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1 gezelter 3808 \documentclass[11pt]{article}
2     \usepackage{amsmath}
3     \usepackage{amssymb}
4 gezelter 3818 \usepackage{times}
5     \usepackage{mathptm}
6 jmichalk 3802 \usepackage{setspace}
7 gezelter 3826 \usepackage{endfloat}
8 gezelter 3808 \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 jmichalk 3802
21 gezelter 3808 % double space list of tables and figures
22 gezelter 3820 %\AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
23 gezelter 3808 \setlength{\abovecaptionskip}{20 pt}
24     \setlength{\belowcaptionskip}{30 pt}
25    
26 gezelter 3820 \bibpunct{}{}{,}{s}{}{;}
27 gezelter 3808 \bibliographystyle{achemso}
28    
29     \begin{document}
30    
31    
32 jmichalk 3802 %%
33     %Introduction
34     % Experimental observations
35     % Previous work on Pt, CO, etc.
36     %
37     %Simulation Methodology
38     % FF (fits and parameters)
39     % MD (setup, equilibration, collection)
40     %
41     % Analysis of trajectories!!!
42     %Discussion
43     % CO preferences for specific locales
44     % CO-CO interactions
45     % Differences between Au & Pt
46     % Causes of 2_layer reordering in Pt
47     %Summary
48     %%
49    
50     %Title
51 gezelter 3818 \title{Molecular Dynamics simulations of the surface reconstructions
52     of Pt(557) and Au(557) under exposure to CO}
53    
54 jmichalk 3816 \author{Joseph R. Michalka, Patrick W. McIntyre and J. Daniel
55 gezelter 3808 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 gezelter 3818
60 jmichalk 3802 %Date
61 gezelter 3818 \date{Dec 15, 2012}
62    
63 jmichalk 3802 %authors
64 gezelter 3808
65 jmichalk 3802 % make the title
66 jmichalk 3817 \maketitle
67 jmichalk 3802
68 gezelter 3808 \begin{doublespace}
69 jmichalk 3802
70 gezelter 3808 \begin{abstract}
71 jmichalk 3802
72 gezelter 3808 \end{abstract}
73 jmichalk 3802
74 gezelter 3808 \newpage
75    
76    
77 jmichalk 3802 \section{Introduction}
78     % Importance: catalytically active metals are important
79     % Sub: Knowledge of how their surface structure affects their ability to catalytically facilitate certain reactions is growing, but is more reactionary than predictive
80     % Sub: Designing catalysis is the future, and will play an important role in numerous processes (ones that are currently seen to be impractical, or at least inefficient)
81     % Theory can explore temperatures and pressures which are difficult to work with in experiments
82     % Sub: Also, easier to observe what is going on and provide reasons and explanations
83     %
84    
85 gezelter 3826 Industrial catalysts usually consist of small particles that exhibit a
86     high concentration of steps, kink sites, and vacancies at the edges of
87     the facets. These sites are thought to be the locations of catalytic
88 gezelter 3808 activity.\cite{ISI:000083038000001,ISI:000083924800001} There is now
89 gezelter 3826 significant evidence that solid surfaces are often structurally,
90     compositionally, and chemically modified by reactants under operating
91     conditions.\cite{Tao2008,Tao:2010,Tao2011} The coupling between
92     surface oxidation states and catalytic activity for CO oxidation on
93     Pt, for instance, is widely documented.\cite{Ertl08,Hendriksen:2002}
94     Despite the well-documented role of these effects on reactivity, the
95     ability to capture or predict them in atomistic models is somewhat
96     limited. While these effects are perhaps unsurprising on the highly
97     disperse, multi-faceted nanoscale particles that characterize
98     industrial catalysts, they are manifest even on ordered, well-defined
99     surfaces. The Pt(557) surface, for example, exhibits substantial and
100     reversible restructuring under exposure to moderate pressures of
101     carbon monoxide.\cite{Tao:2010}
102 jmichalk 3802
103 gezelter 3826 This work an effort to understand the mechanism and timescale for
104     surface restructuring using molecular simulations. Since the dynamics
105     of the process is of particular interest, we utilize classical force
106     fields that represent a compromise between chemical accuracy and the
107     computational efficiency necessary to observe the process of interest.
108 gezelter 3808
109 gezelter 3826 Since restructuring occurs as a result of specific interactions of the
110     catalyst with adsorbates, two metal systems exposed to carbon monoxide
111     were examined in this work. The Pt(557) surface has already been shown
112     to reconstruct under certain conditions. The Au(557) surface, because
113     of a weaker interaction with CO, is less likely to undergo this kind
114     of reconstruction. MORE HERE ON PT AND AU PREVIOUS WORK.
115    
116 jmichalk 3811 %Platinum molecular dynamics
117     %gold molecular dynamics
118 jmichalk 3802
119     \section{Simulation Methods}
120 gezelter 3808 The challenge in modeling any solid/gas interface problem is the
121     development of a sufficiently general yet computationally tractable
122     model of the chemical interactions between the surface atoms and
123     adsorbates. Since the interfaces involved are quite large (10$^3$ -
124     10$^6$ atoms) and respond slowly to perturbations, {\it ab initio}
125     molecular dynamics
126     (AIMD),\cite{KRESSE:1993ve,KRESSE:1993qf,KRESSE:1994ul} Car-Parrinello
127     methods,\cite{CAR:1985bh,Izvekov:2000fv,Guidelli:2000fy} and quantum
128     mechanical potential energy surfaces remain out of reach.
129     Additionally, the ``bonds'' between metal atoms at a surface are
130     typically not well represented in terms of classical pairwise
131     interactions in the same way that bonds in a molecular material are,
132     nor are they captured by simple non-directional interactions like the
133 gezelter 3826 Coulomb potential. For this work, we have used classical molecular
134     dynamics with potential energy surfaces that are specifically tuned
135     for transition metals. In particular, we used the EAM potential for
136     Au-Au and Pt-Pt interactions, while modeling the CO using a rigid
137     three-site model developed by Straub and Karplus for studying
138     photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and
139     Pt-CO cross interactions were parameterized as part of this work.
140 gezelter 3808
141     \subsection{Metal-metal interactions}
142 gezelter 3826 Many of the potentials used for modeling transition metals are based
143     on a non-pairwise additive functional of the local electron
144     density. The embedded atom method (EAM) is perhaps the best known of
145     these
146 gezelter 3808 methods,\cite{Daw84,Foiles86,Johnson89,Daw89,Plimpton93,Voter95a,Lu97,Alemany98}
147     but other models like the Finnis-Sinclair\cite{Finnis84,Chen90} and
148     the quantum-corrected Sutton-Chen method\cite{QSC,Qi99} have simpler
149     parameter sets. The glue model of Ercolessi {\it et al.} is among the
150     fastest of these density functional approaches.\cite{Ercolessi88} In
151     all of these models, atoms are conceptualized as a positively charged
152     core with a radially-decaying valence electron distribution. To
153     calculate the energy for embedding the core at a particular location,
154     the electron density due to the valence electrons at all of the other
155 gezelter 3826 atomic sites is computed at atom $i$'s location,
156 gezelter 3808 \begin{equation*}
157     \bar{\rho}_i = \sum_{j\neq i} \rho_j(r_{ij})
158     \end{equation*}
159     Here, $\rho_j(r_{ij})$ is the function that describes the distance
160     dependence of the valence electron distribution of atom $j$. The
161     contribution to the potential that comes from placing atom $i$ at that
162     location is then
163     \begin{equation*}
164     V_i = F[ \bar{\rho}_i ] + \sum_{j \neq i} \phi_{ij}(r_{ij})
165     \end{equation*}
166     where $F[ \bar{\rho}_i ]$ is an energy embedding functional, and
167     $\phi_{ij}(r_{ij})$ is an pairwise term that is meant to represent the
168     overlap of the two positively charged cores.
169 jmichalk 3807
170 gezelter 3826 % The {\it modified} embedded atom method (MEAM) adds angular terms to
171     % the electron density functions and an angular screening factor to the
172     % pairwise interaction between two
173     % atoms.\cite{BASKES:1994fk,Lee:2000vn,Thijsse:2002ly,Timonova:2011ve}
174     % MEAM has become widely used to simulate systems in which angular
175     % interactions are important (e.g. silicon,\cite{Timonova:2011ve} bcc
176     % metals,\cite{Lee:2001qf} and also interfaces.\cite{Beurden:2002ys})
177     % MEAM presents significant additional computational costs, however.
178 jmichalk 3807
179 gezelter 3826 The EAM, Finnis-Sinclair, and the Quantum Sutton-Chen potentials
180 gezelter 3808 have all been widely used by the materials simulation community for
181     simulations of bulk and nanoparticle
182     properties,\cite{Chui:2003fk,Wang:2005qy,Medasani:2007uq}
183     melting,\cite{Belonoshko00,sankaranarayanan:155441,Sankaranarayanan:2005lr}
184     fracture,\cite{Shastry:1996qg,Shastry:1998dx} crack
185     propagation,\cite{BECQUART:1993rg} and alloying
186     dynamics.\cite{Shibata:2002hh} All of these potentials have their
187     strengths and weaknesses. One of the strengths common to all of the
188     methods is the relatively large library of metals for which these
189     potentials have been
190 gezelter 3826 parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}
191 gezelter 3808
192 gezelter 3826 \subsection{Carbon Monoxide model}
193     Since previous explanations for the surface rearrangements center on
194 gezelter 3808 the large linear quadrupole moment of carbon monoxide, the model
195     chosen for this molecule exhibits this property in an efficient
196 jmichalk 3827 manner. We used a model first proposed by Karplus and Straub to study
197     the photodissociation of CO from myoglobin.\cite{Straub} The Straub and
198     Karplus model is a rigid three site model which places a massless M
199     site at the center of mass along the CO bond. The geometry used along
200     with the interaction parameters are reproduced in Table~1. The effective
201     dipole moment, calculated from the assigned charges, is still
202     small (0.35 D) while the linear quadrupole (-2.40 D~\AA) is close
203     to the experimental (-2.63 D~\AA)\cite{QuadrupoleCO} and quantum
204 jmichalk 3812 mechanical predictions (-2.46 D~\AA)\cite{QuadrupoleCOCalc}.
205 jmichalk 3802 %CO Table
206     \begin{table}[H]
207 gezelter 3826 \caption{Positions, Lennard-Jones parameters ($\sigma$ and
208     $\epsilon$), and charges for the CO-CO
209     interactions borrowed from Ref. \bibpunct{}{}{,}{n}{}{,} \protect\cite{Straub}. Distances are in \AA~, energies are
210     in kcal/mol, and charges are in atomic units.}
211 jmichalk 3802 \centering
212 jmichalk 3810 \begin{tabular}{| c | c | ccc |}
213 jmichalk 3802 \hline
214 jmichalk 3814 & {\it z} & $\sigma$ & $\epsilon$ & q\\
215 jmichalk 3802 \hline
216 jmichalk 3814 \textbf{C} & -0.6457 & 0.0262 & 3.83 & -0.75 \\
217     \textbf{O} & 0.4843 & 0.1591 & 3.12 & -0.85 \\
218     \textbf{M} & 0.0 & - & - & 1.6 \\
219 jmichalk 3802 \hline
220     \end{tabular}
221     \end{table}
222 gezelter 3808
223 gezelter 3826 \subsection{Cross-Interactions between the metals and carbon monoxide}
224 jmichalk 3802
225 gezelter 3826 Since the adsorption of CO onto a platinum surface has been the focus
226     of much experimental \cite{Yeo, Hopster:1978, Ertl:1977, Kelemen:1979}
227     and theoretical work
228     \cite{Beurden:2002ys,Pons:1986,Deshlahra:2009,Feibelman:2001,Mason:2004}
229     there is a significant amount of data on adsorption energies for CO on
230     clean metal surfaces. Parameters reported by Korzeniewski {\it et
231     al.}\cite{Pons:1986} were a starting point for our fits, which were
232     modified to ensure that the Pt-CO interaction favored the atop binding
233     position on Pt(111). This resulting binding energies are on the higher
234     side of the experimentally-reported values. Following Korzeniewski
235     {\it et al.},\cite{Pons:1986} the Pt-C interaction was fit to a deep
236     Lennard-Jones interaction to mimic strong, but short-ranged partial
237     binding between the Pt $d$ orbitals and the $\pi^*$ orbital on CO. The
238     Pt-O interaction was parameterized to a Morse potential with a large
239     range parameter ($r_o$). In most cases, this contributes a weak
240     repulsion which favors the atop site. The resulting potential-energy
241     surface suitably recovers the calculated Pt-C separation length
242     (1.6~\AA)\cite{Beurden:2002ys} and affinity for the atop binding
243     position.\cite{Deshlahra:2012, Hopster:1978}
244 jmichalk 3811
245 jmichalk 3812 %where did you actually get the functionals for citation?
246     %scf calculations, so initial relaxation was of the four layers, but two layers weren't kept fixed, I don't think
247     %same cutoff for slab and slab + CO ? seems low, although feibelmen had values around there...
248 gezelter 3818 The Au-C and Au-O cross-interactions were fit using Lennard-Jones and
249     Morse potentials, respectively, to reproduce Au-CO binding energies.
250 jmichalk 3811
251 gezelter 3826 The fits were refined against gas-surface DFT calculations with a
252     periodic supercell plane-wave basis approach, as implemented in the
253 gezelter 3818 {\sc Quantum ESPRESSO} package.\cite{QE-2009} Electron cores are
254     described with the projector augmented-wave (PAW)
255     method,\cite{PhysRevB.50.17953,PhysRevB.59.1758} with plane waves
256     included to an energy cutoff of 20 Ry. Electronic energies are
257     computed with the PBE implementation of the generalized gradient
258     approximation (GGA) for gold, carbon, and oxygen that was constructed
259     by Rappe, Rabe, Kaxiras, and Joannopoulos.\cite{Perdew_GGA,RRKJ_PP}
260     Ionic relaxations were performed until the energy difference between
261 gezelter 3826 subsequent steps was less than $10^{-8}$ Ry. In testing the CO-Au
262 gezelter 3818 interaction, Au(111) supercells were constructed of four layers of 4
263     Au x 2 Au surface planes and separated from vertical images by six
264     layers of vacuum space. The surface atoms were all allowed to relax.
265 gezelter 3826 Supercell calculations were performed nonspin-polarized with a 4 x 4 x
266     4 Monkhorst-Pack {\bf k}-point sampling of the first Brillouin
267     zone.\cite{Monkhorst:1976,PhysRevB.13.5188} The relaxed gold slab was
268     then used in numerous single point calculations with CO at various
269     heights (and angles relative to the surface) to allow fitting of the
270     empirical force field.
271 gezelter 3818
272 jmichalk 3812 %Hint at future work
273 gezelter 3826 The parameters employed in this work are shown in Table 2 and the
274     binding energies on the 111 surfaces are displayed in Table 3. To
275     speed up the computations, charge transfer and polarization are not
276     being treated in this model, although these effects are likely to
277     affect binding energies and binding site
278     preferences.\cite{Deshlahra:2012}
279 jmichalk 3811
280 jmichalk 3802 %Table of Parameters
281     %Pt Parameter Set 9
282     %Au Parameter Set 35
283     \begin{table}[H]
284 gezelter 3826 \caption{Best fit parameters for metal-CO cross-interactions. Metal-C
285     interactions are modeled with Lennard-Jones potential, while the
286     (mostly-repulsive) metal-O interactions were fit to Morse
287     potentials. Distances are given in \AA~and energies in kcal/mol. }
288 jmichalk 3802 \centering
289     \begin{tabular}{| c | cc | c | ccc |}
290     \hline
291 gezelter 3826 & $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ (\AA$^{-1}$) \\
292 jmichalk 3802 \hline
293     \textbf{Pt-C} & 1.3 & 15 & \textbf{Pt-O} & 3.8 & 3.0 & 1 \\
294     \textbf{Au-C} & 1.9 & 6.5 & \textbf{Au-O} & 3.8 & 0.37 & 0.9\\
295    
296     \hline
297     \end{tabular}
298     \end{table}
299    
300     %Table of energies
301     \begin{table}[H]
302 gezelter 3826 \caption{Adsorption energies for CO on M(111) using the potentials
303     described in this work. All values are in eV}
304 jmichalk 3802 \centering
305     \begin{tabular}{| c | cc |}
306 gezelter 3826 \hline
307     & Calculated & Experimental \\
308     \hline
309     \multirow{2}{*}{\textbf{Pt-CO}} & \multirow{2}{*}{-1.9} & -1.4 \bibpunct{}{}{,}{n}{}{,}
310     (Ref. \protect\cite{Kelemen:1979}) \\
311     & & -1.9 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{Yeo}) \\ \hline
312     \textbf{Au-CO} & -0.39 & -0.40 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{TPD_Gold}) \\
313     \hline
314 jmichalk 3802 \end{tabular}
315     \end{table}
316    
317 gezelter 3826 \subsection{Pt(557) and Au(557) metal interfaces}
318 jmichalk 3802
319 jmichalk 3827 Our model systems are composed of 3888 Pt atoms and 3384 Au atoms in a
320 gezelter 3826 FCC crystal that have been cut along the 557 plane so that they are
321     periodic in the {\it x} and {\it y} directions, and have been rotated
322     to expose two parallel 557 cuts along the positive and negative {\it
323     z}-axis. Simulations of the bare metal interfaces at temperatures
324     ranging from 300~K to 1200~K were done to observe the relative
325     stability of the surfaces without a CO overlayer.
326 jmichalk 3802
327 gezelter 3826 The different bulk (and surface) melting temperatures (1337~K for Au
328     and 2045~K for Pt) suggest that the reconstruction may happen at
329     different temperatures for the two metals. To copy experimental
330     conditions for the CO-exposed surfaces, the bare surfaces were
331     initially run in the canonical (NVT) ensemble at 800~K and 1000~K
332     respectively for 100 ps. Each surface was exposed to a range of CO
333     that was initially placed in the vacuum region. Upon full adsorption,
334     these amounts correspond to 0\%, 5\%, 25\%, 33\%, and 50\% surface
335     coverage. Because of the difference in binding energies, the platinum
336     systems very rarely had CO that was not bound to the surface, while
337     the gold surfaces often had a significant CO population in the gas
338     phase. These systems were allowed to reach thermal equilibrium (over
339     5 ns) before being shifted to the microcanonical (NVE) ensemble for
340     data collection. All of the systems examined had at least 40 ns in the
341     data collection stage, although simulation times for some of the
342     systems exceeded 200ns. All simulations were run using the open
343     source molecular dynamics package, OpenMD.\cite{Ewald,OOPSE,OpenMD}
344 jmichalk 3802
345     % Just results, leave discussion for discussion section
346 jmichalk 3860 % structure
347     % Pt: step wandering, double layers, no triangular motifs
348     % Au: step wandering, no double layers
349     % dynamics
350     % diffusion
351     % time scale, formation, breakage
352 jmichalk 3802 \section{Results}
353 jmichalk 3860 \subsection{Structural remodeling}
354     Tao {\it et al.} showed experimentally that the Pt(557) surface undergoes
355     two separate reconstructions upon CO adsorption.\cite{Tao:2010} The first
356     reconstruction involves a doubling of the step height and plateau length. Similar
357 jmichalk 3862 behavior has been seen to occur on numerous surfaces at varying conditions.\cite{Williams:1994,Williams:1991,Pearl}
358 jmichalk 3860 Of the two systems we examined, the Platinum system showed the most surface
359     reconstruction. Additionally, the amount of reconstruction appears to be
360     dependent on the amount of CO adsorbed upon the surface. This result is likely
361     related to the effect that coverage has on surface diffusion. While both systems
362     displayed step edge wandering, only the Pt surface underwent doubling within
363     the time scales we were modeling. Specifically only the 50 \% coverage Pt system
364 jmichalk 3862 was observed to undergo a complete doubling in the time scales we were able to monitor.
365     This event encouraged us to allow that specific system to run continuously during which two
366     more double layers were created. The other systems, not displaying any large scale changes
367     of interest, were all stopped after 40 ns of simulation. Neverthless, the other Platinum systems tended to show
368     more cumulative lateral movement of the step edges when compared to the Gold systems.
369     The 50 \% Pt system is highlighted in figure \ref{fig:reconstruct} at various times along the
370     simulation showing the evolution of the system.
371 jmichalk 3802
372 jmichalk 3860 The second reconstruction on the Pt(557) surface observed by Tao involved the
373     formation of triangular clusters that stretched across the plateau between two step edges.
374     Neither system, within our simulated time scales, experiences this reconstruction. A constructed
375     system in which the triangular motifs were constructed on the surface will be explored in future
376     work and is shown in the supporting information.
377 jmichalk 3817
378 jmichalk 3860 \subsection{Dynamics}
379 jmichalk 3862 While atomistic-like simulations of stepped surfaces have been performed before \cite{}, they tend to be
380     performed using Monte Carlo techniques\cite{Williams:1991,Williams:1994}. This allows them to efficiently sample the thermodynamic
381     landscape but at the expense of ignoring the dynamics of the system. Previous work, using STM \cite{Pearl},
382     has been able to visualize the coalescing of steps of (system). The time scale of the image acquisition, ~ 70 s/image
383 jmichalk 3860 provides an upper bounds for the time required for the doubling to actually occur. While statistical treatments
384     of step edges are adept at analyzing such systems, it is important to remember that the edges are made
385     up of individual atoms and thus can be examined in numerous ways.
386 gezelter 3826
387 jmichalk 3860 \subsubsection{Transport of surface metal atoms}
388 jmichalk 3862 %forcedSystems/stepSeparation
389 jmichalk 3860 The movement of a step edge is a cooperative effect arising from the individual movements of the atoms
390     making up the step. An ideal metal surface displaying a low index facet (111, 100, 110) is unlikely to
391     experience much surface diffusion because of the large energetic barrier to lift an atom out of the surface.
392 jmichalk 3862 For our surfaces however, the presence of step edges provide a source for mobile metal atoms. Breaking away
393     from the step edge still imposes an energetic penalty around 40 kcal/mole, but is much less than lifting the same metal
394     atom out from the surface, > 60 kcal/mole, and the penalty lowers even further when CO is present in sufficient quantities
395     on the surface, ~20 kcal/mole. Once an adatom exists on the surface, its barrier for diffusion is negligible ( < 4 kcal/mole)
396     and is well able to explore its terrace. Atoms traversing terraces is more difficult, but can be overcome through a joining and lifting stage.
397     By tracking the mobility of individual metal atoms on the Platinum and Gold surfaces we were able to determine
398     the relative diffusion rates and how varying coverages of CO affected the rates. Close
399 jmichalk 3860 observation of the mobile metal atoms showed that they were typically in equilibrium with the
400     step edges, constantly breaking apart and rejoining. Additionally, at times their motion was concerted and
401     two or more atoms would be observed moving together across the surfaces. The primary challenge in quantifying
402 jmichalk 3862 the overall surface mobility was in defining ``mobile" vs. ``static" atoms.
403 gezelter 3826
404 jmichalk 3860 A particle was considered mobile once it had traveled more than 2~\AA~ between saved configurations
405     of the system (10-100 ps). An atom that was truly mobile would typically travel much greater than this, but
406 jmichalk 3862 the 2~\AA~ cutoff was to prevent the in-place vibrational movement of atoms from being included in the analysis.
407 jmichalk 3860 Since diffusion on a surface is strongly affected by local structures, in this case the presence of single and double
408     layer step edges, the diffusion parallel to the step edges was determined separately from the diffusion perpendicular
409     to these edges. The parallel and perpendicular diffusion constants are shown in figure \ref{fig:diff}.
410 gezelter 3826
411 jmichalk 3860 \subsubsection{Double layer formation}
412     The increased amounts of diffusion on Pt at the higher CO coverages appears to play a role in the
413 jmichalk 3862 formation of double layers, seeing as how that was the only system within our observed simulation time
414     that showed the formation. Despite this being the only system where this reconstruction occurs, three separate layers
415     were formed over the extended run time of this system. As mentioned earlier, previous experimental work has given some insight into
416     the upper bounds of the time required for enough atoms to move around to allow two steps to coalesce\cite{Williams:1991,Pearl}.
417 jmichalk 3860 As seen in figure \ref{fig:reconstruct}, the first appearance of a double layer, a nodal site, appears at 19 ns into
418 jmichalk 3862 the simulation. Within 12 ns, nearly half of the step has formed the double layer and by 86 ns, a smooth complete
419     layer has formed. The double layer is complete by 37 ns but is a bit rough.
420     From the appearance of the first node to the initial doubling of the layers ignoring their roughness took ~20 ns.
421     Another ~40 ns was necessary for the layer to completely straighten. The other two layers in this simulation form
422     over a period of 22 ns and 42 ns respectively.
423 jmichalk 3817
424 jmichalk 3862 %Evolution of surface
425 jmichalk 3816 \begin{figure}[H]
426 jmichalk 3862 \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
427     \caption{The Pt(557) / 50\% CO system at a sequence of times after
428     initial exposure to the CO: (a) 258 ps, (b) 19 ns, (c) 31.2 ns, and
429     (d) 86.1 ns. Disruption of the 557 step edges occurs quickly. The
430     doubling of the layers appears only after two adjacent step edges
431     touch. The circled spot in (b) nucleated the growth of the double
432     step observed in the later configurations.}
433     \label{fig:reconstruct}
434     \end{figure}
435    
436     \begin{figure}[H]
437 jmichalk 3839 \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
438 gezelter 3826 \caption{Diffusion constants for mobile surface atoms along directions
439     parallel ($\mathbf{D}_{\parallel}$) and perpendicular
440     ($\mathbf{D}_{\perp}$) to the 557 step edges as a function of CO
441     surface coverage. Diffusion parallel to the step edge is higher
442     than that perpendicular to the edge because of the lower energy
443     barrier associated with going from approximately 7 nearest neighbors
444     to 5, as compared to the 3 of an adatom. Additionally, the observed
445     maximum and subsequent decrease for the Pt system suggests that the
446     CO self-interactions are playing a significant role with regards to
447     movement of the platinum atoms around and more importantly across
448     the surface. }
449     \label{fig:diff}
450 jmichalk 3816 \end{figure}
451    
452 jmichalk 3802
453 jmichalk 3862
454    
455 jmichalk 3802 %Discussion
456     \section{Discussion}
457 jmichalk 3862 In this paper we have shown that we were able to accurately model the initial reconstruction of the
458     Pt (557) surface upon CO adsorption as shown by Tao et al. \cite{Tao:2010}. More importantly, we
459     were able to capture the dynamic processes inherent within this reconstruction.
460 jmichalk 3802
461 jmichalk 3862 \subsection{Mechanism for restructuring}
462     The increased computational cost to examine this system using molecular dynamics rather than
463     a Monte Carlo based approach was necessary so that our predictions on possible mechanisms
464     and driving forces would have support not only from thermodynamic arguments but also from the
465     actual dynamics of the system.
466 gezelter 3826
467     Comparing the results from simulation to those reported previously by
468     Tao et al. the similarities in the platinum and CO system are quite
469 jmichalk 3862 strong. As shown in figure \ref{fig:reconstruct}, the simulated platinum system under a CO
470 gezelter 3826 atmosphere will restructure slightly by doubling the terrace
471     heights. The restructuring appears to occur slowly, one to two
472     platinum atoms at a time. Looking at individual snapshots, these
473     adatoms tend to either rise on top of the plateau or break away from
474     the step edge and then diffuse perpendicularly to the step direction
475     until reaching another step edge. This combination of growth and decay
476     of the step edges appears to be in somewhat of a state of dynamic
477     equilibrium. However, once two previously separated edges meet as
478     shown in figure 1.B, this point tends to act as a focus or growth
479     point for the rest of the edge to meet up, akin to that of a
480     zipper. From the handful of cases where a double layer was formed
481     during the simulation, measuring from the initial appearance of a
482     growth point, the double layer tends to be fully formed within
483     $\sim$~35 ns.
484    
485 jmichalk 3862 There are a number of possible mechanisms to explain the role of
486     adsorbed CO in restructuring the Pt surface. Quadrupolar repulsion
487     between adjacent CO molecules adsorbed on the surface is one
488     possibility. However, the quadrupole-quadrupole interaction is
489     short-ranged and is attractive for some orientations. If the CO
490     molecules are ``locked'' in a specific orientation relative to each other however,
491     this explanation gains some weight. The energetic repulsion between two CO
492     located a distance of 2.77~\AA~apart (nearest-neighbor distance of Pt) with both in a
493     vertical orientation is 8.62 kcal/mole. Moving the CO apart to the second nearest-neighbor
494     distance of 4.8~\AA~or 5.54~\AA~drops the repulsion to nearly 0 kcal/mole. SHOW A NUMBER FOR ROTATION.
495     As mentioned above, the energy barrier for surface diffusion of a platinum adatom is only 4 kcal/mole. So this
496     repulsion between CO can help increase the surface diffusion. However, the residence time of CO was examined
497     and while the majority of the CO is on or near the surface throughout the run, it is extremely mobile. This mobility
498     suggests that the CO are more likely to shift their positions without necessarily dragging the platinum along
499     with them.
500    
501     Another possible and more likely mechanism for the restructuring is in the
502     destabilization of strong Pt-Pt interactions by CO adsorbed on surface
503     Pt atoms. This could have the effect of increasing surface mobility
504     of these atoms. To test this hypothesis, numerous configurations of
505     CO in varying quantities were arranged on the higher and lower plateaus
506     around a step on a otherwise clean Pt (557) surface. One representative
507     configuration is displayed in figure \ref{fig:lambda}. Single or concerted movement
508     of platinum atoms was then examined to determine possible barriers. Because
509     of the forced movement along a pre-defined reaction coordinate that may differ
510     from the true minimum of this path, only the beginning and ending energies
511     are displayed in table \ref{tab:energies}. The presence of CO at suitable
512     sites can lead to lowered barriers for platinum breaking apart from the step edge.
513     Additionally, as highlighted in figure \ref{fig:lambda}, the presence of CO makes the
514     burrowing and lifting nature favorable, whereas without CO, the process is neutral
515     in terms of energetics.
516    
517     %lambda progression of Pt -> shoving its way into the step
518     \begin{figure}[H]
519     \includegraphics[width=\linewidth]{lambdaProgression_atopCO.png}
520     \caption{A model system of the Pt 557 surface was used as the framework for a reaction coordinate.
521     Various numbers, placements, and rotations of CO were examined. The one displayed was a
522     representative sample. As shown in Table , relative to the energy at 0\% there is a slight decrease
523     upon insertion of the platinum atom into the step edge along with the resultant lifting of the other
524     platinum atom.}
525     \label{fig:lambda}
526     \end{figure}
527    
528    
529    
530 jmichalk 3802 \subsection{Diffusion}
531 jmichalk 3862 As shown in the results section, the diffusion parallel to the step edge tends to be
532     much faster than that perpendicular to the step edge. Additionally, the coverage
533     of CO appears to play a slight role in relative rates of diffusion, as shown in figure \ref{fig:diff}
534     Thus, the bottleneck of the double layer formation appears to be the initial formation
535     of this growth point, which seems to be somewhat of a stochastic event. Once it
536     appears, parallel diffusion, along the now slightly angled step edge, will allow for
537     a faster formation of the double layer than if the entire process were dependent on
538     only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the
539     more likely a growth point is to be formed.
540 jmichalk 3802 \\
541 jmichalk 3862
542    
543     %breaking of the double layer upon removal of CO
544 jmichalk 3802 \begin{figure}[H]
545 jmichalk 3862 \includegraphics[width=\linewidth]{doubleLayerBreaking_greenBlue_whiteLetters.png}
546     \caption{Hi}
547     \label{fig:breaking}
548 jmichalk 3802 \end{figure}
549    
550    
551 jmichalk 3862
552    
553 jmichalk 3802 %Peaks!
554 jmichalk 3816 \begin{figure}[H]
555 gezelter 3826 \includegraphics[width=\linewidth]{doublePeaks_noCO.png}
556 jmichalk 3816 \caption{}
557 jmichalk 3862 \label{fig:peaks}
558 jmichalk 3816 \end{figure}
559 jmichalk 3862
560     %clean surface...
561 jmichalk 3827 \begin{figure}[H]
562     \includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
563     \caption{}
564 jmichalk 3862
565 jmichalk 3827 \end{figure}
566 jmichalk 3862 \label{fig:clean}
567 jmichalk 3802 \section{Conclusion}
568    
569    
570 jmichalk 3862 %Things I am not ready to remove yet
571    
572     %Table of Diffusion Constants
573     %Add gold?M
574     % \begin{table}[H]
575     % \caption{}
576     % \centering
577     % \begin{tabular}{| c | cc | cc | }
578     % \hline
579     % &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
580     % \hline
581     % \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ \\
582     % \hline
583     % 50\% & 4.32(2) & 1.185(8) & 1.72(2) & 0.455(6) \\
584     % 33\% & 5.18(3) & 1.999(5) & 1.95(2) & 0.337(4) \\
585     % 25\% & 5.01(2) & 1.574(4) & 1.26(3) & 0.377(6) \\
586     % 5\% & 3.61(2) & 0.355(2) & 1.84(3) & 0.169(4) \\
587     % 0\% & 3.27(2) & 0.147(4) & 1.50(2) & 0.194(2) \\
588     % \hline
589     % \end{tabular}
590     % \end{table}
591    
592 gezelter 3808 \section{Acknowledgments}
593     Support for this project was provided by the National Science
594     Foundation under grant CHE-0848243 and by the Center for Sustainable
595     Energy at Notre Dame (cSEND). Computational time was provided by the
596     Center for Research Computing (CRC) at the University of Notre Dame.
597 jmichalk 3802
598 gezelter 3808 \newpage
599     \bibliography{firstTryBibliography}
600     \end{doublespace}
601     \end{document}