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# Line 43 | Line 43 | Notre Dame, Indiana 46556}
43   \begin{doublespace}
44  
45   \begin{abstract}
46 <  REPLACE ABSTRACT HERE
47 <  With the Non-Isotropic Velocity Scaling (NIVS) approach to Reverse
48 <  Non-Equilibrium Molecular Dynamics (RNEMD) it is possible to impose
49 <  an unphysical thermal flux between different regions of
50 <  inhomogeneous systems such as solid / liquid interfaces.  We have
51 <  applied NIVS to compute the interfacial thermal conductance at a
52 <  metal / organic solvent interface that has been chemically capped by
53 <  butanethiol molecules.  Our calculations suggest that coupling
54 <  between the metal and liquid phases is enhanced by the capping
55 <  agents, leading to a greatly enhanced conductivity at the interface.
56 <  Specifically, the chemical bond between the metal and the capping
57 <  agent introduces a vibrational overlap that is not present without
58 <  the capping agent, and the overlap between the vibrational spectra
59 <  (metal to cap, cap to solvent) provides a mechanism for rapid
60 <  thermal transport across the interface. Our calculations also
61 <  suggest that this is a non-monotonic function of the fractional
62 <  coverage of the surface, as moderate coverages allow diffusive heat
63 <  transport of solvent molecules that have been in close contact with
64 <  the capping agent.
46 >  We present a new method for introducing stable nonequilibrium
47 >  velocity and temperature gradients in molecular dynamics simulations
48 >  of heterogeneous systems. This method conserves the linear momentum
49 >  and total energy of the system and improves previous Reverse
50 >  Non-Equilibrium Molecular Dynamics (RNEMD) methods and maintains
51 >  thermal velocity distributions. It also avoid thermal anisotropy
52 >  occured in NIVS simulations by using isotropic velocity scaling on
53 >  the molecules in specific regions of a system. To test the method,
54 >  we have computed the thermal conductivity and shear viscosity of
55 >  model liquid systems as well as the interfacial frictions of a
56 >  series of  metal/liquid interfaces.
57  
58   \end{abstract}
59  
# Line 218 | Line 210 | thermal anisotropy when applying a momentum flux.
210   scaling. More importantly, separating the momentum flux imposing from
211   velocity scaling avoids the underlying cause that NIVS produced
212   thermal anisotropy when applying a momentum flux.
221 %NEW METHOD DOESN'T CAUSE UNDESIRED CONCOMITENT MOMENTUM FLUX WHEN
222 %IMPOSING A THERMAL FLUX
213  
214   The advantages of the approach over the original momentum swapping
215   approach lies in its nature to preserve a Gaussian
# Line 228 | Line 218 | section will illustrate this effect.
218   diffusion of the neighboring slabs could no longer remedy this effect,
219   and nonthermal distributions would be observed. Results in later
220   section will illustrate this effect.
231 %NEW METHOD (AND NIVS) HAVE LESS PERTURBATION THAN MOMENTUM SWAPPING
221  
222   \section{Computational Details}
223   The algorithm has been implemented in our MD simulation code,
# Line 242 | Line 231 | $z$ axis of these cells were longer and was used as th
231   \subsection{Simulation Protocols}
232   The systems to be investigated are set up in a orthorhombic simulation
233   cell with periodic boundary conditions in all three dimensions. The
234 < $z$ axis of these cells were longer and was used as the gradient axis
234 > $z$ axis of these cells were longer and was set as the gradient axis
235   of temperature and/or momentum. Thus the cells were divided into $N$
236   slabs along this axis, with various $N$ depending on individual
237   system. The $x$ and $y$ axis were usually of the same length in
# Line 259 | Line 248 | the interfaces be established properly for computation
248  
249   While homogeneous fluid systems can be set up with random
250   configurations, our interfacial systems needs extra steps to ensure
251 < the interfaces be established properly for computations.
252 < [AU(THIOL)ORGANIC SOLVENTS: REFER TO JPCC]
253 < [ICE-WATER REFER TO OTHER REF.S]
251 > the interfaces be established properly for computations. The
252 > preparation and equilibration of butanethiol covered gold (111)
253 > surface and further solvation and equilibration process is described
254 > as in reference \cite{kuang:AuThl}.
255  
256 < Metal slabs of 6 or 11 layers of Au atoms were first equilibrated
257 < under atmospheric pressure (1 atm) and 200K. After equilibration,
258 < butanethiol capping agents were placed at three-fold hollow sites on
259 < the Au(111) surfaces. These sites are either {\it fcc} or {\it
260 <  hcp} sites, although Hase {\it et al.} found that they are
261 < equivalent in a heat transfer process,\cite{hase:2010} so we did not
262 < distinguish between these sites in our study. The maximum butanethiol
263 < capacity on Au surface is $1/3$ of the total number of surface Au
264 < atoms, and the packing forms a $(\sqrt{3}\times\sqrt{3})R30^\circ$
265 < structure\cite{doi:10.1021/ja00008a001,doi:10.1021/cr9801317}. A
266 < series of lower coverages was also prepared by eliminating
267 < butanethiols from the higher coverage surface in a regular manner. The
268 < lower coverages were prepared in order to study the relation between
269 < coverage and interfacial conductance.
270 <
271 < The capping agent molecules were allowed to migrate during the
282 < simulations. They distributed themselves uniformly and sampled a
283 < number of three-fold sites throughout out study. Therefore, the
284 < initial configuration does not noticeably affect the sampling of a
285 < variety of configurations of the same coverage, and the final
286 < conductance measurement would be an average effect of these
287 < configurations explored in the simulations.
288 <
289 < After the modified Au-butanethiol surface systems were equilibrated in
290 < the canonical (NVT) ensemble, organic solvent molecules were packed in
291 < the previously empty part of the simulation cells.\cite{packmol} Two
292 < solvents were investigated, one which has little vibrational overlap
293 < with the alkanethiol and which has a planar shape (toluene), and one
294 < which has similar vibrational frequencies to the capping agent and
295 < chain-like shape ({\it n}-hexane).
256 > As for the ice/liquid water interfaces, the basal surface of ice
257 > lattice was first constructed. Hirsch {\it et
258 >  al.}\cite{doi:10.1021/jp048434u} explored the energetics of ice
259 > lattices with different proton orders. We refer to their results and
260 > choose the configuration of the lowest energy after geometry
261 > optimization as the unit cells of our ice lattices. Although
262 > experimental solid/liquid coexistant temperature near normal pressure
263 > is 273K, Bryk and Haymet's simulations of ice/liquid water interfaces
264 > with different models suggest that for SPC/E, the most stable
265 > interface is observed at 225$\pm$5K. Therefore, all our ice/liquid
266 > water simulations were carried out under 225K. To have extra
267 > protection of the ice lattice during initial equilibration (when the
268 > randomly generated liquid phase configuration could release large
269 > amount of energy in relaxation), a constraint method (REF?) was
270 > adopted until the high energy configuration was relaxed.
271 > [MAY ADD A FIGURE HERE FOR BASAL PLANE, MAY INCLUDE PRISM IF POSSIBLE]
272  
273 < The simulation cells were not particularly extensive along the
274 < $z$-axis, as a very long length scale for the thermal gradient may
275 < cause excessively hot or cold temperatures in the middle of the
276 < solvent region and lead to undesired phenomena such as solvent boiling
277 < or freezing when a thermal flux is applied. Conversely, too few
302 < solvent molecules would change the normal behavior of the liquid
303 < phase. Therefore, our $N_{solvent}$ values were chosen to ensure that
304 < these extreme cases did not happen to our simulations. The spacing
305 < between periodic images of the gold interfaces is $45 \sim 75$\AA in
306 < our simulations.
273 > \subsection{Force Field Parameters}
274 > For comparison of our new method with previous work, we retain our
275 > force field parameters consistent with the results we will compare
276 > with. The Lennard-Jones fluid used here for argon , and reduced unit
277 > results are reported for direct comparison purpose.
278  
279 < The initial configurations generated are further equilibrated with the
280 < $x$ and $y$ dimensions fixed, only allowing the $z$-length scale to
281 < change. This is to ensure that the equilibration of liquid phase does
282 < not affect the metal's crystalline structure. Comparisons were made
312 < with simulations that allowed changes of $L_x$ and $L_y$ during NPT
313 < equilibration. No substantial changes in the box geometry were noticed
314 < in these simulations. After ensuring the liquid phase reaches
315 < equilibrium at atmospheric pressure (1 atm), further equilibration was
316 < carried out under canonical (NVT) and microcanonical (NVE) ensembles.
279 > As for our water simulations, SPC/E model is used throughout this work
280 > for consistency. Previous work for transport properties of SPC/E water
281 > model is available\cite{Bedrov:2000,10.1063/1.3330544,Medina2011} so
282 > that unnecessary repetition of previous methods can be avoided.
283  
284 < After the systems reach equilibrium, NIVS was used to impose an
285 < unphysical thermal flux between the metal and the liquid phases. Most
286 < of our simulations were done under an average temperature of
287 < $\sim$200K. Therefore, thermal flux usually came from the metal to the
288 < liquid so that the liquid has a higher temperature and would not
289 < freeze due to lowered temperatures. After this induced temperature
290 < gradient had stabilized, the temperature profile of the simulation cell
291 < was recorded. To do this, the simulation cell is divided evenly into
292 < $N$ slabs along the $z$-axis. The average temperatures of each slab
293 < are recorded for 1$\sim$2 ns. When the slab width $d$ of each slab is
294 < the same, the derivatives of $T$ with respect to slab number $n$ can
295 < be directly used for $G^\prime$ calculations: \begin{equation}
296 <  G^\prime = |J_z|\Big|\frac{\partial^2 T}{\partial z^2}\Big|
297 <         \Big/\left(\frac{\partial T}{\partial z}\right)^2
298 <         = |J_z|\Big|\frac{1}{d^2}\frac{\partial^2 T}{\partial n^2}\Big|
299 <         \Big/\left(\frac{1}{d}\frac{\partial T}{\partial n}\right)^2
300 <         = |J_z|\Big|\frac{\partial^2 T}{\partial n^2}\Big|
301 <         \Big/\left(\frac{\partial T}{\partial n}\right)^2
302 < \label{derivativeG2}
284 > The Au-Au interaction parameters in all simulations are described by
285 > the quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The
286 > QSC potentials include zero-point quantum corrections and are
287 > reparametrized for accurate surface energies compared to the
288 > Sutton-Chen potentials.\cite{Chen90} For gold/water interfaces, the
289 > Spohr potential was adopted\cite{ISI:000167766600035} to depict
290 > Au-H$_2$O interactions.
291 >
292 > The small organic molecules included in our simulations are the Au
293 > surface capping agent butanethiol and liquid hexane and toluene. The
294 > United-Atom
295 > models\cite{TraPPE-UA.thiols,TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes}
296 > for these components were used in this work for better computational
297 > efficiency, while maintaining good accuracy. We refer readers to our
298 > previous work\cite{kuang:AuThl} for further details of these models,
299 > as well as the interactions between Au and the above organic molecule
300 > components.
301 >
302 > \subsection{Thermal conductivities}
303 > When $\vec{j}_z(\vec{p})$ is set to zero and a target $J_z$ is set to
304 > impose kinetic energy transfer, the method can be used for thermal
305 > conductivity computations. Similar to previous RNEMD methods, we
306 > assume linear response of the temperature gradient with respect to the
307 > thermal flux in general case. And the thermal conductivity ($\lambda$)
308 > can be obtained with the imposed kinetic energy flux and the measured
309 > thermal gradient:
310 > \begin{equation}
311 > J_z = -\lambda \frac{\partial T}{\partial z}
312   \end{equation}
313 < The absolute values in Eq. \ref{derivativeG2} appear because the
314 < direction of the flux $\vec{J}$ is in an opposing direction on either
315 < side of the metal slab.
313 > Like other imposed-flux methods, the energy flux was calculated using
314 > the total non-physical energy transferred (${E_{total}}$) from slab
315 > ``c'' to slab ``h'', which is recorded throughout a simulation, and
316 > the time for data collection $t$:
317 > \begin{equation}
318 > J_z = \frac{E_{total}}{2 t L_x L_y}
319 > \end{equation}
320 > where $L_x$ and $L_y$ denotes the dimensions of the plane in a
321 > simulation cell perpendicular to the thermal gradient, and a factor of
322 > two in the denominator is present for the heat transport occurs in
323 > both $+z$ and $-z$ directions. The temperature gradient
324 > ${\langle\partial T/\partial z\rangle}$ can be obtained by a linear
325 > regression of the temperature profile, which is recorded during a
326 > simulation for each slab in a cell. For Lennard-Jones simulations,
327 > thermal conductivities are reported in reduced units
328 > (${\lambda^*=\lambda \sigma^2 m^{1/2} k_B^{-1}\varepsilon^{-1/2}}$).
329  
330 < All of the above simulation procedures use a time step of 1 fs. Each
331 < equilibration stage took a minimum of 100 ps, although in some cases,
332 < longer equilibration stages were utilized.
330 > \subsection{Shear viscosities}
331 > Alternatively, the method can carry out shear viscosity calculations
332 > by switching off $J_z$. One can specify the vector
333 > $\vec{j}_z(\vec{p})$ by choosing the three components
334 > respectively. For shear viscosity simulations, $j_z(p_z)$ is usually
335 > set to zero. Although for isotropic systems, the direction of
336 > $\vec{j}_z(\vec{p})$ on the $xy$ plane should not matter, the ability
337 > of arbitarily specifying the vector direction in our method provides
338 > convenience in anisotropic simulations.
339  
340 < \subsection{Force Field Parameters}
341 < Our simulations include a number of chemically distinct components.
342 < Figure \ref{demoMol} demonstrates the sites defined for both
343 < United-Atom and All-Atom models of the organic solvent and capping
344 < agents in our simulations. Force field parameters are needed for
345 < interactions both between the same type of particles and between
346 < particles of different species.
347 <
348 < \begin{figure}
349 < \includegraphics[width=\linewidth]{structures}
350 < \caption{Structures of the capping agent and solvents utilized in
351 <  these simulations. The chemically-distinct sites (a-e) are expanded
352 <  in terms of constituent atoms for both United Atom (UA) and All Atom
353 <  (AA) force fields.  Most parameters are from References
354 <  \protect\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes,TraPPE-UA.thiols}
355 <  (UA) and \protect\cite{OPLSAA} (AA). Cross-interactions with the Au
356 <  atoms are given in Table 1 in the supporting information.}
357 < \label{demoMol}
364 < \end{figure}
365 <
366 < The Au-Au interactions in metal lattice slab is described by the
367 < quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The QSC
368 < potentials include zero-point quantum corrections and are
369 < reparametrized for accurate surface energies compared to the
370 < Sutton-Chen potentials.\cite{Chen90}
371 <
372 < For the two solvent molecules, {\it n}-hexane and toluene, two
373 < different atomistic models were utilized. Both solvents were modeled
374 < using United-Atom (UA) and All-Atom (AA) models. The TraPPE-UA
375 < parameters\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} are used
376 < for our UA solvent molecules. In these models, sites are located at
377 < the carbon centers for alkyl groups. Bonding interactions, including
378 < bond stretches and bends and torsions, were used for intra-molecular
379 < sites closer than 3 bonds. For non-bonded interactions, Lennard-Jones
380 < potentials are used.
381 <
382 < By eliminating explicit hydrogen atoms, the TraPPE-UA models are
383 < simple and computationally efficient, while maintaining good accuracy.
384 < However, the TraPPE-UA model for alkanes is known to predict a slightly
385 < lower boiling point than experimental values. This is one of the
386 < reasons we used a lower average temperature (200K) for our
387 < simulations. If heat is transferred to the liquid phase during the
388 < NIVS simulation, the liquid in the hot slab can actually be
389 < substantially warmer than the mean temperature in the simulation. The
390 < lower mean temperatures therefore prevent solvent boiling.
391 <
392 < For UA-toluene, the non-bonded potentials between intermolecular sites
393 < have a similar Lennard-Jones formulation. The toluene molecules were
394 < treated as a single rigid body, so there was no need for
395 < intramolecular interactions (including bonds, bends, or torsions) in
396 < this solvent model.
397 <
398 < Besides the TraPPE-UA models, AA models for both organic solvents are
399 < included in our studies as well. The OPLS-AA\cite{OPLSAA} force fields
400 < were used. For hexane, additional explicit hydrogen sites were
401 < included. Besides bonding and non-bonded site-site interactions,
402 < partial charges and the electrostatic interactions were added to each
403 < CT and HC site. For toluene, a flexible model for the toluene molecule
404 < was utilized which included bond, bend, torsion, and inversion
405 < potentials to enforce ring planarity.
406 <
407 < The butanethiol capping agent in our simulations, were also modeled
408 < with both UA and AA model. The TraPPE-UA force field includes
409 < parameters for thiol molecules\cite{TraPPE-UA.thiols} and are used for
410 < UA butanethiol model in our simulations. The OPLS-AA also provides
411 < parameters for alkyl thiols. However, alkyl thiols adsorbed on Au(111)
412 < surfaces do not have the hydrogen atom bonded to sulfur. To derive
413 < suitable parameters for butanethiol adsorbed on Au(111) surfaces, we
414 < adopt the S parameters from Luedtke and Landman\cite{landman:1998} and
415 < modify the parameters for the CTS atom to maintain charge neutrality
416 < in the molecule.  Note that the model choice (UA or AA) for the capping
417 < agent can be different from the solvent. Regardless of model choice,
418 < the force field parameters for interactions between capping agent and
419 < solvent can be derived using Lorentz-Berthelot Mixing Rule:
420 < \begin{eqnarray}
421 <  \sigma_{ij} & = & \frac{1}{2} \left(\sigma_{ii} + \sigma_{jj}\right) \\
422 <  \epsilon_{ij} & = & \sqrt{\epsilon_{ii}\epsilon_{jj}}
423 < \end{eqnarray}
424 <
425 < To describe the interactions between metal (Au) and non-metal atoms,
426 < we refer to an adsorption study of alkyl thiols on gold surfaces by
427 < Vlugt {\it et al.}\cite{vlugt:cpc2007154} They fitted an effective
428 < Lennard-Jones form of potential parameters for the interaction between
429 < Au and pseudo-atoms CH$_x$ and S based on a well-established and
430 < widely-used effective potential of Hautman and Klein for the Au(111)
431 < surface.\cite{hautman:4994} As our simulations require the gold slab
432 < to be flexible to accommodate thermal excitation, the pair-wise form
433 < of potentials they developed was used for our study.
340 > Similar to thermal conductivity computations, linear response of the
341 > momentum gradient with respect to the shear stress is assumed, and the
342 > shear viscosity ($\eta$) can be obtained with the imposed momentum
343 > flux (e.g. in $x$ direction) and the measured gradient:
344 > \begin{equation}
345 > j_z(p_x) = -\eta \frac{\partial v_x}{\partial z}
346 > \end{equation}
347 > where the flux is similarly defined:
348 > \begin{equation}
349 > j_z(p_x) = \frac{P_x}{2 t L_x L_y}
350 > \end{equation}
351 > with $P_x$ being the total non-physical momentum transferred within
352 > the data collection time. Also, the velocity gradient
353 > ${\langle\partial v_x/\partial z\rangle}$ can be obtained using linear
354 > regression of the $x$ component of the mean velocity, $\langle
355 > v_x\rangle$, in each of the bins. For Lennard-Jones simulations, shear
356 > viscosities are reported in reduced units
357 > (${\eta^*=\eta\sigma^2(\varepsilon m)^{-1/2}}$).
358  
359 < The potentials developed from {\it ab initio} calculations by Leng
360 < {\it et al.}\cite{doi:10.1021/jp034405s} are adopted for the
361 < interactions between Au and aromatic C/H atoms in toluene. However,
362 < the Lennard-Jones parameters between Au and other types of particles,
363 < (e.g. AA alkanes) have not yet been established. For these
364 < interactions, the Lorentz-Berthelot mixing rule can be used to derive
365 < effective single-atom LJ parameters for the metal using the fit values
366 < for toluene. These are then used to construct reasonable mixing
367 < parameters for the interactions between the gold and other atoms.
368 < Table 1 in the supporting information summarizes the
369 < ``metal/non-metal'' parameters utilized in our simulations.
359 > \subsection{Interfacial friction and Slip length}
360 > While the shear stress results in a velocity gradient within bulk
361 > fluid phase, its effect at a solid-liquid interface could vary due to
362 > the interaction strength between the two phases. The interfacial
363 > friction coefficient $\kappa$ is defined to relate the shear stress
364 > (e.g. along $x$-axis) and the relative fluid velocity tangent to the
365 > interface:
366 > \begin{equation}
367 > j_z(p_x)|_{interface} = \kappa\Delta v_x|_{interface}
368 > \end{equation}
369 > Under ``stick'' boundary condition, $\Delta v_x|_{interface}
370 > \rightarrow 0$, which leads to $\kappa\rightarrow\infty$. However, for
371 > ``slip'' boundary condition at the solid-liquid interface, $\kappa$
372 > becomes finite. To characterize the interfacial boundary conditions,
373 > slip length ($\delta$) is defined using $\kappa$ and the shear
374 > viscocity of liquid phase ($\eta$):
375 > \begin{equation}
376 > \delta = \frac{\eta}{\kappa}
377 > \end{equation}
378 > so that $\delta\rightarrow 0$ in the ``no-slip'' boundary condition,
379 > and depicts how ``slippery'' an interface is. Figure \ref{slipLength}
380 > illustrates how this quantity is defined and computed for a
381 > solid-liquid interface. [MAY INCLUDE A SNAPSHOT IN FIGURE]
382  
447 \section{Results}
448 [L-J COMPARED TO RNEMD NIVS; WATER COMPARED TO RNEMD NIVS AND EMD;
449 SLIP BOUNDARY VS STICK BOUNDARY; ICE-WATER INTERFACES]
450
451 There are many factors contributing to the measured interfacial
452 conductance; some of these factors are physically motivated
453 (e.g. coverage of the surface by the capping agent coverage and
454 solvent identity), while some are governed by parameters of the
455 methodology (e.g. applied flux and the formulas used to obtain the
456 conductance). In this section we discuss the major physical and
457 calculational effects on the computed conductivity.
458
459 \subsection{Effects due to capping agent coverage}
460
461 A series of different initial conditions with a range of surface
462 coverages was prepared and solvated with various with both of the
463 solvent molecules. These systems were then equilibrated and their
464 interfacial thermal conductivity was measured with the NIVS
465 algorithm. Figure \ref{coverage} demonstrates the trend of conductance
466 with respect to surface coverage.
467
383   \begin{figure}
384 < \includegraphics[width=\linewidth]{coverage}
385 < \caption{The interfacial thermal conductivity ($G$) has a
386 <  non-monotonic dependence on the degree of surface capping.  This
387 <  data is for the Au(111) / butanethiol / solvent interface with
388 <  various UA force fields at $\langle T\rangle \sim $200K.}
389 < \label{coverage}
384 > \includegraphics[width=\linewidth]{defDelta}
385 > \caption{The slip length $\delta$ can be obtained from a velocity
386 >  profile of a solid-liquid interface simulation. An example of
387 >  Au/hexane interfaces is shown. Calculation for the left side is
388 >  illustrated. The right side is similar to the left side.}
389 > \label{slipLength}
390   \end{figure}
391  
392 < In partially covered surfaces, the derivative definition for
393 < $G^\prime$ (Eq. \ref{derivativeG}) becomes difficult to apply, as the
394 < location of maximum change of $\lambda$ becomes washed out.  The
395 < discrete definition (Eq. \ref{discreteG}) is easier to apply, as the
396 < Gibbs dividing surface is still well-defined. Therefore, $G$ (not
397 < $G^\prime$) was used in this section.
392 > In our method, a shear stress can be applied similar to shear
393 > viscosity computations by applying an unphysical momentum flux
394 > (e.g. $j_z(p_x)$). A corresponding velocity profile can be obtained as
395 > shown in Figure \ref{slipLength}, in which the velocity gradients
396 > within liquid phase and velocity difference at the liquid-solid
397 > interface can be measured respectively. Further calculations and
398 > characterizations of the interface can be carried out using these
399 > data.
400  
401 < From Figure \ref{coverage}, one can see the significance of the
402 < presence of capping agents. When even a small fraction of the Au(111)
403 < surface sites are covered with butanethiols, the conductivity exhibits
404 < an enhancement by at least a factor of 3.  Capping agents are clearly
405 < playing a major role in thermal transport at metal / organic solvent
406 < surfaces.
401 > \section{Results and Discussions}
402 > \subsection{Lennard-Jones fluid}
403 > Our orthorhombic simulation cell of Lennard-Jones fluid has identical
404 > parameters to our previous work\cite{kuang:164101} to facilitate
405 > comparison. Thermal conductivitis and shear viscosities were computed
406 > with the algorithm applied to the simulations. The results of thermal
407 > conductivity are compared with our previous NIVS algorithm. However,
408 > since the NIVS algorithm could produce temperature anisotropy for
409 > shear viscocity computations, these results are instead compared to
410 > the momentum swapping approaches. Table \ref{LJ} lists these
411 > calculations with various fluxes in reduced units.
412  
491 We note a non-monotonic behavior in the interfacial conductance as a
492 function of surface coverage. The maximum conductance (largest $G$)
493 happens when the surfaces are about 75\% covered with butanethiol
494 caps.  The reason for this behavior is not entirely clear.  One
495 explanation is that incomplete butanethiol coverage allows small gaps
496 between butanethiols to form. These gaps can be filled by transient
497 solvent molecules.  These solvent molecules couple very strongly with
498 the hot capping agent molecules near the surface, and can then carry
499 away (diffusively) the excess thermal energy from the surface.
500
501 There appears to be a competition between the conduction of the
502 thermal energy away from the surface by the capping agents (enhanced
503 by greater coverage) and the coupling of the capping agents with the
504 solvent (enhanced by interdigitation at lower coverages).  This
505 competition would lead to the non-monotonic coverage behavior observed
506 here.
507
508 Results for rigid body toluene solvent, as well as the UA hexane, are
509 within the ranges expected from prior experimental
510 work.\cite{Wilson:2002uq,cahill:793,PhysRevB.80.195406} This suggests
511 that explicit hydrogen atoms might not be required for modeling
512 thermal transport in these systems.  C-H vibrational modes do not see
513 significant excited state population at low temperatures, and are not
514 likely to carry lower frequency excitations from the solid layer into
515 the bulk liquid.
516
517 The toluene solvent does not exhibit the same behavior as hexane in
518 that $G$ remains at approximately the same magnitude when the capping
519 coverage increases from 25\% to 75\%.  Toluene, as a rigid planar
520 molecule, cannot occupy the relatively small gaps between the capping
521 agents as easily as the chain-like {\it n}-hexane.  The effect of
522 solvent coupling to the capping agent is therefore weaker in toluene
523 except at the very lowest coverage levels.  This effect counters the
524 coverage-dependent conduction of heat away from the metal surface,
525 leading to a much flatter $G$ vs. coverage trend than is observed in
526 {\it n}-hexane.
527
528 \subsection{Effects due to Solvent \& Solvent Models}
529 In addition to UA solvent and capping agent models, AA models have
530 also been included in our simulations.  In most of this work, the same
531 (UA or AA) model for solvent and capping agent was used, but it is
532 also possible to utilize different models for different components.
533 We have also included isotopic substitutions (Hydrogen to Deuterium)
534 to decrease the explicit vibrational overlap between solvent and
535 capping agent. Table \ref{modelTest} summarizes the results of these
536 studies.
537
413   \begin{table*}
414    \begin{minipage}{\linewidth}
415      \begin{center}
416 +
417 +      \caption{Thermal conductivity ($\lambda^*$) and shear viscosity
418 +        ($\eta^*$) (in reduced units) of a Lennard-Jones fluid at
419 +        ${\langle T^* \rangle = 0.72}$ and ${\rho^* = 0.85}$ computed
420 +        at various momentum fluxes.  The new method yields similar
421 +        results to previous RNEMD methods. All results are reported in
422 +        reduced unit. Uncertainties are indicated in parentheses.}
423        
424 <      \caption{Computed interfacial thermal conductance ($G$ and
543 <        $G^\prime$) values for interfaces using various models for
544 <        solvent and capping agent (or without capping agent) at
545 <        $\langle T\rangle\sim$200K.  Here ``D'' stands for deuterated
546 <        solvent or capping agent molecules. Error estimates are
547 <        indicated in parentheses.}
548 <      
549 <      \begin{tabular}{llccc}
424 >      \begin{tabular}{cccccc}
425          \hline\hline
426 <        Butanethiol model & Solvent & $G$ & $G^\prime$ \\
427 <        (or bare surface) & model & \multicolumn{2}{c}{(MW/m$^2$/K)} \\
426 >        \multicolumn{2}{c}{Momentum Exchange} &
427 >        \multicolumn{2}{c}{$\lambda^*$} &
428 >        \multicolumn{2}{c}{$\eta^*$} \\
429          \hline
430 <        UA    & UA hexane    & 131(9)    & 87(10)    \\
431 <              & UA hexane(D) & 153(5)    & 136(13)   \\
556 <              & AA hexane    & 131(6)    & 122(10)   \\
557 <              & UA toluene   & 187(16)   & 151(11)   \\
558 <              & AA toluene   & 200(36)   & 149(53)   \\
430 >        Swap Interval $t^*$ & Equivalent $J_z^*$ or $j_z^*(p_x)$ &
431 >        NIVS & This work & Swapping & This work \\
432          \hline
433 <        AA    & UA hexane    & 116(9)    & 129(8)    \\
434 <              & AA hexane    & 442(14)   & 356(31)   \\
435 <              & AA hexane(D) & 222(12)   & 234(54)   \\
436 <              & UA toluene   & 125(25)   & 97(60)    \\
437 <              & AA toluene   & 487(56)   & 290(42)   \\
565 <        \hline
566 <        AA(D) & UA hexane    & 158(25)   & 172(4)    \\
567 <              & AA hexane    & 243(29)   & 191(11)   \\
568 <              & AA toluene   & 364(36)   & 322(67)   \\
569 <        \hline
570 <        bare  & UA hexane    & 46.5(3.2) & 49.4(4.5) \\
571 <              & UA hexane(D) & 43.9(4.6) & 43.0(2.0) \\
572 <              & AA hexane    & 31.0(1.4) & 29.4(1.3) \\
573 <              & UA toluene   & 70.1(1.3) & 65.8(0.5) \\
433 >        0.116 & 0.16  & 7.30(0.10) & 6.25(0.23) & 3.57(0.06) & 3.53(0.16)\\
434 >        0.232 & 0.09  & 6.95(0.09) & 8.02(0.56) & 3.64(0.05) & 3.43(0.17)\\
435 >        0.463 & 0.047 & 7.19(0.07) & 6.48(0.15) & 3.52(0.16) & 3.51(0.08)\\
436 >        0.926 & 0.024 & 7.19(0.28) & 7.02(0.13) & 3.72(0.05) & 3.79(0.11)\\
437 >        1.158 & 0.019 & 7.98(0.33) & 7.37(0.23) & 3.42(0.06) & 3.53(0.06)\\
438          \hline\hline
439        \end{tabular}
440 <      \label{modelTest}
440 >      \label{LJ}
441      \end{center}
442    \end{minipage}
443   \end{table*}
444  
445 < To facilitate direct comparison between force fields, systems with the
446 < same capping agent and solvent were prepared with the same length
447 < scales for the simulation cells.
445 > \subsubsection{Thermal conductivity}
446 > Our thermal conductivity calculations with this method yields
447 > comparable results to the previous NIVS algorithm. This indicates that
448 > the thermal gradients rendered using this method are also close to
449 > previous RNEMD methods. Simulations with moderately higher thermal
450 > fluxes tend to yield more reliable thermal gradients and thus avoid
451 > large errors, while overly high thermal fluxes could introduce side
452 > effects such as non-linear temperature gradient response or
453 > inadvertent phase transitions.
454  
455 < On bare metal / solvent surfaces, different force field models for
456 < hexane yield similar results for both $G$ and $G^\prime$, and these
457 < two definitions agree with each other very well. This is primarily an
458 < indicator of weak interactions between the metal and the solvent.
455 > Since the scaling operation is isotropic in this method, one does not
456 > need extra care to ensure temperature isotropy between the $x$, $y$
457 > and $z$ axes, while thermal anisotropy might happen if the criteria
458 > function for choosing scaling coefficients does not perform as
459 > expected. Furthermore, this method avoids inadvertent concomitant
460 > momentum flux when only thermal flux is imposed, which could not be
461 > achieved with swapping or NIVS approaches. The thermal energy exchange
462 > in swapping ($\vec{p}_i$ in slab ``c'' with $\vec{p}_j$ in slab ``h'')
463 > or NIVS (total slab momentum conponemts $P^\alpha$ scaled to $\alpha
464 > P^\alpha$) would not obtain this result unless thermal flux vanishes
465 > (i.e. $\vec{p}_i=\vec{p}_j$ or $\alpha=1$ which are trivial to apply a
466 > thermal flux). In this sense, this method contributes to having
467 > minimal perturbation to a simulation while imposing thermal flux.
468  
469 < For the fully-covered surfaces, the choice of force field for the
470 < capping agent and solvent has a large impact on the calculated values
471 < of $G$ and $G^\prime$.  The AA thiol to AA solvent conductivities are
472 < much larger than their UA to UA counterparts, and these values exceed
473 < the experimental estimates by a large measure.  The AA force field
474 < allows significant energy to go into C-H (or C-D) stretching modes,
475 < and since these modes are high frequency, this non-quantum behavior is
476 < likely responsible for the overestimate of the conductivity.  Compared
477 < to the AA model, the UA model yields more reasonable conductivity
599 < values with much higher computational efficiency.
469 > \subsubsection{Shear viscosity}
470 > Table \ref{LJ} also compares our shear viscosity results with momentum
471 > swapping approach. Our calculations show that our method predicted
472 > similar values for shear viscosities to the momentum swapping
473 > approach, as well as the velocity gradient profiles. Moderately larger
474 > momentum fluxes are helpful to reduce the errors of measured velocity
475 > gradients and thus the final result. However, it is pointed out that
476 > the momentum swapping approach tends to produce nonthermal velocity
477 > distributions.\cite{Maginn:2010}
478  
479 < \subsubsection{Are electronic excitations in the metal important?}
480 < Because they lack electronic excitations, the QSC and related embedded
481 < atom method (EAM) models for gold are known to predict unreasonably
482 < low values for bulk conductivity
483 < ($\lambda$).\cite{kuang:164101,ISI:000207079300006,Clancy:1992} If the
484 < conductance between the phases ($G$) is governed primarily by phonon
485 < excitation (and not electronic degrees of freedom), one would expect a
486 < classical model to capture most of the interfacial thermal
487 < conductance.  Our results for $G$ and $G^\prime$ indicate that this is
610 < indeed the case, and suggest that the modeling of interfacial thermal
611 < transport depends primarily on the description of the interactions
612 < between the various components at the interface.  When the metal is
613 < chemically capped, the primary barrier to thermal conductivity appears
614 < to be the interface between the capping agent and the surrounding
615 < solvent, so the excitations in the metal have little impact on the
616 < value of $G$.
479 > To examine that temperature isotropy holds in simulations using our
480 > method, we measured the three one-dimensional temperatures in each of
481 > the slabs (Figure \ref{tempXyz}). Note that the $x$-dimensional
482 > temperatures were calculated after subtracting the effects from bulk
483 > velocities of the slabs. The one-dimensional temperature profiles
484 > showed no observable difference between the three dimensions. This
485 > ensures that isotropic scaling automatically preserves temperature
486 > isotropy and that our method is useful in shear viscosity
487 > computations.
488  
489 < \subsection{Effects due to methodology and simulation parameters}
489 > \begin{figure}
490 > \includegraphics[width=\linewidth]{tempXyz}
491 > \caption{Unlike the previous NIVS algorithm, the new method does not
492 >  produce a thermal anisotropy. No temperature difference between
493 >  different dimensions were observed beyond the magnitude of the error
494 >  bars. Note that the two ``hotter'' regions are caused by the shear
495 >  stress, as reported by Tenney and Maginn\cite{Maginn:2010}, but not
496 >  an effect that only observed in our methods.}
497 > \label{tempXyz}
498 > \end{figure}
499  
500 < We have varied the parameters of the simulations in order to
501 < investigate how these factors would affect the computation of $G$.  Of
502 < particular interest are: 1) the length scale for the applied thermal
503 < gradient (modified by increasing the amount of solvent in the system),
504 < 2) the sign and magnitude of the applied thermal flux, 3) the average
505 < temperature of the simulation (which alters the solvent density during
506 < equilibration), and 4) the definition of the interfacial conductance
507 < (Eqs. (\ref{discreteG}) or (\ref{derivativeG})) used in the
508 < calculation.
500 > Furthermore, the velocity distribution profiles are tested by imposing
501 > a large shear stress into the simulations. Figure \ref{vDist}
502 > demonstrates how our method is able to maintain thermal velocity
503 > distributions against the momentum swapping approach even under large
504 > imposed fluxes. Previous swapping methods tend to deplete particles of
505 > positive velocities in the negative velocity slab (``c'') and vice
506 > versa in slab ``h'', where the distributions leave a notch. This
507 > problematic profiles become significant when the imposed-flux becomes
508 > larger and diffusions from neighboring slabs could not offset the
509 > depletion. Simutaneously, abnormal peaks appear corresponding to
510 > excessive velocity swapped from the other slab. This nonthermal
511 > distributions limit applications of the swapping approach in shear
512 > stress simulations. Our method avoids the above problematic
513 > distributions by altering the means of applying momentum
514 > fluxes. Comparatively, velocity distributions recorded from
515 > simulations with our method is so close to the ideal thermal
516 > prediction that no observable difference is shown in Figure
517 > \ref{vDist}. Conclusively, our method avoids problems happened in
518 > previous RNEMD methods and provides a useful means for shear viscosity
519 > computations.
520  
521 < Systems of different lengths were prepared by altering the number of
522 < solvent molecules and extending the length of the box along the $z$
523 < axis to accomodate the extra solvent.  Equilibration at the same
524 < temperature and pressure conditions led to nearly identical surface
525 < areas ($L_x$ and $L_y$) available to the metal and capping agent,
526 < while the extra solvent served mainly to lengthen the axis that was
527 < used to apply the thermal flux.  For a given value of the applied
528 < flux, the different $z$ length scale has only a weak effect on the
529 < computed conductivities.
521 > \begin{figure}
522 > \includegraphics[width=\linewidth]{velDist}
523 > \caption{Velocity distributions that develop under the swapping and
524 >  our methods at high flux. These distributions were obtained from
525 >  Lennard-Jones simulations with $j_z^*(p_x)\sim 0.4$ (equivalent to a
526 >  swapping interval of 20 time steps). This is a relatively large flux
527 >  to demonstrate the nonthermal distributions that develop under the
528 >  swapping method. Distributions produced by our method are very close
529 >  to the ideal thermal situations.}
530 > \label{vDist}
531 > \end{figure}
532  
533 < \subsubsection{Effects of applied flux}
534 < The NIVS algorithm allows changes in both the sign and magnitude of
535 < the applied flux.  It is possible to reverse the direction of heat
536 < flow simply by changing the sign of the flux, and thermal gradients
537 < which would be difficult to obtain experimentally ($5$ K/\AA) can be
538 < easily simulated.  However, the magnitude of the applied flux is not
539 < arbitrary if one aims to obtain a stable and reliable thermal gradient.
540 < A temperature gradient can be lost in the noise if $|J_z|$ is too
541 < small, and excessive $|J_z|$ values can cause phase transitions if the
542 < extremes of the simulation cell become widely separated in
543 < temperature.  Also, if $|J_z|$ is too large for the bulk conductivity
651 < of the materials, the thermal gradient will never reach a stable
652 < state.  
533 > \subsection{Bulk SPC/E water}
534 > Since our method was in good performance of thermal conductivity and
535 > shear viscosity computations for simple Lennard-Jones fluid, we extend
536 > our applications of these simulations to complex fluid like SPC/E
537 > water model. A simulation cell with 1000 molecules was set up in the
538 > same manner as in \cite{kuang:164101}. For thermal conductivity
539 > simulations, measurements were taken to compare with previous RNEMD
540 > methods; for shear viscosity computations, simulations were run under
541 > a series of temperatures (with corresponding pressure relaxation using
542 > the isobaric-isothermal ensemble[CITE NIVS REF 32]), and results were
543 > compared to available data from Equilibrium MD methods[CITATIONS].
544  
545 < Within a reasonable range of $J_z$ values, we were able to study how
546 < $G$ changes as a function of this flux.  In what follows, we use
547 < positive $J_z$ values to denote the case where energy is being
548 < transferred by the method from the metal phase and into the liquid.
549 < The resulting gradient therefore has a higher temperature in the
550 < liquid phase.  Negative flux values reverse this transfer, and result
551 < in higher temperature metal phases.  The conductance measured under
552 < different applied $J_z$ values is listed in Tables 2 and 3 in the
662 < supporting information. These results do not indicate that $G$ depends
663 < strongly on $J_z$ within this flux range. The linear response of flux
664 < to thermal gradient simplifies our investigations in that we can rely
665 < on $G$ measurement with only a small number $J_z$ values.
545 > \subsubsection{Thermal conductivity}
546 > Table \ref{spceThermal} summarizes our thermal conductivity
547 > computations under different temperatures and thermal gradients, in
548 > comparison to the previous NIVS results\cite{kuang:164101} and
549 > experimental measurements\cite{WagnerKruse}. Note that no appreciable
550 > drift of total system energy or temperature was observed when our
551 > method is applied, which indicates that our algorithm conserves total
552 > energy even for systems involving electrostatic interactions.
553  
554 < The sign of $J_z$ is a different matter, however, as this can alter
555 < the temperature on the two sides of the interface. The average
556 < temperature values reported are for the entire system, and not for the
557 < liquid phase, so at a given $\langle T \rangle$, the system with
558 < positive $J_z$ has a warmer liquid phase.  This means that if the
559 < liquid carries thermal energy via diffusive transport, {\it positive}
560 < $J_z$ values will result in increased molecular motion on the liquid
674 < side of the interface, and this will increase the measured
675 < conductivity.
554 > Measurements using our method established similar temperature
555 > gradients to the previous NIVS method. Our simulation results are in
556 > good agreement with those from previous simulations. And both methods
557 > yield values in reasonable agreement with experimental
558 > values. Simulations using moderately higher thermal gradient or those
559 > with longer gradient axis ($z$) for measurement seem to have better
560 > accuracy, from our results.
561  
562 < \subsubsection{Effects due to average temperature}
562 > \begin{table*}
563 >  \begin{minipage}{\linewidth}
564 >    \begin{center}
565 >      
566 >      \caption{Thermal conductivity of SPC/E water under various
567 >        imposed thermal gradients. Uncertainties are indicated in
568 >        parentheses.}
569 >      
570 >      \begin{tabular}{ccccc}
571 >        \hline\hline
572 >        $\langle T\rangle$ & $\langle dT/dz\rangle$ & \multicolumn{3}{c}
573 >        {$\lambda (\mathrm{W m}^{-1} \mathrm{K}^{-1})$} \\
574 >        (K) & (K/\AA) & This work & Previous NIVS\cite{kuang:164101} &
575 >        Experiment\cite{WagnerKruse} \\
576 >        \hline
577 >        300 & 0.8 & 0.815(0.027)     & 0.770(0.008) & 0.61 \\
578 >        318 & 0.8 & 0.801(0.024)     & 0.750(0.032) & 0.64 \\
579 >            & 1.6 & 0.766(0.007)     & 0.778(0.019) &      \\
580 >            & 0.8 & 0.786(0.009)\footnote{Simulation with $L_z$
581 >                     twice as long.} &              &      \\
582 >        \hline\hline
583 >      \end{tabular}
584 >      \label{spceThermal}
585 >    \end{center}
586 >  \end{minipage}
587 > \end{table*}
588  
589 < We also studied the effect of average system temperature on the
590 < interfacial conductance.  The simulations are first equilibrated in
591 < the NPT ensemble at 1 atm.  The TraPPE-UA model for hexane tends to
592 < predict a lower boiling point (and liquid state density) than
593 < experiments.  This lower-density liquid phase leads to reduced contact
594 < between the hexane and butanethiol, and this accounts for our
595 < observation of lower conductance at higher temperatures.  In raising
596 < the average temperature from 200K to 250K, the density drop of
597 < $\sim$20\% in the solvent phase leads to a $\sim$40\% drop in the
598 < conductance.
589 > \subsubsection{Shear viscosity}
590 > The improvement our method achieves for shear viscosity computations
591 > enables us to apply it on SPC/E water models. The series of
592 > temperatures under which our shear viscosity calculations were carried
593 > out covers the liquid range under normal pressure. Our simulations
594 > predict a similar trend of $\eta$ vs. $T$ to EMD results we refer to
595 > (Table \ref{spceShear}). Considering subtlties such as temperature or
596 > pressure/density errors in these two series of measurements, our
597 > results show no significant difference from those with EMD
598 > methods. Since each value reported using our method takes only one
599 > single trajectory of simulation, instead of average from many
600 > trajectories when using EMD, our method provides an effective means
601 > for shear viscosity computations.
602  
603 < Similar behavior is observed in the TraPPE-UA model for toluene,
604 < although this model has better agreement with the experimental
605 < densities of toluene.  The expansion of the toluene liquid phase is
606 < not as significant as that of the hexane (8.3\% over 100K), and this
607 < limits the effect to $\sim$20\% drop in thermal conductivity.
603 > \begin{table*}
604 >  \begin{minipage}{\linewidth}
605 >    \begin{center}
606 >      
607 >      \caption{Computed shear viscosity of SPC/E water under different
608 >        temperatures. Results are compared to those obtained with EMD
609 >        method[CITATION]. Uncertainties are indicated in parentheses.}
610 >      
611 >      \begin{tabular}{cccc}
612 >        \hline\hline
613 >        $T$ & $\partial v_x/\partial z$ & \multicolumn{2}{c}
614 >        {$\eta (\mathrm{mPa}\cdot\mathrm{s})$} \\
615 >        (K) & (10$^{10}$s$^{-1}$) & This work & Previous simulations[CITATION]\\
616 >        \hline
617 >        273 &  & 1.218(0.004) &  \\
618 >            &  & 1.140(0.012) &  \\
619 >        303 &  & 0.646(0.008) &  \\
620 >        318 &  & 0.536(0.007) &  \\
621 >            &  & 0.510(0.007) &  \\
622 >            &  &  &  \\
623 >        333 &  & 0.428(0.002) &  \\
624 >        363 &  & 0.279(0.014) &  \\
625 >            &  & 0.306(0.001) &  \\
626 >        \hline\hline
627 >      \end{tabular}
628 >      \label{spceShear}
629 >    \end{center}
630 >  \end{minipage}
631 > \end{table*}
632  
633 < Although we have not mapped out the behavior at a large number of
634 < temperatures, is clear that there will be a strong temperature
635 < dependence in the interfacial conductance when the physical properties
636 < of one side of the interface (notably the density) change rapidly as a
637 < function of temperature.
633 > [MAY COMBINE JZPX AND JZKE TO RUN ONE JOB BUT GET ETA=F(T)]
634 > [PUT RESULTS AND FIGURE HERE IF IT WORKS]
635 > \subsection{Interfacial frictions and slip lengths}
636 > An attractive aspect of our method is the ability to apply momentum
637 > and/or thermal flux in nonhomogeneous systems, where molecules of
638 > different identities (or phases) are segregated in different
639 > regions. We have previously studied the interfacial thermal transport
640 > of a series of metal gold-liquid
641 > surfaces\cite{kuang:164101,kuang:AuThl}, and attemptions have been
642 > made to investigate the relationship between this phenomenon and the
643 > interfacial frictions.
644  
645 < Besides the lower interfacial thermal conductance, surfaces at
646 < relatively high temperatures are susceptible to reconstructions,
647 < particularly when butanethiols fully cover the Au(111) surface. These
648 < reconstructions include surface Au atoms which migrate outward to the
649 < S atom layer, and butanethiol molecules which embed into the surface
650 < Au layer. The driving force for this behavior is the strong Au-S
651 < interactions which are modeled here with a deep Lennard-Jones
652 < potential. This phenomenon agrees with reconstructions that have been
653 < experimentally
654 < observed.\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}.  Vlugt
655 < {\it et al.} kept their Au(111) slab rigid so that their simulations
656 < could reach 300K without surface
714 < reconstructions.\cite{vlugt:cpc2007154} Since surface reconstructions
715 < blur the interface, the measurement of $G$ becomes more difficult to
716 < conduct at higher temperatures.  For this reason, most of our
717 < measurements are undertaken at $\langle T\rangle\sim$200K where
718 < reconstruction is minimized.
719 <
720 < However, when the surface is not completely covered by butanethiols,
721 < the simulated system appears to be more resistent to the
722 < reconstruction. Our Au / butanethiol / toluene system had the Au(111)
723 < surfaces 90\% covered by butanethiols, but did not see this above
724 < phenomena even at $\langle T\rangle\sim$300K.  That said, we did
725 < observe butanethiols migrating to neighboring three-fold sites during
726 < a simulation.  Since the interface persisted in these simulations, we
727 < were able to obtain $G$'s for these interfaces even at a relatively
728 < high temperature without being affected by surface reconstructions.
645 > Table \ref{etaKappaDelta} includes these computations and previous
646 > calculations of corresponding interfacial thermal conductance. For
647 > bare Au(111) surfaces, slip boundary conditions were observed for both
648 > organic and aqueous liquid phases, corresponding to previously
649 > computed low interfacial thermal conductance. Instead, the butanethiol
650 > covered Au(111) surface appeared to be sticky to the organic liquid
651 > molecules in our simulations. We have reported conductance enhancement
652 > effect for this surface capping agent,\cite{kuang:AuThl} and these
653 > observations have a qualitative agreement with the thermal conductance
654 > results. This agreement also supports discussions on the relationship
655 > between surface wetting and slip effect and thermal conductance of the
656 > interface.[CITE BARRAT, GARDE]
657  
658 < \section{Discussion}
659 < [COMBINE W. RESULTS]
660 < The primary result of this work is that the capping agent acts as an
661 < efficient thermal coupler between solid and solvent phases.  One of
662 < the ways the capping agent can carry out this role is to down-shift
663 < between the phonon vibrations in the solid (which carry the heat from
664 < the gold) and the molecular vibrations in the liquid (which carry some
665 < of the heat in the solvent).
658 > \begin{table*}
659 >  \begin{minipage}{\linewidth}
660 >    \begin{center}
661 >      
662 >      \caption{Computed interfacial friction coefficient values for
663 >        interfaces with various components for liquid and solid
664 >        phase. Error estimates are indicated in parentheses.}
665 >      
666 >      \begin{tabular}{llcccccc}
667 >        \hline\hline
668 >        Solid & Liquid & $T$ & $j_z(p_x)$ & $\eta_{liquid}$ & $\kappa$
669 >        & $\delta$ & $G$\footnote{References \cite{kuang:AuThl} and
670 >          \cite{kuang:164101}.} \\
671 >        surface & molecules & K & MPa & mPa$\cdot$s & Pa$\cdot$s/m & nm
672 >        & MW/m$^2$/K \\
673 >        \hline
674 >        Au(111) & hexane & 200 & 1.08 & 0.20() & 5.3$\times$10$^4$() &
675 >        3.7 & 46.5 \\
676 >                &        &     & 2.15 & 0.14() & 5.3$\times$10$^4$() &
677 >        2.7 &      \\
678 >        Au-SC$_4$H$_9$ & hexane & 200 & 2.16 & 0.29() & $\infty$ & 0 &
679 >        131 \\
680 >                       &        &     & 5.39 & 0.32() & $\infty$ & 0 &
681 >            \\
682 >        \hline
683 >        Au(111) & toluene & 200 & 1.08 & 0.72() & 1.?$\times$10$^5$() &
684 >        4.6 & 70.1 \\
685 >                &         &     & 2.16 & 0.54() & 1.?$\times$10$^5$() &
686 >        4.9 &      \\
687 >        Au-SC$_4$H$_9$ & toluene & 200 & 5.39 & 0.98() & $\infty$ & 0
688 >        & 187 \\
689 >                       &         &     & 10.8 & 0.99() & $\infty$ & 0
690 >        &     \\
691 >        \hline
692 >        Au(111) & water & 300 & 1.08 & 0.40() & 1.9$\times$10$^4$() &
693 >        20.7 & 1.65 \\
694 >                &       &     & 2.16 & 0.79() & 1.9$\times$10$^4$() &
695 >        41.9 &      \\
696 >        \hline
697 >        ice(basal) & water & 225 & 19.4 & 15.8() & $\infty$ & 0 & \\
698 >        \hline\hline
699 >      \end{tabular}
700 >      \label{etaKappaDelta}
701 >    \end{center}
702 >  \end{minipage}
703 > \end{table*}
704  
705 < To investigate the mechanism of interfacial thermal conductance, the
706 < vibrational power spectrum was computed. Power spectra were taken for
707 < individual components in different simulations. To obtain these
708 < spectra, simulations were run after equilibration in the
709 < microcanonical (NVE) ensemble and without a thermal
710 < gradient. Snapshots of configurations were collected at a frequency
711 < that is higher than that of the fastest vibrations occurring in the
712 < simulations. With these configurations, the velocity auto-correlation
713 < functions can be computed:
748 < \begin{equation}
749 < C_A (t) = \langle\vec{v}_A (t)\cdot\vec{v}_A (0)\rangle
750 < \label{vCorr}
751 < \end{equation}
752 < The power spectrum is constructed via a Fourier transform of the
753 < symmetrized velocity autocorrelation function,
754 < \begin{equation}
755 <  \hat{f}(\omega) =
756 <  \int_{-\infty}^{\infty} C_A (t) e^{-2\pi it\omega}\,dt
757 < \label{fourier}
758 < \end{equation}
705 > An interesting effect alongside the surface friction change is
706 > observed on the shear viscosity of liquids in the regions close to the
707 > solid surface. Note that $\eta$ measured near a ``slip'' surface tends
708 > to be smaller than that near a ``stick'' surface. This suggests that
709 > an interface could affect the dynamic properties on its neighbor
710 > regions. It is known that diffusions of solid particles in liquid
711 > phase is affected by their surface conditions (stick or slip
712 > boundary).[CITE SCHMIDT AND SKINNER] Our observations could provide
713 > support to this phenomenon.
714  
715 < \subsection{The role of specific vibrations}
716 < The vibrational spectra for gold slabs in different environments are
717 < shown as in Figure \ref{specAu}. Regardless of the presence of
718 < solvent, the gold surfaces which are covered by butanethiol molecules
719 < exhibit an additional peak observed at a frequency of
720 < $\sim$165cm$^{-1}$.  We attribute this peak to the S-Au bonding
721 < vibration. This vibration enables efficient thermal coupling of the
722 < surface Au layer to the capping agents. Therefore, in our simulations,
723 < the Au / S interfaces do not appear to be the primary barrier to
724 < thermal transport when compared with the butanethiol / solvent
770 < interfaces.  This supports the results of Luo {\it et
771 <  al.}\cite{Luo20101}, who reported $G$ for Au-SAM junctions roughly
772 < twice as large as what we have computed for the thiol-liquid
773 < interfaces.
715 > In addition to these previously studied interfaces, we attempt to
716 > construct ice-water interfaces and the basal plane of ice lattice was
717 > first studied. In contrast to the Au(111)/water interface, where the
718 > friction coefficient is relatively small and large slip effect
719 > presents, the ice/liquid water interface demonstrates strong
720 > interactions and appears to be sticky. The supercooled liquid phase is
721 > an order of magnitude viscous than measurements in previous
722 > section. It would be of interst to investigate the effect of different
723 > ice lattice planes (such as prism surface) on interfacial friction and
724 > corresponding liquid viscosity.
725  
775 \begin{figure}
776 \includegraphics[width=\linewidth]{vibration}
777 \caption{The vibrational power spectrum for thiol-capped gold has an
778  additional vibrational peak at $\sim $165cm$^{-1}$.  Bare gold
779  surfaces (both with and without a solvent over-layer) are missing
780  this peak.   A similar peak at  $\sim $165cm$^{-1}$ also appears in
781  the vibrational power spectrum for the butanethiol capping agents.}
782 \label{specAu}
783 \end{figure}
784
785 Also in this figure, we show the vibrational power spectrum for the
786 bound butanethiol molecules, which also exhibits the same
787 $\sim$165cm$^{-1}$ peak.
788
789 \subsection{Overlap of power spectra}
790 A comparison of the results obtained from the two different organic
791 solvents can also provide useful information of the interfacial
792 thermal transport process.  In particular, the vibrational overlap
793 between the butanethiol and the organic solvents suggests a highly
794 efficient thermal exchange between these components.  Very high
795 thermal conductivity was observed when AA models were used and C-H
796 vibrations were treated classically. The presence of extra degrees of
797 freedom in the AA force field yields higher heat exchange rates
798 between the two phases and results in a much higher conductivity than
799 in the UA force field. The all-atom classical models include high
800 frequency modes which should be unpopulated at our relatively low
801 temperatures.  This artifact is likely the cause of the high thermal
802 conductance in all-atom MD simulations.
803
804 The similarity in the vibrational modes available to solvent and
805 capping agent can be reduced by deuterating one of the two components
806 (Fig. \ref{aahxntln}).  Once either the hexanes or the butanethiols
807 are deuterated, one can observe a significantly lower $G$ and
808 $G^\prime$ values (Table \ref{modelTest}).
809
810 \begin{figure}
811 \includegraphics[width=\linewidth]{aahxntln}
812 \caption{Spectra obtained for all-atom (AA) Au / butanethiol / solvent
813  systems. When butanethiol is deuterated (lower left), its
814  vibrational overlap with hexane decreases significantly.  Since
815  aromatic molecules and the butanethiol are vibrationally dissimilar,
816  the change is not as dramatic when toluene is the solvent (right).}
817 \label{aahxntln}
818 \end{figure}
819
820 For the Au / butanethiol / toluene interfaces, having the AA
821 butanethiol deuterated did not yield a significant change in the
822 measured conductance. Compared to the C-H vibrational overlap between
823 hexane and butanethiol, both of which have alkyl chains, the overlap
824 between toluene and butanethiol is not as significant and thus does
825 not contribute as much to the heat exchange process.
826
827 Previous observations of Zhang {\it et al.}\cite{hase:2010} indicate
828 that the {\it intra}molecular heat transport due to alkylthiols is
829 highly efficient.  Combining our observations with those of Zhang {\it
830  et al.}, it appears that butanethiol acts as a channel to expedite
831 heat flow from the gold surface and into the alkyl chain.  The
832 vibrational coupling between the metal and the liquid phase can
833 therefore be enhanced with the presence of suitable capping agents.
834
835 Deuterated models in the UA force field did not decouple the thermal
836 transport as well as in the AA force field.  The UA models, even
837 though they have eliminated the high frequency C-H vibrational
838 overlap, still have significant overlap in the lower-frequency
839 portions of the infrared spectra (Figure \ref{uahxnua}).  Deuterating
840 the UA models did not decouple the low frequency region enough to
841 produce an observable difference for the results of $G$ (Table
842 \ref{modelTest}).
843
844 \begin{figure}
845 \includegraphics[width=\linewidth]{uahxnua}
846 \caption{Vibrational power spectra for UA models for the butanethiol
847  and hexane solvent (upper panel) show the high degree of overlap
848  between these two molecules, particularly at lower frequencies.
849  Deuterating a UA model for the solvent (lower panel) does not
850  decouple the two spectra to the same degree as in the AA force
851  field (see Fig \ref{aahxntln}).}
852 \label{uahxnua}
853 \end{figure}
854
726   \section{Conclusions}
727 < The NIVS algorithm has been applied to simulations of
728 < butanethiol-capped Au(111) surfaces in the presence of organic
729 < solvents. This algorithm allows the application of unphysical thermal
730 < flux to transfer heat between the metal and the liquid phase. With the
731 < flux applied, we were able to measure the corresponding thermal
732 < gradients and to obtain interfacial thermal conductivities. Under
733 < steady states, 2-3 ns trajectory simulations are sufficient for
734 < computation of this quantity.
727 > Our simulations demonstrate the validity of our method in RNEMD
728 > computations of thermal conductivity and shear viscosity in atomic and
729 > molecular liquids. Our method maintains thermal velocity distributions
730 > and avoids thermal anisotropy in previous NIVS shear stress
731 > simulations, as well as retains attractive features of previous RNEMD
732 > methods. There is no {\it a priori} restrictions to the method to be
733 > applied in various ensembles, so prospective applications to
734 > extended-system methods are possible.
735  
736 < Our simulations have seen significant conductance enhancement in the
737 < presence of capping agent, compared with the bare gold / liquid
738 < interfaces. The vibrational coupling between the metal and the liquid
739 < phase is enhanced by a chemically-bonded capping agent. Furthermore,
740 < the coverage percentage of the capping agent plays an important role
870 < in the interfacial thermal transport process. Moderately low coverages
871 < allow higher contact between capping agent and solvent, and thus could
872 < further enhance the heat transfer process, giving a non-monotonic
873 < behavior of conductance with increasing coverage.
736 > Furthermore, using this method, investigations can be carried out to
737 > characterize interfacial interactions. Our method is capable of
738 > effectively imposing both thermal and momentum flux accross an
739 > interface and thus facilitates studies that relates dynamic property
740 > measurements to the chemical details of an interface.
741  
742 < Our results, particularly using the UA models, agree well with
743 < available experimental data.  The AA models tend to overestimate the
744 < interfacial thermal conductance in that the classically treated C-H
745 < vibrations become too easily populated. Compared to the AA models, the
746 < UA models have higher computational efficiency with satisfactory
747 < accuracy, and thus are preferable in modeling interfacial thermal
881 < transport.
742 > Another attractive feature of our method is the ability of
743 > simultaneously imposing thermal and momentum flux in a
744 > system. potential researches that might be benefit include complex
745 > systems that involve thermal and momentum gradients. For example, the
746 > Soret effects under a velocity gradient would be of interest to
747 > purification and separation researches.
748  
883 Of the two definitions for $G$, the discrete form
884 (Eq. \ref{discreteG}) was easier to use and gives out relatively
885 consistent results, while the derivative form (Eq. \ref{derivativeG})
886 is not as versatile. Although $G^\prime$ gives out comparable results
887 and follows similar trend with $G$ when measuring close to fully
888 covered or bare surfaces, the spatial resolution of $T$ profile
889 required for the use of a derivative form is limited by the number of
890 bins and the sampling required to obtain thermal gradient information.
891
892 Vlugt {\it et al.} have investigated the surface thiol structures for
893 nanocrystalline gold and pointed out that they differ from those of
894 the Au(111) surface.\cite{landman:1998,vlugt:cpc2007154} This
895 difference could also cause differences in the interfacial thermal
896 transport behavior. To investigate this problem, one would need an
897 effective method for applying thermal gradients in non-planar
898 (i.e. spherical) geometries.
899
749   \section{Acknowledgments}
750   Support for this project was provided by the National Science
751   Foundation under grant CHE-0848243. Computational time was provided by
# Line 909 | Line 758 | Dame.
758  
759   \end{doublespace}
760   \end{document}
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