < electron density. The embedded atom method (EAM) is perhaps the best
168 < known of these
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 {\it et al.} is among the
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,
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*}
# Line 168 | Line 187 | $\phi_{ij}(r_{ij})$ is an pairwise term that is meant
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 an pairwise term that is meant to represent the
191 < overlap of the two positively charged cores.  
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.
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, MEAM, and the Quantum Sutton-Chen potentials
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} All of these potentials have their
210 < strengths and weaknesses.  One of the strengths common to all of the
211 < methods is the relatively large library of metals for which these
212 < potentials have been
213 < parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}
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 < \subsection{CO}
223 < Since one explanation for the strong surface CO repulsion on metals is
224 < the large linear quadrupole moment of carbon monoxide, the model
225 < chosen for this molecule exhibits this property in an efficient
226 < manner.  We used a model first proposed by Karplus and Straub to study
227 < the photodissociation of CO from myoglobin.\cite{Straub} The Straub and
228 < Karplus model is a rigid three site model which places a massless M
229 < site at the center of mass along the CO bond.  The geometry used along
230 < with the interaction parameters are reproduced in Table 1. The effective
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{Positions, $\sigma$, $\epsilon$ and charges for CO geometry
241 < and self-interactions\cite{Straub}. Distances are in \AA~, energies are
242 < 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 | c | ccc |}
246   \hline
217 \multicolumn{5}{|c|}{\textbf{Self-Interactions}}\\
218 \hline
247   &  {\it z} & $\sigma$ & $\epsilon$ & q\\
248   \hline
249 < \textbf{C} & -0.6457 &  0.0262  & 3.83   &   -0.75 \\
250 < \textbf{O} &  0.4843 &   0.1591 &   3.12 &   -0.85 \\
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
253   \end{tabular}
254 + \label{tab:CO}
255   \end{table}
256  
257 < \subsection{Cross-Interactions}
257 > \subsection{Cross-Interactions between the metals and carbon monoxide}
258  
259 < One hurdle that must be overcome in classical molecular simulations
260 < is the proper parameterization of the potential interactions present
261 < in the system. Since the adsorption of CO onto a platinum surface has been
262 < the focus of many experimental \cite{Yeo, Hopster:1978, Ertl:1977, Kelemen:1979}
263 < and theoretical studies \cite{Beurden:2002ys,Pons:1986,Deshlahra:2009,Feibelman:2001,Mason:2004}
264 < there is a large amount of data in the literature to fit too. We started with parameters
265 < reported by Korzeniewski et al. \cite{Pons:1986} and then
266 < modified them to ensure that the Pt-CO interaction favored
267 < an atop binding position for the CO upon the Pt surface. This
268 < constraint led to the binding energies being on the higher side
269 < of reported values. Following the method laid out by Korzeniewski,
270 < the Pt-C interaction was fit to a strong Lennard-Jones 12-6
271 < interaction to mimic binding, while the Pt-O interaction
272 < was parameterized to a Morse potential with a large $r_o$
273 < to contribute a weak repulsion. The resultant potential-energy
274 < surface suitably recovers the calculated Pt-C bond length ( 1.6\AA)\cite{Beurden:2002ys} and affinity
275 < for the atop binding position.\cite{Deshlahra:2012, Hopster:1978}
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 fit using Lennard-Jones and
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 <
287 < The fits were refined against gas-surface calculations using DFT with
288 < a periodic supercell plane-wave basis approach, as implemented in the
289 < {\sc Quantum ESPRESSO} package.\cite{QE-2009} Electron cores are
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 < Ionic relaxations were performed until the energy difference between
264 < subsequent steps was less than 0.0001 eV.  In testing the CO-Au
265 < interaction, Au(111) supercells were constructed of four layers of 4
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 < Supercell calculations were performed nonspin-polarized, and energies
300 < were converged to within 0.03 meV per Au atom with a 4 x 4 x 4
301 < Monkhorst-Pack\cite{Monkhorst:1976,PhysRevB.13.5188} {\bf k}-point
302 < sampling of the first Brillouin zone.  The relaxed gold slab was then
303 < used in numerous single point calculations with CO at various heights
304 < (and angles relative to the surface) to allow fitting of the empirical
305 < force field.
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   %Hint at future work
309 < The fit parameter sets employed in this work are shown in Table 2 and their
310 < reproduction of the binding energies are displayed in Table 3. Currently,
311 < charge transfer is not being treated in this system, however, that is a goal
312 < for future work as the effect has been seen to affect binding energies and
313 < binding site preferences. \cite{Deshlahra:2012}
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  
283
284
285
286 \subsection{Construction and Equilibration of 557 Metal interfaces}
287
288 Our model systems are composed of approximately 4000 metal atoms
289 cut along the 557 plane so that they are periodic in the {\it x} and {\it y}
290 directions exposing the 557 plane in the {\it z} direction. Runs at various
291 temperatures ranging from 300~K to 1200~K were started with the intent
292 of viewing relative stability of the surface when CO was not present in the
293 system.  Owing to the different melting points (1337~K for Au and 2045~K for Pt),
294 the bare crystal systems were initially run in the Canonical ensemble at
295 800~K and 1000~K respectively for 100 ps. Various amounts of CO were
296 placed in the vacuum region, which upon full adsorption to the surface
297 corresponded to 5\%, 25\%, 33\%, and 50\% coverages. Because of the
298 high temperature and the difference in binding energies, the platinum systems
299 very rarely had CO that was not adsorbed to the surface whereas the gold systems
300 often had a substantial minority of CO away from the surface.
301 These systems were again allowed to reach thermal equilibrium before being run in the
302 microcanonical ensemble. All of the systems examined in this work were
303 run for at least 40 ns. A subset that were undergoing interesting effects
304 have been allowed to continue running with one system approaching 200 ns.
305 All simulations were run using the open source molecular dynamics package, OpenMD. \cite{Ewald, OOPSE}
306
307
308
309
310
311
312 %\subsection{System}
313 %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.
314
315
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
326 &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ \\
327 \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{Adsorption 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:1979}-- -1.9~\cite{Yeo} \\
347 < \textbf{Au-CO} & -0.39 & -0.40~\cite{TPD_Gold} \\
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\cite{Au:melting}
368 + and 2045~K for Pt\cite{Pt:melting}) 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 < An ideal metal surface displaying a low-energy facet, a (111) face for
395 < instance, is unlikely to experience much surface diffusion because of
396 < the large energy barrier associated with atoms 'lifting' from the top
397 < layer to then be able to explore the surface. Rougher surfaces, those
398 < that already contain numerous adatoms, step edges, and kinks, should
399 < have concomitantly higher surface diffusion rates. Tao et al. showed
400 < that the platinum 557 surface undergoes two separate reconstructions
401 < upon CO adsorption. \cite{Tao:2010} The first reconstruction involves a
402 < doubling of the step edge height which is accomplished by a doubling
403 < of the plateau length. The second reconstruction led to the formation of
404 < triangular motifs stretching across the lengthened plateaus.
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 which were not exposed to CO
397 > did experience minor roughening of the step-edge because
398 > of the elevated temperatures, but the
399 > (557) lattice was well-maintained throughout the simulation
400 > time. The Au systems were limited to greater amounts of
401 > roughening, i.e. breakup of the step-edge, and some step
402 > wandering. The lower coverage Pt systems experienced
403 > similar restructuring but to a greater extent when
404 > compared to the Au systems. The 50\% coverage
405 > Pt system was unique among our simulations in that it
406 > formed numerous double layers through step coalescence,
407 > similar to results reported by Tao et al.\cite{Tao:2010}
408  
369 As shown in Figure 2, over a period of approximately 100 ns, the surface
370 has reconstructed from a 557 surface by doubling the step height and
371 step length. Focusing on only the platinum, or gold, atoms that were
372 deemed mobile on the surface, an analysis of the surface diffusion was
373 performed. A particle was considered mobile once it had traveled more
374 than 2~\AA between snapshots. This immediately eliminates all of the
375 bulk metal and greatly limits the number of surface atoms examined.
376 Since diffusion on a surface is strongly affected by overcoming energy
377 barriers, the diffusion parallel to the step edge axis was determined
378 separately from the diffusion perpendicular to the step edge. The results
379 at various coverages on both platinum and gold are shown in Table 4.
409  
410 < %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 has been running continuously. The lowered diffusion constant at longer run times will be examined in-depth in the discussion section.
410 > \subsubsection{Step wandering}
411 > The 0\% coverage surfaces for both metals showed minimal
412 > movement at their respective run temperatures. As the CO
413 > coverage increased however, the mobility of the surface,
414 > adatoms and step-edges alike, also increased. Additionally,
415 > at the higher coverages on both metals, there was more
416 > step-wandering. Except for the 50\% Pt system, the step-edges
417 > did not coalesce in any of the other simulations, instead preferring
418 > to keep nearly the same distance between steps as in the
419 > original (557) lattice. Previous work by Williams et al.\cite{Williams:1991, Williams:1994}
420 > highlights the repulsion that exists between step-edges even
421 > when no direct interactions are present in the system. This
422 > repulsion arises because the entropy of the step-edges is constrained,
423 > since step-edge crossing is not allowed. This entropic repulsion
424 > does not completely define the interactions between steps,
425 > which is why some surfaces will undergo step coalescence,
426 > where additional attractive interactions can overcome the
427 > repulsion\cite{Williams:1991} and others will not. The presence and concentration
428 > of adsorbates, as shown in this work, can affect these step interactions, potentially
429 > leading to a new surface structure as the thermodynamic minimum.
430  
431 + \subsubsection{Double layers}
432 + Tao et al. have shown experimentally that the Pt(557) surface
433 + undergoes two separate reconstructions upon CO adsorption.\cite{Tao:2010}
434 + The first involves a doubling of the step height and plateau length.
435 + Similar behavior has been seen to occur on numerous surfaces
436 + at varying conditions: Ni(977), Si(111).\cite{Williams:1994,Williams:1991,Pearl}
437 + Of the two systems we examined, the Pt system showed a greater
438 + propensity for reconstruction when compared to the Au system
439 + because of the larger surface mobility and extent of step wandering.
440 + The amount of reconstruction is correlated to the amount of CO
441 + adsorbed upon the surface.  This appears to be related to the
442 + effect that adsorbate coverage has on edge breakup and on the
443 + surface diffusion of metal adatoms. While both systems displayed
444 + step-edge wandering, only the 50\% Pt surface underwent the
445 + doubling seen by Tao et al.\cite{Tao:2010} within the time scales studied here.
446 + Over longer periods, (150~ns) two more double layers formed
447 + on this interface. Although double layer formation did not occur
448 + in the other Pt systems, they show more step-wandering and
449 + general roughening compared to their Au counterparts. The
450 + 50\% Pt system is highlighted in Figure \ref{fig:reconstruct} at
451 + various times along the simulation showing the evolution of a step-edge.
452 +
453 + The second reconstruction on the Pt(557) surface observed by
454 + Tao involved the formation of triangular clusters that stretched
455 + across the plateau between two step-edges. Neither system, within
456 + the 40~ns time scale or the extended simulation time of 150~ns for
457 + the 50\% Pt system, experienced this reconstruction.
458 +
459 + \subsection{Dynamics}
460 + Previous atomistic simulations of stepped surfaces dealt largely
461 + with the energetics and structures at different conditions
462 + \cite{Williams:1991,Williams:1994}. Consequently, the most common
463 + technique utilized to date has been Monte Carlo sampling. Monte Carlo gives an efficient
464 + sampling of the equilibrium thermodynamic landscape at the expense
465 + of ignoring the dynamics of the system. Previous experimental work by Pearl and
466 + Sibener\cite{Pearl}, using STM, has been able to capture the coalescing
467 + of steps on Ni(977). The time scale of the image acquisition,
468 + $\sim$70~s/image provides an upper bound for the time required for
469 + the doubling to occur. In this section we give data on dynamic and
470 + transport properties, e.g. diffusion, layer formation time, etc.
471 +
472 +
473 + \subsubsection{Transport of surface metal atoms}
474 + %forcedSystems/stepSeparation
475 + The movement or wandering of a step-edge is a cooperative effect
476 + arising from the individual movements of the atoms making up the steps. An ideal metal surface
477 + displaying a low index facet, (111) or (100), is unlikely to experience
478 + much surface diffusion because of the large energetic barrier that must
479 + be overcome to lift an atom out of the surface. The presence of step-edges and other surface features
480 + on higher-index facets provide a lower energy source for mobile metal atoms.
481 + Breaking away from the step-edge on a clean surface still imposes an
482 + energetic penalty around $\sim$~40 kcal/mol, but this is significantly easier than lifting
483 + the same metal atom vertically out of the surface,  \textgreater~60 kcal/mol.
484 + The penalty lowers significantly when CO is present in sufficient quantities
485 + on the surface. For certain distributions of CO, the penalty can fall as low as
486 + $\sim$~20 kcal/mol. Once an adatom exists on the surface, the barrier for
487 + diffusion is negligible ( \textless~4 kcal/mol for a Pt adatom). These adatoms are
488 + able to explore the terrace before rejoining either the original step-edge or
489 + becoming a part of a different edge. It is a more difficult process for an atom
490 + to traverse to a separate terrace although the presence of CO can lower the
491 + energy barrier required to lift or lower the adatom. By tracking the mobility of individual
492 + metal atoms on the Pt and Au surfaces we were able to determine the relative
493 + diffusion constants, as well as how varying coverages of CO affect the diffusion. Close
494 + observation of the mobile metal atoms showed that they were typically in
495 + equilibrium with the step-edges, dynamically breaking apart and rejoining the edges.
496 + At times, their motion was concerted and two or more adatoms would be
497 + observed moving together across the surfaces.
498 +
499 + A particle was considered ``mobile'' once it had traveled more than 2~\AA~
500 + between saved configurations of the system (typically 10-100 ps). An atom that was
501 + truly mobile would typically travel much greater distances than this, but the 2~\AA~cutoff
502 + was used to prevent swamping the diffusion data with the in-place vibrational
503 + movement of buried atoms. Diffusion on a surface is strongly affected by
504 + local structures and in this work, the presence of single and double layer
505 + step-edges causes the diffusion parallel to the step-edges to be different
506 + from the diffusion perpendicular to these edges. Parallel and perpendicular
507 + diffusion constants are shown in Figure \ref{fig:diff}.
508 +
509 + The lack of a definite trend in the Au diffusion data is likely due
510 + to the weaker bonding between Au and CO. This leads to a lower
511 + coverage ({\it x}-axis) when compared to dosage amount, which
512 + then further limits the affects of the surface diffusion. The correlation
513 + between coverage and Pt diffusion rates conversely shows a
514 + definite trend marred by the highest coverage surface. Two
515 + explanations arise for this drop. First, upon a visual inspection of
516 + the system, after a double layer has been formed, it maintains its
517 + stability strongly and is no longer a good source for adatoms. By
518 + performing the same diffusion calculation but on a shorter run time
519 + (20~ns), only including data before the formation of the double layer,
520 + provides a $\mathbf{D}_{\perp}$ diffusion constant of $1.69~\pm~0.08$
521 + and a $\mathbf{D}_{\parallel}$ diffusion constant of $6.30~\pm~0.08$.
522 + This places the parallel diffusion constant more closely in line with the
523 + expected trend, while the perpendicular diffusion constant does not
524 + drop as far. A secondary explanation arising from our analysis of the
525 + mechanism of double layer formation show the affect that CO on the
526 + surface has with respect to overcoming surface diffusion of Pt. If the
527 + coverage is too sparse, the Pt engages in minimal interactions and
528 + thus minimal diffusion. As coverage increases, there are more favorable
529 + arrangements of CO on the surface allowing the formation of a path,
530 + a minimum energy trajectory, for the adatom to explore the surface.
531 + As the CO is constantly moving on the surface, this path is constantly
532 + changing. If the coverage becomes too great, the paths could
533 + potentially be clogged leading to a decrease in diffusion despite
534 + their being more adatoms and step-wandering.
535 +
536 + \subsubsection{Dynamics of double layer formation}
537 + The increased diffusion on Pt at the higher
538 + CO coverages plays a primary role in double layer formation. However, this is not
539 + a complete explanation -- the 33\%~Pt system
540 + has higher diffusion constants but did not show
541 + any signs of edge doubling in the observed run time. On the
542 + 50\%~Pt system, one layer formed within the first 40~ns of simulation time, while two more were formed as the system was run for an additional
543 + 110~ns (150~ns total). Previous experimental
544 + work gives insight into the upper bounds of the
545 + time required for step coalescence.\cite{Williams:1991,Pearl}
546 + In this system, as seen in Figure \ref{fig:reconstruct}, the first
547 + appearance of a double layer, appears at 19~ns
548 + into the simulation. Within 12~ns of this nucleation event, nearly half of the step has
549 + formed the double layer and by 86~ns, the complete layer
550 + has been flattened out. The double layer could be considered
551 + ``complete" by 37~ns but remains a bit rough. From the
552 + appearance of the first nucleation event to the first observed double layer, the process took $\sim$20~ns. Another
553 + $\sim$40~ns was necessary for the layer to completely straighten.
554 + The other two layers in this simulation formed over periods of
555 + 22~ns and 42~ns respectively. Comparing this to the upper
556 + bounds of the image scan, it is likely that most aspects of this
557 + reconstruction occur very rapidly. A possible explanation
558 + for this rapid reconstruction is the elevated temperatures
559 + under which our systems were simulated. It is probable that the process would
560 + take longer at lower temperatures.
561 +
562 + %Evolution of surface
563   \begin{figure}[H]
564 < \includegraphics[scale=0.6]{DiffusionComparison_error.png}
565 < \caption{Diffusion parallel to the step edge will always be higher than that perpendicular to the edge because of the lower energy barrier associated with going from approximately 7 nearest neighbors to 5, as compared to the 3 of an adatom. Additionally, the observed maximum and subsequent decrease for the Pt system suggests that the CO self-interactions are playing a significant role with regards to movement of the platinum atoms around and more importantly across the surface. }
564 > \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
565 > \caption{The Pt(557) / 50\% CO system at a sequence of times after
566 >  initial exposure to the CO: (a) 258~ps, (b) 19~ns, (c) 31.2~ns, and
567 >  (d) 86.1~ns. Disruption of the (557) step-edges occurs quickly.  The
568 >  doubling of the layers appears only after two adjacent step-edges
569 >  touch.  The circled spot in (b) nucleated the growth of the double
570 >  step observed in the later configurations.}
571 >  \label{fig:reconstruct}
572   \end{figure}
573  
574 < %Table of Diffusion Constants
575 < %Add gold?M
574 > \begin{figure}[H]
575 > \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
576 > \caption{Diffusion constants for mobile surface atoms along directions
577 >  parallel ($\mathbf{D}_{\parallel}$) and perpendicular
578 >  ($\mathbf{D}_{\perp}$) to the (557) step-edges as a function of CO
579 >  surface coverage.  Diffusion parallel to the step-edge is higher
580 >  than that perpendicular to the edge because of the lower energy
581 >  barrier associated with traversing along the edge as compared to
582 >  completely breaking away. Additionally, the observed
583 >  maximum and subsequent decrease for the Pt system suggests that the
584 >  CO self-interactions are playing a significant role with regards to
585 >  movement of the Pt atoms around and across the surface. }
586 > \label{fig:diff}
587 > \end{figure}
588 >
589 >
590 >
591 >
592 > %Discussion
593 > \section{Discussion}
594 > We have shown that the classical potential models are able to model the initial reconstruction of the
595 > Pt(557) surface upon CO adsorption as shown by Tao et al. \cite{Tao:2010}. More importantly, we
596 > were able to observe features of the dynamic processes necessary for this reconstruction.
597 >
598 > \subsection{Mechanism for restructuring}
599 > Since the Au surface showed no large scale restructuring throughout
600 > our simulation time our discussion will focus on the 50\% Pt-CO system
601 > which did undergo the doubling featured in Figure \ref{fig:reconstruct}.
602 > Similarities of our results to those reported previously by
603 > Tao et al.\cite{Tao:2010} are quite
604 > strong. The simulated Pt
605 > system exposed to a large dosage of CO readily restructures by doubling the terrace
606 > 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.
607 > The adatoms either
608 > break away from the step-edge and stay on the lower terrace or they lift
609 > up onto a higher terrace. Once ``free'', they diffuse on the terrace
610 > until reaching another step-edge or rejoining their original edge.  
611 > This combination of growth and decay of the step-edges is in a state of
612 > dynamic equilibrium. However, once two previously separated edges
613 > meet as shown in Figure 1.B, this nucleates the rest of the edge to meet up, forming a double layer.
614 > 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.
615 >
616 > A number of possible mechanisms exist to explain the role of adsorbed
617 > CO in restructuring the Pt surface. Quadrupolar repulsion between adjacent
618 > CO molecules adsorbed on the surface is one possibility.  However,
619 > the quadrupole-quadrupole interaction is short-ranged and is attractive for
620 > some orientations.  If the CO molecules are ``locked'' in a specific orientation
621 > relative to each other, through atop adsorption for example, this explanation
622 > gains some credence.  The energetic repulsion between two CO located a
623 > distance of 2.77~\AA~apart (nearest-neighbor distance of Pt) and both in
624 > a  vertical orientation, is 8.62 kcal/mol. Moving the CO apart to the second
625 > nearest-neighbor distance of 4.8~\AA~or 5.54~\AA~drops the repulsion to
626 > nearly 0 kcal/mol. Allowing the CO's to leave a purely vertical orientation
627 > 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.
628 > As mentioned above, the energy barrier for surface diffusion
629 > of a Pt adatom is only 4 kcal/mol. So this repulsion between neighboring CO molecules can
630 > increase the surface diffusion. However, the residence time of CO on Pt was
631 > examined and while the majority of the CO is on or near the surface throughout
632 > the run, most molecules are mobile. This mobility suggests that the CO are more
633 > likely to shift their positions without necessarily the Pt along with them.
634 >
635 > Another possible and more likely mechanism for the restructuring is in the
636 > destabilization of strong Pt-Pt interactions by CO adsorbed on surface
637 > Pt atoms.  This would then have the effect of increasing surface mobility
638 > of these atoms.  To test this hypothesis, numerous configurations of
639 > CO in varying quantities were arranged on the higher and lower plateaus
640 > around a step on a otherwise clean Pt(557) surface. One representative
641 > configuration is displayed in Figure \ref{fig:lambda}. Single or concerted movement
642 > of Pt atoms was then examined to determine possible barriers. Because
643 > the movement was forced along a pre-defined reaction coordinate that may differ
644 > from the true minimum of this path, only the beginning and ending energies
645 > are displayed in Table \ref{tab:rxcoord} with the corresponding beginning and ending reaction coordinates in Figure \ref{fig:lambdaTable}. These values suggest that the presence of CO at suitable
646 > locations can lead to lowered barriers for Pt breaking apart from the step-edge.
647 > Additionally, as highlighted in Figure \ref{fig:lambda}, the presence of CO makes the
648 > burrowing and lifting of adatoms favorable, whereas without CO, the process is neutral
649 > in terms of energetics.
650 >
651 > %lambda progression of Pt -> shoving its way into the step
652 > \begin{figure}[H]
653 > \includegraphics[width=\linewidth]{lambdaProgression_atopCO_withLambda.png}
654 > \caption{A model system of the Pt(557) surface was used as the framework
655 > for exploring energy barriers along a reaction coordinate. Various numbers,
656 > placements, and rotations of CO were examined as they affect Pt movement.
657 > The coordinate displayed in this Figure was a representative run. As shown
658 > in Table \ref{tab:rxcoord}, relative to the energy of the system at 0\%, there
659 > is a slight decrease upon insertion of the Pt atom into the step-edge along
660 > with the resultant lifting of the other Pt atom when CO is present at certain positions.}
661 > \label{fig:lambda}
662 > \end{figure}
663 >
664 > \begin{figure}[H]
665 > \includegraphics[totalheight=0.9\textheight]{lambdaTable.png}
666 > \caption{}
667 > \label{fig:lambdaTable}
668 > \end{figure}
669 >
670 >
671 >
672   \begin{table}[H]
673 < \caption{Platinum and gold 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. Units are \AA\textsuperscript{2}/ns}
673 > \caption{}
674   \centering
675 < \begin{tabular}{| c | cc | cc | c |}
675 > \begin{tabular}{| c || c | c | c | c |}
676   \hline
677 < \textbf{System Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$  & \textbf{Time (ns)}\\
677 > \textbf{System} & 0.5~\AA & 2~\AA & 4~\AA & 6~\AA \\
678   \hline
679 < &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} & \\
680 < \hline
681 < 50\% & 4.32 $\pm$ 0.02 & 1.185 $\pm$ 0.008 & 1.72 $\pm$ 0.02 & 0.455 $\pm$ 0.006 & 40 \\
682 < 33\% & 5.18 $\pm$ 0.03 & 1.999 $\pm$ 0.005 & 1.95 $\pm$ 0.02 & 0.337 $\pm$ 0.004 & 40   \\
683 < 25\% & 5.01 $\pm$ 0.02 & 1.574 $\pm$ 0.004 & 1.26 $\pm$ 0.03 & 0.377 $\pm$ 0.006 & 40  \\
684 < 5\%   & 3.61 $\pm$ 0.02 & 0.355 $\pm$ 0.002 & 1.84 $\pm$ 0.03 & 0.169 $\pm$ 0.004 & 40  \\
403 < 0\%   & 3.27 $\pm$ 0.02 & 0.147 $\pm$ 0.004 & 1.50 $\pm$ 0.02 & 0.194 $\pm$ 0.002  & 40  \\
679 > A & 6.38 & 38.34 & 44.65 & 47.60 \\
680 > B & -20.72 & 0.67 & 17.33 & 24.28 \\
681 > C & 4.92 & 27.02 & 41.05 & 47.43 \\
682 > D & -16.97 & 21.21 & 35.87 & 40.93 \\
683 > E & 5.92 & 30.96 & 43.69 & 49.23 \\
684 > F & 8.53 & 46.23 & 53.98 & 65.55 \\
685   \hline
686   \end{tabular}
687 + \label{tab:rxcoord}
688   \end{table}
689  
690  
409
410 %Discussion
411 \section{Discussion}
412 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.
413
691   \subsection{Diffusion}
692 < 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?)
692 > The diffusion parallel to the step-edge tends to be
693 > much larger than that perpendicular to the step-edge. The dynamic
694 > equilibrium that is established between the step-edge and adatom interface. The coverage
695 > of CO also appears to play a slight role in relative rates of diffusion, as shown in Figure \ref{fig:diff}.
696 > The
697 > Thus, the bottleneck of the double layer formation appears to be the initial formation
698 > of this growth point, which seems to be somewhat of a stochastic event. Once it
699 > appears, parallel diffusion, along the now slightly angled step-edge, will allow for
700 > a faster formation of the double layer than if the entire process were dependent on
701 > only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the
702 > more likely a growth point is to be formed.
703   \\
704 < \\
705 < %Evolution of surface
704 >
705 >
706 > %breaking of the double layer upon removal of CO
707   \begin{figure}[H]
708 < \includegraphics[scale=0.5]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
709 < \caption{Four snapshots of the $\frac{1}{2}$ monolayer system at various times a) 258 ps b) 19 ns c) 31.2 ns and 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.}
708 > \includegraphics[width=\linewidth]{doubleLayerBreaking_greenBlue_whiteLetters.png}
709 > \caption{(A)  0~ps, (B) 100~ps, (C) 1~ns, after the removal of CO. The presence of the CO
710 > helped maintain the stability of the double layer and upon removal the two layers break
711 > and begin separating. The separation is not a simple pulling apart however, rather
712 > there is a mixing of the lower and upper atoms at the edge.}
713 > \label{fig:breaking}
714   \end{figure}
715  
716  
717  
718  
719   %Peaks!
720 < \begin{figure}[H]
721 < \includegraphics[scale=0.25]{doublePeaks_noCO.png}
722 < \caption{}
723 < \end{figure}
720 > %\begin{figure}[H]
721 > %\includegraphics[width=\linewidth]{doublePeaks_noCO.png}
722 > %\caption{At the initial formation of this double layer  ( $\sim$ 37 ns) there is a degree
723 > %of roughness inherent to the edge. The next $\sim$ 40 ns show the edge with
724 > %aspects of waviness and by 80 ns the double layer is completely formed and smooth. }
725 > %\label{fig:peaks}
726 > %\end{figure}
727 >
728 >
729 > %Don't think I need this
730 > %clean surface...
731 > %\begin{figure}[H]
732 > %\includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
733 > %\caption{}
734 >
735 > %\end{figure}
736 > %\label{fig:clean}
737 >
738 >
739   \section{Conclusion}
740 + 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.
741  
742 + %Things I am not ready to remove yet
743  
744 + %Table of Diffusion Constants
745 + %Add gold?M
746 + % \begin{table}[H]
747 + %   \caption{}
748 + %   \centering
749 + % \begin{tabular}{| c | cc | cc | }
750 + %   \hline
751 + %   &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
752 + %   \hline
753 + %   \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$  \\
754 + %   \hline
755 + %   50\% & 4.32(2) & 1.185(8)  & 1.72(2) & 0.455(6) \\
756 + %   33\% & 5.18(3)  & 1.999(5)  & 1.95(2) & 0.337(4)   \\
757 + %   25\% & 5.01(2)  & 1.574(4)  & 1.26(3) & 0.377(6) \\
758 + %   5\%   & 3.61(2)  & 0.355(2)  & 1.84(3)  & 0.169(4)  \\
759 + %   0\%   & 3.27(2)  & 0.147(4)  & 1.50(2)  & 0.194(2)   \\
760 + %   \hline
761 + % \end{tabular}
762 + % \end{table}
763 +
764   \section{Acknowledgments}
765   Support for this project was provided by the National Science
766   Foundation under grant CHE-0848243 and by the Center for Sustainable

Diff Legend

Removed lines
+ Added lines
< Changed lines
> Changed lines