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# Line 53 | Line 53 | Notre Dame, Indiana 46556}
53    scaling (NIVS) on the molecules in specific regions of a system, it
54    is possible to impose momentum or thermal flux between regions of a
55    simulation while conserving the linear momentum and total energy of
56 <  the system.  To test the methods, we have computed the thermal
56 >  the system.  To test the method, we have computed the thermal
57    conductivity of model liquid and solid systems as well as the
58    interfacial thermal conductivity of a metal-water interface.  We
59    find that the NIVS-RNEMD improves the problematic velocity
# Line 114 | Line 114 | computing difficult to measure quantities.
114   relations\cite{daivis:541,mondello:9327} or the Helfand moment
115   approach of Viscardy {\it et
116    al.}\cite{Viscardy:2007bh,Viscardy:2007lq}) because these rely on
117 < computing difficult to measure quantities.
117 > computing and integrating long-time correlation functions that are
118 > subject to noise issues.
119  
120   Another attractive feature of RNEMD is that it conserves both total
121   linear momentum and total energy during the swaps (as long as the two
# Line 289 | Line 290 | one would also like each scaling as gentle as possible
290   isotropic fluid as possible.  With this in mind, we would like the
291   kinetic energies in the three different directions could become as
292   close as each other as possible after each scaling.  Simultaneously,
293 < one would also like each scaling as gentle as possible, i.e. ${x,y,z
294 <  \rightarrow 1}$, in order to avoid large perturbation to the system.
295 < To do this, we pick the intersection point which maintains the three
296 < scaling variables ${x, y, z}$ as well as the ratio of kinetic energies
297 < ${K_c^z/K_c^x, K_c^z/K_c^y}$ as close as possible to 1.
293 > one would also like each scaling to be as gentle as possible, i.e.
294 > ${x,y,z \rightarrow 1}$, in order to avoid large perturbations to the
295 > system.  To do this, we pick the intersection point which maintains
296 > the three scaling variables ${x, y, z}$ as well as the ratio of
297 > kinetic energies ${K_c^z/K_c^x, K_c^z/K_c^y}$ as close as possible to
298 > 1.
299  
300   After the valid scaling parameters are arrived at by solving geometric
301   intersection problems in $x, y, z$ space in order to obtain cold slab
# Line 383 | Line 385 | To test the temperature homogeneity, directional momen
385   NIVS-RNEMD simulation was carried out using a target momentum flux set
386   to produce the same flux experienced in the swapping simulation.
387  
388 < To test the temperature homogeneity, directional momentum and
389 < temperature distributions were accumulated for molecules in each of
390 < the slabs.  Transport coefficients were computed using the temperature
391 < (and momentum) gradients across the $z$-axis as well as the total
392 < momentum flux the system experienced during data collection portion of
393 < the simulation.
388 > To test the temperature homogeneity, momentum and temperature
389 > distributions (for all three dimensions) were accumulated for
390 > molecules in each of the slabs.  Transport coefficients were computed
391 > using the temperature (and momentum) gradients across the $z$-axis as
392 > well as the total momentum flux the system experienced during data
393 > collection portion of the simulation.
394  
395   \subsection{Shear viscosities}
396  
# Line 429 | Line 431 | G = \frac{E_{total}}{2 t L_x L_y \left( \langle T_{gol
431   be approximated as:
432  
433   \begin{equation}
434 < G = \frac{E_{total}}{2 t L_x L_y \left( \langle T_{gold}\rangle -
435 <    \langle T_{water}\rangle \right)}
434 > G = \frac{E_{total}}{2 t L_x L_y \left( \langle T_\mathrm{hot}\rangle -
435 >    \langle T_\mathrm{cold}\rangle \right)}
436   \label{interfaceCalc}
437   \end{equation}
438   where ${E_{total}}$ is the imposed non-physical kinetic energy
439 < transfer and ${\langle T_{gold}\rangle}$ and ${\langle
440 <  T_{water}\rangle}$ are the average observed temperature of gold and
441 < water phases respectively.  If the interfacial conductance is {\it
442 <  not} small, it is also be possible to compute the interfacial
443 < thermal conductivity using this method utilizing the change in the
444 < slope of the thermal gradient ($\partial^2 \langle T \rangle / \partial
445 < z^2$) at the interface.
439 > transfer and ${\langle T_\mathrm{hot}\rangle}$ and ${\langle
440 >  T_\mathrm{cold}\rangle}$ are the average observed temperature of the
441 > two separated phases.  If the interfacial conductance is {\it not}
442 > small, it would also be possible to compute the interfacial thermal
443 > conductivity using this method by computing the change in the slope of
444 > the thermal gradient ($\partial^2 \langle T \rangle /
445 > \partial z^2$) at the interface.
446  
447   \section{Results}
448  
# Line 464 | Line 466 | similar thermal flux under the two different methods (
466   Our thermal conductivity calculations show that the NIVS method agrees
467   well with the swapping method. Five different swap intervals were
468   tested (Table \ref{LJ}). Similar thermal gradients were observed with
469 < similar thermal flux under the two different methods (Figure
469 > similar thermal flux under the two different methods (Fig.
470   \ref{thermalGrad}). Furthermore, the 1-d temperature profiles showed
471 < no observable differences between the $x$, $y$ and $z$ axes (Figure
472 < \ref{thermalGrad} c), so even though we are using a non-isotropic
473 < scaling method, none of the three directions are experience
474 < disproportionate heating due to the velocity scaling.
471 > no observable differences between the $x$, $y$ and $z$ axes (lower
472 > panel of Fig. \ref{thermalGrad}), so even though we are using a
473 > non-isotropic scaling method, none of the three directions are
474 > experience disproportionate heating due to the velocity scaling.
475  
476   \begin{table*}
477    \begin{minipage}{\linewidth}
# Line 519 | Line 521 | During these simulations, velocities were recorded eve
521  
522   \subsubsection*{Velocity Distributions}
523  
524 < During these simulations, velocities were recorded every 1000 steps
525 < and were used to produce distributions of both velocity and speed in
526 < each of the slabs. From these distributions, we observed that under
527 < relatively high non-physical kinetic energy flux, the speed of
528 < molecules in slabs where swapping occured could deviate from the
524 > To test the effects on the velocity distributions, we accumulated
525 > velocities every 100 steps and produced distributions of both velocity
526 > and speed in each of the slabs. From these distributions, we observed
527 > that under high non-physical kinetic energy flux, the speed of
528 > molecules in slabs where {\it swapping} occured could deviate from the
529   Maxwell-Boltzmann distribution. This behavior was also noted by Tenney
530   and Maginn.\cite{Maginn:2010} Figure \ref{thermalHist} shows how these
531   distributions deviate from an ideal distribution. In the ``hot'' slab,
532   the probability density is notched at low speeds and has a substantial
533 < shoulder at higher speeds relative to the ideal MB distribution. In
534 < the cold slab, the opposite notching and shouldering occurs.  This
535 < phenomenon is more obvious at higher swapping rates.
533 > shoulder at higher speeds relative to the ideal distribution. In the
534 > cold slab, the opposite notching and shouldering occurs.  This
535 > phenomenon is more obvious at high swapping rates.
536  
537   The peak of the velocity distribution is substantially flattened in
538   the hot slab, and is overly sharp (with truncated wings) in the cold
539   slab. This problem is rooted in the mechanism of the swapping method.
540   Continually depleting low (high) speed particles in the high (low)
541 < temperature slab is not complemented by diffusions of low (high) speed
542 < particles from neighboring slabs, unless the swapping rate is
541 > temperature slab is not complemented by diffusion of low (high) speed
542 > particles from neighboring slabs unless the swapping rate is
543   sufficiently small. Simutaneously, surplus low speed particles in the
544 < low temperature slab do not have sufficient time to diffuse to
545 < neighboring slabs.  Since the thermal exchange rate must reach a
546 < minimum level to produce an observable thermal gradient, the
547 < swapping-method RNEMD has a relatively narrow choice of exchange times
546 < that can be utilized.
544 > cold slab do not have sufficient time to diffuse to neighboring slabs.
545 > Since the thermal exchange rate must reach a minimum level to produce
546 > an observable thermal gradient, the swapping-method RNEMD has a
547 > relatively narrow choice of exchange times that can be utilized.
548  
549   For comparison, NIVS-RNEMD produces a speed distribution closer to the
550 < Maxwell-Boltzmann curve (Figure \ref{thermalHist}).  The reason for
551 < this is simple; upon velocity scaling, a Gaussian distribution remains
550 > Maxwell-Boltzmann curve (Fig. \ref{thermalHist}).  The reason for this
551 > is simple; upon velocity scaling, a Gaussian distribution remains
552   Gaussian.  Although a single scaling move is non-isotropic in three
553   dimensions, our criteria for choosing a set of scaling coefficients
554   helps maintain the distributions as close to isotropic as possible.
555 < Consequently, NIVS-RNEMD is able to impose an unphysical thermal flux
556 < as the previous RNEMD methods but without large perturbations to the
557 < velocity distributions in the two slabs.
555 > Consequently, NIVS-RNEMD is able to impose a non-physical thermal flux
556 > without large perturbations to the velocity distributions in the two
557 > slabs.
558  
559   \begin{figure}
560   \includegraphics[width=\linewidth]{thermalHist}
# Line 572 | Line 573 | predicted comparable shear viscosities to swap RNEMD m
573  
574   \subsubsection*{Shear Viscosity}
575   Our calculations (Table \ref{LJ}) show that velocity-scaling RNEMD
576 < predicted comparable shear viscosities to swap RNEMD method. The
577 < average molecular momentum gradients of these samples are shown in
578 < Figure \ref{shear} (a) and (b).
576 > predicted similar values for shear viscosities to the swapping RNEMD
577 > method. The average molecular momentum gradients of these samples are
578 > shown in the upper two panels of Fig. \ref{shear}.
579  
580   \begin{figure}
581    \includegraphics[width=\linewidth]{shear}
# Line 588 | Line 589 | particularly in the hot and cold slabs.  Figure \ref{s
589  
590   Observations of the three one-dimensional temperatures in each of the
591   slabs shows that NIVS-RNEMD does produce some thermal anisotropy,
592 < particularly in the hot and cold slabs.  Figure \ref{shear} (c)
593 < indicates that with a relatively large imposed momentum flux,
594 < $j_z(p_x)$, the $x$ direction approaches a different temperature from
595 < the $y$ and $z$ directions in both the hot and cold bins.  This is an
596 < artifact of the scaling constraints.  After the momentum gradient has
597 < been established, $P_c^x < 0$.  Consequently, the scaling factor $x$
598 < is nearly always greater than one in order to satisfy the constraints.
599 < This will continually increase the kinetic energy in $x$-dimension,
600 < $K_c^x$.  If there is not enough time for the kinetic energy to
601 < exchange among different directions and different slabs, the system
602 < will exhibit the observed thermal anisotropy in the hot and cold bins.
592 > particularly in the hot and cold slabs.  The lower panel of Fig.
593 > \ref{shear} indicates that with a relatively large imposed momentum
594 > flux, $j_z(p_x)$, the $x$ direction approaches a different temperature
595 > from the $y$ and $z$ directions in both the hot and cold bins.  This
596 > is an artifact of the scaling constraints.  After a momentum gradient
597 > has been established, $P_c^x$ is always less than zero.  Consequently,
598 > the scaling factor $x$ is always greater than one in order to satisfy
599 > the constraints.  This will continually increase the kinetic energy in
600 > $x$-dimension, $K_c^x$.  If there is not enough time for the kinetic
601 > energy to exchange among different directions and different slabs, the
602 > system will exhibit the observed thermal anisotropy in the hot and
603 > cold bins.
604  
605   Although results between scaling and swapping methods are comparable,
606   the inherent temperature anisotropy does make NIVS-RNEMD method less
607   attractive than swapping RNEMD for shear viscosity calculations.  We
608 < note that this problem appears only when momentum flux is applied, and
609 < does not appear in thermal flux calculations.
608 > note that this problem appears only when a large {\it linear} momentum
609 > flux is applied, and does not appear in {\it thermal} flux
610 > calculations.
611  
612   \subsection{Bulk SPC/E water}
613  
614   We compared the thermal conductivity of SPC/E water using NIVS-RNEMD
615   to the work of Bedrov {\it et al.}\cite{Bedrov:2000}, which employed
616   the original swapping RNEMD method.  Bedrov {\it et
617 <  al.}\cite{Bedrov:2000} argued that exchange of the molecule
618 < center-of-mass velocities instead of single atom velocities in a
619 < molecule conserves the total kinetic energy and linear momentum.  This
620 < principle is also adopted Fin our simulations. Scaling was applied to
621 < the center-of-mass velocities of the rigid bodies of SPC/E model water
619 < molecules.
617 >  al.}\cite{Bedrov:2000} argued that exchange of the molecular
618 > center-of-mass velocities instead of single atom velocities conserves
619 > the total kinetic energy and linear momentum.  This principle is also
620 > adopted in our simulations. Scaling was applied to the center-of-mass
621 > velocities of SPC/E water molecules.
622  
623   To construct the simulations, a simulation box consisting of 1000
624   molecules were first equilibrated under ambient pressure and
# Line 717 | Line 719 | gradients were established by applying a set of target
719   in volume. Following adjustment of the box volume, equilibrations in
720   both the canonical and microcanonical ensembles were carried out. With
721   the simulation cell divided evenly into 10 slabs, different thermal
722 < gradients were established by applying a set of target thermal
721 < transfer fluxes.
722 > gradients were established by applying a set of target thermal fluxes.
723  
724   The results for the thermal conductivity of gold are shown in Table
725   \ref{AuThermal}.  In these calculations, the end and middle slabs were
726 < excluded in thermal gradient linear regession. EAM predicts slightly
727 < larger thermal conductivities than QSC.  However, both values are
728 < smaller than experimental value by a factor of more than 200. This
726 > excluded from the thermal gradient linear regession. EAM predicts
727 > slightly larger thermal conductivities than QSC.  However, both values
728 > are smaller than experimental value by a factor of more than 200. This
729   behavior has been observed previously by Richardson and Clancy, and
730   has been attributed to the lack of electronic contribution in these
731   force fields.\cite{Clancy:1992} It should be noted that the density of
# Line 785 | Line 786 | molecules within 3 \AA radius of any gold atom.  The f
786   relax under ambient temperature and pressure.  A separate (but
787   identically sized) box of SPC/E water was also equilibrated at ambient
788   conditions.  The two boxes were combined by removing all water
789 < molecules within 3 \AA radius of any gold atom.  The final
789 > molecules within 3 \AA~ radius of any gold atom.  The final
790   configuration contained 1862 SPC/E water molecules.
791  
792   The Spohr potential was adopted in depicting the interaction between
# Line 799 | Line 800 | glass cages have predicted values for $G$ between 100
800   phase.\cite{Cahill:793,RevModPhys.61.605} Experiments on the thermal
801   conductivity of gold nanoparticles and nanorods in solvent and in
802   glass cages have predicted values for $G$ between 100 and 350
803 < (MW/m$^2$/K).  The experiments typically have multiple gold surfaces
804 < that have been protected by a capping agent (citrate or CTAB) or which
805 < are in direct contact with various glassy solids.  In these cases, the
806 < acoustic impedance mismatch would be substantially reduced, leading to
807 < much higher interfacial conductances.  It is also possible, however,
808 < that the lack of electronic effects that gives rise to the low thermal
809 < conductivity of EAM gold is also causing a low reading for this
810 < particular interface.
803 > (MW/m$^2$/K), two orders of magnitude larger than the value reported
804 > here.  The experiments typically have multiple surfaces that have been
805 > protected by ionic surfactants, either
806 > citrate\cite{Wilson:2002uq,plech:195423} or cetyltrimethylammonium
807 > bromide (CTAB), or which are in direct contact with various glassy
808 > solids.  In these cases, the acoustic impedance mismatch would be
809 > substantially reduced, leading to much higher interfacial
810 > conductances.  It is also possible, however, that the lack of
811 > electronic effects that gives rise to the low thermal conductivity of
812 > EAM gold is also causing a low reading for this particular interface.
813  
814 < Under this low thermal conductance, both gold and water phase have
815 < sufficient time to eliminate temperature difference inside
816 < respectively (Figure \ref{interface} b). With indistinguishable
817 < temperature difference within respective phase, it is valid to assume
818 < that the temperature difference between gold and water on surface
819 < would be approximately the same as the difference between the gold and
820 < water phase. This assumption enables convenient calculation of $G$
818 < using Eq.  \ref{interfaceCalc} instead of measuring temperatures of
819 < thin layer of water and gold close enough to surface, which would have
820 < greater fluctuation and lower accuracy. Reported results (Table
821 < \ref{interfaceRes}) are of two orders of magnitude smaller than our
822 < calculations on homogeneous systems, and thus have larger relative
823 < errors than our calculation results on homogeneous systems.
814 > Under this low thermal conductance, both gold and water phases have
815 > sufficient time to eliminate local temperature differences (Fig.
816 > \ref{interface}). With flat thermal profiles within each phase, it is
817 > valid to assume that the temperature difference between gold and water
818 > surfaces would be approximately the same as the difference between the
819 > gold and water bulk regions.  This assumption enables convenient
820 > calculation of $G$ using Eq. \ref{interfaceCalc}.
821  
822   \begin{figure}
823   \includegraphics[width=\linewidth]{interface}
# Line 860 | Line 857 | NIVS-RNEMD simulation method is developed and tested o
857  
858  
859   \section{Conclusions}
860 < NIVS-RNEMD simulation method is developed and tested on various
861 < systems. Simulation results demonstrate its validity in thermal
862 < conductivity calculations, from Lennard-Jones fluid to multi-atom
863 < molecule like water and metal crystals. NIVS-RNEMD improves
864 < non-Boltzmann-Maxwell distributions, which exist inb previous RNEMD
865 < methods. Furthermore, it develops a valid means for unphysical thermal
860 >
861 > Our simulations demonstrate that validity of non-isotropic velocity
862 > scaling (NIVS) in RNEMD calculations of thermal conductivity in atomic
863 > and molecular liquids and solids.  NIVS-RNEMD improves the problematic
864 > velocity distributions which can develop in other RNEMD methods.
865 > Furthermore, it provides a means for carrying out non-physical thermal
866   transfer between different species of molecules, and thus extends its
867 < applicability to interfacial systems. Our calculation of gold/water
868 < interfacial thermal conductivity demonstrates this advantage over
869 < previous RNEMD methods. NIVS-RNEMD has also limited application on
870 < shear viscosity calculations, but could cause temperature difference
871 < among different dimensions under high momentum flux. Modification is
872 < necessary to extend the applicability of NIVS-RNEMD in shear viscosity
873 < calculations.
867 > applicability to interfacial systems. Our calculation of the gold /
868 > water interfacial thermal conductivity demonstrates this advantage
869 > over previous RNEMD methods.  NIVS-RNEMD also has limited applications
870 > for shear viscosity calculations, but has the potential to cause
871 > temperature anisotropy under high momentum fluxes. Further work will
872 > be necessary to eliminate the one-dimensional heating if shear
873 > viscosities are required.
874  
875   \section{Acknowledgments}
876   The authors would like to thank Craig Tenney and Ed Maginn for many

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