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# Line 29 | Line 29
29   9.0in \textwidth 6.5in \brokenpenalty=10000
30  
31   % double space list of tables and figures
32 < % \AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
32 > % \AtBeginDelayedFloats{\renewcomand{\baselinestretch}{1.66}}
33   \setlength{\abovecaptionskip}{20 pt}
34   \setlength{\belowcaptionskip}{30 pt}
35  
# Line 79 | Line 79 | We have adapted the Velocity Shearing and Scaling Reve
79   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
80   \section{Introduction}
81  
82 + Non-equilibrium Molecular Dynamics (NEMD) methods impose a temperature
83 + or velocity {\it gradient} on a
84 + system,\cite{ASHURST:1975tg,Evans:1982zk,ERPENBECK:1984sp,MAGINN:1993hc,Berthier:2002ij,Evans:2002ai,Schelling:2002dp,PhysRevA.34.1449,JiangHao_jp802942v}
85 + and use linear response theory to connect the resulting thermal or
86 + momentum flux to transport coefficients of bulk materials.  However,
87 + for heterogeneous systems, such as phase boundaries or interfaces, it
88 + is often unclear what shape of gradient should be imposed at the
89 + boundary between materials.
90  
91 + \begin{figure}
92 + \includegraphics[width=\linewidth]{figures/npVSS}
93 + \caption{Schematics of periodic (left) and non-periodic (right)
94 +  Velocity Shearing and Scaling RNEMD. A kinetic energy or momentum
95 +  flux is applied from region B to region A. Thermal gradients are
96 +  depicted by a color gradient. Linear or angular velocity gradients
97 +  are shown as arrows.}
98 + \label{fig:VSS}
99 + \end{figure}
100 +
101 + Reverse Non-Equilibrium Molecular Dynamics (RNEMD) methods impose an
102 + unphysical {\it flux} between different regions or ``slabs'' of the
103 + simulation
104 + box.\cite{MullerPlathe:1997xw,ISI:000080382700030,Kuang:2010uq} The
105 + system responds by developing a temperature or velocity {\it gradient}
106 + between the two regions.  The gradients which develop in response to
107 + the applied flux are then related (via linear response theory) to the
108 + transport coefficient of interest. Since the amount of the applied
109 + flux is known exactly, and measurement of a gradient is generally less
110 + complicated, imposed-flux methods typically take shorter simulation
111 + times to obtain converged results. At interfaces, the observed
112 + gradients often exhibit near-discontinuities at the boundaries between
113 + dissimilar materials.  RNEMD methods do not need many trajectories to
114 + provide information about transport properties, and they have become
115 + widely used to compute thermal and mechanical transport in both
116 + homogeneous liquids and
117 + solids~\cite{MullerPlathe:1997xw,ISI:000080382700030,Maginn:2010} as
118 + well as heterogeneous
119 + interfaces.\cite{garde:nl2005,garde:PhysRevLett2009,kuang:AuThl}
120 +
121   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
122   % **METHODOLOGY**
123   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
124 < \section{Methodology}
124 > \section{Velocity Shearing and Scaling (VSS) for non-periodic systems}
125 > The VSS-RNEMD approach uses a series of simultaneous velocity shearing
126 > and scaling exchanges between the two slabs.\cite{2012MolPh.110..691K}
127 > This method imposes energy and momentum conservation constraints while
128 > simultaneously creating a desired flux between the two slabs.  These
129 > constraints ensure that all configurations are sampled from the same
130 > microcanonical (NVE) ensemble.
131  
132 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
133 < % NON-PERIODIC DYNAMICS
134 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
135 < \subsection{Dynamics for non-periodic systems}
132 > We have extended the VSS method for use in {\it non-periodic}
133 > simulations, in which the ``slabs'' have been generalized to two
134 > separated regions of space.  These regions could be defined as
135 > concentric spheres (as in figure \ref{fig:npVSS}), or one of the regions
136 > can be defined in terms of a dynamically changing ``hull'' comprising
137 > the surface atoms of the cluster.  This latter definition is identical
138 > to the hull used in the Langevin Hull algorithm.
139  
140 < We have run all tests using the Langevin Hull nonperiodic simulation methodology.\cite{Vardeman2011} The Langevin Hull is especially useful for simulating heterogeneous mixtures of materials with different compressibilities, which are typically problematic for traditional affine transform methods. We have had success applying this method to
141 < several different systems including bare metal nanoparticles, liquid water clusters, and explicitly solvated nanoparticles. Calculated physical properties such as the isothermal compressibility of water and the bulk modulus of gold nanoparticles are in good agreement with previous theoretical and experimental results. The Langevin Hull uses a Delaunay tesselation to create a dynamic convex hull composed of triangular facets with vertices at atomic sites. Atomic sites included in the hull are coupled to an external bath defined by a temperature, pressure and viscosity. Atoms not included in the hull are subject to standard Newtonian dynamics. For these tests, thermal coupling to the bath was turned off to avoid interference with any imposed kinetic flux. Systems containing liquids were run under moderate pressure ($\sim$ 5 atm) to avoid the formation of a substantial vapor phase.
140 > We present here a new set of constraints that are more general than
141 > the VSS constraints.  For the non-periodic variant, the constraints
142 > fix both the total energy and total {\it angular} momentum of the
143 > system while simultaneously imposing a thermal and angular momentum
144 > flux between the two regions.
145  
146 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
147 < % NON-PERIODIC RNEMD
148 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
149 < \subsection{VSS-RNEMD for non-periodic systems}
100 <
101 < The most useful RNEMD approach developed so far utilizes a series of
102 < simultaneous velocity shearing and scaling (VSS) exchanges between the two
103 < regions.\cite{Kuang2012} This method provides a set of conservation constraints
104 < while simultaneously creating a desired flux between the two regions. Satisfying
105 < the constraint equations ensures that the new configurations are sampled from the
106 < same NVE ensemble.
107 <
108 < We have implemented this new method in OpenMD, our group molecular dynamics code.\cite{openmd} The adaptation of VSS-RNEMD for non-periodic systems is relatively
109 < straightforward. The major modifications to the method are the addition of a rotational shearing term and the use of more versatile hot / cold regions instead
110 < of rectangular slabs. A temperature profile along the $r$ coordinate is created by recording the average temperature of concentric spherical shells.
111 <
112 < % \begin{figure}
113 < %       \center{\includegraphics[width=7in]{figures/VSS}}
114 < %       \caption{Schematics of periodic (left) and nonperiodic (right) Velocity Shearing and Scaling RNEMD. A kinetic energy or momentum flux is applied from region B to region A. Thermal gradients are depicted by a color gradient. Linear or angular velocity gradients are shown as arrows.}
115 < %       \label{fig:VSS}
116 < % \end{figure}
117 <
118 < At each time interval, the particle velocities ($\mathbf{v}_i$ and
119 < $\mathbf{v}_j$) in the cold and hot shells ($C$ and $H$) are modified by a
120 < velocity scaling coefficient ($c$ and $h$), an additive linear velocity shearing
121 < term ($\mathbf{a}_c$ and $\mathbf{a}_h$), and an additive angular velocity
122 < shearing term ($\mathbf{b}_c$ and $\mathbf{b}_h$). Here, $\langle
123 < \mathbf{v}_{i,j} \rangle$ and $\langle \mathbf{\omega}_{i,j} \rangle$ are the
124 < average linear and angular velocities for each shell.
146 > After each $\Delta t$ time interval, the particle velocities
147 > ($\mathbf{v}_i$ and $\mathbf{v}_j$) in the two shells ($A$ and $B$)
148 > are modified by a velocity scaling coefficient ($a$ and $b$) and by a
149 > rotational shearing term ($\mathbf{c}_a$ and $\mathbf{c}_b$).
150   \begin{displaymath}
151   \begin{array}{rclcl}
152 < & \underline{~~~~~~~~~~\mathrm{scaling}~~~~~~~~~~} & &
153 < \underline{\mathrm{rotational \; shearing}} \\  \\
152 > & \underline{~~~~~~~~\mathrm{scaling}~~~~~~~~} & &
153 > \underline{\mathrm{rotational~shearing}} \\  \\
154   \mathbf{v}_i $~~~$\leftarrow &
155 <  c \, \left(\mathbf{v}_i - \langle \omega_c
156 <  \rangle \times r_i\right) & + & \mathbf{b}_c \times r_i \\
155 >  a \left(\mathbf{v}_i - \langle \omega_a
156 >  \rangle \times \mathbf{r}_i\right) & + & \mathbf{c}_a \times \mathbf{r}_i \\
157   \mathbf{v}_j $~~~$\leftarrow &
158 <  h \, \left(\mathbf{v}_j - \langle \omega_h
159 <  \rangle \times r_j\right) & + & \mathbf{b}_h \times r_j
158 >  b  \left(\mathbf{v}_j - \langle \omega_b
159 >  \rangle \times \mathbf{r}_j\right) & + & \mathbf{c}_b \times \mathbf{r}_j
160   \end{array}
161   \end{displaymath}
162 <
162 > Here $\langle\mathbf{\omega}_a\rangle$ and
163 > $\langle\mathbf{\omega}_b\rangle$ are the instantaneous angular
164 > velocities of each shell, and $\mathbf{r}_i$ is the position of
165 > particle $i$ relative to a fixed point in space (usually the center of
166 > mass of the cluster).  Particles in the shells also receive an
167 > additive ``angular shear'' to their velocities.  The amount of shear
168 > is governed by the imposed angular momentum flux,
169 > $\mathbf{j}_r(\mathbf{L})$,
170   \begin{eqnarray}
171 < \mathbf{b}_c & = & - \mathbf{j}_r(\mathbf{L}) \; \Delta \, t \; I_c^{-1} + \langle \omega_c \rangle \label{eq:bc}\\
172 < \mathbf{b}_h & = & + \mathbf{j}_r(\mathbf{L}) \; \Delta \, t \; I_h^{-1} + \langle \omega_h \rangle \label{eq:bh}
171 > \mathbf{c}_a & = & - \mathbf{j}_r(\mathbf{L}) \cdot
172 > \overleftrightarrow{I_a}^{-1} \Delta t   + \langle \omega_a \rangle \label{eq:bc}\\
173 > \mathbf{c}_b & = & + \mathbf{j}_r(\mathbf{L}) \cdot
174 > \overleftrightarrow{I_b}^{-1}  \Delta t  + \langle \omega_b \rangle \label{eq:bh}
175   \end{eqnarray}
176 + where $\overleftrightarrow{I}_{\{a,b\}}$ is the moment of inertia tensor for
177 + each of the two shells.
178  
179 < The total energy is constrained via two quadratic formulae,
179 > To simultaneously impose a thermal flux ($J_r$) between the shells we
180 > use energy conservation constraints,
181   \begin{eqnarray}
182 < K_c - J_r \; \Delta \, t & = & c^2 \, (K_c - \frac{1}{2}\langle \omega_c \rangle \cdot I_c\langle \omega_c \rangle) + \frac{1}{2} \mathbf{b}_c \cdot I_c \, \mathbf{b}_c \label{eq:Kc}\\
183 < K_h + J_r \; \Delta \, t & = & h^2 \, (K_h - \frac{1}{2}\langle \omega_h \rangle \cdot I_h\langle \omega_h \rangle) + \frac{1}{2} \mathbf{b}_h \cdot I_h \, \mathbf{b}_h \label{eq:Kh}
182 > K_a - J_r \Delta t & = & a^2 \left(K_a - \frac{1}{2}\langle
183 > \omega_a \rangle \cdot \overleftrightarrow{I_a} \cdot \langle \omega_a
184 > \rangle \right) + \frac{1}{2} \mathbf{c}_a \cdot \overleftrightarrow{I_a}
185 > \cdot \mathbf{c}_a \label{eq:Kc}\\
186 > K_b + J_r \Delta t & = & b^2 \left(K_b - \frac{1}{2}\langle
187 > \omega_b \rangle \cdot \overleftrightarrow{I_b} \cdot \langle \omega_b
188 > \rangle \right) + \frac{1}{2} \mathbf{c}_b \cdot \overleftrightarrow{I_b} \cdot \mathbf{c}_b \label{eq:Kh}
189   \end{eqnarray}
190 + Simultaneous solution of these quadratic formulae for the scaling
191 + coefficients, $a$ and $b$, will ensure that the simulation samples
192 + from the original microcanonical (NVE) ensemble.  Here $K_{\{a,b\}}$
193 + is the instantaneous translational kinetic energy of each shell.  At
194 + each time interval, we solve for $a$, $b$, $\mathbf{c}_a$, and
195 + $\mathbf{c}_b$, subject to the imposed angular momentum flux,
196 + $j_r(\mathbf{L})$, and thermal flux, $J_r$ values.  The new particle
197 + velocities are computed, and the simulation continues. System
198 + configurations after the transformations have exactly the same energy
199 + ({\it and} angular momentum) as before the moves.
200  
201 < the simultaneous
202 < solution of which provide the velocity scaling coefficients $c$ and $h$. Given an
203 < imposed angular momentum flux, $\mathbf{j}_{r} \left( \mathbf{L} \right)$, and/or
204 < thermal flux, $J_r$, equations \ref{eq:bc} - \ref{eq:Kh} are sufficient to obtain
205 < the velocity scaling ($c$ and $h$) and shearing ($\mathbf{b}_c,\,$ and $\mathbf{b}_h$) at each time interval.
201 > As the simulation progresses, the velocity transformations can be
202 > performed on a regular basis, and the system will develop a
203 > temperature and/or angular velocity gradient in response to the
204 > applied flux.  Using the slope of the radial temperature or velocity
205 > gradients, it is quite simple to obtain both the thermal conductivity
206 > ($\lambda$) and shear viscosity ($\eta$),
207 > \begin{equation}
208 >  J_r = -\lambda \frac{\partial T}{\partial
209 >    r} \hspace{2in} j_r(\mathbf{L}_z) = -\eta \frac{\partial
210 >    \omega_z}{\partial r}
211 > \end{equation}
212 > of a liquid cluster.
213  
214 + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
215 + % NON-PERIODIC DYNAMICS
216 + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
217 + \subsection{Dynamics for non-periodic systems}
218 +
219 + We have run all tests using the Langevin Hull nonperiodic simulation methodology.\cite{Vardeman2011} The Langevin Hull is especially useful for simulating heterogeneous mixtures of materials with different compressibilities, which are typically problematic for traditional affine transform methods. We have had success applying this method to
220 + several different systems including bare metal nanoparticles, liquid water clusters, and explicitly solvated nanoparticles. Calculated physical properties such as the isothermal compressibility of water and the bulk modulus of gold nanoparticles are in good agreement with previous theoretical and experimental results. The Langevin Hull uses a Delaunay tesselation to create a dynamic convex hull composed of triangular facets with vertices at atomic sites. Atomic sites included in the hull are coupled to an external bath defined by a temperature, pressure and viscosity. Atoms not included in the hull are subject to standard Newtonian dynamics. For these tests, thermal coupling to the bath was turned off to avoid interference with any imposed flux. Systems containing liquids were run under moderate pressure ($\sim$ 5 atm) to avoid the formation of a substantial vapor phase.
221 +
222   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
223   % **COMPUTATIONAL DETAILS**
224   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Line 190 | Line 257 | The thermal conductivity, $\lambda$, can be calculated
257   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
258   \subsection{Thermal conductivities}
259  
260 < The thermal conductivity, $\lambda$, can be calculated using the imposed kinetic energy flux, $J_r$, and thermal gradient, $\frac{\partial T}{\partial r}$ measured from the resulting temperature profile
260 > Fourier's Law of heat conduction in radial coordinates is
261  
262   \begin{equation}
263 <        J_r = -\lambda \frac{\partial T}{\partial r}
263 >        q_r = -\lambda A \frac{dT}{dr}
264 >        \label{eq:fourier}
265   \end{equation}
266  
267 + Substituting the area of a sphere and integrating between $r = r_1$ and $r_2$ and $T = T_1$ and $T_2$, we arrive at an expression for the heat flow between the concentric spherical RNEMD shells:
268 +
269 + \begin{equation}
270 +        q_r = - \frac{4 \pi \lambda (T_2 - T_1)}{\frac{1}{r_1} - \frac{1}{r_2}}
271 +        \label{eq:Q}
272 + \end{equation}
273 +
274 + Once a stable thermal gradient has been established between the two regions, the thermal conductivity, $\lambda$, can be calculated using the the temperature difference between the selected RNEMD regions, the radii of the two shells, and the heat, $q_r$, transferred between the regions.
275 +
276 + \begin{equation}
277 +        \lambda = \frac{q_r (\frac{1}{r_2} - \frac{1}{r_1})}{4 \pi (T_2 - T_1)}
278 +        \label{eq:lambda}
279 + \end{equation}
280 +
281 + The heat transferred between the two RNEMD regions is the amount of transferred kinetic energy over the length of the simulation, t
282 +
283 + \begin{equation}
284 +        q_r = \frac{KE}{t}
285 +        \label{eq:heat}
286 + \end{equation}
287 +
288   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
289   % INTERFACIAL THERMAL CONDUCTANCE
290   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Line 217 | Line 306 | The slip length, $\delta$, is defined as the ratio of
306   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
307   \subsection{Interfacial friction}
308  
309 < The slip length, $\delta$, is defined as the ratio of the interfacial friction coefficient, $\kappa$, and dynamic solvent viscosity, $\eta$
309 > Analytical solutions for the rotational friction coefficients for a solvated spherical body of radius $r$ under ideal ``stick'' boundary conditions can be estimated using Stokes' law
310  
311   \begin{equation}
312 <        \delta = \frac{\eta}{\kappa}
312 >        \Xi^{rr} = 8 \pi \eta r^3
313 >        \label{eq:Xistick}.
314   \end{equation}
315  
316 < and is measured from a radial angular momentum profile generated from a nonperiodic VSS-RNEMD simulation.
316 > where $\eta$ is the dynamic viscosity of the surrounding solvent and was determined for TraPPE-UA hexane by applying a traditional VSS-RNEMD linear momentum flux to a periodic box of solvent under the same temperature and pressure conditions as the nonperiodic systems.
317  
228 Analytical solutions for the rotational friction coefficients for a solvated spherical body of radius $r$ under ``stick'' boundary conditions can be estimated using Stokes' law
229
230 \begin{equation}
231        \Xi = 8 \pi \eta r^3 \label{eq:Xi}.
232 \end{equation}
233
234 where $\eta$ is the dynamic viscosity of the surrounding solvent and was determined for TraPPE-UA hexane under these condition by applying a traditional VSS-RNEMD linear momentum flux to a periodic box of solvent.
235
318   For general ellipsoids with semiaxes $a$, $b$, and $c$, Perrin's extension of Stokes' law provides exact solutions for symmetric prolate $(a \geq b = c)$ and oblate $(a < b = c)$ ellipsoids. For simplicity, we define a Perrin Factor, $S$,
319  
320   \begin{equation}
321 <        S = \frac{2}{\sqrt{a^2 - b^2}} ln \left[ \frac{a + \sqrt{a^2 - b^2}}{b} \right]. \label{eq:S}
321 >        S = \frac{2}{\sqrt{a^2 - b^2}} ln \left[ \frac{a + \sqrt{a^2 - b^2}}{b} \right].        \label{eq:S}
322   \end{equation}
323  
324   For a prolate ellipsoidal rod, demonstrated here, the rotational resistance tensor $\Xi$ is a $3 \times 3$ diagonal matrix with elements
325   \begin{equation}
326          \Xi^{rr}_a = \frac{32 \pi}{2} \eta \frac{ \left( a^2 - b^2 \right) b^2}{2a - b^2 S}
327 < \label{eq:Xia}
327 >        \label{eq:Xia}
328 > \end{equation}\vspace{-0.45in}\\
329 > \begin{equation}
330 >        \Xi^{rr}_{b,c} = \frac{32 \pi}{2} \eta \frac{ \left( a^4 - b^4 \right)}{ \left( 2a^2 - b^2 \right)S - 2a}.
331 >        \label{eq:Xibc}
332   \end{equation}
333 +
334 + The effective rotational friction coefficient at the interface can be extracted from nonperiodic VSS-RNEMD simulations quite easily using the applied torque ($\tau$) and the observed angular velocity of the gold structure ($\omega_{Au}$)
335 +
336   \begin{equation}
337 <        \Xi^{rr}_{b,c} = \frac{32 \pi}{2} \eta \frac{ \left( a^4 - b^4 \right)}{ \left( 2a^2 - b^2 \right)S - 2a}.                                      \label{eq:Xibc}
337 >        \Xi^{rr}_{\mathit{eff}} = \frac{\tau}{\omega_{Au}}
338 >        \label{eq:Xieff}
339   \end{equation}
340  
341 + The applied torque required to overcome the interfacial friction and maintain constant rotation of the gold is
342 +
343 + \begin{equation}
344 +        \tau = \frac{L}{2 t}
345 +        \label{eq:tau}  
346 + \end{equation}
347 +
348 + where $L$ is the total angular momentum exchanged between the two RNEMD regions and $t$ is the length of the simulation.
349 +
350   % However, the friction between hexane solvent and gold more likely falls within ``slip'' boundary conditions. Hu and Zwanzig\cite{Zwanzig} investigated the rotational friction coefficients for spheroids under slip boundary conditions and obtained numerial results for a scaling factor as a function of $\tau$, the ratio of the shorter semiaxes and the longer semiaxis of the spheroid. For the sphere and prolate ellipsoid shown here, the values of $\tau$ are $1$ and $0.3939$, respectively. According to the values tabulated by Hu and Zwanzig, the sphere friction coefficient approaches $0$, while the ellipsoidal friction coefficient must be scaled by a factor of $0.880$ to account for the reduced interfacial friction under ``slip'' boundary conditions.
351  
352 < Another useful quantity is the friction factor $f$, or the friction coefficient of a non-spherical shape divided by the friction coefficient of a sphere of equivalent volume. The nanoparticle and ellipsoidal nanorod dimensions used here were specifically chosen to create structures with equal volumes.
352 > % Another useful quantity is the friction factor $f$, or the friction coefficient of a non-spherical shape divided by the friction coefficient of a sphere of equivalent volume. The nanoparticle and ellipsoidal nanorod dimensions used here were specifically chosen to create structures with equal volumes.
353  
354   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
355   % **TESTS AND APPLICATIONS**
# Line 262 | Line 361 | Calculated values for the thermal conductivity of a 40
361   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
362   \subsection{Thermal conductivities}
363  
364 < Calculated values for the thermal conductivity of a 40 \AA$~$ radius gold nanoparticle (15707 atoms) at different kinetic energy flux values are shown in Table \ref{table:goldconductivity}. For these calculations, the hot and cold slabs were excluded from the linear regression of the thermal gradient. The measured linear slope $\langle dT / dr \rangle$ is linearly dependent on the applied kinetic energy flux $J_r$. Calculated thermal conductivity values compare well with previous bulk QSC values of 1.08 -- 1.26 W m$^{-1}$ K$^{-1}$\cite{Kuang2010}, though still significantly lower than the experimental value of 320 W m$^{-1}$ K$^{-1}$, as the QSC force field neglects significant electronic contributions to heat conduction. The small increase relative to previous simulated bulk values is due to a slight increase in gold density -- as expected, an increase in density results in higher thermal conductivity values. The increased density is a result of nanoparticle curvature relative to an infinite bulk slab, which introduces surface tension that increases ambient density.
364 > Calculated values for the thermal conductivity of a 40 \AA$~$ radius gold nanoparticle (15707 atoms) at different kinetic energy flux values are shown in Table \ref{table:goldTC}. For these calculations, the hot and cold slabs were excluded from the linear regression of the thermal gradient. The measured linear slope $\langle dT / dr \rangle$ is linearly dependent on the applied kinetic energy flux $J_r$. Calculated thermal conductivity values compare well with previous bulk QSC values of 1.08 -- 1.26 W m$^{-1}$ K$^{-1}$\cite{Kuang2010}, though still significantly lower than the experimental value of 320 W m$^{-1}$ K$^{-1}$, as the QSC force field neglects significant electronic contributions to heat conduction.
365  
366 + % The small increase relative to previous simulated bulk values is due to a slight increase in gold density -- as expected, an increase in density results in higher thermal conductivity values. The increased density is a result of nanoparticle curvature relative to an infinite bulk slab, which introduces surface tension that increases ambient density.
367 +
368   \begin{longtable}{ccc}
369   \caption{Calculated thermal conductivity of a crystalline gold nanoparticle of radius 40 \AA. Calculations were performed at 300 K and ambient density. Gold-gold interactions are described by the Quantum Sutton-Chen potential.}
370   \\ \hline \hline
371   {$J_r$} & {$\langle dT / dr \rangle$} & {$\boldsymbol \lambda$}\\
372   {\small(kcal fs$^{-1}$ \AA$^{-2}$)} & {\small(K \AA$^{-1}$)} & {\small(W m$^{-1}$ K$^{-1}$)}\\ \hline
373 < 3.25$\times 10^{-6}$ & 0.11435 & 1.9753 \\
374 < 6.50$\times 10^{-6}$ & 0.2324 & 1.9438 \\
375 < 1.30$\times 10^{-5}$ & 0.44922 & 2.0113 \\
376 < 3.25$\times 10^{-5}$ & 1.1802 & 1.9139 \\
377 < 6.50$\times 10^{-5}$ & 2.339 & 1.9314
373 > 3.25$\times 10^{-6}$ & 0.11435 & 1.0143 \\
374 > 6.50$\times 10^{-6}$ & 0.2324 & 0.9982 \\
375 > 1.30$\times 10^{-5}$ & 0.44922 & 1.0328 \\
376 > 3.25$\times 10^{-5}$ & 1.1802 & 0.9828 \\
377 > 6.50$\times 10^{-5}$ & 2.339 & 0.9918 \\
378 > \hline
379 > This work & & 1.0040
380   \\ \hline \hline
381 < \label{table:goldconductivity}
381 > \label{table:goldTC}
382   \end{longtable}
383  
384 < Calculated values for the thermal conductivity of a cluster of 6912 SPC/E water molecules are shown in Table \ref{table:waterconductivity}.
384 > Calculated values for the thermal conductivity of a cluster of 6912 SPC/E water molecules are shown in Table \ref{table:waterTC}. As with the gold nanoparticle thermal conductivity calculations, the RNEMD regions were excluded from the $\langle dT / dr \rangle$ fit. Again, the measured slope is linearly dependent on the applied kinetic energy flux $J_r$. The average calculated thermal conductivity from this work, $0.8841$ W m$^{-1}$ K$^{-1}$, compares very well to previous nonequilibrium molecular dynamics results (0.81 and 0.87 W m$^{-1}$ K$^{-1}$\cite{Romer2012, Zhang2005}) and experimental values (0.607 W m$^{-1}$ K$^{-1}$\cite{WagnerKruse})
385  
386   \begin{longtable}{ccc}
387 < \caption{Calculated thermal conductivity of a cluster of 6912 SPC/E water molecules. Calculations were performed at 300 K and ambient density.}
387 > \caption{Calculated thermal conductivity of a cluster of 6912 SPC/E water molecules. Calculations were performed at 300 K and 5 atm.}
388   \\ \hline \hline
389   {$J_r$} & {$\langle dT / dr \rangle$} & {$\boldsymbol \lambda$}\\
390   {\small(kcal fs$^{-1}$ \AA$^{-2}$)} & {\small(K \AA$^{-1}$)} & {\small(W m$^{-1}$ K$^{-1}$)}\\ \hline
391 < 1.00$\times 10^{-5}$ & 0.38683 & 1.79665486\\
392 < 3.00$\times 10^{-5}$ & 1.1643 & 1.79077557\\
393 < 6.00$\times 10^{-5}$ & 2.2262 & 1.87314707\\
394 < \hline \hline
395 < \label{table:waterconductivity}
391 > 1$\times 10^{-5}$ & 0.38683 & 0.8698 \\
392 > 3$\times 10^{-5}$ & 1.1643 & 0.9098 \\
393 > 6$\times 10^{-5}$ & 2.2262 & 0.8727 \\
394 > \hline
395 > This work & & 0.8841 \\
396 > Zhang, et al\cite{Zhang2005} & & 0.81 \\
397 > R$\ddot{\mathrm{o}}$mer, et al\cite{Romer2012} & & 0.87 \\
398 > Experiment\cite{WagnerKruse} & & 0.61
399 > \\ \hline \hline
400 > \label{table:waterTC}
401   \end{longtable}
402  
403   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Line 298 | Line 406 | Calculated values for the thermal conductivity of a cl
406   \subsection{Interfacial thermal conductance}
407  
408   \begin{longtable}{ccc}
409 < \caption{Caption.}
409 > \caption{Calculated interfacial thermal conductance (G) values for gold nanoparticles of varying radii solvated in explicit TraPPE-UA hexane. The nanoparticle G values are compared to previous results for a gold slab in TraPPE-UA hexane, revealing increased interfacial thermal conductance for non-planar interfaces.}
410   \\ \hline \hline
411 < {Nanoparticle Radius} & {$\boldsymbol \lambda$}\\
412 < {\small(\AA)} & {\small(W m$^{-1}$ K$^{-1}$)}\\ \hline
413 < 20 & 59.66\\
414 < 30 & 57.88\\
415 < 40 & \\
416 < $\infty$ & \\
411 > {Nanoparticle Radius} & {G}\\
412 > {\small(\AA)} & {\small(W m$^{-2}$ K$^{-1}$)}\\ \hline
413 > 20 & {49.3} \\
414 > 30 & {46.9} \\
415 > 40 & {47.3} \\
416 > slab & {30.2} \\
417   \hline \hline
418 < \label{table:waterconductivity}
418 > \label{table:interfacialconductance}
419   \end{longtable}
420  
421   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Line 315 | Line 423 | Table \ref{table:interfacialfrictionstick} shows the c
423   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
424   \subsection{Interfacial friction}
425  
426 < Table \ref{table:interfacialfrictionstick} shows the calculated interfacial friction coefficients $\kappa$ for spherical gold nanoparticles and a prolate ellipsoidal gold nanorod in TraPPE-UA hexane. An angular momentum flux was applied between the A and B regions defined as the gold structure and hexane molecules beyond a certain radius, respectively. The resulting angular velocity gradient resulted in the gold structure rotating about the prescribed axis within the solvent.
426 > Table \ref{table:couple} shows the calculated rotational friction coefficients $\Xi^{rr}$ for spherical gold nanoparticles and a prolate ellipsoidal gold nanorod in TraPPE-UA hexane. An angular momentum flux was applied between the A and B regions defined as the gold structure and hexane molecules beyond a certain radius, respectively. The resulting angular velocity gradient causes the gold structure to rotate about the prescribed axis.
427          
428 < \begin{longtable}{lccccc}
429 < \caption{Calculated ``stick'' interfacial friction coefficients ($\kappa$) and friction factors ($f$) of gold nanostructures solvated in TraPPE-UA hexane at 230 K. The ellipsoid is oriented with the long axis along the $z$ direction.}
428 > \begin{longtable}{lcccc}
429 > \caption{Comparison of rotational friction coefficients under ideal ``stick'' conditions ($\Xi^{rr}_{\mathit{stick}}$) calculated via Stokes' and Perrin's laws and effective rotational friction coefficients ($\Xi^{rr}_{\mathit{eff}}$) of gold nanostructures solvated in TraPPE-UA hexane at 230 K. The ellipsoid is oriented with the long axis along the $z$ direction.}
430   \\ \hline \hline
431 < {Structure} & {Axis of Rotation} & {$\kappa_{VSS}$} & {$\kappa_{calc}$} & {$f_{VSS}$} & {$f_{calc}$}\\
432 < {} & {} & {\small($10^{-29}$ Pa s m$^{3}$)} & {\small($10^{-29}$ Pa s m$^{3}$)} & {} & {}\\  \hline
433 < {Sphere (r = 20 \AA)} & {$x = y = z$} & {} & {6.13239} & {1} & {1}\\
434 < {Sphere (r = 30 \AA)} & {$x = y = z$} & {} & {20.6968} & {1} & {1}\\
435 < {Sphere (r = 40 \AA)} & {$x = y = z$} & {} & {49.0591} & {1} & {1}\\
436 < {Prolate Ellipsoid} & {$x = y$} & {} & {8.22846} & {} & {1.92477}\\
437 < {Prolate Ellipsoid} & {$z$} & {} & {3.28634} & {} & {0.768726}\\
431 > {Structure} & {Axis of Rotation} & {$\Xi^{rr}_{\mathit{stick}}$} & {$\Xi^{rr}_{\mathit{eff}}$} & {$\Xi^{rr}_{\mathit{eff}}$ / $\Xi^{rr}_{\mathit{stick}}$}\\
432 > {} & {} & {\small(amu A$^2$ fs$^{-1}$)} & {\small(amu A$^2$ fs$^{-1}$)} & \\  \hline
433 > Sphere (r = 20 \AA) & {$x = y = z$} & {3314} & {2386} & {0.720}\\
434 > Sphere (r = 30 \AA) & {$x = y = z$} & {11749} & {8415} & {0.716}\\
435 > Sphere (r = 40 \AA) & {$x = y = z$} & {34464} & {47544} & {1.380}\\
436 > Prolate Ellipsoid & {$x = y$} & {4991} & {3128} & {0.627}\\
437 > Prolate Ellipsoid & {$z$} & {1993} & {1590} & {0.798}\\
438    \hline \hline
439 < \label{table:interfacialfrictionstick}
439 > \label{table:couple}
440   \end{longtable}
441  
334 % \begin{longtable}{lccc}
335 % \caption{Calculated ``slip'' interfacial friction coefficients ($\kappa$) and friction factors ($f$) of gold nanostructures solvated in TraPPE-UA hexane. The ellipsoid is oriented with the long axis along the $z$ direction.}
336 % \\ \hline \hline
337 % {Structure} & {Axis of rotation} & {$\kappa_{VSS}$} & {$\kappa_{calc}$}\\
338 % {} & {} & {\small($10^{-29}$ Pa s m$^{3}$)} & {\small($10^{-29}$ Pa s m$^{3}$)}\\  \hline
339 % {Sphere} & {$x = y = z$} & {} & {0}\\
340 % {Prolate Ellipsoid} & {$x = y$} & {} & {0}\\
341 % {Prolate Ellipsoid} & {$z$} & {} & {7.9295392}\\  \hline \hline
342 % \label{table:interfacialfrictionslip}
343 % \end{longtable}
442  
443 +
444   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
445   % **DISCUSSION**
446   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

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