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# Line 218 | Line 218 | thermal anisotropy when applying a momentum flux.
218   scaling. More importantly, separating the momentum flux imposing from
219   velocity scaling avoids the underlying cause that NIVS produced
220   thermal anisotropy when applying a momentum flux.
221 %NEW METHOD DOESN'T CAUSE UNDESIRED CONCOMITENT MOMENTUM FLUX WHEN
222 %IMPOSING A THERMAL FLUX
221  
222   The advantages of the approach over the original momentum swapping
223   approach lies in its nature to preserve a Gaussian
# Line 389 | Line 387 | solid-liquid interface.
387   so that $\delta\rightarrow 0$ in the ``no-slip'' boundary condition,
388   and depicts how ``slippery'' an interface is. Figure \ref{slipLength}
389   illustrates how this quantity is defined and computed for a
390 < solid-liquid interface.
390 > solid-liquid interface. [MAY INCLUDE A SNAPSHOT IN FIGURE]
391  
392   \begin{figure}
393   \includegraphics[width=\linewidth]{defDelta}
# Line 409 | Line 407 | TO BULK VALUES]
407   data.
408   [MENTION IN RESULTS THAT ETA OBTAINED HERE DOES NOT NECESSARILY EQUAL
409   TO BULK VALUES]
412
413 \section{Results}
414 [L-J COMPARED TO RNEMD NIVS; WATER COMPARED TO RNEMD NIVS AND EMD;
415 SLIP BOUNDARY VS STICK BOUNDARY; ICE-WATER INTERFACES]
410  
411 < There are many factors contributing to the measured interfacial
412 < conductance; some of these factors are physically motivated
413 < (e.g. coverage of the surface by the capping agent coverage and
414 < solvent identity), while some are governed by parameters of the
415 < methodology (e.g. applied flux and the formulas used to obtain the
416 < conductance). In this section we discuss the major physical and
417 < calculational effects on the computed conductivity.
411 > \section{Results and Discussions}
412 > \subsection{Lennard-Jones fluid}
413 > Our orthorhombic simulation cell of Lennard-Jones fluid has identical
414 > parameters to our previous work\cite{kuang:164101} to facilitate
415 > comparison. Thermal conductivitis and shear viscosities were computed
416 > with the algorithm applied to the simulations. The results of thermal
417 > conductivity are compared with our previous NIVS algorithm. However,
418 > since the NIVS algorithm could produce temperature anisotropy for
419 > shear viscocity computations, these results are instead compared to
420 > the momentum swapping approaches. Table \ref{LJ} lists these
421 > calculations with various fluxes in reduced units.
422  
423 < \subsection{Effects due to capping agent coverage}
423 > \begin{table*}
424 >  \begin{minipage}{\linewidth}
425 >    \begin{center}
426 >
427 >      \caption{Thermal conductivity ($\lambda^*$) and shear viscosity
428 >        ($\eta^*$) (in reduced units) of a Lennard-Jones fluid at
429 >        ${\langle T^* \rangle = 0.72}$ and ${\rho^* = 0.85}$ computed
430 >        at various momentum fluxes.  The new method yields similar
431 >        results to previous RNEMD methods. All results are reported in
432 >        reduced unit. Uncertainties are indicated in parentheses.}
433 >      
434 >      \begin{tabular}{cccccc}
435 >        \hline\hline
436 >        \multicolumn{2}{c}{Momentum Exchange} &
437 >        \multicolumn{2}{c}{$\lambda^*$} &
438 >        \multicolumn{2}{c}{$\eta^*$} \\
439 >        \hline
440 >        Swap Interval & Equivalent $J_z^*$ or $j_z^*(p_x)$ &
441 >        NIVS & This work & Swapping & This work \\
442 >        \hline
443 >        0.116 & 0.16  & 7.30(0.10) & 6.25(0.23) & 3.57(0.06) & 3.53(0.16)\\
444 >        0.232 & 0.09  & 6.95(0.09) & 8.02(0.56) & 3.64(0.05) & 3.43(0.17)\\
445 >        0.463 & 0.047 & 7.19(0.07) & 6.48(0.15) & 3.52(0.16) & 3.51(0.08)\\
446 >        0.926 & 0.024 & 7.19(0.28) & 7.02(0.13) & 3.72(0.05) & 3.79(0.11)\\
447 >        1.158 & 0.019 & 7.98(0.33) & 7.37(0.23) & 3.42(0.06) & 3.53(0.06)\\
448 >        \hline\hline
449 >      \end{tabular}
450 >      \label{LJ}
451 >    \end{center}
452 >  \end{minipage}
453 > \end{table*}
454  
455 < A series of different initial conditions with a range of surface
456 < coverages was prepared and solvated with various with both of the
457 < solvent molecules. These systems were then equilibrated and their
458 < interfacial thermal conductivity was measured with the NIVS
459 < algorithm. Figure \ref{coverage} demonstrates the trend of conductance
460 < with respect to surface coverage.
455 > \subsubsection{Thermal conductivity}
456 > Our thermal conductivity calculations with this method yields
457 > comparable results to the previous NIVS algorithm. This indicates that
458 > the thermal gradients rendered using this method are also close to
459 > previous RNEMD methods. Simulations with moderately higher thermal
460 > fluxes tend to yield more reliable thermal gradients and thus avoid
461 > large errors, while overly high thermal fluxes could introduce side
462 > effects such as non-linear temperature gradient response or
463 > inadvertent phase transitions.
464  
465 + Since the scaling operation is isotropic in this method, one does not
466 + need extra care to ensure temperature isotropy between the $x$, $y$
467 + and $z$ axes, while thermal anisotropy might happen if the criteria
468 + function for choosing scaling coefficients does not perform as
469 + expected. Furthermore, this method avoids inadvertent concomitant
470 + momentum flux when only thermal flux is imposed, which could not be
471 + achieved with swapping or NIVS approaches. The thermal energy exchange
472 + in swapping ($\vec{p}_i$ in slab ``c'' with $\vec{p}_j$ in slab ``j'')
473 + or NIVS (total slab momentum conponemts $P^\alpha$ scaled to $\alpha
474 + P^\alpha$) would not obtain this result unless thermal flux vanishes
475 + (i.e. $\vec{p}_i=\vec{p}_j$ or $\alpha=1$ which are trivial to apply a
476 + thermal flux). In this sense, this method contributes to having
477 + minimal perturbation to a simulation while imposing thermal flux.
478 +
479 + \subsubsection{Shear viscosity}
480 + Table \ref{LJ} also compares our shear viscosity results with momentum
481 + swapping approach. Our calculations show that our method predicted
482 + similar values for shear viscosities to the momentum swapping
483 + approach, as well as the velocity gradient profiles. Moderately larger
484 + momentum fluxes are helpful to reduce the errors of measured velocity
485 + gradients and thus the final result. However, it is pointed out that
486 + the momentum swapping approach tends to produce nonthermal velocity
487 + distributions.\cite{Maginn:2010}
488 +
489 + To examine that temperature isotropy holds in simulations using our
490 + method, we measured the three one-dimensional temperatures in each of
491 + the slabs (Figure \ref{tempXyz}). Note that the $x$-dimensional
492 + temperatures were calculated after subtracting the effects from bulk
493 + velocities of the slabs. The one-dimensional temperature profiles
494 + showed no observable difference between the three dimensions. This
495 + ensures that isotropic scaling automatically preserves temperature
496 + isotropy and that our method is useful in shear viscosity
497 + computations.
498 +
499   \begin{figure}
500 < \includegraphics[width=\linewidth]{coverage}
501 < \caption{The interfacial thermal conductivity ($G$) has a
502 <  non-monotonic dependence on the degree of surface capping.  This
438 <  data is for the Au(111) / butanethiol / solvent interface with
439 <  various UA force fields at $\langle T\rangle \sim $200K.}
440 < \label{coverage}
500 > \includegraphics[width=\linewidth]{tempXyz}
501 > \caption{.}
502 > \label{tempXyz}
503   \end{figure}
504  
505 < In partially covered surfaces, the derivative definition for
506 < $G^\prime$ (Eq. \ref{derivativeG}) becomes difficult to apply, as the
507 < location of maximum change of $\lambda$ becomes washed out.  The
508 < discrete definition (Eq. \ref{discreteG}) is easier to apply, as the
509 < Gibbs dividing surface is still well-defined. Therefore, $G$ (not
510 < $G^\prime$) was used in this section.
505 > Furthermore, the velocity distribution profiles are tested by imposing
506 > a large shear stress into the simulations. Figure \ref{vDist}
507 > demonstrates how our method is able to maintain thermal velocity
508 > distributions against the momentum swapping approach even under large
509 > imposed fluxes. Previous swapping methods tend to deplete particles of
510 > positive velocities in the negative velocity slab (``c'') and vice
511 > versa in slab ``h'', where the distributions leave a notch. This
512 > problematic profiles become significant when the imposed-flux becomes
513 > larger and diffusions from neighboring slabs could not offset the
514 > depletion. Simutaneously, abnormal peaks appear corresponding to
515 > excessive velocity swapped from the other slab. This nonthermal
516 > distributions limit applications of the swapping approach in shear
517 > stress simulations. Our method avoids the above problematic
518 > distributions by altering the means of applying momentum
519 > fluxes. Comparatively, velocity distributions recorded from
520 > simulations with our method is so close to the ideal thermal
521 > prediction that no observable difference is shown in Figure
522 > \ref{vDist}. Conclusively, our method avoids problems happened in
523 > previous RNEMD methods and provides a useful means for shear viscosity
524 > computations.
525  
526 < From Figure \ref{coverage}, one can see the significance of the
527 < presence of capping agents. When even a small fraction of the Au(111)
528 < surface sites are covered with butanethiols, the conductivity exhibits
529 < an enhancement by at least a factor of 3.  Capping agents are clearly
530 < playing a major role in thermal transport at metal / organic solvent
455 < surfaces.
526 > \begin{figure}
527 > \includegraphics[width=\linewidth]{velDist}
528 > \caption{.}
529 > \label{vDist}
530 > \end{figure}
531  
532 < We note a non-monotonic behavior in the interfacial conductance as a
533 < function of surface coverage. The maximum conductance (largest $G$)
459 < happens when the surfaces are about 75\% covered with butanethiol
460 < caps.  The reason for this behavior is not entirely clear.  One
461 < explanation is that incomplete butanethiol coverage allows small gaps
462 < between butanethiols to form. These gaps can be filled by transient
463 < solvent molecules.  These solvent molecules couple very strongly with
464 < the hot capping agent molecules near the surface, and can then carry
465 < away (diffusively) the excess thermal energy from the surface.
532 > \subsection{Bulk SPC/E water}
533 > [WATER COMPARED TO RNEMD NIVS AND EMD]
534  
535 < There appears to be a competition between the conduction of the
536 < thermal energy away from the surface by the capping agents (enhanced
469 < by greater coverage) and the coupling of the capping agents with the
470 < solvent (enhanced by interdigitation at lower coverages).  This
471 < competition would lead to the non-monotonic coverage behavior observed
472 < here.
535 > \subsubsection{Thermal conductivity}
536 > [VSIS DOES AS WELL AS NIVS]
537  
538 < Results for rigid body toluene solvent, as well as the UA hexane, are
539 < within the ranges expected from prior experimental
476 < work.\cite{Wilson:2002uq,cahill:793,PhysRevB.80.195406} This suggests
477 < that explicit hydrogen atoms might not be required for modeling
478 < thermal transport in these systems.  C-H vibrational modes do not see
479 < significant excited state population at low temperatures, and are not
480 < likely to carry lower frequency excitations from the solid layer into
481 < the bulk liquid.
538 > \subsubsection{Shear viscosity}
539 > [COMPARE W EMD]
540  
541 < The toluene solvent does not exhibit the same behavior as hexane in
484 < that $G$ remains at approximately the same magnitude when the capping
485 < coverage increases from 25\% to 75\%.  Toluene, as a rigid planar
486 < molecule, cannot occupy the relatively small gaps between the capping
487 < agents as easily as the chain-like {\it n}-hexane.  The effect of
488 < solvent coupling to the capping agent is therefore weaker in toluene
489 < except at the very lowest coverage levels.  This effect counters the
490 < coverage-dependent conduction of heat away from the metal surface,
491 < leading to a much flatter $G$ vs. coverage trend than is observed in
492 < {\it n}-hexane.
541 > [MAY HAVE A FIRURE FOR DATA]
542  
543 < \subsection{Effects due to Solvent \& Solvent Models}
544 < In addition to UA solvent and capping agent models, AA models have
545 < also been included in our simulations.  In most of this work, the same
546 < (UA or AA) model for solvent and capping agent was used, but it is
498 < also possible to utilize different models for different components.
499 < We have also included isotopic substitutions (Hydrogen to Deuterium)
500 < to decrease the explicit vibrational overlap between solvent and
501 < capping agent. Table \ref{modelTest} summarizes the results of these
502 < studies.
543 > [MAY COMBINE JZPX AND JZKE TO RUN ONE JOB BUT GET ETA=F(T)]
544 > [PUT RESULT AND FIGURE HERE IF IT WORKS]
545 > \subsection{Interfacial frictions}
546 > [SLIP BOUNDARY VS STICK BOUNDARY; ICE-WATER INTERFACES]
547  
548 + qualitative agreement w interfacial thermal conductance
549 +
550 + [FUTURE WORK HERE OR IN CONCLUSIONS]
551 +
552 +
553   \begin{table*}
554    \begin{minipage}{\linewidth}
555      \begin{center}
# Line 523 | Line 572 | studies.
572                & UA toluene   & 187(16)   & 151(11)   \\
573                & AA toluene   & 200(36)   & 149(53)   \\
574          \hline
526        AA    & UA hexane    & 116(9)    & 129(8)    \\
527              & AA hexane    & 442(14)   & 356(31)   \\
528              & AA hexane(D) & 222(12)   & 234(54)   \\
529              & UA toluene   & 125(25)   & 97(60)    \\
530              & AA toluene   & 487(56)   & 290(42)   \\
531        \hline
532        AA(D) & UA hexane    & 158(25)   & 172(4)    \\
533              & AA hexane    & 243(29)   & 191(11)   \\
534              & AA toluene   & 364(36)   & 322(67)   \\
535        \hline
575          bare  & UA hexane    & 46.5(3.2) & 49.4(4.5) \\
576                & UA hexane(D) & 43.9(4.6) & 43.0(2.0) \\
577                & AA hexane    & 31.0(1.4) & 29.4(1.3) \\
# Line 544 | Line 583 | To facilitate direct comparison between force fields,
583    \end{minipage}
584   \end{table*}
585  
547 To facilitate direct comparison between force fields, systems with the
548 same capping agent and solvent were prepared with the same length
549 scales for the simulation cells.
550
586   On bare metal / solvent surfaces, different force field models for
587   hexane yield similar results for both $G$ and $G^\prime$, and these
588   two definitions agree with each other very well. This is primarily an
# Line 564 | Line 599 | values with much higher computational efficiency.
599   to the AA model, the UA model yields more reasonable conductivity
600   values with much higher computational efficiency.
601  
567 \subsubsection{Are electronic excitations in the metal important?}
568 Because they lack electronic excitations, the QSC and related embedded
569 atom method (EAM) models for gold are known to predict unreasonably
570 low values for bulk conductivity
571 ($\lambda$).\cite{kuang:164101,ISI:000207079300006,Clancy:1992} If the
572 conductance between the phases ($G$) is governed primarily by phonon
573 excitation (and not electronic degrees of freedom), one would expect a
574 classical model to capture most of the interfacial thermal
575 conductance.  Our results for $G$ and $G^\prime$ indicate that this is
576 indeed the case, and suggest that the modeling of interfacial thermal
577 transport depends primarily on the description of the interactions
578 between the various components at the interface.  When the metal is
579 chemically capped, the primary barrier to thermal conductivity appears
580 to be the interface between the capping agent and the surrounding
581 solvent, so the excitations in the metal have little impact on the
582 value of $G$.
583
584 \subsection{Effects due to methodology and simulation parameters}
585
586 We have varied the parameters of the simulations in order to
587 investigate how these factors would affect the computation of $G$.  Of
588 particular interest are: 1) the length scale for the applied thermal
589 gradient (modified by increasing the amount of solvent in the system),
590 2) the sign and magnitude of the applied thermal flux, 3) the average
591 temperature of the simulation (which alters the solvent density during
592 equilibration), and 4) the definition of the interfacial conductance
593 (Eqs. (\ref{discreteG}) or (\ref{derivativeG})) used in the
594 calculation.
595
596 Systems of different lengths were prepared by altering the number of
597 solvent molecules and extending the length of the box along the $z$
598 axis to accomodate the extra solvent.  Equilibration at the same
599 temperature and pressure conditions led to nearly identical surface
600 areas ($L_x$ and $L_y$) available to the metal and capping agent,
601 while the extra solvent served mainly to lengthen the axis that was
602 used to apply the thermal flux.  For a given value of the applied
603 flux, the different $z$ length scale has only a weak effect on the
604 computed conductivities.
605
606 \subsubsection{Effects of applied flux}
607 The NIVS algorithm allows changes in both the sign and magnitude of
608 the applied flux.  It is possible to reverse the direction of heat
609 flow simply by changing the sign of the flux, and thermal gradients
610 which would be difficult to obtain experimentally ($5$ K/\AA) can be
611 easily simulated.  However, the magnitude of the applied flux is not
612 arbitrary if one aims to obtain a stable and reliable thermal gradient.
613 A temperature gradient can be lost in the noise if $|J_z|$ is too
614 small, and excessive $|J_z|$ values can cause phase transitions if the
615 extremes of the simulation cell become widely separated in
616 temperature.  Also, if $|J_z|$ is too large for the bulk conductivity
617 of the materials, the thermal gradient will never reach a stable
618 state.  
619
620 Within a reasonable range of $J_z$ values, we were able to study how
621 $G$ changes as a function of this flux.  In what follows, we use
622 positive $J_z$ values to denote the case where energy is being
623 transferred by the method from the metal phase and into the liquid.
624 The resulting gradient therefore has a higher temperature in the
625 liquid phase.  Negative flux values reverse this transfer, and result
626 in higher temperature metal phases.  The conductance measured under
627 different applied $J_z$ values is listed in Tables 2 and 3 in the
628 supporting information. These results do not indicate that $G$ depends
629 strongly on $J_z$ within this flux range. The linear response of flux
630 to thermal gradient simplifies our investigations in that we can rely
631 on $G$ measurement with only a small number $J_z$ values.
632
633 The sign of $J_z$ is a different matter, however, as this can alter
634 the temperature on the two sides of the interface. The average
635 temperature values reported are for the entire system, and not for the
636 liquid phase, so at a given $\langle T \rangle$, the system with
637 positive $J_z$ has a warmer liquid phase.  This means that if the
638 liquid carries thermal energy via diffusive transport, {\it positive}
639 $J_z$ values will result in increased molecular motion on the liquid
640 side of the interface, and this will increase the measured
641 conductivity.
642
602   \subsubsection{Effects due to average temperature}
603  
604   We also studied the effect of average system temperature on the
# Line 665 | Line 624 | Besides the lower interfacial thermal conductance, sur
624   of one side of the interface (notably the density) change rapidly as a
625   function of temperature.
626  
668 Besides the lower interfacial thermal conductance, surfaces at
669 relatively high temperatures are susceptible to reconstructions,
670 particularly when butanethiols fully cover the Au(111) surface. These
671 reconstructions include surface Au atoms which migrate outward to the
672 S atom layer, and butanethiol molecules which embed into the surface
673 Au layer. The driving force for this behavior is the strong Au-S
674 interactions which are modeled here with a deep Lennard-Jones
675 potential. This phenomenon agrees with reconstructions that have been
676 experimentally
677 observed.\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}.  Vlugt
678 {\it et al.} kept their Au(111) slab rigid so that their simulations
679 could reach 300K without surface
680 reconstructions.\cite{vlugt:cpc2007154} Since surface reconstructions
681 blur the interface, the measurement of $G$ becomes more difficult to
682 conduct at higher temperatures.  For this reason, most of our
683 measurements are undertaken at $\langle T\rangle\sim$200K where
684 reconstruction is minimized.
685
686 However, when the surface is not completely covered by butanethiols,
687 the simulated system appears to be more resistent to the
688 reconstruction. Our Au / butanethiol / toluene system had the Au(111)
689 surfaces 90\% covered by butanethiols, but did not see this above
690 phenomena even at $\langle T\rangle\sim$300K.  That said, we did
691 observe butanethiols migrating to neighboring three-fold sites during
692 a simulation.  Since the interface persisted in these simulations, we
693 were able to obtain $G$'s for these interfaces even at a relatively
694 high temperature without being affected by surface reconstructions.
695
696 \section{Discussion}
697 [COMBINE W. RESULTS]
698 The primary result of this work is that the capping agent acts as an
699 efficient thermal coupler between solid and solvent phases.  One of
700 the ways the capping agent can carry out this role is to down-shift
701 between the phonon vibrations in the solid (which carry the heat from
702 the gold) and the molecular vibrations in the liquid (which carry some
703 of the heat in the solvent).
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:
714 \begin{equation}
715 C_A (t) = \langle\vec{v}_A (t)\cdot\vec{v}_A (0)\rangle
716 \label{vCorr}
717 \end{equation}
718 The power spectrum is constructed via a Fourier transform of the
719 symmetrized velocity autocorrelation function,
720 \begin{equation}
721  \hat{f}(\omega) =
722  \int_{-\infty}^{\infty} C_A (t) e^{-2\pi it\omega}\,dt
723 \label{fourier}
724 \end{equation}
725
726 \subsection{The role of specific vibrations}
727 The vibrational spectra for gold slabs in different environments are
728 shown as in Figure \ref{specAu}. Regardless of the presence of
729 solvent, the gold surfaces which are covered by butanethiol molecules
730 exhibit an additional peak observed at a frequency of
731 $\sim$165cm$^{-1}$.  We attribute this peak to the S-Au bonding
732 vibration. This vibration enables efficient thermal coupling of the
733 surface Au layer to the capping agents. Therefore, in our simulations,
734 the Au / S interfaces do not appear to be the primary barrier to
735 thermal transport when compared with the butanethiol / solvent
736 interfaces.  This supports the results of Luo {\it et
737  al.}\cite{Luo20101}, who reported $G$ for Au-SAM junctions roughly
738 twice as large as what we have computed for the thiol-liquid
739 interfaces.
740
741 \begin{figure}
742 \includegraphics[width=\linewidth]{vibration}
743 \caption{The vibrational power spectrum for thiol-capped gold has an
744  additional vibrational peak at $\sim $165cm$^{-1}$.  Bare gold
745  surfaces (both with and without a solvent over-layer) are missing
746  this peak.   A similar peak at  $\sim $165cm$^{-1}$ also appears in
747  the vibrational power spectrum for the butanethiol capping agents.}
748 \label{specAu}
749 \end{figure}
750
751 Also in this figure, we show the vibrational power spectrum for the
752 bound butanethiol molecules, which also exhibits the same
753 $\sim$165cm$^{-1}$ peak.
754
755 \subsection{Overlap of power spectra}
756 A comparison of the results obtained from the two different organic
757 solvents can also provide useful information of the interfacial
758 thermal transport process.  In particular, the vibrational overlap
759 between the butanethiol and the organic solvents suggests a highly
760 efficient thermal exchange between these components.  Very high
761 thermal conductivity was observed when AA models were used and C-H
762 vibrations were treated classically. The presence of extra degrees of
763 freedom in the AA force field yields higher heat exchange rates
764 between the two phases and results in a much higher conductivity than
765 in the UA force field. The all-atom classical models include high
766 frequency modes which should be unpopulated at our relatively low
767 temperatures.  This artifact is likely the cause of the high thermal
768 conductance in all-atom MD simulations.
769
770 The similarity in the vibrational modes available to solvent and
771 capping agent can be reduced by deuterating one of the two components
772 (Fig. \ref{aahxntln}).  Once either the hexanes or the butanethiols
773 are deuterated, one can observe a significantly lower $G$ and
774 $G^\prime$ values (Table \ref{modelTest}).
775
776 \begin{figure}
777 \includegraphics[width=\linewidth]{aahxntln}
778 \caption{Spectra obtained for all-atom (AA) Au / butanethiol / solvent
779  systems. When butanethiol is deuterated (lower left), its
780  vibrational overlap with hexane decreases significantly.  Since
781  aromatic molecules and the butanethiol are vibrationally dissimilar,
782  the change is not as dramatic when toluene is the solvent (right).}
783 \label{aahxntln}
784 \end{figure}
785
786 For the Au / butanethiol / toluene interfaces, having the AA
787 butanethiol deuterated did not yield a significant change in the
788 measured conductance. Compared to the C-H vibrational overlap between
789 hexane and butanethiol, both of which have alkyl chains, the overlap
790 between toluene and butanethiol is not as significant and thus does
791 not contribute as much to the heat exchange process.
792
793 Previous observations of Zhang {\it et al.}\cite{hase:2010} indicate
794 that the {\it intra}molecular heat transport due to alkylthiols is
795 highly efficient.  Combining our observations with those of Zhang {\it
796  et al.}, it appears that butanethiol acts as a channel to expedite
797 heat flow from the gold surface and into the alkyl chain.  The
798 vibrational coupling between the metal and the liquid phase can
799 therefore be enhanced with the presence of suitable capping agents.
800
801 Deuterated models in the UA force field did not decouple the thermal
802 transport as well as in the AA force field.  The UA models, even
803 though they have eliminated the high frequency C-H vibrational
804 overlap, still have significant overlap in the lower-frequency
805 portions of the infrared spectra (Figure \ref{uahxnua}).  Deuterating
806 the UA models did not decouple the low frequency region enough to
807 produce an observable difference for the results of $G$ (Table
808 \ref{modelTest}).
809
810 \begin{figure}
811 \includegraphics[width=\linewidth]{uahxnua}
812 \caption{Vibrational power spectra for UA models for the butanethiol
813  and hexane solvent (upper panel) show the high degree of overlap
814  between these two molecules, particularly at lower frequencies.
815  Deuterating a UA model for the solvent (lower panel) does not
816  decouple the two spectra to the same degree as in the AA force
817  field (see Fig \ref{aahxntln}).}
818 \label{uahxnua}
819 \end{figure}
820
627   \section{Conclusions}
628 + [VSIS WORKS! COMBINES NICE FEATURES OF PREVIOUS RNEMD METHODS AND
629 + IMPROVEMENTS TO THEIR PROBLEMS!]
630 +
631   The NIVS algorithm has been applied to simulations of
632   butanethiol-capped Au(111) surfaces in the presence of organic
633   solvents. This algorithm allows the application of unphysical thermal
# Line 846 | Line 655 | Of the two definitions for $G$, the discrete form
655   accuracy, and thus are preferable in modeling interfacial thermal
656   transport.
657  
849 Of the two definitions for $G$, the discrete form
850 (Eq. \ref{discreteG}) was easier to use and gives out relatively
851 consistent results, while the derivative form (Eq. \ref{derivativeG})
852 is not as versatile. Although $G^\prime$ gives out comparable results
853 and follows similar trend with $G$ when measuring close to fully
854 covered or bare surfaces, the spatial resolution of $T$ profile
855 required for the use of a derivative form is limited by the number of
856 bins and the sampling required to obtain thermal gradient information.
857
858 Vlugt {\it et al.} have investigated the surface thiol structures for
859 nanocrystalline gold and pointed out that they differ from those of
860 the Au(111) surface.\cite{landman:1998,vlugt:cpc2007154} This
861 difference could also cause differences in the interfacial thermal
862 transport behavior. To investigate this problem, one would need an
863 effective method for applying thermal gradients in non-planar
864 (i.e. spherical) geometries.
865
658   \section{Acknowledgments}
659   Support for this project was provided by the National Science
660   Foundation under grant CHE-0848243. Computational time was provided by
# Line 875 | Line 667 | Dame.
667  
668   \end{doublespace}
669   \end{document}
878

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