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23   \setlength{\belowcaptionskip}{30 pt}
24  
25   %\renewcommand\citemid{\ } % no comma in optional reference note
26 < \bibpunct{[}{]}{,}{s}{}{;}
27 < \bibliographystyle{aip}
26 > \bibpunct{[}{]}{,}{n}{}{;}
27 > \bibliographystyle{achemso}
28  
29   \begin{document}
30  
# Line 73 | Line 73 | molecules, and is affected by the models used in the s
73   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
74  
75   \section{Introduction}
76 [BACKGROUND FOR INTERFACIAL THERMAL CONDUCTANCE PROBLEM]
76   Interfacial thermal conductance is extensively studied both
77 < experimentally and computationally, and systems with interfaces
78 < present are generally heterogeneous. Although interfaces are commonly
79 < barriers to heat transfer, it has been
80 < reported\cite{doi:10.1021/la904855s} that under specific circustances,
81 < e.g. with certain capping agents present on the surface, interfacial
82 < conductance can be significantly enhanced. However, heat conductance
83 < of molecular and nano-scale interfaces will be affected by the
84 < chemical details of the surface and is challenging to
85 < experimentalist. The lower thermal flux through interfaces is even
87 < more difficult to measure with EMD and forward NEMD simulation
88 < methods. Therefore, developing good simulation methods will be
89 < desirable in order to investigate thermal transport across interfaces.
77 > experimentally and computationally\cite{cahill:793}, due to its
78 > importance in nanoscale science and technology. Reliability of
79 > nanoscale devices depends on their thermal transport
80 > properties. Unlike bulk homogeneous materials, nanoscale materials
81 > features significant presence of interfaces, and these interfaces
82 > could dominate the heat transfer behavior of these
83 > materials. Furthermore, these materials are generally heterogeneous,
84 > which challenges traditional research methods for homogeneous
85 > systems.
86  
87 + Heat conductance of molecular and nano-scale interfaces will be
88 + affected by the chemical details of the surface. Experimentally,
89 + various interfaces have been investigated for their thermal
90 + conductance properties. Wang {\it et al.} studied heat transport
91 + through long-chain hydrocarbon monolayers on gold substrate at
92 + individual molecular level\cite{Wang10082007}; Schmidt {\it et al.}
93 + studied the role of CTAB on thermal transport between gold nanorods
94 + and solvent\cite{doi:10.1021/jp8051888}; Juv\'e {\it et al.} studied
95 + the cooling dynamics, which is controlled by thermal interface
96 + resistence of glass-embedded metal
97 + nanoparticles\cite{PhysRevB.80.195406}. Although interfaces are
98 + commonly barriers for heat transport, Alper {\it et al.} suggested
99 + that specific ligands (capping agents) could completely eliminate this
100 + barrier ($G\rightarrow\infty$)\cite{doi:10.1021/la904855s}.
101 +
102 + Theoretical and computational models have also been used to study the
103 + interfacial thermal transport in order to gain an understanding of
104 + this phenomena at the molecular level. Recently, Hase and coworkers
105 + employed Non-Equilibrium Molecular Dynamics (NEMD) simulations to
106 + study thermal transport from hot Au(111) substrate to a self-assembled
107 + monolayer of alkylthiol with relatively long chain (8-20 carbon
108 + atoms)\cite{hase:2010,hase:2011}. However, ensemble averaged
109 + measurements for heat conductance of interfaces between the capping
110 + monolayer on Au and a solvent phase has yet to be studied.
111 + The comparatively low thermal flux through interfaces is
112 + difficult to measure with Equilibrium MD or forward NEMD simulation
113 + methods. Therefore, the Reverse NEMD (RNEMD) methods would have the
114 + advantage of having this difficult to measure flux known when studying
115 + the thermal transport across interfaces, given that the simulation
116 + methods being able to effectively apply an unphysical flux in
117 + non-homogeneous systems.
118 +
119   Recently, we have developed the Non-Isotropic Velocity Scaling (NIVS)
120   algorithm for RNEMD simulations\cite{kuang:164101}. This algorithm
121   retains the desirable features of RNEMD (conservation of linear
122   momentum and total energy, compatibility with periodic boundary
123   conditions) while establishing true thermal distributions in each of
124 < the two slabs. Furthermore, it allows more effective thermal exchange
125 < between particles of different identities, and thus enables extensive
126 < study of interfacial conductance.
124 > the two slabs. Furthermore, it allows effective thermal exchange
125 > between particles of different identities, and thus makes the study of
126 > interfacial conductance much simpler.
127  
128 + The work presented here deals with the Au(111) surface covered to
129 + varying degrees by butanethiol, a capping agent with short carbon
130 + chain, and solvated with organic solvents of different molecular
131 + properties. Different models were used for both the capping agent and
132 + the solvent force field parameters. Using the NIVS algorithm, the
133 + thermal transport across these interfaces was studied and the
134 + underlying mechanism for this phenomena was investigated.
135 +
136 + [MAY ADD WHY STUDY AU-THIOL SURFACE; CITE SHAOYI JIANG]
137 +
138   \section{Methodology}
139 < \subsection{Algorithm}
140 < [BACKGROUND FOR MD METHODS]
141 < There have been many algorithms for computing thermal conductivity
142 < using molecular dynamics simulations. However, interfacial conductance
143 < is at least an order of magnitude smaller. This would make the
144 < calculation even more difficult for those slowly-converging
145 < equilibrium methods. Imposed-flux non-equilibrium
139 > \subsection{Imposd-Flux Methods in MD Simulations}
140 > For systems with low interfacial conductivity one must have a method
141 > capable of generating relatively small fluxes, compared to those
142 > required for bulk conductivity. This requirement makes the calculation
143 > even more difficult for those slowly-converging equilibrium
144 > methods\cite{Viscardy:2007lq}.
145 > Forward methods impose gradient, but in interfacail conditions it is
146 > not clear what behavior to impose at the boundary...
147 > Imposed-flux reverse non-equilibrium
148   methods\cite{MullerPlathe:1997xw} have the flux set {\it a priori} and
149 < the response of temperature or momentum gradients are easier to
150 < measure than the flux, if unknown, and thus, is a preferable way to
151 < the forward NEMD methods. Although the momentum swapping approach for
152 < flux-imposing can be used for exchanging energy between particles of
153 < different identity, the kinetic energy transfer efficiency is affected
154 < by the mass difference between the particles, which limits its
115 < application on heterogeneous interfacial systems.
149 > the thermal response becomes easier to
150 > measure than the flux. Although M\"{u}ller-Plathe's original momentum
151 > swapping approach can be used for exchanging energy between particles
152 > of different identity, the kinetic energy transfer efficiency is
153 > affected by the mass difference between the particles, which limits
154 > its application on heterogeneous interfacial systems.
155  
156 < The non-isotropic velocity scaling (NIVS)\cite{kuang:164101} approach in
157 < non-equilibrium MD simulations is able to impose relatively large
158 < kinetic energy flux without obvious perturbation to the velocity
159 < distribution of the simulated systems. Furthermore, this approach has
156 > The non-isotropic velocity scaling (NIVS)\cite{kuang:164101} approach to
157 > non-equilibrium MD simulations is able to impose a wide range of
158 > kinetic energy fluxes without obvious perturbation to the velocity
159 > distributions of the simulated systems. Furthermore, this approach has
160   the advantage in heterogeneous interfaces in that kinetic energy flux
161   can be applied between regions of particles of arbitary identity, and
162 < the flux quantity is not restricted by particle mass difference.
162 > the flux will not be restricted by difference in particle mass.
163  
164   The NIVS algorithm scales the velocity vectors in two separate regions
165   of a simulation system with respective diagonal scaling matricies. To
166   determine these scaling factors in the matricies, a set of equations
167   including linear momentum conservation and kinetic energy conservation
168 < constraints and target momentum/energy flux satisfaction is
169 < solved. With the scaling operation applied to the system in a set
170 < frequency, corresponding momentum/temperature gradients can be built,
171 < which can be used for computing transportation properties and other
172 < applications related to momentum/temperature gradients. The NIVS
134 < algorithm conserves momenta and energy and does not depend on an
135 < external thermostat.
168 > constraints and target energy flux satisfaction is solved. With the
169 > scaling operation applied to the system in a set frequency, bulk
170 > temperature gradients can be easily established, and these can be used
171 > for computing thermal conductivities. The NIVS algorithm conserves
172 > momenta and energy and does not depend on an external thermostat.
173  
174   \subsection{Defining Interfacial Thermal Conductivity $G$}
175   For interfaces with a relatively low interfacial conductance, the bulk
# Line 150 | Line 187 | When the interfacial conductance is {\it not} small, t
187    T_\mathrm{cold}\rangle}$ are the average observed temperature of the
188   two separated phases.
189  
190 < When the interfacial conductance is {\it not} small, two ways can be
191 < used to define $G$.
190 > When the interfacial conductance is {\it not} small, there are two
191 > ways to define $G$.
192  
193 < One way is to assume the temperature is discretely different on two
194 < sides of the interface, $G$ can be calculated with the thermal flux
195 < applied $J$ and the maximum temperature difference measured along the
196 < thermal gradient max($\Delta T$), which occurs at the interface, as:
193 > One way is to assume the temperature is discrete on the two sides of
194 > the interface. $G$ can be calculated using the applied thermal flux
195 > $J$ and the maximum temperature difference measured along the thermal
196 > gradient max($\Delta T$), which occurs at the Gibbs deviding surface
197 > (Figure \ref{demoPic}):
198   \begin{equation}
199   G=\frac{J}{\Delta T}
200   \label{discreteG}
201   \end{equation}
202  
203 + \begin{figure}
204 + \includegraphics[width=\linewidth]{method}
205 + \caption{Interfacial conductance can be calculated by applying an
206 +  (unphysical) kinetic energy flux between two slabs, one located
207 +  within the metal and another on the edge of the periodic box.  The
208 +  system responds by forming a thermal response or a gradient.  In
209 +  bulk liquids, this gradient typically has a single slope, but in
210 +  interfacial systems, there are distinct thermal conductivity
211 +  domains.  The interfacial conductance, $G$ is found by measuring the
212 +  temperature gap at the Gibbs dividing surface, or by using second
213 +  derivatives of the thermal profile.}
214 + \label{demoPic}
215 + \end{figure}
216 +
217   The other approach is to assume a continuous temperature profile along
218   the thermal gradient axis (e.g. $z$) and define $G$ at the point where
219   the magnitude of thermal conductivity $\lambda$ change reach its
# Line 177 | Line 229 | difference method and thus calculate $G^\prime$.
229  
230   With the temperature profile obtained from simulations, one is able to
231   approximate the first and second derivatives of $T$ with finite
232 < difference method and thus calculate $G^\prime$.
232 > difference methods and thus calculate $G^\prime$.
233  
234 < In what follows, both definitions are used for calculation and comparison.
234 > In what follows, both definitions have been used for calculation and
235 > are compared in the results.
236  
237 < [IMPOSE G DEFINITION INTO OUR SYSTEMS]
238 < To facilitate the use of the above definitions in calculating $G$ and
239 < $G^\prime$, we have a metal slab with its (111) surfaces perpendicular
240 < to the $z$-axis of our simulation cells. With or withour capping
241 < agents on the surfaces, the metal slab is solvated with organic
189 < solvents, as illustrated in Figure \ref{demoPic}.
237 > To compare the above definitions ($G$ and $G^\prime$), we have modeled
238 > a metal slab with its (111) surfaces perpendicular to the $z$-axis of
239 > our simulation cells. Both with and without capping agents on the
240 > surfaces, the metal slab is solvated with simple organic solvents, as
241 > illustrated in Figure \ref{demoPic}.
242  
243 < \begin{figure}
244 < \includegraphics[width=\linewidth]{demoPic}
245 < \caption{A sample showing how a metal slab has its (111) surface
246 <  covered by capping agent molecules and solvated by hexane.}
247 < \label{demoPic}
248 < \end{figure}
249 <
250 < With a simulation cell setup following the above manner, one is able
199 < to equilibrate the system and impose an unphysical thermal flux
200 < between the liquid and the metal phase with the NIVS algorithm. Under
201 < a stablized thermal gradient induced by periodically applying the
202 < unphysical flux, one is able to obtain a temperature profile and the
203 < physical thermal flux corresponding to it, which equals to the
204 < unphysical flux applied by NIVS. These data enables the evaluation of
205 < the interfacial thermal conductance of a surface. Figure \ref{gradT}
206 < is an example how those stablized thermal gradient can be used to
207 < obtain the 1st and 2nd derivatives of the temperature profile.
243 > With the simulation cell described above, we are able to equilibrate
244 > the system and impose an unphysical thermal flux between the liquid
245 > and the metal phase using the NIVS algorithm. By periodically applying
246 > the unphysical flux, we are able to obtain a temperature profile and
247 > its spatial derivatives. These quantities enable the evaluation of the
248 > interfacial thermal conductance of a surface. Figure \ref{gradT} is an
249 > example how those applied thermal fluxes can be used to obtain the 1st
250 > and 2nd derivatives of the temperature profile.
251  
252   \begin{figure}
253   \includegraphics[width=\linewidth]{gradT}
254 < \caption{The 1st and 2nd derivatives of temperature profile can be
255 <  obtained with finite difference approximation.}
254 > \caption{A sample of Au-butanethiol/hexane interfacial system and the
255 >  temperature profile after a kinetic energy flux is imposed to
256 >  it. The 1st and 2nd derivatives of the temperature profile can be
257 >  obtained with finite difference approximation (lower panel).}
258   \label{gradT}
259   \end{figure}
260  
216 [MAY INCLUDE POWER SPECTRUM PROTOCOL]
217
261   \section{Computational Details}
262   \subsection{Simulation Protocol}
263 < In our simulations, Au is used to construct a metal slab with bare
264 < (111) surface perpendicular to the $z$-axis. Different slab thickness
265 < (layer numbers of Au) are simulated. This metal slab is first
266 < equilibrated under normal pressure (1 atm) and a desired
267 < temperature. After equilibration, butanethiol is used as the capping
268 < agent molecule to cover the bare Au (111) surfaces evenly. The sulfur
269 < atoms in the butanethiol molecules would occupy the three-fold sites
270 < of the surfaces, and the maximal butanethiol capacity on Au surface is
271 < $1/3$ of the total number of surface Au atoms[CITATION]. A series of
272 < different coverage surfaces is investigated in order to study the
273 < relation between coverage and conductance.
263 > The NIVS algorithm has been implemented in our MD simulation code,
264 > OpenMD\cite{Meineke:2005gd,openmd}, and was used for our
265 > simulations. Different slab thickness (layer numbers of Au) were
266 > simulated. Metal slabs were first equilibrated under atmospheric
267 > pressure (1 atm) and a desired temperature (e.g. 200K). After
268 > equilibration, butanethiol capping agents were placed at three-fold
269 > sites on the Au(111) surfaces. The maximum butanethiol capacity on Au
270 > surface is $1/3$ of the total number of surface Au
271 > atoms\cite{vlugt:cpc2007154}. A series of different coverages was
272 > investigated in order to study the relation between coverage and
273 > interfacial conductance.
274  
275 < [COVERAGE DISCRIPTION] However, since the interactions between surface
276 < Au and butanethiol is non-bonded, the capping agent molecules are
277 < allowed to migrate to an empty neighbor three-fold site during a
278 < simulation. Therefore, the initial configuration would not severely
279 < affect the sampling of a variety of configurations of the same
280 < coverage, and the final conductance measurement would be an average
281 < effect of these configurations explored in the simulations. [MAY NEED FIGURES]
275 > The capping agent molecules were allowed to migrate during the
276 > simulations. They distributed themselves uniformly and sampled a
277 > number of three-fold sites throughout out study. Therefore, the
278 > initial configuration would not noticeably affect the sampling of a
279 > variety of configurations of the same coverage, and the final
280 > conductance measurement would be an average effect of these
281 > configurations explored in the simulations. [MAY NEED FIGURES]
282  
283 < After the modified Au-butanethiol surface systems are equilibrated
284 < under canonical ensemble, Packmol\cite{packmol} is used to pack
285 < organic solvent molecules in the previously vacuum part of the
286 < simulation cells, which guarantees that short range repulsive
287 < interactions do not disrupt the simulations. Two solvents are
288 < investigated, one which has little vibrational overlap with the
246 < alkanethiol and plane-like shape (toluene), and one which has similar
247 < vibrational frequencies and chain-like shape ({\it n}-hexane). [MAY
248 < EXPLAIN WHY WE CHOOSE THEM]
283 > After the modified Au-butanethiol surface systems were equilibrated
284 > under canonical ensemble, organic solvent molecules were packed in the
285 > previously empty part of the simulation cells\cite{packmol}. Two
286 > solvents were investigated, one which has little vibrational overlap
287 > with the alkanethiol and a planar shape (toluene), and one which has
288 > similar vibrational frequencies and chain-like shape ({\it n}-hexane).
289  
290 < The spacing filled by solvent molecules, i.e. the gap between
290 > The space filled by solvent molecules, i.e. the gap between
291   periodically repeated Au-butanethiol surfaces should be carefully
292   chosen. A very long length scale for the thermal gradient axis ($z$)
293   may cause excessively hot or cold temperatures in the middle of the
# Line 256 | Line 296 | corresponding spacing is usually $35 \sim 60$\AA.
296   solvent molecules would change the normal behavior of the liquid
297   phase. Therefore, our $N_{solvent}$ values were chosen to ensure that
298   these extreme cases did not happen to our simulations. And the
299 < corresponding spacing is usually $35 \sim 60$\AA.
299 > corresponding spacing is usually $35 \sim 75$\AA.
300  
301   The initial configurations generated by Packmol are further
302   equilibrated with the $x$ and $y$ dimensions fixed, only allowing
# Line 287 | Line 327 | Our simulations include various components. Therefore,
327   \end{equation}
328  
329   \subsection{Force Field Parameters}
330 < Our simulations include various components. Therefore, force field
331 < parameter descriptions are needed for interactions both between the
332 < same type of particles and between particles of different species.
330 > Our simulations include various components. Figure \ref{demoMol}
331 > demonstrates the sites defined for both United-Atom and All-Atom
332 > models of the organic solvent and capping agent molecules in our
333 > simulations. Force field parameter descriptions are needed for
334 > interactions both between the same type of particles and between
335 > particles of different species.
336  
337 + \begin{figure}
338 + \includegraphics[width=\linewidth]{structures}
339 + \caption{Structures of the capping agent and solvents utilized in
340 +  these simulations. The chemically-distinct sites (a-e) are expanded
341 +  in terms of constituent atoms for both United Atom (UA) and All Atom
342 +  (AA) force fields.  Most parameters are from
343 +  Refs. \protect\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} (UA) and
344 +  \protect\cite{OPLSAA} (AA).  Cross-interactions with the Au atoms are given
345 +  in Table \ref{MnM}.}
346 + \label{demoMol}
347 + \end{figure}
348 +
349   The Au-Au interactions in metal lattice slab is described by the
350 < quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The QSC
350 > quantum Sutton-Chen (QSC) formulation\cite{PhysRevB.59.3527}. The QSC
351   potentials include zero-point quantum corrections and are
352   reparametrized for accurate surface energies compared to the
353   Sutton-Chen potentials\cite{Chen90}.
354  
300 Figure [REF] demonstrates how we name our pseudo-atoms of the
301 molecules in our simulations.
302 [FIGURE FOR MOLECULE NOMENCLATURE]
303
355   For both solvent molecules, straight chain {\it n}-hexane and aromatic
356   toluene, United-Atom (UA) and All-Atom (AA) models are used
357   respectively. The TraPPE-UA
358   parameters\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} are used
359 < for our UA solvent molecules. In these models, pseudo-atoms are
360 < located at the carbon centers for alkyl groups. By eliminating
361 < explicit hydrogen atoms, these models are simple and computationally
362 < efficient, while maintains good accuracy. However, the TraPPE-UA for
363 < alkanes is known to predict a lower boiling point than experimental
313 < values. Considering that after an unphysical thermal flux is applied
314 < to a system, the temperature of ``hot'' area in the liquid phase would be
315 < significantly higher than the average, to prevent over heating and
316 < boiling of the liquid phase, the average temperature in our
317 < simulations should be much lower than the liquid boiling point. [MORE DISCUSSION]
318 < For UA-toluene model, rigid body constraints are applied, so that the
319 < benzene ring and the methyl-CRar bond are kept rigid. This would save
320 < computational time.[MORE DETAILS]
359 > for our UA solvent molecules. In these models, sites are located at
360 > the carbon centers for alkyl groups. Bonding interactions, including
361 > bond stretches and bends and torsions, were used for intra-molecular
362 > sites not separated by more than 3 bonds. Otherwise, for non-bonded
363 > interactions, Lennard-Jones potentials are used. [MORE CITATION?]
364  
365 + By eliminating explicit hydrogen atoms, these models are simple and
366 + computationally efficient, while maintains good accuracy. However, the
367 + TraPPE-UA for alkanes is known to predict a lower boiling point than
368 + experimental values. Considering that after an unphysical thermal flux
369 + is applied to a system, the temperature of ``hot'' area in the liquid
370 + phase would be significantly higher than the average, to prevent over
371 + heating and boiling of the liquid phase, the average temperature in
372 + our simulations should be much lower than the liquid boiling point.
373 +
374 + For UA-toluene model, the non-bonded potentials between
375 + inter-molecular sites have a similar Lennard-Jones formulation. For
376 + intra-molecular interactions, considering the stiffness of the benzene
377 + ring, rigid body constraints are applied for further computational
378 + efficiency. All bonds in the benzene ring and between the ring and the
379 + methyl group remain rigid during the progress of simulations.
380 +
381   Besides the TraPPE-UA models, AA models for both organic solvents are
382   included in our studies as well. For hexane, the OPLS-AA\cite{OPLSAA}
383 < force field is used. [MORE DETAILS]
384 < For toluene, the United Force Field developed by Rapp\'{e} {\it et
385 <  al.}\cite{doi:10.1021/ja00051a040} is adopted.[MORE DETAILS]
383 > force field is used. Additional explicit hydrogen sites were
384 > included. Besides bonding and non-bonded site-site interactions,
385 > partial charges and the electrostatic interactions were added to each
386 > CT and HC site. For toluene, the United Force Field developed by
387 > Rapp\'{e} {\it et al.}\cite{doi:10.1021/ja00051a040} is
388 > adopted. Without the rigid body constraints, bonding interactions were
389 > included. For the aromatic ring, improper torsions (inversions) were
390 > added as an extra potential for maintaining the planar shape.
391 > [MORE CITATION?]
392  
393   The capping agent in our simulations, the butanethiol molecules can
394   either use UA or AA model. The TraPPE-UA force fields includes
# Line 332 | Line 397 | Au(111) surfaces, we adopt the S parameters from [CITA
397   parameters for alkyl thiols. However, alkyl thiols adsorbed on Au(111)
398   surfaces do not have the hydrogen atom bonded to sulfur. To adapt this
399   change and derive suitable parameters for butanethiol adsorbed on
400 < Au(111) surfaces, we adopt the S parameters from [CITATION CF VLUGT]
401 < and modify parameters for its neighbor C atom for charge balance in
402 < the molecule. Note that the model choice (UA or AA) of capping agent
403 < can be different from the solvent. Regardless of model choice, the
404 < force field parameters for interactions between capping agent and
405 < solvent can be derived using Lorentz-Berthelot Mixing Rule:
400 > Au(111) surfaces, we adopt the S parameters from Luedtke and
401 > Landman\cite{landman:1998} and modify parameters for its neighbor C
402 > atom for charge balance in the molecule. Note that the model choice
403 > (UA or AA) of capping agent can be different from the
404 > solvent. Regardless of model choice, the force field parameters for
405 > interactions between capping agent and solvent can be derived using
406 > Lorentz-Berthelot Mixing Rule:
407 > \begin{eqnarray}
408 > \sigma_{ij} & = & \frac{1}{2} \left(\sigma_{ii} + \sigma_{jj}\right) \\
409 > \epsilon_{ij} & = & \sqrt{\epsilon_{ii}\epsilon_{jj}}
410 > \end{eqnarray}
411  
342
412   To describe the interactions between metal Au and non-metal capping
413   agent and solvent particles, we refer to an adsorption study of alkyl
414   thiols on gold surfaces by Vlugt {\it et
415    al.}\cite{vlugt:cpc2007154} They fitted an effective Lennard-Jones
416   form of potential parameters for the interaction between Au and
417   pseudo-atoms CH$_x$ and S based on a well-established and widely-used
418 < effective potential of Hautman and Klein[CITATION] for the Au(111)
419 < surface. As our simulations require the gold lattice slab to be
420 < non-rigid so that it could accommodate kinetic energy for thermal
418 > effective potential of Hautman and Klein\cite{hautman:4994} for the
419 > Au(111) surface. As our simulations require the gold lattice slab to
420 > be non-rigid so that it could accommodate kinetic energy for thermal
421   transport study purpose, the pair-wise form of potentials is
422   preferred.
423  
424   Besides, the potentials developed from {\it ab initio} calculations by
425   Leng {\it et al.}\cite{doi:10.1021/jp034405s} are adopted for the
426 < interactions between Au and aromatic C/H atoms in toluene.[MORE DETAILS]
426 > interactions between Au and aromatic C/H atoms in toluene. A set of
427 > pseudo Lennard-Jones parameters were provided for Au in their force
428 > fields. By using the Mixing Rule, this can be used to derive pair-wise
429 > potentials for non-bonded interactions between Au and non-metal sites.
430  
431   However, the Lennard-Jones parameters between Au and other types of
432 < particles in our simulations are not yet well-established. For these
433 < interactions, we attempt to derive their parameters using the Mixing
434 < Rule. To do this, the ``Metal-non-Metal'' (MnM) interaction parameters
435 < for Au is first extracted from the Au-CH$_x$ parameters by applying
436 < the Mixing Rule reversely. Table \ref{MnM} summarizes these ``MnM''
432 > particles, such as All-Atom normal alkanes in our simulations are not
433 > yet well-established. For these interactions, we attempt to derive
434 > their parameters using the Mixing Rule. To do this, Au pseudo
435 > Lennard-Jones parameters for ``Metal-non-Metal'' (MnM) interactions
436 > were first extracted from the Au-CH$_x$ parameters by applying the
437 > Mixing Rule reversely. Table \ref{MnM} summarizes these ``MnM''
438   parameters in our simulations.
439  
440   \begin{table*}
441    \begin{minipage}{\linewidth}
442      \begin{center}
443 <      \caption{Lennard-Jones parameters for Au-non-Metal
444 <        interactions in our simulations.}
445 <      
446 <      \begin{tabular}{ccc}
443 >      \caption{Non-bonded interaction parameters (including cross
444 >        interactions with Au atoms) for both force fields used in this
445 >        work.}      
446 >      \begin{tabular}{lllllll}
447          \hline\hline
448 <        Non-metal atom   & $\sigma$ & $\epsilon$ \\
449 <        (or pseudo-atom) & \AA      & kcal/mol  \\
448 >        & Site  & $\sigma_{ii}$ & $\epsilon_{ii}$ & $q_i$ &
449 >        $\sigma_{Au-i}$ & $\epsilon_{Au-i}$ \\
450 >        & & (\AA) & (kcal/mol) & ($e$) & (\AA) & (kcal/mol) \\
451          \hline
452 <        S    & 2.40   & 8.465   \\
453 <        CH3  & 3.54   & 0.2146  \\
454 <        CH2  & 3.54   & 0.1749  \\
455 <        CT3  & 3.365  & 0.1373  \\
456 <        CT2  & 3.365  & 0.1373  \\
457 <        CTT  & 3.365  & 0.1373  \\
458 <        HC   & 2.865  & 0.09256 \\
459 <        CHar & 3.4625 & 0.1680  \\
460 <        CRar & 3.555  & 0.1604  \\
461 <        CA   & 3.173  & 0.0640  \\
462 <        HA   & 2.746  & 0.0414  \\
452 >        United Atom (UA)
453 >        &CH3  & 3.75  & 0.1947  & -      & 3.54   & 0.2146  \\
454 >        &CH2  & 3.95  & 0.0914  & -      & 3.54   & 0.1749  \\
455 >        &CHar & 3.695 & 0.1003  & -      & 3.4625 & 0.1680  \\
456 >        &CRar & 3.88  & 0.04173 & -      & 3.555  & 0.1604  \\
457 >        \hline
458 >        All Atom (AA)
459 >        &CT3  & 3.50  & 0.066   & -0.18  & 3.365  & 0.1373  \\
460 >        &CT2  & 3.50  & 0.066   & -0.12  & 3.365  & 0.1373  \\
461 >        &CTT  & 3.50  & 0.066   & -0.065 & 3.365  & 0.1373  \\
462 >        &HC   & 2.50  & 0.030   &  0.06  & 2.865  & 0.09256 \\
463 >        &CA   & 3.55  & 0.070   & -0.115 & 3.173  & 0.0640  \\
464 >        &HA   & 2.42  & 0.030   &  0.115 & 2.746  & 0.0414  \\
465 >        \hline
466 >        Both UA and AA
467 >        & S   & 4.45  & 0.25    & -      & 2.40   & 8.465   \\
468          \hline\hline
469        \end{tabular}
470        \label{MnM}
# Line 406 | Line 485 | during equilibrating the liquid phase. Due to the stif
485   results.
486  
487   In some of our simulations, we allowed $L_x$ and $L_y$ to change
488 < during equilibrating the liquid phase. Due to the stiffness of the Au
489 < slab, $L_x$ and $L_y$ would not change noticeably after
490 < equilibration. Although $L_z$ could fluctuate $\sim$1\% after a system
491 < is fully equilibrated in the NPT ensemble, this fluctuation, as well
492 < as those comparably smaller to $L_x$ and $L_y$, would not be magnified
493 < on the calculated $G$'s, as shown in Table \ref{AuThiolHexaneUA}. This
494 < insensivity to $L_i$ fluctuations allows reliable measurement of $G$'s
495 < without the necessity of extremely cautious equilibration process.
488 > during equilibrating the liquid phase. Due to the stiffness of the
489 > crystalline Au structure, $L_x$ and $L_y$ would not change noticeably
490 > after equilibration. Although $L_z$ could fluctuate $\sim$1\% after a
491 > system is fully equilibrated in the NPT ensemble, this fluctuation, as
492 > well as those of $L_x$ and $L_y$ (which is significantly smaller),
493 > would not be magnified on the calculated $G$'s, as shown in Table
494 > \ref{AuThiolHexaneUA}. This insensivity to $L_i$ fluctuations allows
495 > reliable measurement of $G$'s without the necessity of extremely
496 > cautious equilibration process.
497  
498   As stated in our computational details, the spacing filled with
499   solvent molecules can be chosen within a range. This allows some
# Line 440 | Line 520 | $J_z$ is listed in Table \ref{AuThiolHexaneUA} and [RE
520   the thermal flux across the interface. For our simulations, we denote
521   $J_z$ to be positive when the physical thermal flux is from the liquid
522   to metal, and negative vice versa. The $G$'s measured under different
523 < $J_z$ is listed in Table \ref{AuThiolHexaneUA} and [REF]. These
524 < results do not suggest that $G$ is dependent on $J_z$ within this flux
525 < range. The linear response of flux to thermal gradient simplifies our
526 < investigations in that we can rely on $G$ measurement with only a
527 < couple $J_z$'s and do not need to test a large series of fluxes.
523 > $J_z$ is listed in Table \ref{AuThiolHexaneUA} and
524 > \ref{AuThiolToluene}. These results do not suggest that $G$ is
525 > dependent on $J_z$ within this flux range. The linear response of flux
526 > to thermal gradient simplifies our investigations in that we can rely
527 > on $G$ measurement with only a couple $J_z$'s and do not need to test
528 > a large series of fluxes.
529  
449 %ADD MORE TO TABLE
530   \begin{table*}
531    \begin{minipage}{\linewidth}
532      \begin{center}
533        \caption{Computed interfacial thermal conductivity ($G$ and
534          $G^\prime$) values for the 100\% covered Au-butanethiol/hexane
535          interfaces with UA model and different hexane molecule numbers
536 <        at different temperatures using a range of energy fluxes.}
536 >        at different temperatures using a range of energy
537 >        fluxes. Error estimates indicated in parenthesis.}
538        
539 <      \begin{tabular}{cccccccc}
539 >      \begin{tabular}{ccccccc}
540          \hline\hline
541 <        $\langle T\rangle$ & & $L_x$ & $L_y$ & $L_z$ & $J_z$ &
542 <        $G$ & $G^\prime$ \\
543 <        (K) & $N_{hexane}$ & \multicolumn{3}{c}{(\AA)} & (GW/m$^2$) &
541 >        $\langle T\rangle$ & $N_{hexane}$ & Fixed & $\rho_{hexane}$ &
542 >        $J_z$ & $G$ & $G^\prime$ \\
543 >        (K) & & $L_x$ \& $L_y$? & (g/cm$^3$) & (GW/m$^2$) &
544          \multicolumn{2}{c}{(MW/m$^2$/K)} \\
545          \hline
546 <        200 & 266 & 29.86 & 25.80 & 113.1 & -0.96 &
547 <        102()  & 80.0() \\
548 <            & 200 & 29.84 & 25.81 &  93.9 &  1.92 &
549 <        129()  & 87.3() \\
550 <            &     & 29.84 & 25.81 &  95.3 &  1.93 &
551 <        131()  & 77.5() \\
552 <            & 166 & 29.84 & 25.81 &  85.7 &  0.97 &
553 <        115()  & 69.3() \\
554 <            &     &       &       &       &  1.94 &
555 <        125()  & 87.1() \\
556 <        250 & 200 & 29.84 & 25.87 & 106.8 &  0.96 &
557 <        81.8() & 67.0() \\
558 <            & 166 & 29.87 & 25.84 &  94.8 &  0.98 &
559 <        79.0() & 62.9() \\
560 <            &     & 29.84 & 25.85 &  95.0 &  1.44 &
561 <        76.2() & 64.8() \\
546 >        200 & 266 & No  & 0.672 & -0.96 & 102(3)    & 80.0(0.8) \\
547 >            & 200 & Yes & 0.694 &  1.92 & 129(11)   & 87.3(0.3) \\
548 >            &     & Yes & 0.672 &  1.93 & 131(16)   & 78(13)    \\
549 >            &     & No  & 0.688 &  0.96 & 125(16)   & 90.2(15)  \\
550 >            &     &     &       &  1.91 & 139(10)   & 101(10)   \\
551 >            &     &     &       &  2.83 & 141(6)    & 89.9(9.8) \\
552 >            & 166 & Yes & 0.679 &  0.97 & 115(19)   & 69(18)    \\
553 >            &     &     &       &  1.94 & 125(9)    & 87.1(0.2) \\
554 >            &     & No  & 0.681 &  0.97 & 141(30)   & 78(22)    \\
555 >            &     &     &       &  1.92 & 138(4)    & 98.9(9.5) \\
556 >        \hline
557 >        250 & 200 & No  & 0.560 &  0.96 & 75(10)    & 61.8(7.3) \\
558 >            &     &     &       & -0.95 & 49.4(0.3) & 45.7(2.1) \\
559 >            & 166 & Yes & 0.570 &  0.98 & 79.0(3.5) & 62.9(3.0) \\
560 >            &     & No  & 0.569 &  0.97 & 80.3(0.6) & 67(11)    \\
561 >            &     &     &       &  1.44 & 76.2(5.0) & 64.8(3.8) \\
562 >            &     &     &       & -0.95 & 56.4(2.5) & 54.4(1.1) \\
563 >            &     &     &       & -1.85 & 47.8(1.1) & 53.5(1.5) \\
564          \hline\hline
565        \end{tabular}
566        \label{AuThiolHexaneUA}
# Line 493 | Line 576 | butanethiol as well.[MAY NEED FIGURE] And this reduced
576   temperature is higher than 250K. Additionally, the equilibrated liquid
577   hexane density under 250K becomes lower than experimental value. This
578   expanded liquid phase leads to lower contact between hexane and
579 < butanethiol as well.[MAY NEED FIGURE] And this reduced contact would
579 > butanethiol as well.[MAY NEED SLAB DENSITY FIGURE]
580 > And this reduced contact would
581   probably be accountable for a lower interfacial thermal conductance,
582   as shown in Table \ref{AuThiolHexaneUA}.
583  
# Line 508 | Line 592 | in that higher degree of contact could yield increased
592   important role in the thermal transport process across the interface
593   in that higher degree of contact could yield increased conductance.
594  
511 [ADD Lxyz AND ERROR ESTIMATE TO TABLE]
595   \begin{table*}
596    \begin{minipage}{\linewidth}
597      \begin{center}
598        \caption{Computed interfacial thermal conductivity ($G$ and
599          $G^\prime$) values for a 90\% coverage Au-butanethiol/toluene
600          interface at different temperatures using a range of energy
601 <        fluxes.}
601 >        fluxes. Error estimates indicated in parenthesis.}
602        
603 <      \begin{tabular}{cccc}
603 >      \begin{tabular}{ccccc}
604          \hline\hline
605 <        $\langle T\rangle$ & $J_z$ & $G$ & $G^\prime$ \\
606 <        (K) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\
605 >        $\langle T\rangle$ & $\rho_{toluene}$ & $J_z$ & $G$ & $G^\prime$ \\
606 >        (K) & (g/cm$^3$) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\
607          \hline
608 <        200 & -1.86 & 180() & 135() \\
609 <            &  2.15 & 204() & 113() \\
610 <            & -3.93 & 175() & 114() \\
611 <        300 & -1.91 & 143() & 125() \\
612 <            & -4.19 & 134() & 113() \\
608 >        200 & 0.933 &  2.15 & 204(12) & 113(12) \\
609 >            &       & -1.86 & 180(3)  & 135(21) \\
610 >            &       & -3.93 & 176(5)  & 113(12) \\
611 >        \hline
612 >        300 & 0.855 & -1.91 & 143(5)  & 125(2)  \\
613 >            &       & -4.19 & 135(9)  & 113(12) \\
614          \hline\hline
615        \end{tabular}
616        \label{AuThiolToluene}
# Line 558 | Line 642 | above. Our Au-butanethiol/toluene system did not see t
642  
643   However, when the surface is not completely covered by butanethiols,
644   the simulated system is more resistent to the reconstruction
645 < above. Our Au-butanethiol/toluene system did not see this phenomena
646 < even at $<T>\sim$300K. The Au(111) surfaces have a 90\% coverage of
647 < butanethiols and have empty three-fold sites. These empty sites could
648 < help prevent surface reconstruction in that they provide other means
649 < of capping agent relaxation. It is observed that butanethiols can
650 < migrate to their neighbor empty sites during a simulation. Therefore,
651 < we were able to obtain $G$'s for these interfaces even at a relatively
652 < high temperature without being affected by surface reconstructions.
645 > above. Our Au-butanethiol/toluene system had the Au(111) surfaces 90\%
646 > covered by butanethiols, but did not see this above phenomena even at
647 > $\langle T\rangle\sim$300K. The empty three-fold sites not occupied by
648 > capping agents could help prevent surface reconstruction in that they
649 > provide other means of capping agent relaxation. It is observed that
650 > butanethiols can migrate to their neighbor empty sites during a
651 > simulation. Therefore, we were able to obtain $G$'s for these
652 > interfaces even at a relatively high temperature without being
653 > affected by surface reconstructions.
654  
655   \subsection{Influence of Capping Agent Coverage on $G$}
656   To investigate the influence of butanethiol coverage on interfacial
657   thermal conductance, a series of different coverage Au-butanethiol
658   surfaces is prepared and solvated with various organic
659   molecules. These systems are then equilibrated and their interfacial
660 < thermal conductivity are measured with our NIVS algorithm. Table
661 < \ref{tlnUhxnUhxnD} lists these results for direct comparison between
662 < different coverages of butanethiol. To study the isotope effect in
663 < interfacial thermal conductance, deuterated UA-hexane is included as
664 < well.
660 > thermal conductivity are measured with our NIVS algorithm. Figure
661 > \ref{coverage} demonstrates the trend of conductance change with
662 > respect to different coverages of butanethiol. To study the isotope
663 > effect in interfacial thermal conductance, deuterated UA-hexane is
664 > included as well.
665  
666   It turned out that with partial covered butanethiol on the Au(111)
667 < surface, the derivative definition for $G$ (Eq. \ref{derivativeG}) has
668 < difficulty to apply, due to the difficulty in locating the maximum of
669 < change of $\lambda$. Instead, the discrete definition
670 < (Eq. \ref{discreteG}) is easier to apply, as max($\Delta T$) can still
671 < be well-defined. Therefore, $G$'s (not $G^\prime$) are used for this
672 < section.
667 > surface, the derivative definition for $G^\prime$
668 > (Eq. \ref{derivativeG}) was difficult to apply, due to the difficulty
669 > in locating the maximum of change of $\lambda$. Instead, the discrete
670 > definition (Eq. \ref{discreteG}) is easier to apply, as the Gibbs
671 > deviding surface can still be well-defined. Therefore, $G$ (not
672 > $G^\prime$) was used for this section.
673  
674 < From Table \ref{tlnUhxnUhxnD}, one can see the significance of the
674 > From Figure \ref{coverage}, one can see the significance of the
675   presence of capping agents. Even when a fraction of the Au(111)
676   surface sites are covered with butanethiols, the conductivity would
677   see an enhancement by at least a factor of 3. This indicates the
678   important role cappping agent is playing for thermal transport
679 < phenomena on metal/organic solvent surfaces.
679 > phenomena on metal / organic solvent surfaces.
680  
681   Interestingly, as one could observe from our results, the maximum
682   conductance enhancement (largest $G$) happens while the surfaces are
# Line 610 | Line 695 | case, $G$ decrease could not be offset but instead acc
695   would not offset this effect. Eventually, when butanethiol coverage
696   continues to decrease, solvent-capping agent contact actually
697   decreases with the disappearing of butanethiol molecules. In this
698 < case, $G$ decrease could not be offset but instead accelerated.
698 > case, $G$ decrease could not be offset but instead accelerated. [NEED
699 > SNAPSHOT SHOWING THE PHENOMENA]
700  
701   A comparison of the results obtained from differenet organic solvents
702   can also provide useful information of the interfacial thermal
# Line 620 | Line 706 | difference for the results of $G$. [MAY NEED FIGURE]
706   studies, even though eliminating C-H vibration samplings, still have
707   C-C vibrational frequencies different from each other. However, these
708   differences in the infrared range do not seem to produce an observable
709 < difference for the results of $G$. [MAY NEED FIGURE]
709 > difference for the results of $G$. [MAY NEED SPECTRA FIGURE]
710  
711   Furthermore, results for rigid body toluene solvent, as well as other
712   UA-hexane solvents, are reasonable within the general experimental
# Line 629 | Line 715 | trend with those for Au-butanethiol/hexane in that $G$
715   such as Au-thiol/organic solvent.
716  
717   However, results for Au-butanethiol/toluene do not show an identical
718 < trend with those for Au-butanethiol/hexane in that $G$'s remain at
718 > trend with those for Au-butanethiol/hexane in that $G$ remains at
719   approximately the same magnitue when butanethiol coverage differs from
720   25\% to 75\%. This might be rooted in the molecule shape difference
721 < for plane-like toluene and chain-like {\it n}-hexane. Due to this
721 > for planar toluene and chain-like {\it n}-hexane. Due to this
722   difference, toluene molecules have more difficulty in occupying
723   relatively small gaps among capping agents when their coverage is not
724   too low. Therefore, the solvent-capping agent contact may keep
# Line 641 | Line 727 | can see a plateau of $G$ vs. butanethiol coverage in o
727   its effect to the process of interfacial thermal transport. Thus, one
728   can see a plateau of $G$ vs. butanethiol coverage in our results.
729  
730 < [NEED ERROR ESTIMATE, MAY ALSO PUT J HERE]
731 < \begin{table*}
732 <  \begin{minipage}{\linewidth}
733 <    \begin{center}
734 <      \caption{Computed interfacial thermal conductivity ($G$) values
735 <        for the Au-butanethiol/solvent interface with various UA
736 <        models and different capping agent coverages at $\langle
737 <        T\rangle\sim$200K using certain energy flux respectively.}
652 <      
653 <      \begin{tabular}{cccc}
654 <        \hline\hline
655 <        Thiol & \multicolumn{3}{c}{$G$(MW/m$^2$/K)} \\
656 <        coverage (\%) & hexane & hexane(D) & toluene \\
657 <        \hline
658 <        0.0   & 46.5() & 43.9() & 70.1() \\
659 <        25.0  & 151()  & 153()  & 249()  \\
660 <        50.0  & 172()  & 182()  & 214()  \\
661 <        75.0  & 242()  & 229()  & 244()  \\
662 <        88.9  & 178()  & -      & -      \\
663 <        100.0 & 137()  & 153()  & 187()  \\
664 <        \hline\hline
665 <      \end{tabular}
666 <      \label{tlnUhxnUhxnD}
667 <    \end{center}
668 <  \end{minipage}
669 < \end{table*}
730 > \begin{figure}
731 > \includegraphics[width=\linewidth]{coverage}
732 > \caption{Comparison of interfacial thermal conductivity ($G$) values
733 >  for the Au-butanethiol/solvent interface with various UA models and
734 >  different capping agent coverages at $\langle T\rangle\sim$200K
735 >  using certain energy flux respectively.}
736 > \label{coverage}
737 > \end{figure}
738  
739   \subsection{Influence of Chosen Molecule Model on $G$}
740   [MAY COMBINE W MECHANISM STUDY]
# Line 679 | Line 747 | these studies.
747   the previous section. Table \ref{modelTest} summarizes the results of
748   these studies.
749  
682 [MORE DATA; ERROR ESTIMATE]
750   \begin{table*}
751    \begin{minipage}{\linewidth}
752      \begin{center}
# Line 687 | Line 754 | these studies.
754        \caption{Computed interfacial thermal conductivity ($G$ and
755          $G^\prime$) values for interfaces using various models for
756          solvent and capping agent (or without capping agent) at
757 <        $\langle T\rangle\sim$200K.}
757 >        $\langle T\rangle\sim$200K. (D stands for deuterated solvent
758 >        or capping agent molecules; ``Avg.'' denotes results that are
759 >        averages of simulations under different $J_z$'s. Error
760 >        estimates indicated in parenthesis.)}
761        
762 <      \begin{tabular}{ccccc}
762 >      \begin{tabular}{llccc}
763          \hline\hline
764          Butanethiol model & Solvent & $J_z$ & $G$ & $G^\prime$ \\
765          (or bare surface) & model & (GW/m$^2$) &
766          \multicolumn{2}{c}{(MW/m$^2$/K)} \\
767          \hline
768 <        UA    & AA hexane  & 1.94 & 135()  & 129()  \\
769 <              &            & 2.86 & 126()  & 115()  \\
770 <              & AA toluene & 1.89 & 200()  & 149()  \\
771 <        AA    & UA hexane  & 1.94 & 116()  & 129()  \\
772 <              & AA hexane  & 3.76 & 451()  & 378()  \\
773 <              &            & 4.71 & 432()  & 334()  \\
774 <              & AA toluene & 3.79 & 487()  & 290()  \\
775 <        AA(D) & UA hexane  & 1.94 & 158()  & 172()  \\
776 <        bare  & AA hexane  & 0.96 & 31.0() & 29.4() \\
768 >        UA    & UA hexane    & Avg. & 131(9)    & 87(10)    \\
769 >              & UA hexane(D) & 1.95 & 153(5)    & 136(13)   \\
770 >              & AA hexane    & Avg. & 131(6)    & 122(10)   \\
771 >              & UA toluene   & 1.96 & 187(16)   & 151(11)   \\
772 >              & AA toluene   & 1.89 & 200(36)   & 149(53)   \\
773 >        \hline
774 >        AA    & UA hexane    & 1.94 & 116(9)    & 129(8)    \\
775 >              & AA hexane    & Avg. & 442(14)   & 356(31)   \\
776 >              & AA hexane(D) & 1.93 & 222(12)   & 234(54)   \\
777 >              & UA toluene   & 1.98 & 125(25)   & 97(60)    \\
778 >              & AA toluene   & 3.79 & 487(56)   & 290(42)   \\
779 >        \hline
780 >        AA(D) & UA hexane    & 1.94 & 158(25)   & 172(4)    \\
781 >              & AA hexane    & 1.92 & 243(29)   & 191(11)   \\
782 >              & AA toluene   & 1.93 & 364(36)   & 322(67)   \\
783 >        \hline
784 >        bare  & UA hexane    & Avg. & 46.5(3.2) & 49.4(4.5) \\
785 >              & UA hexane(D) & 0.98 & 43.9(4.6) & 43.0(2.0) \\
786 >              & AA hexane    & 0.96 & 31.0(1.4) & 29.4(1.3) \\
787 >              & UA toluene   & 1.99 & 70.1(1.3) & 65.8(0.5) \\
788          \hline\hline
789        \end{tabular}
790        \label{modelTest}
# Line 726 | Line 807 | the upper bond of experimental value range. This is pr
807   interfaces, using AA model for both butanethiol and hexane yields
808   substantially higher conductivity values than using UA model for at
809   least one component of the solvent and capping agent, which exceeds
810 < the upper bond of experimental value range. This is probably due to
811 < the classically treated C-H vibrations in the AA model, which should
812 < not be appreciably populated at normal temperatures. In comparison,
813 < once either the hexanes or the butanethiols are deuterated, one can
814 < see a significantly lower $G$ and $G^\prime$. In either of these
815 < cases, the C-H(D) vibrational overlap between the solvent and the
816 < capping agent is removed. [MAY NEED FIGURE] Conclusively, the
810 > the general range of experimental measurement results. This is
811 > probably due to the classically treated C-H vibrations in the AA
812 > model, which should not be appreciably populated at normal
813 > temperatures. In comparison, once either the hexanes or the
814 > butanethiols are deuterated, one can see a significantly lower $G$ and
815 > $G^\prime$. In either of these cases, the C-H(D) vibrational overlap
816 > between the solvent and the capping agent is removed.
817 > [MAY NEED SPECTRA FIGURE] Conclusively, the
818   improperly treated C-H vibration in the AA model produced
819   over-predicted results accordingly. Compared to the AA model, the UA
820   model yields more reasonable results with higher computational
# Line 740 | Line 822 | measurement results.
822  
823   However, for Au-butanethiol/toluene interfaces, having the AA
824   butanethiol deuterated did not yield a significant change in the
825 < measurement results.
826 < . , so extra degrees of freedom
827 < such as the C-H vibrations could enhance heat exchange between these
828 < two phases and result in a much higher conductivity.
825 > measurement results. Compared to the C-H vibrational overlap between
826 > hexane and butanethiol, both of which have alkyl chains, that overlap
827 > between toluene and butanethiol is not so significant and thus does
828 > not have as much contribution to the ``Intramolecular Vibration
829 > Redistribution''[CITE HASE]. Conversely, extra degrees of freedom such
830 > as the C-H vibrations could yield higher heat exchange rate between
831 > these two phases and result in a much higher conductivity.
832  
748
833   Although the QSC model for Au is known to predict an overly low value
834 < for bulk metal gold conductivity[CITE NIVSRNEMD], our computational
834 > for bulk metal gold conductivity\cite{kuang:164101}, our computational
835   results for $G$ and $G^\prime$ do not seem to be affected by this
836 < drawback of the model for metal. Instead, the modeling of interfacial
837 < thermal transport behavior relies mainly on an accurate description of
838 < the interactions between components occupying the interfaces.
836 > drawback of the model for metal. Instead, our results suggest that the
837 > modeling of interfacial thermal transport behavior relies mainly on
838 > the accuracy of the interaction descriptions between components
839 > occupying the interfaces.
840  
841   \subsection{Mechanism of Interfacial Thermal Conductance Enhancement
842    by Capping Agent}
843 < %OR\subsection{Vibrational spectrum study on conductance mechanism}
843 > [OR: Vibrational Spectrum Study on Conductance Mechanism]
844  
845   [MAY INTRODUCE PROTOCOL IN METHODOLOGY/COMPUTATIONAL DETAIL, EQN'S]
846  
# Line 767 | Line 852 | power spectrum via a Fourier transform.
852   the velocity auto-correlation functions, which is used to construct a
853   power spectrum via a Fourier transform.
854  
855 < The gold surfaces covered by
856 < butanethiol molecules, compared to bare gold surfaces, exhibit an
857 < additional peak observed at a frequency of $\sim$170cm$^{-1}$, which
858 < is attributed to the vibration of the S-Au bond. This vibration
859 < enables efficient thermal transport from surface Au atoms to the
860 < capping agents. Simultaneously, as shown in the lower panel of
861 < Fig. \ref{vibration}, the large overlap of the vibration spectra of
862 < butanethiol and hexane in the all-atom model, including the C-H
863 < vibration, also suggests high thermal exchange efficiency. The
864 < combination of these two effects produces the drastic interfacial
865 < thermal conductance enhancement in the all-atom model.
855 > [MAY RELATE TO HASE'S]
856 > The gold surfaces covered by butanethiol molecules, compared to bare
857 > gold surfaces, exhibit an additional peak observed at the frequency of
858 > $\sim$170cm$^{-1}$, which is attributed to the S-Au bonding
859 > vibration. This vibration enables efficient thermal transport from
860 > surface Au layer to the capping agents.
861 > [MAY PUT IN OTHER SECTION] Simultaneously, as shown in
862 > the lower panel of Fig. \ref{vibration}, the large overlap of the
863 > vibration spectra of butanethiol and hexane in the All-Atom model,
864 > including the C-H vibration, also suggests high thermal exchange
865 > efficiency. The combination of these two effects produces the drastic
866 > interfacial thermal conductance enhancement in the All-Atom model.
867  
868 < [MAY NEED TO CONVERT TO JPEG]
868 > [NEED SEPARATE FIGURE. MAY NEED TO CONVERT TO JPEG]
869   \begin{figure}
870   \includegraphics[width=\linewidth]{vibration}
871   \caption{Vibrational spectra obtained for gold in different
872 <  environments (upper panel) and for Au/thiol/hexane simulation in
787 <  all-atom model (lower panel).}
872 >  environments.}
873   \label{vibration}
874   \end{figure}
875  
876 < [COMPARISON OF TWO G'S; AU SLAB WIDTHS; ETC]
876 > [MAY ADD COMPARISON OF G AND G', AU SLAB WIDTHS, ETC]
877   % The results show that the two definitions used for $G$ yield
878   % comparable values, though $G^\prime$ tends to be smaller.
879  
# Line 800 | Line 885 | gold/liquid interfaces. The acoustic impedance mismatc
885   corresponding thermal gradient and to obtain interfacial thermal
886   conductivities. Our simulations have seen significant conductance
887   enhancement with the presence of capping agent, compared to the bare
888 < gold/liquid interfaces. The acoustic impedance mismatch between the
888 > gold / liquid interfaces. The acoustic impedance mismatch between the
889   metal and the liquid phase is effectively eliminated by proper capping
890   agent. Furthermore, the coverage precentage of the capping agent plays
891   an important role in the interfacial thermal transport process.

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