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1 \documentclass[11pt]{article}
2 \usepackage{amsmath}
3 \usepackage{amssymb}
4 \usepackage{times}
5 \usepackage{mathptm}
6 \usepackage{setspace}
7 \usepackage{endfloat}
8 \usepackage{caption}
9 %\usepackage{tabularx}
10 \usepackage{graphicx}
11 \usepackage{multirow}
12 %\usepackage{booktabs}
13 %\usepackage{bibentry}
14 %\usepackage{mathrsfs}
15 \usepackage[square, comma, sort&compress]{natbib}
16 \usepackage{url}
17 \pagestyle{plain} \pagenumbering{arabic} \oddsidemargin 0.0cm
18 \evensidemargin 0.0cm \topmargin -21pt \headsep 10pt \textheight
19 9.0in \textwidth 6.5in \brokenpenalty=10000
20
21 % double space list of tables and figures
22 %\AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
23 \setlength{\abovecaptionskip}{20 pt}
24 \setlength{\belowcaptionskip}{30 pt}
25
26 \bibpunct{}{}{,}{s}{}{;}
27 \bibliographystyle{achemso}
28
29 \begin{document}
30
31
32 %%
33 %Introduction
34 % Experimental observations
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 \title{Molecular Dynamics simulations of the surface reconstructions
52 of Pt(557) and Au(557) under exposure to CO}
53
54 \author{Joseph R. Michalka, Patrick W. McIntyre and J. Daniel
55 Gezelter\footnote{Corresponding author. \ Electronic mail: gezelter@nd.edu} \\
56 Department of Chemistry and Biochemistry,\\
57 University of Notre Dame\\
58 Notre Dame, Indiana 46556}
59
60 %Date
61 \date{Mar 5, 2013}
62
63 %authors
64
65 % make the title
66 \maketitle
67
68 \begin{doublespace}
69
70 \begin{abstract}
71 We examine surface reconstructions of Pt and Au(557) under
72 various CO coverages using molecular dynamics in order to
73 explore possible mechanisms for any observed reconstructions
74 and their dynamics. The metal-CO interactions were parameterized
75 as part of this work so that an efficient large-scale treatment of
76 this system could be undertaken. The large difference in binding
77 strengths of the metal-CO interactions was found to play a significant
78 role with regards to step-edge stability and adatom diffusion. A
79 small correlation between coverage and the diffusion constant
80 was also determined. The energetics of CO adsorbed to the surface
81 is sufficient to explain the reconstructions observed on the Pt
82 systems and the lack of reconstruction of the Au systems.
83
84 \end{abstract}
85
86 \newpage
87
88
89 \section{Introduction}
90 % Importance: catalytically active metals are important
91 % Sub: Knowledge of how their surface structure affects their ability to catalytically facilitate certain reactions is growing, but is more reactionary than predictive
92 % 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)
93 % Theory can explore temperatures and pressures which are difficult to work with in experiments
94 % Sub: Also, easier to observe what is going on and provide reasons and explanations
95 %
96
97 Industrial catalysts usually consist of small particles that exhibit a
98 high concentration of steps, kink sites, and vacancies at the edges of
99 the facets. These sites are thought to be the locations of catalytic
100 activity.\cite{ISI:000083038000001,ISI:000083924800001} There is now
101 significant evidence that solid surfaces are often structurally,
102 compositionally, and chemically modified by reactants under operating
103 conditions.\cite{Tao2008,Tao:2010,Tao2011} The coupling between
104 surface oxidation states and catalytic activity for CO oxidation on
105 Pt, for instance, is widely documented.\cite{Ertl08,Hendriksen:2002}
106 Despite the well-documented role of these effects on reactivity, the
107 ability to capture or predict them in atomistic models is somewhat
108 limited. While these effects are perhaps unsurprising on the highly
109 disperse, multi-faceted nanoscale particles that characterize
110 industrial catalysts, they are manifest even on ordered, well-defined
111 surfaces. The Pt(557) surface, for example, exhibits substantial and
112 reversible restructuring under exposure to moderate pressures of
113 carbon monoxide.\cite{Tao:2010}
114
115 This work is an attempt to understand the mechanism and timescale for
116 surface restructuring by 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 reconstruct under certain conditions. The Au(557) surface, because
124 of a weaker interaction with CO, is less likely to undergo this kind
125 of reconstruction.
126
127
128
129 %Platinum molecular dynamics
130 %gold molecular dynamics
131
132 \section{Simulation Methods}
133 The challenge in modeling any solid/gas interface is the
134 development of a sufficiently general yet computationally tractable
135 model of the chemical interactions between the surface atoms and
136 adsorbates. Since the interfaces involved are quite large (10$^3$ -
137 10$^6$ atoms) and respond slowly to perturbations, {\it ab initio}
138 molecular dynamics
139 (AIMD),\cite{KRESSE:1993ve,KRESSE:1993qf,KRESSE:1994ul} Car-Parrinello
140 methods,\cite{CAR:1985bh,Izvekov:2000fv,Guidelli:2000fy} and quantum
141 mechanical potential energy surfaces remain out of reach.
142 Additionally, the ``bonds'' between metal atoms at a surface are
143 typically not well represented in terms of classical pairwise
144 interactions in the same way that bonds in a molecular material are,
145 nor are they captured by simple non-directional interactions like the
146 Coulomb potential. For this work, we have used classical molecular
147 dynamics with potential energy surfaces that are specifically tuned
148 for transition metals. In particular, we used the EAM potential for
149 Au-Au and Pt-Pt interactions\cite{EAM}. The CO was modeled using a rigid
150 three-site model developed by Straub and Karplus for studying
151 photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and
152 Pt-CO cross interactions were parameterized as part of this work.
153
154 \subsection{Metal-metal interactions}
155 Many of the potentials used for modeling transition metals are based
156 on a non-pairwise additive functional of the local electron
157 density. The embedded atom method (EAM) is perhaps the best known of
158 these
159 methods,\cite{Daw84,Foiles86,Johnson89,Daw89,Plimpton93,Voter95a,Lu97,Alemany98}
160 but other models like the Finnis-Sinclair\cite{Finnis84,Chen90} and
161 the quantum-corrected Sutton-Chen method\cite{QSC,Qi99} have simpler
162 parameter sets. The glue model of Ercolessi et al. is among the
163 fastest of these density functional approaches.\cite{Ercolessi88} In
164 all of these models, atoms are conceptualized as a positively charged
165 core with a radially-decaying valence electron distribution. To
166 calculate the energy for embedding the core at a particular location,
167 the electron density due to the valence electrons at all of the other
168 atomic sites is computed at atom $i$'s location,
169 \begin{equation*}
170 \bar{\rho}_i = \sum_{j\neq i} \rho_j(r_{ij})
171 \end{equation*}
172 Here, $\rho_j(r_{ij})$ is the function that describes the distance
173 dependence of the valence electron distribution of atom $j$. The
174 contribution to the potential that comes from placing atom $i$ at that
175 location is then
176 \begin{equation*}
177 V_i = F[ \bar{\rho}_i ] + \sum_{j \neq i} \phi_{ij}(r_{ij})
178 \end{equation*}
179 where $F[ \bar{\rho}_i ]$ is an energy embedding functional, and
180 $\phi_{ij}(r_{ij})$ is a pairwise term that is meant to represent the
181 repulsive overlap of the two positively charged cores.
182
183 % The {\it modified} embedded atom method (MEAM) adds angular terms to
184 % the electron density functions and an angular screening factor to the
185 % pairwise interaction between two
186 % atoms.\cite{BASKES:1994fk,Lee:2000vn,Thijsse:2002ly,Timonova:2011ve}
187 % MEAM has become widely used to simulate systems in which angular
188 % interactions are important (e.g. silicon,\cite{Timonova:2011ve} bcc
189 % metals,\cite{Lee:2001qf} and also interfaces.\cite{Beurden:2002ys})
190 % MEAM presents significant additional computational costs, however.
191
192 The EAM, Finnis-Sinclair, and the Quantum Sutton-Chen (QSC) potentials
193 have all been widely used by the materials simulation community for
194 simulations of bulk and nanoparticle
195 properties,\cite{Chui:2003fk,Wang:2005qy,Medasani:2007uq}
196 melting,\cite{Belonoshko00,sankaranarayanan:155441,Sankaranarayanan:2005lr}
197 fracture,\cite{Shastry:1996qg,Shastry:1998dx} crack
198 propagation,\cite{BECQUART:1993rg} and alloying
199 dynamics.\cite{Shibata:2002hh} All of these potentials have their
200 strengths and weaknesses. \cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}
201
202 \subsection{Carbon Monoxide model}
203 Previous explanations for the surface rearrangements center on
204 the large linear quadrupole moment of carbon monoxide.\cite{Tao:2010}
205 We used a model first proposed by Karplus and Straub to study
206 the photodissociation of CO from myoglobin because it reproduces
207 the quadrupole moment well.\cite{Straub} The Straub and
208 Karplus model, treats CO as a rigid three site molecule with a massless M
209 site at the molecular center of mass. The geometry and interaction
210 parameters are reproduced in Table~\ref{tab:CO}. The effective
211 dipole moment, calculated from the assigned charges, is still
212 small (0.35 D) while the linear quadrupole (-2.40 D~\AA) is close
213 to the experimental (-2.63 D~\AA)\cite{QuadrupoleCO} and quantum
214 mechanical predictions (-2.46 D~\AA)\cite{QuadrupoleCOCalc}.
215 %CO Table
216 \begin{table}[H]
217 \caption{Positions, Lennard-Jones parameters ($\sigma$ and
218 $\epsilon$), and charges for the CO-CO
219 interactions in Ref.\bibpunct{}{}{,}{n}{}{,} \protect\cite{Straub}. Distances are in \AA, energies are
220 in kcal/mol, and charges are in atomic units.}
221 \centering
222 \begin{tabular}{| c | c | ccc |}
223 \hline
224 & {\it z} & $\sigma$ & $\epsilon$ & q\\
225 \hline
226 \textbf{C} & -0.6457 & 3.83 & 0.0262 & -0.75 \\
227 \textbf{O} & 0.4843 & 3.12 & 0.1591 & -0.85 \\
228 \textbf{M} & 0.0 & - & - & 1.6 \\
229 \hline
230 \end{tabular}
231 \label{tab:CO}
232 \end{table}
233
234 \subsection{Cross-Interactions between the metals and carbon monoxide}
235
236 Since the adsorption of CO onto a Pt surface has been the focus
237 of much experimental \cite{Yeo, Hopster:1978, Ertl:1977, Kelemen:1979}
238 and theoretical work
239 \cite{Beurden:2002ys,Pons:1986,Deshlahra:2009,Feibelman:2001,Mason:2004}
240 there is a significant amount of data on adsorption energies for CO on
241 clean metal surfaces. An earlier model by Korzeniewski {\it et
242 al.}\cite{Pons:1986} served as a starting point for our fits. The parameters were
243 modified to ensure that the Pt-CO interaction favored the atop binding
244 position on Pt(111). These parameters are reproduced in Table~\ref{tab:co_parameters}.
245 The modified parameters yield binding energies that are slightly higher
246 than the experimentally-reported values as shown in Table~\ref{tab:co_energies}. Following Korzeniewski
247 et al.,\cite{Pons:1986} the Pt-C interaction was fit to a deep
248 Lennard-Jones interaction to mimic strong, but short-ranged partial
249 binding between the Pt $d$ orbitals and the $\pi^*$ orbital on CO. The
250 Pt-O interaction was modeled with a Morse potential with a large
251 equilibrium distance, ($r_o$). These choices ensure that the C is preferred
252 over O as the surface-binding atom. In most cases, the Pt-O parameterization contributes a weak
253 repulsion which favors the atop site. The resulting potential-energy
254 surface suitably recovers the calculated Pt-C separation length
255 (1.6~\AA)\cite{Beurden:2002ys} and affinity for the atop binding
256 position.\cite{Deshlahra:2012, Hopster:1978}
257
258 %where did you actually get the functionals for citation?
259 %scf calculations, so initial relaxation was of the four layers, but two layers weren't kept fixed, I don't think
260 %same cutoff for slab and slab + CO ? seems low, although feibelmen had values around there...
261 The Au-C and Au-O cross-interactions were also fit using Lennard-Jones and
262 Morse potentials, respectively, to reproduce Au-CO binding energies.
263 The limited experimental data for CO adsorption on Au required refining the fits against plane-wave DFT calculations.
264 Adsorption energies were obtained from gas-surface DFT calculations with a
265 periodic supercell plane-wave basis approach, as implemented in the
266 {\sc Quantum ESPRESSO} package.\cite{QE-2009} Electron cores were
267 described with the projector augmented-wave (PAW)
268 method,\cite{PhysRevB.50.17953,PhysRevB.59.1758} with plane waves
269 included to an energy cutoff of 20 Ry. Electronic energies are
270 computed with the PBE implementation of the generalized gradient
271 approximation (GGA) for gold, carbon, and oxygen that was constructed
272 by Rappe, Rabe, Kaxiras, and Joannopoulos.\cite{Perdew_GGA,RRKJ_PP}
273 In testing the Au-CO interaction, Au(111) supercells were constructed of four layers of 4
274 Au x 2 Au surface planes and separated from vertical images by six
275 layers of vacuum space. The surface atoms were all allowed to relax
276 before CO was added to the system. Electronic relaxations were
277 performed until the energy difference between subsequent steps
278 was less than $10^{-8}$ Ry. Nonspin-polarized supercell calculations
279 were performed with a 4~x~4~x~4 Monkhorst-Pack {\bf k}-point sampling of the first Brillouin
280 zone.\cite{Monkhorst:1976,PhysRevB.13.5188} The relaxed gold slab was
281 then used in numerous single point calculations with CO at various
282 heights (and angles relative to the surface) to allow fitting of the
283 empirical force field.
284
285 %Hint at future work
286 The parameters employed for the metal-CO cross-interactions in this work
287 are shown in Table~\ref{tab:co_parameters} and the binding energies on the
288 (111) surfaces are displayed in Table~\ref{tab:co_energies}. Charge transfer
289 and polarization are neglected in this model, although these effects are likely to
290 affect binding energies and binding site preferences, and will be addressed in
291 a future work.\cite{Deshlahra:2012,StreitzMintmire:1994}
292
293 %Table of Parameters
294 %Pt Parameter Set 9
295 %Au Parameter Set 35
296 \begin{table}[H]
297 \caption{Best fit parameters for metal-CO cross-interactions. Metal-C
298 interactions are modeled with Lennard-Jones potentials. While the
299 metal-O interactions were fit to Morse
300 potentials. Distances are given in \AA~and energies in kcal/mol. }
301 \centering
302 \begin{tabular}{| c | cc | c | ccc |}
303 \hline
304 & $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ (\AA$^{-1}$) \\
305 \hline
306 \textbf{Pt-C} & 1.3 & 15 & \textbf{Pt-O} & 3.8 & 3.0 & 1 \\
307 \textbf{Au-C} & 1.9 & 6.5 & \textbf{Au-O} & 3.8 & 0.37 & 0.9\\
308
309 \hline
310 \end{tabular}
311 \label{tab:co_parameters}
312 \end{table}
313
314 %Table of energies
315 \begin{table}[H]
316 \caption{Adsorption energies for a single CO at the atop site on M(111) at the atop site using the potentials
317 described in this work. All values are in eV.}
318 \centering
319 \begin{tabular}{| c | cc |}
320 \hline
321 & Calculated & Experimental \\
322 \hline
323 \multirow{2}{*}{\textbf{Pt-CO}} & \multirow{2}{*}{-1.9} & -1.4 \bibpunct{}{}{,}{n}{}{,}
324 (Ref. \protect\cite{Kelemen:1979}) \\
325 & & -1.9 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{Yeo}) \\ \hline
326 \textbf{Au-CO} & -0.39 & -0.40 \bibpunct{}{}{,}{n}{}{,} (Ref. \protect\cite{TPD_Gold}) \\
327 \hline
328 \end{tabular}
329 \label{tab:co_energies}
330 \end{table}
331
332 \subsection{Pt(557) and Au(557) metal interfaces}
333
334 Our model systems are composed of 3888 Pt atoms and 3384 Au atoms in a
335 FCC crystal that have been cut along the (557) plane so that they are
336 periodic in the {\it x} and {\it y} directions, and have been oriented
337 to expose two aligned (557) cuts along the extended {\it
338 z}-axis. Simulations of the bare metal interfaces at temperatures
339 ranging from 300~K to 1200~K were performed to observe the relative
340 stability of the surfaces without a CO overlayer.
341
342 The different bulk melting temperatures (1337~K for Au
343 and 2045~K for Pt) suggest that any possible reconstruction should happen at
344 different temperatures for the two metals. The bare Au and Pt surfaces were
345 initially run in the canonical (NVT) ensemble at 800~K and 1000~K
346 respectively for 100 ps. The two surfaces were relatively stable at these
347 temperatures when no CO was present, but experienced increased surface
348 mobility on addition of CO. Each surface was then dosed with different concentrations of CO
349 that was initially placed in the vacuum region. Upon full adsorption,
350 these concentrations correspond to 0\%, 5\%, 25\%, 33\%, and 50\% surface
351 coverage. Higher coverages resulted in CO double layer formation, which introduces artifacts that are not relevant to (557) reconstruction.
352 Because of the difference in binding energies, nearly all of the CO was bound to the Pt surface, while
353 the Au surfaces often had a significant CO population in the gas
354 phase. These systems were allowed to reach thermal equilibrium (over
355 5 ns) before being run in the microcanonical (NVE) ensemble for
356 data collection. All of the systems examined had at least 40 ns in the
357 data collection stage, although simulation times for some of the
358 systems exceeded 200~ns. Simulations were run using the open
359 source molecular dynamics package, OpenMD.\cite{Ewald,OOPSE}
360
361 % Just results, leave discussion for discussion section
362 % structure
363 % Pt: step wandering, double layers, no triangular motifs
364 % Au: step wandering, no double layers
365 % dynamics
366 % diffusion
367 % time scale, formation, breakage
368 \section{Results}
369 \subsection{Structural remodeling}
370 Tao et al. have shown experimentally that the Pt(557) surface
371 undergoes two separate reconstructions upon CO
372 adsorption.\cite{Tao:2010} The first involves a doubling of
373 the step height and plateau length. Similar behavior has been
374 seen to occur on numerous surfaces at varying conditions: Ni(977), Si(111).
375 \cite{Williams:1994,Williams:1991,Pearl} Of the two systems
376 we examined, the Pt system showed a larger amount of
377 reconstruction when compared to the Au system. The amount
378 of reconstruction is correlated to the amount of CO
379 adsorbed upon the surface. This appears to be related to the
380 effect that adsorbate coverage has on edge breakup and on the surface
381 diffusion of metal adatoms. While both systems displayed step-edge
382 wandering, only the Pt surface underwent the doubling seen by
383 Tao et al. within the time scales studied here.
384 Only the 50~\% coverage Pt system exhibited
385 a complete doubling in the time scales we
386 were able to monitor. Over longer periods (150~ns) two more double layers formed on this interface.
387 Although double layer formation did not occur in the other Pt systems, they show
388 more lateral movement of the step-edges
389 compared to the Au systems. The 50\% Pt system is highlighted
390 in Figure \ref{fig:reconstruct} at various times along the simulation
391 showing the evolution of a step-edge.
392
393 The second reconstruction on the Pt(557) surface observed by
394 Tao involved the formation of triangular clusters that stretched
395 across the plateau between two step-edges. Neither system, within
396 the 40~ns time scale, experienced this reconstruction.
397
398 \subsection{Dynamics}
399 While atomistic-like simulations of stepped surfaces have been
400 performed before, they tend to be performed using Monte Carlo
401 techniques\cite{Williams:1991,Williams:1994}. This allows them
402 to efficiently sample the equilibrium thermodynamic landscape
403 but at the expense of ignoring the dynamics of the system. Previous
404 work by Pearl and Sibener\cite{Pearl}, using STM, has been able to
405 visualize the coalescing of steps of Ni(977). The time scale of the image
406 acquisition, $\sim$70 s/image provides an upper bounds for the time
407 required for the doubling to actually occur. Statistical treatments of step-edges
408 are adept at analyzing such systems. However, in a system where
409 the number of steps is limited, examining the individual atoms that make
410 up the steps can provide useful information as well.
411
412
413 \subsubsection{Transport of surface metal atoms}
414 %forcedSystems/stepSeparation
415 The movement or wandering of a step-edge is a cooperative effect
416 arising from the individual movements, primarily through surface
417 diffusion, of the atoms making up the step. An ideal metal surface
418 displaying a low index facet, (111) or (100) is unlikely to experience
419 much surface diffusion because of the large energetic barrier that must
420 be overcome to lift an atom out of the surface. The presence of step-edges
421 on higher-index surfaces provide a source for mobile metal atoms.
422 Breaking away from the step-edge on a clean surface still imposes an
423 energetic penalty around $\sim$~40 kcal/mole, but is much less than lifting
424 the same metal atom out from the surface, \textgreater~60 kcal/mole, and
425 the penalty lowers even further when CO is present in sufficient quantities
426 on the surface. For certain tested distributions of CO, the penalty was lowered
427 to $\sim$~20 kcal/mole. Once an adatom exists on the surface, its barrier for
428 diffusion is negligible ( \textless~4 kcal/mole) and is well able to explore the
429 terrace before potentially rejoining its original step-edge or becoming a part
430 of a different edge. Atoms traversing separate terraces is a more difficult
431 process, but can be overcome through a joining and lifting stage which is
432 examined in the discussion section. By tracking the mobility of individual
433 metal atoms on the Pt and Au surfaces we were able to determine the relative
434 diffusion rates and how varying coverages of CO affected the rates. Close
435 observation of the mobile metal atoms showed that they were typically in
436 equilibrium with the step-edges, constantly breaking apart and rejoining.
437 At times their motion was concerted and two or more adatoms would be
438 observed moving together across the surfaces. The primary challenge in
439 quantifying the overall surface mobility was in defining ``mobile" vs. ``static" atoms.
440
441 A particle was considered mobile once it had traveled more than 2~\AA~
442 between saved configurations of the system (10-100 ps). An atom that was
443 truly mobile would typically travel much greater than this, but the 2~\AA~ cutoff
444 was to prevent the in-place vibrational movement of non-surface atoms from
445 being included in the analysis. Diffusion on a surface is strongly affected by
446 local structures and in this work the presence of single and double layer
447 step-edges causes the diffusion parallel to the step-edges to be different
448 from the diffusion perpendicular to these edges. This led us to compute
449 those diffusions separately as seen in Figure \ref{fig:diff}.
450
451 \subsubsection{Double layer formation}
452 The increased amounts of diffusion on Pt at the higher CO coverages appears
453 to play a primary role in the formation of double layers, although this conclusion
454 does not explain the 33\% coverage Pt system. On the 50\% system, three
455 separate layers were formed over the extended run time of this system. As
456 mentioned earlier, previous experimental work has given some insight into the
457 upper bounds of the time required for enough atoms to move around to allow two
458 steps to coalesce\cite{Williams:1991,Pearl}. As seen in Figure \ref{fig:reconstruct},
459 the first appearance of a double layer, a nodal site, appears at 19 ns into the
460 simulation. Within 12 ns, nearly half of the step has formed the double layer and
461 by 86 ns, a smooth complete layer has formed. The double layer is ``complete" by
462 37 ns but is a bit rough. From the appearance of the first node to the initial doubling
463 of the layers ignoring their roughness took $\sim$~20 ns. Another ~40 ns was
464 necessary for the layer to completely straighten. The other two layers in this
465 simulation form over a period of 22 ns and 42 ns respectively. Comparing this to
466 the upper bounds of the image scan, it is likely that aspects of this reconstruction
467 occur very quickly.
468
469 %Evolution of surface
470 \begin{figure}[H]
471 \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
472 \caption{The Pt(557) / 50\% CO system at a sequence of times after
473 initial exposure to the CO: (a) 258 ps, (b) 19 ns, (c) 31.2 ns, and
474 (d) 86.1 ns. Disruption of the (557) step-edges occurs quickly. The
475 doubling of the layers appears only after two adjacent step-edges
476 touch. The circled spot in (b) nucleated the growth of the double
477 step observed in the later configurations.}
478 \label{fig:reconstruct}
479 \end{figure}
480
481 \begin{figure}[H]
482 \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
483 \caption{Diffusion constants for mobile surface atoms along directions
484 parallel ($\mathbf{D}_{\parallel}$) and perpendicular
485 ($\mathbf{D}_{\perp}$) to the (557) step-edges as a function of CO
486 surface coverage. Diffusion parallel to the step-edge is higher
487 than that perpendicular to the edge because of the lower energy
488 barrier associated with traversing along the edge as compared to
489 completely breaking away. Additionally, the observed
490 maximum and subsequent decrease for the Pt system suggests that the
491 CO self-interactions are playing a significant role with regards to
492 movement of the Pt atoms around and across the surface. }
493 \label{fig:diff}
494 \end{figure}
495
496
497
498
499 %Discussion
500 \section{Discussion}
501 In this paper we have shown that we were able to accurately model the initial reconstruction of the
502 Pt(557) surface upon CO adsorption as shown by Tao et al. \cite{Tao:2010}. More importantly, we
503 were able to observe the dynamic processes necessary for this reconstruction.
504
505 \subsection{Mechanism for restructuring}
506 Comparing the results from simulation to those reported previously by
507 Tao et al.\cite{Tao:2010} the similarities in the Pt-CO system are quite
508 strong. As shown in Figure \ref{fig:reconstruct}, the simulated Pt
509 system under a CO atmosphere will restructure by doubling the terrace
510 heights. The restructuring occurs slowly, one to two Pt atoms at a time.
511 Looking at individual configurations of the system, the adatoms either
512 break away from the step-edge and stay on the lower terrace or they lift
513 up onto the higher terrace. Once ``free'' they will diffuse on the terrace
514 until reaching another step-edge or coming back to their original edge.
515 This combination of growth and decay of the step-edges is in a state of
516 dynamic equilibrium. However, once two previously separated edges
517 meet as shown in Figure 1.B, this meeting point tends to act as a focus
518 or growth point for the rest of the edge to meet up, akin to that of a zipper.
519 From the handful of cases where a double layer was formed during the
520 simulation, measuring from the initial appearance of a growth point, the
521 double layer tends to be fully formed within $\sim$~35 ns.
522
523 A number of possible mechanisms exist to explain the role of adsorbed
524 CO in restructuring the Pt surface. Quadrupolar repulsion between adjacent
525 CO molecules adsorbed on the surface is one likely possibility. However,
526 the quadrupole-quadrupole interaction is short-ranged and is attractive for
527 some orientations. If the CO molecules are ``locked'' in a specific orientation
528 relative to each other, through atop adsorption perhaps, this explanation
529 gains some weight. The energetic repulsion between two CO located a
530 distance of 2.77~\AA~apart (nearest-neighbor distance of Pt) with both in
531 a vertical orientation is 8.62 kcal/mole. Moving the CO apart to the second
532 nearest-neighbor distance of 4.8~\AA~or 5.54~\AA~drops the repulsion to
533 nearly 0 kcal/mole. Allowing the CO's to leave a purely vertical orientation
534 also quickly drops the repulsion, a minimum is reached at $\sim$24 degrees
535 of 6.2 kcal/mole. As mentioned above, the energy barrier for surface diffusion
536 of a Pt adatom is only 4 kcal/mole. So this repulsion between CO can help
537 increase the surface diffusion. However, the residence time of CO was
538 examined and while the majority of the CO is on or near the surface throughout
539 the run, it is extremely mobile. This mobility suggests that the CO are more
540 likely to shift their positions without necessarily dragging the Pt along with them.
541
542 Another possible and more likely mechanism for the restructuring is in the
543 destabilization of strong Pt-Pt interactions by CO adsorbed on surface
544 Pt atoms. This would then have the effect of increasing surface mobility
545 of these atoms. To test this hypothesis, numerous configurations of
546 CO in varying quantities were arranged on the higher and lower plateaus
547 around a step on a otherwise clean Pt(557) surface. One representative
548 configuration is displayed in Figure \ref{fig:lambda}. Single or concerted movement
549 of Pt atoms was then examined to determine possible barriers. Because
550 the movement was forced along a pre-defined reaction coordinate that may differ
551 from the true minimum of this path, only the beginning and ending energies
552 are displayed in Table \ref{tab:energies}. These values suggest that the presence of CO at suitable
553 locations can lead to lowered barriers for Pt breaking apart from the step-edge.
554 Additionally, as highlighted in Figure \ref{fig:lambda}, the presence of CO makes the
555 burrowing and lifting of adatoms favorable, whereas without CO, the process is neutral
556 in terms of energetics.
557
558 %lambda progression of Pt -> shoving its way into the step
559 \begin{figure}[H]
560 \includegraphics[width=\linewidth]{lambdaProgression_atopCO.png}
561 \caption{A model system of the Pt(557) surface was used as the framework
562 for exploring energy barriers along a reaction coordinate. Various numbers,
563 placements, and rotations of CO were examined as they affect Pt movement.
564 The coordinate displayed in this Figure was a representative run. As shown
565 in Table \ref{tab:rxcoord}, relative to the energy of the system at 0\%, there
566 is a slight decrease upon insertion of the Pt atom into the step-edge along
567 with the resultant lifting of the other Pt atom when CO is present at certain positions.}
568 \label{fig:lambda}
569 \end{figure}
570
571
572
573 \subsection{Diffusion}
574 As shown in the results section, the diffusion parallel to the step-edge tends to be
575 much larger than that perpendicular to the step-edge, likely because of the dynamic
576 equilibrium that is established between the step-edge and adatom interface. The coverage
577 of CO also appears to play a slight role in relative rates of diffusion, as shown in Figure \ref{fig:diff}.
578 The
579 Thus, the bottleneck of the double layer formation appears to be the initial formation
580 of this growth point, which seems to be somewhat of a stochastic event. Once it
581 appears, parallel diffusion, along the now slightly angled step-edge, will allow for
582 a faster formation of the double layer than if the entire process were dependent on
583 only perpendicular diffusion across the plateaus. Thus, the larger $D_{\perp}$, the
584 more likely a growth point is to be formed.
585 \\
586
587
588 %breaking of the double layer upon removal of CO
589 \begin{figure}[H]
590 \includegraphics[width=\linewidth]{doubleLayerBreaking_greenBlue_whiteLetters.png}
591 %:
592 \caption{(A) 0 ps, (B) 100 ps, (C) 1 ns, after the removal of CO. The presence of the CO
593 helped maintain the stability of the double layer and upon removal the two layers break
594 and begin separating. The separation is not a simple pulling apart however, rather
595 there is a mixing of the lower and upper atoms at the edge.}
596 \label{fig:breaking}
597 \end{figure}
598
599
600
601
602 %Peaks!
603 \begin{figure}[H]
604 \includegraphics[width=\linewidth]{doublePeaks_noCO.png}
605 \caption{At the initial formation of this double layer ( $\sim$ 37 ns) there is a degree
606 of roughness inherent to the edge. The next $\sim$ 40 ns show the edge with
607 aspects of waviness and by 80 ns the double layer is completely formed and smooth. }
608 \label{fig:peaks}
609 \end{figure}
610
611
612 %Don't think I need this
613 %clean surface...
614 %\begin{figure}[H]
615 %\includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
616 %\caption{}
617
618 %\end{figure}
619 %\label{fig:clean}
620
621
622 \section{Conclusion}
623 In this work we have shown the reconstruction of the Pt(557) crystalline surface upon adsorption of CO in < $\mu s$. Only the highest coverage Pt system showed this initial reconstruction similar to that seen previously. The strong interaction between Pt and CO and the limited interaction between Au and CO helps explain the differences between the two systems.
624
625 %Things I am not ready to remove yet
626
627 %Table of Diffusion Constants
628 %Add gold?M
629 % \begin{table}[H]
630 % \caption{}
631 % \centering
632 % \begin{tabular}{| c | cc | cc | }
633 % \hline
634 % &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
635 % \hline
636 % \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ \\
637 % \hline
638 % 50\% & 4.32(2) & 1.185(8) & 1.72(2) & 0.455(6) \\
639 % 33\% & 5.18(3) & 1.999(5) & 1.95(2) & 0.337(4) \\
640 % 25\% & 5.01(2) & 1.574(4) & 1.26(3) & 0.377(6) \\
641 % 5\% & 3.61(2) & 0.355(2) & 1.84(3) & 0.169(4) \\
642 % 0\% & 3.27(2) & 0.147(4) & 1.50(2) & 0.194(2) \\
643 % \hline
644 % \end{tabular}
645 % \end{table}
646
647 \section{Acknowledgments}
648 Support for this project was provided by the National Science
649 Foundation under grant CHE-0848243 and by the Center for Sustainable
650 Energy at Notre Dame (cSEND). Computational time was provided by the
651 Center for Research Computing (CRC) at the University of Notre Dame.
652
653 \newpage
654 \bibliography{firstTryBibliography}
655 \end{doublespace}
656 \end{document}