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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}
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12   %\usepackage{booktabs}
13   %\usepackage{bibentry}
14   %\usepackage{mathrsfs}
13 %\usepackage[ref]{overcite}
15   \usepackage[square, comma, sort&compress]{natbib}
16   \usepackage{url}
17   \pagestyle{plain} \pagenumbering{arabic} \oddsidemargin 0.0cm
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19   9.0in \textwidth 6.5in \brokenpenalty=10000
20  
21   % double space list of tables and figures
22 < \AtBeginDelayedFloats{\renewcommand{\baselinestretch}{1.66}}
22 > %\AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
23   \setlength{\abovecaptionskip}{20 pt}
24   \setlength{\belowcaptionskip}{30 pt}
25  
26 < %\renewcommand\citemid{\ } % no comma in optional reference note
26 < \bibpunct{[}{]}{,}{n}{}{;}
26 > \bibpunct{}{}{,}{s}{}{;}
27   \bibliographystyle{achemso}
28  
29   \begin{document}
# Line 48 | Line 48
48   %%
49  
50   %Title
51 < \title{Investigation of the Pt and Au 557 Surface Reconstructions
52 <  under a CO Atmosphere}
53 < \author{Joseph R. Michalka, Patrick W. MacIntyre and J. Daniel
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{Dec 15,  2012}
61 > \date{Dec 15, 2012}
62 >
63   %authors
64  
65   % make the title
# Line 79 | Line 82 | Industrial catalysts usually consist of small particle
82   %       Sub: Also, easier to observe what is going on and provide reasons and explanations
83   %
84  
85 < Industrial catalysts usually consist of small particles exposing
86 < different atomic terminations that exhibit a high concentration of
87 < step, kink sites, and vacancies at the edges of the facets.  These
85 < sites are thought to be the locations of catalytic
85 > 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   activity.\cite{ISI:000083038000001,ISI:000083924800001} There is now
89 < significant evidence to demonstrate that solid surfaces are often
90 < structurally, compositionally, and chemically {\it modified} by
91 < reactants under operating conditions.\cite{Tao2008,Tao:2010,Tao2011}
92 < The coupling between surface oxidation state and catalytic activity
93 < for CO oxidation on Pt, for instance, is widely
94 < documented.\cite{Ertl08,Hendriksen:2002} Despite the well-documented
95 < role of these effects on reactivity, the ability to capture or predict
96 < them in atomistic models is currently somewhat limited.  While these
97 < effects are perhaps unsurprising on the highly disperse, multi-faceted
98 < nanoscale particles that characterize industrial catalysts, they are
99 < manifest even on ordered, well-defined surfaces. The Pt(557) surface,
100 < for example, exhibits substantial and reversible restructuring under
101 < exposure to moderate pressures of carbon monoxide.\cite{Tao:2010}
89 > 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  
103 < This work is part of an ongoing effort to understand the causes,
104 < mechanisms and timescales for surface restructuring using molecular
105 < simulation methods.  Since the dynamics of the process is of
106 < particular interest, we utilize classical molecular dynamic methods
107 < with force fields that represent a compromise between chemical
106 < accuracy and the computational efficiency necessary to observe the
107 < process of interest.
103 > 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  
109 < High-index surfaces of catalytically active metals are an important area of exploration because they are typically more reactive than an ideal surface of the same metal. The greater number of low-coordinated surface atoms is believed responsible for this increased reactivity \cite{}. Additionally, the activity and specificity of many metals towards certain chemical processes has been shown to strongly depend on the structure of the surface \cite{}. Prior work has also shown that reaction conditions, such as high pressures and high temperatures are able to cause reconstructions of the metallic surface, either through changing the displayed surface facets or by changing the number and types of high-index sites available for reactions \cite{doi:10.1126/science.1197461,doi:10.1021/nn3015322, doi:10.1021/jp302379x}. A greater understanding of these high-index surfaces and the restructuring processes they undergo is needed as a prerequisite for more intelligent catalyst design. While current experimental work has started exploring systems at \emph{in situ} conditions, for a long time such experiments were limited to ideal surfaces in high vacuum. New techniques, such as ambient pressure XPS (AP-XPS) \cite{}, high-pressure XPS (HP-XPS) \cite{}, high-pressure STM \cite{}, environmental transmission electron microscopy (E-TEM) \cite{} and many others, are providing clearer pictures of the processes that are occurring on metal surfaces under these conditions. Nevertheless, all of these techniques still have limitations, especially in observing what is occurring at an atomic level. Theoretical models and simulations in combination with experiment have proven their worth in explaining the underlying reasons for some of these reconstructions \cite{}.
110 < \\
111 < By examining two different metal-CO systems the effect that the metal and the metal-CO interaction plays can be elucidated. Our first system is composed of platinum and CO and has been the subject of many experimental and theoretical studies primarily because of platinum's strong reactivity toward CO oxidation. The focus has primarily been on adsorption energies, preferred adsorption sites, and catalytic activities. The second system we examined is composed of gold and CO. The gold-CO interaction is much weaker than the platinum-CO interaction and it seems likely that this difference in attraction would lead to differences in any potential surface reconstructions.
112 < %It has also been a good test for new quantum methods because of the difficulty with modeling the preference CO has for the atop binding site \cite{doi:10.1021/jp002302t}.
113 < %Now that dynamic surface events are known to play a role in many catalytic systems, additional research is being done to more closely examine many systems. Recent work by Tao et al. \cite{doi:10.1126/science.1182122} shows that a high-index platinum surface undergoes surface reconstructions when exposed to a small amount of CO, $\sim$~1 torr. Unexpectedly,  the reconstruction was metastable and reverted upon removal of the CO. Work by McCarthy et al. \cite{doi:10.1021/jp302379x} examined temperature programmed desorption's of CO from various platinum samples and saw that species which had large amounts of low-coordinated surface atoms, highly sputtered surfaces or small nano particles, developed a higher temperature desorption peak, suggesting that binding of CO to the platinum surface is strongly dependent on local geometry.
109 > 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 + %Platinum molecular dynamics
117 + %gold molecular dynamics
118  
116
117
118
119   \section{Simulation Methods}
120   The challenge in modeling any solid/gas interface problem is the
121   development of a sufficiently general yet computationally tractable
# Line 130 | Line 130 | Coulomb potential.  For this work, we have been using
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 < Coulomb potential.  For this work, we have been using classical
134 < molecular dynamics with potential energy surfaces that are
135 < specifically tuned for transition metals.  In particular, we use the
136 < EAM potential for Au-Au and Pt-Pt interactions, while modeling the CO
137 < using a model developed by Straub and Karplus for studying
138 < photodissociation of CO from myoglobin.\cite{Straub} The Au-CO and Pt-CO
139 < cross interactions were parameterized as part of this work.
133 > 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    
141   \subsection{Metal-metal interactions}
142 < Many of the potentials used for classical simulation of transition
143 < metals are based on a non-pairwise additive functional of the local
144 < electron density. The embedded atom method (EAM) is perhaps the best
145 < known of these
142 > 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   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
# Line 152 | Line 152 | atomic sites is computed at atom $i$'s location,
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 < atomic sites is computed at atom $i$'s location,
155 > atomic sites is computed at atom $i$'s location,
156   \begin{equation*}
157   \bar{\rho}_i = \sum_{j\neq i} \rho_j(r_{ij})
158   \end{equation*}
# Line 167 | Line 167 | The {\it modified} embedded atom method (MEAM) adds an
167   $\phi_{ij}(r_{ij})$ is an pairwise term that is meant to represent the
168   overlap of the two positively charged cores.  
169  
170 < 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.
170 > % 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  
179 < The EAM, Finnis-Sinclair, MEAM, and the Quantum Sutton-Chen potentials
179 > The EAM, Finnis-Sinclair, and the Quantum Sutton-Chen potentials
180   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}
# Line 187 | Line 187 | parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin19
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 < parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}
190 > parameterized.\cite{Foiles86,PhysRevB.37.3924,Rifkin1992,mishin99:_inter,mishin01:cu,mishin02:b2nial,zope03:tial_ap,mishin05:phase_fe_ni}  
191  
192 < \subsection{CO}
193 < Since one explanation for the strong surface CO repulsion on metals is
192 > \subsection{Carbon Monoxide model}
193 > Since previous explanations for the surface rearrangements center on
194   the large linear quadrupole moment of carbon monoxide, the model
195   chosen for this molecule exhibits this property in an efficient
196   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 along with the interaction
200 < parameters are reproduced in Table 1. The effective dipole moment is still
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{}) and quantum mechanical predictions (WHAT VALUE, Coriana et al?).
203 > to the experimental (-2.63 D~\AA)\cite{QuadrupoleCO} and quantum
204 > mechanical predictions (-2.46 D~\AA)\cite{QuadrupoleCOCalc}.
205   %CO Table
206   \begin{table}[H]
207 < \caption{Positions, $\sigma$, $\epsilon$ and charges for CO geometry and self-interactions\cite{}. Distances are in \AA~, energies are in kcal/mol, and charges are in $e$.}
207 >  \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   \centering
212   \begin{tabular}{| c | c | ccc |}
213   \hline
214 < \multicolumn{5}{|c|}{\textbf{Self-Interactions}}\\
214 > &  {\it z} & $\sigma$ & $\epsilon$ & q\\
215   \hline
216 < &  r & $\sigma$ & $\epsilon$ & q\\
216 > \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   \hline
213 \textbf{C} & 0.0 &  0.0262  & 3.83   &   -0.75 \\
214 \textbf{O} &  1.13 &   0.1591 &   3.12 &   -0.85 \\
215 \textbf{M} & 0.6457 & -  &  -  &    1.6 \\
216 \hline
220   \end{tabular}
221   \end{table}
222  
223 < \subsection{Cross-Interactions}
221 < The cross-interactions between the metals and the CO needed to be parameterized. Previous attempts at parameterization have used two different functional forms to model these interactions\cite{}. A LJ model was fit for the Metal-Carbon interaction and a Morse potential was parameterized for the Metal-Oxygen interaction. The parameter sets chosen, as shown in Table 2, did a suitable job at reproducing experimental adsorption energies as shown in Table 3, but more importantly, they were able to capture the binding site preference. The Pt-CO parameters show a slight preference for the atop binding site which matches the experimental observations.
223 > \subsection{Cross-Interactions between the metals and carbon monoxide}
224  
225 < \subsection{Construction and Equilibration of 557 Metal interfaces}
225 > 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  
245 < Our model systems are composed of approximately 4000 metal atoms cut along the 557 plane. The bare crystals were initially run in the Canonical ensemble at 1000K and 800K respectively for Pt and Au. The difference in temperature is necessary because of the two metals different melting points. Various amounts of CO were added to the simulation box and allowed to absorb to the metal surfaces over a short period of 100 ps. After further thermal relaxation the simulations were all run for at least 40 ns. A subset of the runs that showed interesting effects were allowed to run longer. The system
245 > %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 > 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  
251 + The fits were refined against gas-surface DFT calculations with a
252 + periodic supercell plane-wave basis approach, as implemented in the
253 + {\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 + subsequent steps was less than $10^{-8}$ Ry.  In testing the CO-Au
262 + 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 + 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  
272 < Our model systems are composed of approximately 4000 metal atoms cut along the 557 plane. This cut creates a stepped surface of 6x(111) surface plateaus separated by a single (100) atomic step height. The abundance of low-coordination atoms along the step edges acts as a suitable model for industrial catalysts which tend to have a high concentration of high-index sites. Experimental work has shown that such surfaces are notable for reconstructing upon adsorption\cite{}. Reconstructions have been seen for the Pt 557 surface that involve doubling of the step height and further formation of nano clusters with a triangular motif \cite{doi:10.1126/science.1182122}. To shed insight on whether this reconstruction is limited to the platinum surface, simulations of gold under similar conditions will also be examined. To properly observe these changes, our system size needs to be greater than the periodic phenomena we are examining. The large size and the long time scales needed precluded us from using quantum approaches. Thus, a forcefield describing the Metal-Metal, CO-CO, and CO-Metal interactions was parameterized and the simulations were run using OpenMD\cite{} an open-source molecular dynamics package.
272 > %Hint at future work
273 > 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  
230
231
232
233 %\subsection{System}
234 %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.
235
236
280   %Table  of Parameters
281   %Pt Parameter Set 9
282   %Au Parameter Set 35
283   \begin{table}[H]
284 < \caption{Best fit parameters for metal-adsorbate interactions. Distances are in \AA~and energies are in kcal/mol}
284 >  \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   \centering
289   \begin{tabular}{| c | cc | c | ccc |}
290   \hline
291 < \multicolumn{7}{| c |}{\textbf{Cross-Interactions} }\\
291 > &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ (\AA$^{-1}$) \\
292   \hline
247 &  $\sigma$ & $\epsilon$ & & $r$ & $D$ & $\gamma$ \\
248 \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  
# Line 255 | Line 299 | Our model systems are composed of approximately 4000 m
299  
300   %Table of energies
301   \begin{table}[H]
302 < \caption{Adsorption energies in eV}
302 >  \caption{Adsorption energies for CO on M(111) using the potentials
303 >    described in this work.  All values are in eV}
304   \centering
305   \begin{tabular}{| c | cc |}
306 < \hline
307 < & Calc. & Exp. \\
308 < \hline
309 < \textbf{Pt-CO} & -1.9 & -1.4~\cite{Kelemen}-- -1.9~\cite{Yeo} \\
310 < \textbf{Au-CO} & -0.39 & -0.44~\cite{TPD_Gold_CO} \\
311 < \hline
306 >  \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   \end{tabular}
315   \end{table}
316  
317 + \subsection{Pt(557) and Au(557) metal interfaces}
318  
319 + Our model systems are composed of 3888 Pt atoms and 3384 Au atoms in a
320 + 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  
327 + 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  
273
274
345   % Just results, leave discussion for discussion section
346 + % 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   \section{Results}
353 < \subsection{Diffusion}
354 < While an ideal metallic surface is unlikely to experience much surface diffusion, high-index surfaces have large numbers of low-coordinated atoms which have a much easier time overcoming the energetic barriers limiting diffusion, leading to easier surface reconstructions. Surface movement was divided between the parallel ($\parallel$) and perpendicular ($\perp$) directions relative to the step edge. We were then able to calculate diffusion constants as a function of CO coverage. As can be seen in Table 4, the presence and amount of CO directly affects the diffusion constants of surface platinum atoms. The presence of two 50\% coverage systems is to show how the diffusion process is affected by time. The majority of the systems were run for approximately 50 ns while the half monolayer system been running continuously. The lowered diffusion constant at longer run times will be examined in-depth in the discussion section.
353 > \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 > behavior has been seen to occur on numerous surfaces at varying conditions.\cite{}
358 > 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 > was observed to undergo doubling in the time scales we were able to monitor.
365 > Although, the other Platinum systems tended to show more cumulative lateral movement of
366 > the step edges when compared to the Gold systems. The 50 \% Pt system is highlighted
367 > in figure \ref{fig:reconstruct} at various times along the simulation showing
368 > the evolution of the system.
369  
370 < %Table of Diffusion Constants
371 < %Add gold?M
372 < \begin{table}[H]
373 < \caption{Platinum diffusion constants parallel and perpendicular to the 557 step edge. As the coverage increases, the diffusion constants parallel and  perpendicular to the step edge both initially increase and then decrease slightly. There were two approaches of analysis. One looking at the surface atoms that had moved more than a prescribed amount over the run time and the other looking at all surface atoms. Units are \AA\textsuperscript{2}/ns}
374 < \centering
285 < \begin{tabular}{| c | ccc | ccc | c |}
286 < \hline
287 < \textbf{System Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & \textbf{Atoms} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & \textbf{Atoms} & \textbf{Time (ns)}\\
288 < \hline
289 < &\multicolumn{3}{c|}{\textbf{Mobile}}&\multicolumn{3}{c|}{\textbf{Surface Atoms}} & \\
290 < \hline
291 < 50\% & 3.74 & 0.89 & 497 & 2.05 & 0.49 & 912 & 116 \\
292 < 50\% & 5.81 & 1.59 & 365 & 2.41 & 0.68 & 912 & 46   \\
293 < 33\% & 6.73 & 2.47 & 332 & 2.51 & 0.93 & 912 & 46   \\
294 < 25\% & 5.38 & 2.04 & 361 & 2.18 & 0.84 & 912 & 46  \\
295 < 5\% & 5.54 & 0.63 & 230 & 1.44 & 0.19 & 912 & 46  \\
296 < 0\% & 3.53 & 0.61 & 282 & 1.11 & 0.22 & 912 & 56  \\
297 < \hline
298 < 50\%-r & 6.91 & 2.00 & 198 & 2.23 & 0.68  & 925 & 25\\
299 < 0\%-r  & 4.73 & 0.27 & 128 & 0.72 & 0.05 & 925 & 43\\
300 < \hline
301 < \end{tabular}
302 < \end{table}
370 > The second reconstruction on the Pt(557) surface observed by Tao involved the
371 > formation of triangular clusters that stretched across the plateau between two step edges.
372 > Neither system, within our simulated time scales, experiences this reconstruction. A constructed
373 > system in which the triangular motifs were constructed on the surface will be explored in future
374 > work and is shown in the supporting information.
375  
376 + \subsection{Dynamics}
377 + While atomistic simulations of stepped surfaces have been performed before \cite{}, they tend to be
378 + performed using Monte Carlo techniques\cite{}. This allows them to efficiently sample the thermodynamic
379 + landscape but at the expense of ignoring the dynamics of the system. Previous work, using STM (?)\cite{},
380 + has been able to visualize the coalescing of steps of (system). The time scale of the image acquisition
381 + provides an upper bounds for the time required for the doubling to actually occur. While statistical treatments
382 + of step edges are adept at analyzing such systems, it is important to remember that the edges are made
383 + up of individual atoms and thus can be examined in numerous ways.
384  
385 + \subsubsection{Transport of surface metal atoms}
386 + The movement of a step edge is a cooperative effect arising from the individual movements of the atoms
387 + making up the step. An ideal metal surface displaying a low index facet (111, 100, 110) is unlikely to
388 + experience much surface diffusion because of the large energetic barrier to lift an atom out of the surface.
389 + For our surfaces, the presence of step edges provide a source for mobile metal atoms. Breaking away
390 + from the step edge is still an energetic penalty around (value) but is much less than lifting the same metal
391 + atom out from the surface and the penalty lowers even further when CO is present in sufficient quantities
392 + on the surface. Once an adatom exists on the surface, its barrier for diffusion is negligible ( < 4 kcal/mole)
393 + and is well able to explore its terrace because both steps act as barriers constraining the area in which
394 + diffusion is allowed. By tracking the mobility of individual metal atoms on the surface we were able to determine
395 + the relative diffusion rates and how varying coverages of CO affected the diffusion constants. Close
396 + observation of the mobile metal atoms showed that they were typically in equilibrium with the
397 + step edges, constantly breaking apart and rejoining. Additionally, at times their motion was concerted and
398 + two or more atoms would be observed moving together across the surfaces. The primary challenge in quantifying
399 + the overall surface mobility is in defining ``mobile" vs. ``static" atoms.
400  
401 + A particle was considered mobile once it had traveled more than 2~\AA~ between saved configurations
402 + of the system (10-100 ps). An atom that was truly mobile would typically travel much greater than this, but
403 + the 2~\AA~ cutoff was to prevent the in place vibrational movement of atoms from being included in the analysis.
404 + Since diffusion on  a surface is strongly affected by local structures, in this case the presence of single and double
405 + layer step edges, the diffusion parallel to the step edges was determined separately from the diffusion perpendicular
406 + to these edges. The parallel and perpendicular diffusion constants are shown in figure \ref{fig:diff}.
407 +
408 + \subsubsection{Double layer formation}
409 + The increased amounts of diffusion on Pt at the higher CO coverages appears to play a role in the
410 + formation of double layers. Seeing as how that was the only system within our observed simulation time
411 + that showed the formation. As mentioned earlier, previous experimental work has given some insight into
412 + the upper bounds of the time required for enough atoms to move around to allow two steps to coalesce\cite{}.
413 + As seen in figure \ref{fig:reconstruct}, the first appearance of a double layer, a nodal site, appears at 19 ns into
414 + the simulation. Within 10 ns, nearly half of the step has formed the double layer and by 86 ns, the complete
415 + layer has formed. From the appearance of the first node to the complete doubling of the layers, only ~65 ns
416 + have elapsed. The other two layers in this simulation form over a period of ---- and ---- ns respectively.
417 +
418 + \begin{figure}[H]
419 + \includegraphics[width=\linewidth]{DiffusionComparison_errorXY_remade.pdf}
420 + \caption{Diffusion constants for mobile surface atoms along directions
421 +  parallel ($\mathbf{D}_{\parallel}$) and perpendicular
422 +  ($\mathbf{D}_{\perp}$) to the 557 step edges as a function of CO
423 +  surface coverage.  Diffusion parallel to the step edge is higher
424 +  than that perpendicular to the edge because of the lower energy
425 +  barrier associated with going from approximately 7 nearest neighbors
426 +  to 5, as compared to the 3 of an adatom. Additionally, the observed
427 +  maximum and subsequent decrease for the Pt system suggests that the
428 +  CO self-interactions are playing a significant role with regards to
429 +  movement of the platinum atoms around and more importantly across
430 +  the surface. }
431 + \label{fig:diff}
432 + \end{figure}
433 +
434 + %Table of Diffusion Constants
435 + %Add gold?M
436 + % \begin{table}[H]
437 + %   \caption{}
438 + %   \centering
439 + % \begin{tabular}{| c | cc | cc | }
440 + %   \hline
441 + %   &\multicolumn{2}{c|}{\textbf{Platinum}}&\multicolumn{2}{c|}{\textbf{Gold}} \\
442 + %   \hline
443 + %   \textbf{Surface Coverage} & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$ & $\mathbf{D}_{\parallel}$ & $\mathbf{D}_{\perp}$  \\
444 + %   \hline
445 + %   50\% & 4.32(2) & 1.185(8)  & 1.72(2) & 0.455(6) \\
446 + %   33\% & 5.18(3)  & 1.999(5)  & 1.95(2) & 0.337(4)   \\
447 + %   25\% & 5.01(2)  & 1.574(4)  & 1.26(3) & 0.377(6) \\
448 + %   5\%   & 3.61(2)  & 0.355(2)  & 1.84(3)  & 0.169(4)  \\
449 + %   0\%   & 3.27(2)  & 0.147(4)  & 1.50(2)  & 0.194(2)   \\
450 + %   \hline
451 + % \end{tabular}
452 + % \end{table}
453 +
454   %Discussion
455   \section{Discussion}
308 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.
456  
457 + Mechanism for restructuring
458 +
459 + There are a number of possible mechanisms to explain the role of
460 + adsorbed CO in restructuring the Pt surface. Quadrupolar repulsion
461 + between adjacent CO molecules adsorbed on the surface is one
462 + possibility.  However, the quadrupole-quadrupole interaction is
463 + short-ranged and is attractive for some orientations.  If the CO
464 + molecules are locked in a specific orientation relative to each other,
465 + this explanation gains some weight.  
466 +
467 + Another possible mechanism for the restructuring is in the
468 + destabilization of strong Pt-Pt interactions by CO adsorbed on surface
469 + Pt atoms.  This could have the effect of increasing surface mobility
470 + of these atoms.  
471 +
472 + Comparing the results from simulation to those reported previously by
473 + Tao et al. the similarities in the platinum and CO system are quite
474 + strong. As shown in figure, the simulated platinum system under a CO
475 + atmosphere will restructure slightly by doubling the terrace
476 + heights. The restructuring appears to occur slowly, one to two
477 + platinum atoms at a time. Looking at individual snapshots, these
478 + adatoms tend to either rise on top of the plateau or break away from
479 + the step edge and then diffuse perpendicularly to the step direction
480 + until reaching another step edge. This combination of growth and decay
481 + of the step edges appears to be in somewhat of a state of dynamic
482 + equilibrium. However, once two previously separated edges meet as
483 + shown in figure 1.B, this point tends to act as a focus or growth
484 + point for the rest of the edge to meet up, akin to that of a
485 + zipper. From the handful of cases where a double layer was formed
486 + during the simulation, measuring from the initial appearance of a
487 + growth point, the double layer tends to be fully formed within
488 + $\sim$~35 ns.
489 +
490   \subsection{Diffusion}
491   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?)
492   \\
493   \\
494   %Evolution of surface
495   \begin{figure}[H]
496 < \includegraphics[scale=0.5]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
497 < \caption{Four snapshots at various times a) 258 ps b) 19 ns c) 31.2 ns d) 86.1 ns. Slight disruption of the surface occurs fairly quickly. However, the doubling of the layers seems to be very dependent on the initial linking of two separate step edges. The focal point in b, appears to be a growth spot for the rest of the double layer.}
496 > \includegraphics[width=\linewidth]{ProgressionOfDoubleLayerFormation_yellowCircle.png}
497 > \caption{The Pt(557) / 50\% CO system at a sequence of times after
498 >  initial exposure to the CO: (a) 258 ps, (b) 19 ns, (c) 31.2 ns, and
499 >  (d) 86.1 ns. Disruption of the 557 step edges occurs quickly.  The
500 >  doubling of the layers appears only after two adjacent step edges
501 >  touch.  The circled spot in (b) nucleated the growth of the double
502 >  step observed in the later configurations.}
503 >  \label{fig:reconstruct}
504   \end{figure}
505  
506  
321
322
507   %Peaks!
508 < \includegraphics[scale=0.25]{doublePeaks_noCO.png}
508 > \begin{figure}[H]
509 > \includegraphics[width=\linewidth]{doublePeaks_noCO.png}
510 > \caption{}
511 > \end{figure}
512 > \begin{figure}[H]
513 > \includegraphics[width=\linewidth]{557_300K_cleanPDF.pdf}
514 > \caption{}
515 > \end{figure}
516   \section{Conclusion}
517  
518  

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