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\begin{document} |
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\begin{abstract} |
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|
48 |
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We have developed a Non-Isotropic Velocity Scaling algorithm for |
49 |
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setting up and maintaining stable thermal gradients in non-equilibrium |
50 |
< |
molecular dynamics simulations. This approach effectively imposes |
51 |
< |
unphysical thermal flux even between particles of different |
52 |
< |
identities, conserves linear momentum and kinetic energy, and |
53 |
< |
minimally perturbs the velocity profile of a system when compared with |
54 |
< |
previous RNEMD methods. We have used this method to simulate thermal |
55 |
< |
conductance at metal / organic solvent interfaces both with and |
56 |
< |
without the presence of thiol-based capping agents. We obtained |
57 |
< |
values comparable with experimental values, and observed significant |
58 |
< |
conductance enhancement with the presence of capping agents. Computed |
59 |
< |
power spectra indicate the acoustic impedance mismatch between metal |
60 |
< |
and liquid phase is greatly reduced by the capping agents and thus |
61 |
< |
leads to higher interfacial thermal transfer efficiency. |
48 |
> |
With the Non-Isotropic Velocity Scaling algorithm (NIVS) we have |
49 |
> |
developed, an unphysical thermal flux can be effectively set up even |
50 |
> |
for non-homogeneous systems like interfaces in non-equilibrium |
51 |
> |
molecular dynamics simulations. In this work, this algorithm is |
52 |
> |
applied for simulating thermal conductance at metal / organic solvent |
53 |
> |
interfaces with various coverages of butanethiol capping |
54 |
> |
agents. Different solvents and force field models were tested. Our |
55 |
> |
results suggest that the United-Atom models are able to provide an |
56 |
> |
estimate of the interfacial thermal conductivity comparable to |
57 |
> |
experiments in our simulations with satisfactory computational |
58 |
> |
efficiency. From our results, the acoustic impedance mismatch between |
59 |
> |
metal and liquid phase is effectively reduced by the capping |
60 |
> |
agents, and thus leads to interfacial thermal conductance |
61 |
> |
enhancement. Furthermore, this effect is closely related to the |
62 |
> |
capping agent coverage on the metal surfaces and the type of solvent |
63 |
> |
molecules, and is affected by the models used in the simulations. |
64 |
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|
65 |
|
\end{abstract} |
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|
73 |
|
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% |
74 |
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|
75 |
|
\section{Introduction} |
74 |
– |
|
76 |
|
Interfacial thermal conductance is extensively studied both |
77 |
< |
experimentally and computationally, and systems with interfaces |
78 |
< |
present are generally heterogeneous. Although interfaces are commonly |
79 |
< |
barriers to heat transfer, it has been |
80 |
< |
reported\cite{doi:10.1021/la904855s} that under specific circustances, |
81 |
< |
e.g. with certain capping agents present on the surface, interfacial |
82 |
< |
conductance can be significantly enhanced. However, heat conductance |
83 |
< |
of molecular and nano-scale interfaces will be affected by the |
84 |
< |
chemical details of the surface and is challenging to |
85 |
< |
experimentalist. The lower thermal flux through interfaces is even |
85 |
< |
more difficult to measure with EMD and forward NEMD simulation |
86 |
< |
methods. Therefore, developing good simulation methods will be |
87 |
< |
desirable in order to investigate thermal transport across interfaces. |
77 |
> |
experimentally and computationally\cite{cahill:793}, due to its |
78 |
> |
importance in nanoscale science and technology. Reliability of |
79 |
> |
nanoscale devices depends on their thermal transport |
80 |
> |
properties. Unlike bulk homogeneous materials, nanoscale materials |
81 |
> |
features significant presence of interfaces, and these interfaces |
82 |
> |
could dominate the heat transfer behavior of these |
83 |
> |
materials. Furthermore, these materials are generally heterogeneous, |
84 |
> |
which challenges traditional research methods for homogeneous |
85 |
> |
systems. |
86 |
|
|
87 |
+ |
Heat conductance of molecular and nano-scale interfaces will be |
88 |
+ |
affected by the chemical details of the surface. Experimentally, |
89 |
+ |
various interfaces have been investigated for their thermal |
90 |
+ |
conductance properties. Wang {\it et al.} studied heat transport |
91 |
+ |
through long-chain hydrocarbon monolayers on gold substrate at |
92 |
+ |
individual molecular level\cite{Wang10082007}; Schmidt {\it et al.} |
93 |
+ |
studied the role of CTAB on thermal transport between gold nanorods |
94 |
+ |
and solvent\cite{doi:10.1021/jp8051888}; Juv\'e {\it et al.} studied |
95 |
+ |
the cooling dynamics, which is controlled by thermal interface |
96 |
+ |
resistence of glass-embedded metal |
97 |
+ |
nanoparticles\cite{PhysRevB.80.195406}. Although interfaces are |
98 |
+ |
commonly barriers for heat transport, Alper {\it et al.} suggested |
99 |
+ |
that specific ligands (capping agents) could completely eliminate this |
100 |
+ |
barrier ($G\rightarrow\infty$)\cite{doi:10.1021/la904855s}. |
101 |
+ |
|
102 |
+ |
Theoretical and computational models have also been used to study the |
103 |
+ |
interfacial thermal transport in order to gain an understanding of |
104 |
+ |
this phenomena at the molecular level. Recently, Hase and coworkers |
105 |
+ |
employed Non-Equilibrium Molecular Dynamics (NEMD) simulations to |
106 |
+ |
study thermal transport from hot Au(111) substrate to a self-assembled |
107 |
+ |
monolayer of alkylthiol with relatively long chain (8-20 carbon |
108 |
+ |
atoms)\cite{hase:2010,hase:2011}. However, ensemble averaged |
109 |
+ |
measurements for heat conductance of interfaces between the capping |
110 |
+ |
monolayer on Au and a solvent phase has yet to be studied. |
111 |
+ |
The comparatively low thermal flux through interfaces is |
112 |
+ |
difficult to measure with Equilibrium MD or forward NEMD simulation |
113 |
+ |
methods. Therefore, the Reverse NEMD (RNEMD) methods would have the |
114 |
+ |
advantage of having this difficult to measure flux known when studying |
115 |
+ |
the thermal transport across interfaces, given that the simulation |
116 |
+ |
methods being able to effectively apply an unphysical flux in |
117 |
+ |
non-homogeneous systems. |
118 |
+ |
|
119 |
|
Recently, we have developed the Non-Isotropic Velocity Scaling (NIVS) |
120 |
|
algorithm for RNEMD simulations\cite{kuang:164101}. This algorithm |
121 |
|
retains the desirable features of RNEMD (conservation of linear |
122 |
|
momentum and total energy, compatibility with periodic boundary |
123 |
|
conditions) while establishing true thermal distributions in each of |
124 |
< |
the two slabs. Furthermore, it allows more effective thermal exchange |
125 |
< |
between particles of different identities, and thus enables extensive |
126 |
< |
study of interfacial conductance. |
124 |
> |
the two slabs. Furthermore, it allows effective thermal exchange |
125 |
> |
between particles of different identities, and thus makes the study of |
126 |
> |
interfacial conductance much simpler. |
127 |
|
|
128 |
+ |
The work presented here deals with the Au(111) surface covered to |
129 |
+ |
varying degrees by butanethiol, a capping agent with short carbon |
130 |
+ |
chain, and solvated with organic solvents of different molecular |
131 |
+ |
properties. Different models were used for both the capping agent and |
132 |
+ |
the solvent force field parameters. Using the NIVS algorithm, the |
133 |
+ |
thermal transport across these interfaces was studied and the |
134 |
+ |
underlying mechanism for this phenomena was investigated. |
135 |
+ |
|
136 |
+ |
[MAY ADD WHY STUDY AU-THIOL SURFACE; CITE SHAOYI JIANG] |
137 |
+ |
|
138 |
|
\section{Methodology} |
139 |
< |
\subsection{Algorithm} |
140 |
< |
There have been many algorithms for computing thermal conductivity |
141 |
< |
using molecular dynamics simulations. However, interfacial conductance |
142 |
< |
is at least an order of magnitude smaller. This would make the |
143 |
< |
calculation even more difficult for those slowly-converging |
144 |
< |
equilibrium methods. Imposed-flux non-equilibrium |
139 |
> |
\subsection{Imposd-Flux Methods in MD Simulations} |
140 |
> |
For systems with low interfacial conductivity one must have a method |
141 |
> |
capable of generating relatively small fluxes, compared to those |
142 |
> |
required for bulk conductivity. This requirement makes the calculation |
143 |
> |
even more difficult for those slowly-converging equilibrium |
144 |
> |
methods\cite{Viscardy:2007lq}. |
145 |
> |
Forward methods impose gradient, but in interfacial conditions it is |
146 |
> |
not clear what behavior to impose at the boundary... |
147 |
> |
Imposed-flux reverse non-equilibrium |
148 |
|
methods\cite{MullerPlathe:1997xw} have the flux set {\it a priori} and |
149 |
< |
the response of temperature or momentum gradients are easier to |
150 |
< |
measure than the flux, if unknown, and thus, is a preferable way to |
151 |
< |
the forward NEMD methods. Although the momentum swapping approach for |
152 |
< |
flux-imposing can be used for exchanging energy between particles of |
153 |
< |
different identity, the kinetic energy transfer efficiency is affected |
154 |
< |
by the mass difference between the particles, which limits its |
112 |
< |
application on heterogeneous interfacial systems. |
149 |
> |
the thermal response becomes easier to |
150 |
> |
measure than the flux. Although M\"{u}ller-Plathe's original momentum |
151 |
> |
swapping approach can be used for exchanging energy between particles |
152 |
> |
of different identity, the kinetic energy transfer efficiency is |
153 |
> |
affected by the mass difference between the particles, which limits |
154 |
> |
its application on heterogeneous interfacial systems. |
155 |
|
|
156 |
< |
The non-isotropic velocity scaling (NIVS)\cite{kuang:164101} approach in |
157 |
< |
non-equilibrium MD simulations is able to impose relatively large |
158 |
< |
kinetic energy flux without obvious perturbation to the velocity |
159 |
< |
distribution of the simulated systems. Furthermore, this approach has |
156 |
> |
The non-isotropic velocity scaling (NIVS)\cite{kuang:164101} approach to |
157 |
> |
non-equilibrium MD simulations is able to impose a wide range of |
158 |
> |
kinetic energy fluxes without obvious perturbation to the velocity |
159 |
> |
distributions of the simulated systems. Furthermore, this approach has |
160 |
|
the advantage in heterogeneous interfaces in that kinetic energy flux |
161 |
|
can be applied between regions of particles of arbitary identity, and |
162 |
< |
the flux quantity is not restricted by particle mass difference. |
162 |
> |
the flux will not be restricted by difference in particle mass. |
163 |
|
|
164 |
|
The NIVS algorithm scales the velocity vectors in two separate regions |
165 |
|
of a simulation system with respective diagonal scaling matricies. To |
166 |
|
determine these scaling factors in the matricies, a set of equations |
167 |
|
including linear momentum conservation and kinetic energy conservation |
168 |
< |
constraints and target momentum/energy flux satisfaction is |
169 |
< |
solved. With the scaling operation applied to the system in a set |
170 |
< |
frequency, corresponding momentum/temperature gradients can be built, |
171 |
< |
which can be used for computing transportation properties and other |
172 |
< |
applications related to momentum/temperature gradients. The NIVS |
131 |
< |
algorithm conserves momenta and energy and does not depend on an |
132 |
< |
external thermostat. |
168 |
> |
constraints and target energy flux satisfaction is solved. With the |
169 |
> |
scaling operation applied to the system in a set frequency, bulk |
170 |
> |
temperature gradients can be easily established, and these can be used |
171 |
> |
for computing thermal conductivities. The NIVS algorithm conserves |
172 |
> |
momenta and energy and does not depend on an external thermostat. |
173 |
|
|
174 |
< |
(wondering how much detail of algorithm should be put here...) |
174 |
> |
\subsection{Defining Interfacial Thermal Conductivity $G$} |
175 |
> |
For interfaces with a relatively low interfacial conductance, the bulk |
176 |
> |
regions on either side of an interface rapidly come to a state in |
177 |
> |
which the two phases have relatively homogeneous (but distinct) |
178 |
> |
temperatures. The interfacial thermal conductivity $G$ can therefore |
179 |
> |
be approximated as: |
180 |
> |
\begin{equation} |
181 |
> |
G = \frac{E_{total}}{2 t L_x L_y \left( \langle T_\mathrm{hot}\rangle - |
182 |
> |
\langle T_\mathrm{cold}\rangle \right)} |
183 |
> |
\label{lowG} |
184 |
> |
\end{equation} |
185 |
> |
where ${E_{total}}$ is the imposed non-physical kinetic energy |
186 |
> |
transfer and ${\langle T_\mathrm{hot}\rangle}$ and ${\langle |
187 |
> |
T_\mathrm{cold}\rangle}$ are the average observed temperature of the |
188 |
> |
two separated phases. |
189 |
|
|
136 |
– |
\subsection{Force Field Parameters} |
137 |
– |
Our simulation systems consists of metal gold lattice slab solvated by |
138 |
– |
organic solvents. In order to study the role of capping agents in |
139 |
– |
interfacial thermal conductance, butanethiol is chosen to cover gold |
140 |
– |
surfaces in comparison to no capping agent present. |
141 |
– |
|
142 |
– |
The Au-Au interactions in metal lattice slab is described by the |
143 |
– |
quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The QSC |
144 |
– |
potentials include zero-point quantum corrections and are |
145 |
– |
reparametrized for accurate surface energies compared to the |
146 |
– |
Sutton-Chen potentials\cite{Chen90}. |
147 |
– |
|
148 |
– |
Straight chain {\it n}-hexane and aromatic toluene are respectively |
149 |
– |
used as solvents. For hexane, both United-Atom\cite{TraPPE-UA.alkanes} |
150 |
– |
and All-Atom\cite{OPLSAA} force fields are used for comparison; for |
151 |
– |
toluene, United-Atom\cite{TraPPE-UA.alkylbenzenes} force fields are |
152 |
– |
used with rigid body constraints applied. (maybe needs more details |
153 |
– |
about rigid body) |
154 |
– |
|
155 |
– |
Buatnethiol molecules are used as capping agent for some of our |
156 |
– |
simulations. United-Atom\cite{TraPPE-UA.thiols} and All-Atom models |
157 |
– |
are respectively used corresponding to the force field type of |
158 |
– |
solvent. |
159 |
– |
|
160 |
– |
To describe the interactions between metal Au and non-metal capping |
161 |
– |
agent and solvent, we refer to Vlugt\cite{vlugt:cpc2007154} and derive |
162 |
– |
other interactions which are not parametrized in their work. (can add |
163 |
– |
hautman and klein's paper here and more discussion; need to put |
164 |
– |
aromatic-metal interaction approximation here) |
165 |
– |
|
166 |
– |
[TABULATED FORCE FIELD PARAMETERS NEEDED] |
167 |
– |
|
168 |
– |
\section{Computational Details} |
169 |
– |
\subsection{System Geometry} |
170 |
– |
Our simulation systems consists of a lattice Au slab with the (111) |
171 |
– |
surface perpendicular to the $z$-axis, and a solvent layer between the |
172 |
– |
periodic Au slabs along the $z$-axis. To set up the interfacial |
173 |
– |
system, the Au slab is first equilibrated without solvent under room |
174 |
– |
pressure and a desired temperature. After the metal slab is |
175 |
– |
equilibrated, United-Atom or All-Atom butanethiols are replicated on |
176 |
– |
the Au surface, each occupying the (??) among three Au atoms, and is |
177 |
– |
equilibrated under NVT ensemble. According to (CITATION), the maximal |
178 |
– |
thiol capacity on Au surface is $1/3$ of the total number of surface |
179 |
– |
Au atoms. |
180 |
– |
|
181 |
– |
\cite{packmol} |
182 |
– |
|
183 |
– |
\subsection{Simulation Parameters} |
184 |
– |
|
190 |
|
When the interfacial conductance is {\it not} small, there are two |
191 |
< |
ways to define $G$. If we assume the temperature is discretely |
192 |
< |
different on two sides of the interface, $G$ can be calculated with |
193 |
< |
the thermal flux applied $J$ and the temperature difference measured |
194 |
< |
$\Delta T$ as: |
191 |
> |
ways to define $G$. |
192 |
> |
|
193 |
> |
One way is to assume the temperature is discrete on the two sides of |
194 |
> |
the interface. $G$ can be calculated using the applied thermal flux |
195 |
> |
$J$ and the maximum temperature difference measured along the thermal |
196 |
> |
gradient max($\Delta T$), which occurs at the Gibbs deviding surface |
197 |
> |
(Figure \ref{demoPic}): |
198 |
|
\begin{equation} |
199 |
|
G=\frac{J}{\Delta T} |
200 |
|
\label{discreteG} |
201 |
|
\end{equation} |
202 |
< |
We can as well assume a continuous temperature profile along the |
203 |
< |
thermal gradient axis $z$ and define $G$ as the change of bulk thermal |
204 |
< |
conductivity $\lambda$ at a defined interfacial point: |
202 |
> |
|
203 |
> |
\begin{figure} |
204 |
> |
\includegraphics[width=\linewidth]{method} |
205 |
> |
\caption{Interfacial conductance can be calculated by applying an |
206 |
> |
(unphysical) kinetic energy flux between two slabs, one located |
207 |
> |
within the metal and another on the edge of the periodic box. The |
208 |
> |
system responds by forming a thermal response or a gradient. In |
209 |
> |
bulk liquids, this gradient typically has a single slope, but in |
210 |
> |
interfacial systems, there are distinct thermal conductivity |
211 |
> |
domains. The interfacial conductance, $G$ is found by measuring the |
212 |
> |
temperature gap at the Gibbs dividing surface, or by using second |
213 |
> |
derivatives of the thermal profile.} |
214 |
> |
\label{demoPic} |
215 |
> |
\end{figure} |
216 |
> |
|
217 |
> |
The other approach is to assume a continuous temperature profile along |
218 |
> |
the thermal gradient axis (e.g. $z$) and define $G$ at the point where |
219 |
> |
the magnitude of thermal conductivity $\lambda$ change reach its |
220 |
> |
maximum, given that $\lambda$ is well-defined throughout the space: |
221 |
|
\begin{equation} |
222 |
|
G^\prime = \Big|\frac{\partial\lambda}{\partial z}\Big| |
223 |
|
= \Big|\frac{\partial}{\partial z}\left(-J_z\Big/ |
224 |
|
\left(\frac{\partial T}{\partial z}\right)\right)\Big| |
225 |
< |
= J_z\Big|\frac{\partial^2 T}{\partial z^2}\Big| |
225 |
> |
= |J_z|\Big|\frac{\partial^2 T}{\partial z^2}\Big| |
226 |
|
\Big/\left(\frac{\partial T}{\partial z}\right)^2 |
227 |
|
\label{derivativeG} |
228 |
|
\end{equation} |
229 |
+ |
|
230 |
|
With the temperature profile obtained from simulations, one is able to |
231 |
|
approximate the first and second derivatives of $T$ with finite |
232 |
< |
difference method and thus calculate $G^\prime$. |
232 |
> |
difference methods and thus calculate $G^\prime$. |
233 |
|
|
234 |
< |
In what follows, both definitions are used for calculation and comparison. |
234 |
> |
In what follows, both definitions have been used for calculation and |
235 |
> |
are compared in the results. |
236 |
|
|
237 |
< |
\section{Results} |
238 |
< |
\subsection{Toluene Solvent} |
237 |
> |
To compare the above definitions ($G$ and $G^\prime$), we have modeled |
238 |
> |
a metal slab with its (111) surfaces perpendicular to the $z$-axis of |
239 |
> |
our simulation cells. Both with and without capping agents on the |
240 |
> |
surfaces, the metal slab is solvated with simple organic solvents, as |
241 |
> |
illustrated in Figure \ref{gradT}. |
242 |
|
|
243 |
< |
The simulations follow a protocol similar to the previous gold/water |
244 |
< |
interfacial systems. The results (Table \ref{AuThiolToluene}) show a |
245 |
< |
significant conductance enhancement compared to the gold/water |
246 |
< |
interface without capping agent and agree with available experimental |
247 |
< |
data. This indicates that the metal-metal potential, though not |
248 |
< |
predicting an accurate bulk metal thermal conductivity, does not |
249 |
< |
greatly interfere with the simulation of the thermal conductance |
250 |
< |
behavior across a non-metal interface. The solvent model is not |
222 |
< |
particularly volatile, so the simulation cell does not expand |
223 |
< |
significantly under higher temperature. We did not observe a |
224 |
< |
significant conductance decrease when the temperature was increased to |
225 |
< |
300K. The results show that the two definitions used for $G$ yield |
226 |
< |
comparable values, though $G^\prime$ tends to be smaller. |
243 |
> |
With the simulation cell described above, we are able to equilibrate |
244 |
> |
the system and impose an unphysical thermal flux between the liquid |
245 |
> |
and the metal phase using the NIVS algorithm. By periodically applying |
246 |
> |
the unphysical flux, we are able to obtain a temperature profile and |
247 |
> |
its spatial derivatives. These quantities enable the evaluation of the |
248 |
> |
interfacial thermal conductance of a surface. Figure \ref{gradT} is an |
249 |
> |
example how those applied thermal fluxes can be used to obtain the 1st |
250 |
> |
and 2nd derivatives of the temperature profile. |
251 |
|
|
252 |
+ |
\begin{figure} |
253 |
+ |
\includegraphics[width=\linewidth]{gradT} |
254 |
+ |
\caption{A sample of Au-butanethiol/hexane interfacial system and the |
255 |
+ |
temperature profile after a kinetic energy flux is imposed to |
256 |
+ |
it. The 1st and 2nd derivatives of the temperature profile can be |
257 |
+ |
obtained with finite difference approximation (lower panel).} |
258 |
+ |
\label{gradT} |
259 |
+ |
\end{figure} |
260 |
+ |
|
261 |
+ |
\section{Computational Details} |
262 |
+ |
\subsection{Simulation Protocol} |
263 |
+ |
The NIVS algorithm has been implemented in our MD simulation code, |
264 |
+ |
OpenMD\cite{Meineke:2005gd,openmd}, and was used for our |
265 |
+ |
simulations. Different metal slab thickness (layer numbers of Au) were |
266 |
+ |
simulated. Metal slabs were first equilibrated under atmospheric |
267 |
+ |
pressure (1 atm) and a desired temperature (e.g. 200K). After |
268 |
+ |
equilibration, butanethiol capping agents were placed at three-fold |
269 |
+ |
sites on the Au(111) surfaces. The maximum butanethiol capacity on Au |
270 |
+ |
surface is $1/3$ of the total number of surface Au |
271 |
+ |
atoms\cite{vlugt:cpc2007154}[CITE CHEM REV]. |
272 |
+ |
A series of different coverages was |
273 |
+ |
investigated in order to study the relation between coverage and |
274 |
+ |
interfacial conductance. |
275 |
+ |
|
276 |
+ |
The capping agent molecules were allowed to migrate during the |
277 |
+ |
simulations. They distributed themselves uniformly and sampled a |
278 |
+ |
number of three-fold sites throughout out study. Therefore, the |
279 |
+ |
initial configuration would not noticeably affect the sampling of a |
280 |
+ |
variety of configurations of the same coverage, and the final |
281 |
+ |
conductance measurement would be an average effect of these |
282 |
+ |
configurations explored in the simulations. [MAY NEED SNAPSHOTS] |
283 |
+ |
|
284 |
+ |
After the modified Au-butanethiol surface systems were equilibrated |
285 |
+ |
under canonical ensemble, organic solvent molecules were packed in the |
286 |
+ |
previously empty part of the simulation cells\cite{packmol}. Two |
287 |
+ |
solvents were investigated, one which has little vibrational overlap |
288 |
+ |
with the alkanethiol and a planar shape (toluene), and one which has |
289 |
+ |
similar vibrational frequencies and chain-like shape ({\it n}-hexane). |
290 |
+ |
|
291 |
+ |
The space filled by solvent molecules, i.e. the gap between |
292 |
+ |
periodically repeated Au-butanethiol surfaces should be carefully |
293 |
+ |
chosen. A very long length scale for the thermal gradient axis ($z$) |
294 |
+ |
may cause excessively hot or cold temperatures in the middle of the |
295 |
+ |
solvent region and lead to undesired phenomena such as solvent boiling |
296 |
+ |
or freezing when a thermal flux is applied. Conversely, too few |
297 |
+ |
solvent molecules would change the normal behavior of the liquid |
298 |
+ |
phase. Therefore, our $N_{solvent}$ values were chosen to ensure that |
299 |
+ |
these extreme cases did not happen to our simulations. And the |
300 |
+ |
corresponding spacing is usually $35[?] \sim 75$\AA. |
301 |
+ |
|
302 |
+ |
The initial configurations generated are further equilibrated with the |
303 |
+ |
$x$ and $y$ dimensions fixed, only allowing length scale change in $z$ |
304 |
+ |
dimension. This is to ensure that the equilibration of liquid phase |
305 |
+ |
does not affect the metal crystal structure in $x$ and $y$ dimensions. |
306 |
+ |
To investigate this effect, comparisons were made with simulations |
307 |
+ |
allowed to change $L_x$ and $L_y$ during NPT equilibration, and the |
308 |
+ |
results are shown in later sections. After ensuring the liquid phase |
309 |
+ |
reaches equilibrium at atmospheric pressure (1 atm), further |
310 |
+ |
equilibration are followed under NVT and then NVE ensembles. |
311 |
+ |
|
312 |
+ |
After the systems reach equilibrium, NIVS is implemented to impose a |
313 |
+ |
periodic unphysical thermal flux between the metal and the liquid |
314 |
+ |
phase. Most of our simulations are under an average temperature of |
315 |
+ |
$\sim$200K. Therefore, this flux usually comes from the metal to the |
316 |
+ |
liquid so that the liquid has a higher temperature and would not |
317 |
+ |
freeze due to excessively low temperature. This induced temperature |
318 |
+ |
gradient is stablized and the simulation cell is devided evenly into |
319 |
+ |
N slabs along the $z$-axis and the temperatures of each slab are |
320 |
+ |
recorded. When the slab width $d$ of each slab is the same, the |
321 |
+ |
derivatives of $T$ with respect to slab number $n$ can be directly |
322 |
+ |
used for $G^\prime$ calculations: |
323 |
+ |
\begin{equation} |
324 |
+ |
G^\prime = |J_z|\Big|\frac{\partial^2 T}{\partial z^2}\Big| |
325 |
+ |
\Big/\left(\frac{\partial T}{\partial z}\right)^2 |
326 |
+ |
= |J_z|\Big|\frac{1}{d^2}\frac{\partial^2 T}{\partial n^2}\Big| |
327 |
+ |
\Big/\left(\frac{1}{d}\frac{\partial T}{\partial n}\right)^2 |
328 |
+ |
= |J_z|\Big|\frac{\partial^2 T}{\partial n^2}\Big| |
329 |
+ |
\Big/\left(\frac{\partial T}{\partial n}\right)^2 |
330 |
+ |
\label{derivativeG2} |
331 |
+ |
\end{equation} |
332 |
+ |
|
333 |
+ |
\subsection{Force Field Parameters} |
334 |
+ |
Our simulations include various components. Figure \ref{demoMol} |
335 |
+ |
demonstrates the sites defined for both United-Atom and All-Atom |
336 |
+ |
models of the organic solvent and capping agent molecules in our |
337 |
+ |
simulations. Force field parameter descriptions are needed for |
338 |
+ |
interactions both between the same type of particles and between |
339 |
+ |
particles of different species. |
340 |
+ |
|
341 |
+ |
\begin{figure} |
342 |
+ |
\includegraphics[width=\linewidth]{structures} |
343 |
+ |
\caption{Structures of the capping agent and solvents utilized in |
344 |
+ |
these simulations. The chemically-distinct sites (a-e) are expanded |
345 |
+ |
in terms of constituent atoms for both United Atom (UA) and All Atom |
346 |
+ |
(AA) force fields. Most parameters are from |
347 |
+ |
Refs. \protect\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} (UA) and |
348 |
+ |
\protect\cite{OPLSAA} (AA). Cross-interactions with the Au atoms are given |
349 |
+ |
in Table \ref{MnM}.} |
350 |
+ |
\label{demoMol} |
351 |
+ |
\end{figure} |
352 |
+ |
|
353 |
+ |
The Au-Au interactions in metal lattice slab is described by the |
354 |
+ |
quantum Sutton-Chen (QSC) formulation\cite{PhysRevB.59.3527}. The QSC |
355 |
+ |
potentials include zero-point quantum corrections and are |
356 |
+ |
reparametrized for accurate surface energies compared to the |
357 |
+ |
Sutton-Chen potentials\cite{Chen90}. |
358 |
+ |
|
359 |
+ |
For both solvent molecules, straight chain {\it n}-hexane and aromatic |
360 |
+ |
toluene, United-Atom (UA) and All-Atom (AA) models are used |
361 |
+ |
respectively. The TraPPE-UA |
362 |
+ |
parameters\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} are used |
363 |
+ |
for our UA solvent molecules. In these models, sites are located at |
364 |
+ |
the carbon centers for alkyl groups. Bonding interactions, including |
365 |
+ |
bond stretches and bends and torsions, were used for intra-molecular |
366 |
+ |
sites not separated by more than 3 bonds. Otherwise, for non-bonded |
367 |
+ |
interactions, Lennard-Jones potentials are used. [MORE CITATION?] |
368 |
+ |
|
369 |
+ |
By eliminating explicit hydrogen atoms, these models are simple and |
370 |
+ |
computationally efficient, while maintains good accuracy. However, the |
371 |
+ |
TraPPE-UA for alkanes is known to predict a lower boiling point than |
372 |
+ |
experimental values. Considering that after an unphysical thermal flux |
373 |
+ |
is applied to a system, the temperature of ``hot'' area in the liquid |
374 |
+ |
phase would be significantly higher than the average, to prevent over |
375 |
+ |
heating and boiling of the liquid phase, the average temperature in |
376 |
+ |
our simulations should be much lower than the liquid boiling point. |
377 |
+ |
|
378 |
+ |
For UA-toluene model, the non-bonded potentials between |
379 |
+ |
inter-molecular sites have a similar Lennard-Jones formulation. For |
380 |
+ |
intra-molecular interactions, considering the stiffness of the benzene |
381 |
+ |
ring, rigid body constraints are applied for further computational |
382 |
+ |
efficiency. All bonds in the benzene ring and between the ring and the |
383 |
+ |
methyl group remain rigid during the progress of simulations. |
384 |
+ |
|
385 |
+ |
Besides the TraPPE-UA models, AA models for both organic solvents are |
386 |
+ |
included in our studies as well. For hexane, the OPLS-AA\cite{OPLSAA} |
387 |
+ |
force field is used. Additional explicit hydrogen sites were |
388 |
+ |
included. Besides bonding and non-bonded site-site interactions, |
389 |
+ |
partial charges and the electrostatic interactions were added to each |
390 |
+ |
CT and HC site. For toluene, the United Force Field developed by |
391 |
+ |
Rapp\'{e} {\it et al.}\cite{doi:10.1021/ja00051a040} is |
392 |
+ |
adopted. Without the rigid body constraints, bonding interactions were |
393 |
+ |
included. For the aromatic ring, improper torsions (inversions) were |
394 |
+ |
added as an extra potential for maintaining the planar shape. |
395 |
+ |
[MORE CITATION?] |
396 |
+ |
|
397 |
+ |
The capping agent in our simulations, the butanethiol molecules can |
398 |
+ |
either use UA or AA model. The TraPPE-UA force fields includes |
399 |
+ |
parameters for thiol molecules\cite{TraPPE-UA.thiols} and are used for |
400 |
+ |
UA butanethiol model in our simulations. The OPLS-AA also provides |
401 |
+ |
parameters for alkyl thiols. However, alkyl thiols adsorbed on Au(111) |
402 |
+ |
surfaces do not have the hydrogen atom bonded to sulfur. To adapt this |
403 |
+ |
change and derive suitable parameters for butanethiol adsorbed on |
404 |
+ |
Au(111) surfaces, we adopt the S parameters from Luedtke and |
405 |
+ |
Landman\cite{landman:1998} and modify parameters for its neighbor C |
406 |
+ |
atom for charge balance in the molecule. Note that the model choice |
407 |
+ |
(UA or AA) of capping agent can be different from the |
408 |
+ |
solvent. Regardless of model choice, the force field parameters for |
409 |
+ |
interactions between capping agent and solvent can be derived using |
410 |
+ |
Lorentz-Berthelot Mixing Rule: |
411 |
+ |
\begin{eqnarray} |
412 |
+ |
\sigma_{ij} & = & \frac{1}{2} \left(\sigma_{ii} + \sigma_{jj}\right) \\ |
413 |
+ |
\epsilon_{ij} & = & \sqrt{\epsilon_{ii}\epsilon_{jj}} |
414 |
+ |
\end{eqnarray} |
415 |
+ |
|
416 |
+ |
To describe the interactions between metal Au and non-metal capping |
417 |
+ |
agent and solvent particles, we refer to an adsorption study of alkyl |
418 |
+ |
thiols on gold surfaces by Vlugt {\it et |
419 |
+ |
al.}\cite{vlugt:cpc2007154} They fitted an effective Lennard-Jones |
420 |
+ |
form of potential parameters for the interaction between Au and |
421 |
+ |
pseudo-atoms CH$_x$ and S based on a well-established and widely-used |
422 |
+ |
effective potential of Hautman and Klein\cite{hautman:4994} for the |
423 |
+ |
Au(111) surface. As our simulations require the gold lattice slab to |
424 |
+ |
be non-rigid so that it could accommodate kinetic energy for thermal |
425 |
+ |
transport study purpose, the pair-wise form of potentials is |
426 |
+ |
preferred. |
427 |
+ |
|
428 |
+ |
Besides, the potentials developed from {\it ab initio} calculations by |
429 |
+ |
Leng {\it et al.}\cite{doi:10.1021/jp034405s} are adopted for the |
430 |
+ |
interactions between Au and aromatic C/H atoms in toluene. A set of |
431 |
+ |
pseudo Lennard-Jones parameters were provided for Au in their force |
432 |
+ |
fields. By using the Mixing Rule, this can be used to derive pair-wise |
433 |
+ |
potentials for non-bonded interactions between Au and non-metal sites. |
434 |
+ |
|
435 |
+ |
However, the Lennard-Jones parameters between Au and other types of |
436 |
+ |
particles, such as All-Atom normal alkanes in our simulations are not |
437 |
+ |
yet well-established. For these interactions, we attempt to derive |
438 |
+ |
their parameters using the Mixing Rule. To do this, Au pseudo |
439 |
+ |
Lennard-Jones parameters for ``Metal-non-Metal'' (MnM) interactions |
440 |
+ |
were first extracted from the Au-CH$_x$ parameters by applying the |
441 |
+ |
Mixing Rule reversely. Table \ref{MnM} summarizes these ``MnM'' |
442 |
+ |
parameters in our simulations. |
443 |
+ |
|
444 |
|
\begin{table*} |
445 |
|
\begin{minipage}{\linewidth} |
446 |
|
\begin{center} |
447 |
< |
\caption{Computed interfacial thermal conductivity ($G$ and |
448 |
< |
$G^\prime$) values for the Au/butanethiol/toluene interface at |
449 |
< |
different temperatures using a range of energy fluxes.} |
450 |
< |
|
235 |
< |
\begin{tabular}{cccc} |
447 |
> |
\caption{Non-bonded interaction parameters (including cross |
448 |
> |
interactions with Au atoms) for both force fields used in this |
449 |
> |
work.} |
450 |
> |
\begin{tabular}{lllllll} |
451 |
|
\hline\hline |
452 |
< |
$\langle T\rangle$ & $J_z$ & $G$ & $G^\prime$ \\ |
453 |
< |
(K) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ |
452 |
> |
& Site & $\sigma_{ii}$ & $\epsilon_{ii}$ & $q_i$ & |
453 |
> |
$\sigma_{Au-i}$ & $\epsilon_{Au-i}$ \\ |
454 |
> |
& & (\AA) & (kcal/mol) & ($e$) & (\AA) & (kcal/mol) \\ |
455 |
|
\hline |
456 |
< |
200 & 1.86 & 180 & 135 \\ |
457 |
< |
& 2.15 & 204 & 113 \\ |
458 |
< |
& 3.93 & 175 & 114 \\ |
459 |
< |
300 & 1.91 & 143 & 125 \\ |
460 |
< |
& 4.19 & 134 & 113 \\ |
456 |
> |
United Atom (UA) |
457 |
> |
&CH3 & 3.75 & 0.1947 & - & 3.54 & 0.2146 \\ |
458 |
> |
&CH2 & 3.95 & 0.0914 & - & 3.54 & 0.1749 \\ |
459 |
> |
&CHar & 3.695 & 0.1003 & - & 3.4625 & 0.1680 \\ |
460 |
> |
&CRar & 3.88 & 0.04173 & - & 3.555 & 0.1604 \\ |
461 |
> |
\hline |
462 |
> |
All Atom (AA) |
463 |
> |
&CT3 & 3.50 & 0.066 & -0.18 & 3.365 & 0.1373 \\ |
464 |
> |
&CT2 & 3.50 & 0.066 & -0.12 & 3.365 & 0.1373 \\ |
465 |
> |
&CTT & 3.50 & 0.066 & -0.065 & 3.365 & 0.1373 \\ |
466 |
> |
&HC & 2.50 & 0.030 & 0.06 & 2.865 & 0.09256 \\ |
467 |
> |
&CA & 3.55 & 0.070 & -0.115 & 3.173 & 0.0640 \\ |
468 |
> |
&HA & 2.42 & 0.030 & 0.115 & 2.746 & 0.0414 \\ |
469 |
> |
\hline |
470 |
> |
Both UA and AA |
471 |
> |
& S & 4.45 & 0.25 & - & 2.40 & 8.465 \\ |
472 |
|
\hline\hline |
473 |
|
\end{tabular} |
474 |
< |
\label{AuThiolToluene} |
474 |
> |
\label{MnM} |
475 |
|
\end{center} |
476 |
|
\end{minipage} |
477 |
|
\end{table*} |
478 |
|
|
479 |
< |
\subsection{Hexane Solvent} |
479 |
> |
\subsection{Vibrational Spectrum} |
480 |
|
|
481 |
< |
Using the united-atom model, different coverages of capping agent, |
482 |
< |
temperatures of simulations and numbers of solvent molecules were all |
483 |
< |
investigated and Table \ref{AuThiolHexaneUA} shows the results of |
484 |
< |
these computations. The number of hexane molecules in our simulations |
485 |
< |
does not affect the calculations significantly. However, a very long |
486 |
< |
length scale for the thermal gradient axis ($z$) may cause excessively |
260 |
< |
hot or cold temperatures in the middle of the solvent region and lead |
261 |
< |
to undesired phenomena such as solvent boiling or freezing, while too |
262 |
< |
few solvent molecules would change the normal behavior of the liquid |
263 |
< |
phase. Our $N_{hexane}$ values were chosen to ensure that these |
264 |
< |
extreme cases did not happen to our simulations. |
481 |
> |
[MAY ADD EQN'S] |
482 |
> |
To obtain these |
483 |
> |
spectra, one first runs a simulation in the NVE ensemble and collects |
484 |
> |
snapshots of configurations; these configurations are used to compute |
485 |
> |
the velocity auto-correlation functions, which is used to construct a |
486 |
> |
power spectrum via a Fourier transform. |
487 |
|
|
488 |
< |
Table \ref{AuThiolHexaneUA} enables direct comparison between |
489 |
< |
different coverages of capping agent, when other system parameters are |
490 |
< |
held constant. With high coverage of butanethiol on the gold surface, |
491 |
< |
the interfacial thermal conductance is enhanced |
492 |
< |
significantly. Interestingly, a slightly lower butanethiol coverage |
493 |
< |
leads to a moderately higher conductivity. This is probably due to |
494 |
< |
more solvent/capping agent contact when butanethiol molecules are |
495 |
< |
not densely packed, which enhances the interactions between the two |
496 |
< |
phases and lowers the thermal transfer barrier of this interface. |
497 |
< |
% [COMPARE TO AU/WATER IN PAPER] |
488 |
> |
\section{Results and Discussions} |
489 |
> |
[MAY HAVE A BRIEF SUMMARY] |
490 |
> |
\subsection{How Simulation Parameters Affects $G$} |
491 |
> |
[MAY NOT PUT AT FIRST] |
492 |
> |
We have varied our protocol or other parameters of the simulations in |
493 |
> |
order to investigate how these factors would affect the measurement of |
494 |
> |
$G$'s. It turned out that while some of these parameters would not |
495 |
> |
affect the results substantially, some other changes to the |
496 |
> |
simulations would have a significant impact on the measurement |
497 |
> |
results. |
498 |
|
|
499 |
< |
It is also noted that the overall simulation temperature is another |
500 |
< |
factor that affects the interfacial thermal conductance. One |
501 |
< |
possibility of this effect may be rooted in the decrease in density of |
502 |
< |
the liquid phase. We observed that when the average temperature |
503 |
< |
increases from 200K to 250K, the bulk hexane density becomes lower |
504 |
< |
than experimental value, as the system is equilibrated under NPT |
505 |
< |
ensemble. This leads to lower contact between solvent and capping |
506 |
< |
agent, and thus lower conductivity. |
499 |
> |
In some of our simulations, we allowed $L_x$ and $L_y$ to change |
500 |
> |
during equilibrating the liquid phase. Due to the stiffness of the |
501 |
> |
crystalline Au structure, $L_x$ and $L_y$ would not change noticeably |
502 |
> |
after equilibration. Although $L_z$ could fluctuate $\sim$1\% after a |
503 |
> |
system is fully equilibrated in the NPT ensemble, this fluctuation, as |
504 |
> |
well as those of $L_x$ and $L_y$ (which is significantly smaller), |
505 |
> |
would not be magnified on the calculated $G$'s, as shown in Table |
506 |
> |
\ref{AuThiolHexaneUA}. This insensivity to $L_i$ fluctuations allows |
507 |
> |
reliable measurement of $G$'s without the necessity of extremely |
508 |
> |
cautious equilibration process. |
509 |
|
|
510 |
< |
Conductivity values are more difficult to obtain under higher |
511 |
< |
temperatures. This is because the Au surface tends to undergo |
512 |
< |
reconstructions in relatively high temperatures. Surface Au atoms can |
513 |
< |
migrate outward to reach higher Au-S contact; and capping agent |
514 |
< |
molecules can be embedded into the surface Au layer due to the same |
515 |
< |
driving force. This phenomenon agrees with experimental |
516 |
< |
results\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}. A surface |
517 |
< |
fully covered in capping agent is more susceptible to reconstruction, |
518 |
< |
possibly because fully coverage prevents other means of capping agent |
295 |
< |
relaxation, such as migration to an empty neighbor three-fold site. |
510 |
> |
As stated in our computational details, the spacing filled with |
511 |
> |
solvent molecules can be chosen within a range. This allows some |
512 |
> |
change of solvent molecule numbers for the same Au-butanethiol |
513 |
> |
surfaces. We did this study on our Au-butanethiol/hexane |
514 |
> |
simulations. Nevertheless, the results obtained from systems of |
515 |
> |
different $N_{hexane}$ did not indicate that the measurement of $G$ is |
516 |
> |
susceptible to this parameter. For computational efficiency concern, |
517 |
> |
smaller system size would be preferable, given that the liquid phase |
518 |
> |
structure is not affected. |
519 |
|
|
520 |
< |
%MAY ADD MORE DATA TO TABLE |
520 |
> |
Our NIVS algorithm allows change of unphysical thermal flux both in |
521 |
> |
direction and in quantity. This feature extends our investigation of |
522 |
> |
interfacial thermal conductance. However, the magnitude of this |
523 |
> |
thermal flux is not arbitary if one aims to obtain a stable and |
524 |
> |
reliable thermal gradient. A temperature profile would be |
525 |
> |
substantially affected by noise when $|J_z|$ has a much too low |
526 |
> |
magnitude; while an excessively large $|J_z|$ that overwhelms the |
527 |
> |
conductance capacity of the interface would prevent a thermal gradient |
528 |
> |
to reach a stablized steady state. NIVS has the advantage of allowing |
529 |
> |
$J$ to vary in a wide range such that the optimal flux range for $G$ |
530 |
> |
measurement can generally be simulated by the algorithm. Within the |
531 |
> |
optimal range, we were able to study how $G$ would change according to |
532 |
> |
the thermal flux across the interface. For our simulations, we denote |
533 |
> |
$J_z$ to be positive when the physical thermal flux is from the liquid |
534 |
> |
to metal, and negative vice versa. The $G$'s measured under different |
535 |
> |
$J_z$ is listed in Table \ref{AuThiolHexaneUA} and |
536 |
> |
\ref{AuThiolToluene}. These results do not suggest that $G$ is |
537 |
> |
dependent on $J_z$ within this flux range. The linear response of flux |
538 |
> |
to thermal gradient simplifies our investigations in that we can rely |
539 |
> |
on $G$ measurement with only a couple $J_z$'s and do not need to test |
540 |
> |
a large series of fluxes. |
541 |
> |
|
542 |
|
\begin{table*} |
543 |
|
\begin{minipage}{\linewidth} |
544 |
|
\begin{center} |
545 |
|
\caption{Computed interfacial thermal conductivity ($G$ and |
546 |
< |
$G^\prime$) values for the Au/butanethiol/hexane interface |
547 |
< |
with united-atom model and different capping agent coverage |
548 |
< |
and solvent molecule numbers at different temperatures using a |
549 |
< |
range of energy fluxes.} |
546 |
> |
$G^\prime$) values for the 100\% covered Au-butanethiol/hexane |
547 |
> |
interfaces with UA model and different hexane molecule numbers |
548 |
> |
at different temperatures using a range of energy |
549 |
> |
fluxes. Error estimates indicated in parenthesis.} |
550 |
|
|
551 |
< |
\begin{tabular}{cccccc} |
551 |
> |
\begin{tabular}{ccccccc} |
552 |
|
\hline\hline |
553 |
< |
Thiol & $\langle T\rangle$ & & $J_z$ & $G$ & $G^\prime$ \\ |
554 |
< |
coverage (\%) & (K) & $N_{hexane}$ & (GW/m$^2$) & |
553 |
> |
$\langle T\rangle$ & $N_{hexane}$ & Fixed & $\rho_{hexane}$ & |
554 |
> |
$J_z$ & $G$ & $G^\prime$ \\ |
555 |
> |
(K) & & $L_x$ \& $L_y$? & (g/cm$^3$) & (GW/m$^2$) & |
556 |
|
\multicolumn{2}{c}{(MW/m$^2$/K)} \\ |
557 |
|
\hline |
558 |
< |
0.0 & 200 & 200 & 0.96 & 43.3 & 42.7 \\ |
559 |
< |
& & & 1.91 & 45.7 & 42.9 \\ |
560 |
< |
& & 166 & 0.96 & 43.1 & 53.4 \\ |
561 |
< |
88.9 & 200 & 166 & 1.94 & 172 & 108 \\ |
562 |
< |
100.0 & 250 & 200 & 0.96 & 81.8 & 67.0 \\ |
563 |
< |
& & 166 & 0.98 & 79.0 & 62.9 \\ |
564 |
< |
& & & 1.44 & 76.2 & 64.8 \\ |
565 |
< |
& 200 & 200 & 1.92 & 129 & 87.3 \\ |
566 |
< |
& & & 1.93 & 131 & 77.5 \\ |
567 |
< |
& & 166 & 0.97 & 115 & 69.3 \\ |
568 |
< |
& & & 1.94 & 125 & 87.1 \\ |
558 |
> |
200 & 266 & No & 0.672 & -0.96 & 102(3) & 80.0(0.8) \\ |
559 |
> |
& 200 & Yes & 0.694 & 1.92 & 129(11) & 87.3(0.3) \\ |
560 |
> |
& & Yes & 0.672 & 1.93 & 131(16) & 78(13) \\ |
561 |
> |
& & No & 0.688 & 0.96 & 125(16) & 90.2(15) \\ |
562 |
> |
& & & & 1.91 & 139(10) & 101(10) \\ |
563 |
> |
& & & & 2.83 & 141(6) & 89.9(9.8) \\ |
564 |
> |
& 166 & Yes & 0.679 & 0.97 & 115(19) & 69(18) \\ |
565 |
> |
& & & & 1.94 & 125(9) & 87.1(0.2) \\ |
566 |
> |
& & No & 0.681 & 0.97 & 141(30) & 78(22) \\ |
567 |
> |
& & & & 1.92 & 138(4) & 98.9(9.5) \\ |
568 |
> |
\hline |
569 |
> |
250 & 200 & No & 0.560 & 0.96 & 75(10) & 61.8(7.3) \\ |
570 |
> |
& & & & -0.95 & 49.4(0.3) & 45.7(2.1) \\ |
571 |
> |
& 166 & Yes & 0.570 & 0.98 & 79.0(3.5) & 62.9(3.0) \\ |
572 |
> |
& & No & 0.569 & 0.97 & 80.3(0.6) & 67(11) \\ |
573 |
> |
& & & & 1.44 & 76.2(5.0) & 64.8(3.8) \\ |
574 |
> |
& & & & -0.95 & 56.4(2.5) & 54.4(1.1) \\ |
575 |
> |
& & & & -1.85 & 47.8(1.1) & 53.5(1.5) \\ |
576 |
|
\hline\hline |
577 |
|
\end{tabular} |
578 |
|
\label{AuThiolHexaneUA} |
580 |
|
\end{minipage} |
581 |
|
\end{table*} |
582 |
|
|
583 |
< |
For the all-atom model, the liquid hexane phase was not stable under NPT |
584 |
< |
conditions. Therefore, the simulation length scale parameters are |
585 |
< |
adopted from previous equilibration results of the united-atom model |
586 |
< |
at 200K. Table \ref{AuThiolHexaneAA} shows the results of these |
587 |
< |
simulations. The conductivity values calculated with full capping |
588 |
< |
agent coverage are substantially larger than observed in the |
589 |
< |
united-atom model, and is even higher than predicted by |
590 |
< |
experiments. It is possible that our parameters for metal-non-metal |
591 |
< |
particle interactions lead to an overestimate of the interfacial |
592 |
< |
thermal conductivity, although the active C-H vibrations in the |
593 |
< |
all-atom model (which should not be appreciably populated at normal |
594 |
< |
temperatures) could also account for this high conductivity. The major |
343 |
< |
thermal transfer barrier of Au/butanethiol/hexane interface is between |
344 |
< |
the liquid phase and the capping agent, so extra degrees of freedom |
345 |
< |
such as the C-H vibrations could enhance heat exchange between these |
346 |
< |
two phases and result in a much higher conductivity. |
583 |
> |
Furthermore, we also attempted to increase system average temperatures |
584 |
> |
to above 200K. These simulations are first equilibrated in the NPT |
585 |
> |
ensemble under normal pressure. As stated above, the TraPPE-UA model |
586 |
> |
for hexane tends to predict a lower boiling point. In our simulations, |
587 |
> |
hexane had diffculty to remain in liquid phase when NPT equilibration |
588 |
> |
temperature is higher than 250K. Additionally, the equilibrated liquid |
589 |
> |
hexane density under 250K becomes lower than experimental value. This |
590 |
> |
expanded liquid phase leads to lower contact between hexane and |
591 |
> |
butanethiol as well.[MAY NEED SLAB DENSITY FIGURE] |
592 |
> |
And this reduced contact would |
593 |
> |
probably be accountable for a lower interfacial thermal conductance, |
594 |
> |
as shown in Table \ref{AuThiolHexaneUA}. |
595 |
|
|
596 |
+ |
A similar study for TraPPE-UA toluene agrees with the above result as |
597 |
+ |
well. Having a higher boiling point, toluene tends to remain liquid in |
598 |
+ |
our simulations even equilibrated under 300K in NPT |
599 |
+ |
ensembles. Furthermore, the expansion of the toluene liquid phase is |
600 |
+ |
not as significant as that of the hexane. This prevents severe |
601 |
+ |
decrease of liquid-capping agent contact and the results (Table |
602 |
+ |
\ref{AuThiolToluene}) show only a slightly decreased interface |
603 |
+ |
conductance. Therefore, solvent-capping agent contact should play an |
604 |
+ |
important role in the thermal transport process across the interface |
605 |
+ |
in that higher degree of contact could yield increased conductance. |
606 |
+ |
|
607 |
|
\begin{table*} |
608 |
|
\begin{minipage}{\linewidth} |
609 |
|
\begin{center} |
351 |
– |
|
610 |
|
\caption{Computed interfacial thermal conductivity ($G$ and |
611 |
< |
$G^\prime$) values for the Au/butanethiol/hexane interface |
612 |
< |
with all-atom model and different capping agent coverage at |
613 |
< |
200K using a range of energy fluxes.} |
611 |
> |
$G^\prime$) values for a 90\% coverage Au-butanethiol/toluene |
612 |
> |
interface at different temperatures using a range of energy |
613 |
> |
fluxes. Error estimates indicated in parenthesis.} |
614 |
|
|
615 |
< |
\begin{tabular}{cccc} |
615 |
> |
\begin{tabular}{ccccc} |
616 |
|
\hline\hline |
617 |
< |
Thiol & $J_z$ & $G$ & $G^\prime$ \\ |
618 |
< |
coverage (\%) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ |
617 |
> |
$\langle T\rangle$ & $\rho_{toluene}$ & $J_z$ & $G$ & $G^\prime$ \\ |
618 |
> |
(K) & (g/cm$^3$) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ |
619 |
|
\hline |
620 |
< |
0.0 & 0.95 & 28.5 & 27.2 \\ |
621 |
< |
& 1.88 & 30.3 & 28.9 \\ |
622 |
< |
100.0 & 2.87 & 551 & 294 \\ |
623 |
< |
& 3.81 & 494 & 193 \\ |
620 |
> |
200 & 0.933 & 2.15 & 204(12) & 113(12) \\ |
621 |
> |
& & -1.86 & 180(3) & 135(21) \\ |
622 |
> |
& & -3.93 & 176(5) & 113(12) \\ |
623 |
> |
\hline |
624 |
> |
300 & 0.855 & -1.91 & 143(5) & 125(2) \\ |
625 |
> |
& & -4.19 & 135(9) & 113(12) \\ |
626 |
|
\hline\hline |
627 |
|
\end{tabular} |
628 |
< |
\label{AuThiolHexaneAA} |
628 |
> |
\label{AuThiolToluene} |
629 |
|
\end{center} |
630 |
|
\end{minipage} |
631 |
|
\end{table*} |
632 |
|
|
633 |
< |
%subsubsection{Vibrational spectrum study on conductance mechanism} |
633 |
> |
Besides lower interfacial thermal conductance, surfaces in relatively |
634 |
> |
high temperatures are susceptible to reconstructions, when |
635 |
> |
butanethiols have a full coverage on the Au(111) surface. These |
636 |
> |
reconstructions include surface Au atoms migrated outward to the S |
637 |
> |
atom layer, and butanethiol molecules embedded into the original |
638 |
> |
surface Au layer. The driving force for this behavior is the strong |
639 |
> |
Au-S interactions in our simulations. And these reconstructions lead |
640 |
> |
to higher ratio of Au-S attraction and thus is energetically |
641 |
> |
favorable. Furthermore, this phenomenon agrees with experimental |
642 |
> |
results\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}. Vlugt |
643 |
> |
{\it et al.} had kept their Au(111) slab rigid so that their |
644 |
> |
simulations can reach 300K without surface reconstructions. Without |
645 |
> |
this practice, simulating 100\% thiol covered interfaces under higher |
646 |
> |
temperatures could hardly avoid surface reconstructions. However, our |
647 |
> |
measurement is based on assuming homogeneity on $x$ and $y$ dimensions |
648 |
> |
so that measurement of $T$ at particular $z$ would be an effective |
649 |
> |
average of the particles of the same type. Since surface |
650 |
> |
reconstructions could eliminate the original $x$ and $y$ dimensional |
651 |
> |
homogeneity, measurement of $G$ is more difficult to conduct under |
652 |
> |
higher temperatures. Therefore, most of our measurements are |
653 |
> |
undertaken at $\langle T\rangle\sim$200K. |
654 |
> |
|
655 |
> |
However, when the surface is not completely covered by butanethiols, |
656 |
> |
the simulated system is more resistent to the reconstruction |
657 |
> |
above. Our Au-butanethiol/toluene system had the Au(111) surfaces 90\% |
658 |
> |
covered by butanethiols, but did not see this above phenomena even at |
659 |
> |
$\langle T\rangle\sim$300K. The empty three-fold sites not occupied by |
660 |
> |
capping agents could help prevent surface reconstruction in that they |
661 |
> |
provide other means of capping agent relaxation. It is observed that |
662 |
> |
butanethiols can migrate to their neighbor empty sites during a |
663 |
> |
simulation. Therefore, we were able to obtain $G$'s for these |
664 |
> |
interfaces even at a relatively high temperature without being |
665 |
> |
affected by surface reconstructions. |
666 |
> |
|
667 |
> |
\subsection{Influence of Capping Agent Coverage on $G$} |
668 |
> |
To investigate the influence of butanethiol coverage on interfacial |
669 |
> |
thermal conductance, a series of different coverage Au-butanethiol |
670 |
> |
surfaces is prepared and solvated with various organic |
671 |
> |
molecules. These systems are then equilibrated and their interfacial |
672 |
> |
thermal conductivity are measured with our NIVS algorithm. Figure |
673 |
> |
\ref{coverage} demonstrates the trend of conductance change with |
674 |
> |
respect to different coverages of butanethiol. To study the isotope |
675 |
> |
effect in interfacial thermal conductance, deuterated UA-hexane is |
676 |
> |
included as well. |
677 |
> |
|
678 |
> |
It turned out that with partial covered butanethiol on the Au(111) |
679 |
> |
surface, the derivative definition for $G^\prime$ |
680 |
> |
(Eq. \ref{derivativeG}) was difficult to apply, due to the difficulty |
681 |
> |
in locating the maximum of change of $\lambda$. Instead, the discrete |
682 |
> |
definition (Eq. \ref{discreteG}) is easier to apply, as the Gibbs |
683 |
> |
deviding surface can still be well-defined. Therefore, $G$ (not |
684 |
> |
$G^\prime$) was used for this section. |
685 |
> |
|
686 |
> |
From Figure \ref{coverage}, one can see the significance of the |
687 |
> |
presence of capping agents. Even when a fraction of the Au(111) |
688 |
> |
surface sites are covered with butanethiols, the conductivity would |
689 |
> |
see an enhancement by at least a factor of 3. This indicates the |
690 |
> |
important role cappping agent is playing for thermal transport |
691 |
> |
phenomena on metal / organic solvent surfaces. |
692 |
> |
|
693 |
> |
Interestingly, as one could observe from our results, the maximum |
694 |
> |
conductance enhancement (largest $G$) happens while the surfaces are |
695 |
> |
about 75\% covered with butanethiols. This again indicates that |
696 |
> |
solvent-capping agent contact has an important role of the thermal |
697 |
> |
transport process. Slightly lower butanethiol coverage allows small |
698 |
> |
gaps between butanethiols to form. And these gaps could be filled with |
699 |
> |
solvent molecules, which acts like ``heat conductors'' on the |
700 |
> |
surface. The higher degree of interaction between these solvent |
701 |
> |
molecules and capping agents increases the enhancement effect and thus |
702 |
> |
produces a higher $G$ than densely packed butanethiol arrays. However, |
703 |
> |
once this maximum conductance enhancement is reached, $G$ decreases |
704 |
> |
when butanethiol coverage continues to decrease. Each capping agent |
705 |
> |
molecule reaches its maximum capacity for thermal |
706 |
> |
conductance. Therefore, even higher solvent-capping agent contact |
707 |
> |
would not offset this effect. Eventually, when butanethiol coverage |
708 |
> |
continues to decrease, solvent-capping agent contact actually |
709 |
> |
decreases with the disappearing of butanethiol molecules. In this |
710 |
> |
case, $G$ decrease could not be offset but instead accelerated. [NEED |
711 |
> |
SNAPSHOT SHOWING THE PHENOMENA / SLAB DENSITY ANALYSIS] |
712 |
> |
|
713 |
> |
A comparison of the results obtained from differenet organic solvents |
714 |
> |
can also provide useful information of the interfacial thermal |
715 |
> |
transport process. The deuterated hexane (UA) results do not appear to |
716 |
> |
be much different from those of normal hexane (UA), given that |
717 |
> |
butanethiol (UA) is non-deuterated for both solvents. These UA model |
718 |
> |
studies, even though eliminating C-H vibration samplings, still have |
719 |
> |
C-C vibrational frequencies different from each other. However, these |
720 |
> |
differences in the infrared range do not seem to produce an observable |
721 |
> |
difference for the results of $G$. [MAY NEED SPECTRA FIGURE] |
722 |
> |
|
723 |
> |
Furthermore, results for rigid body toluene solvent, as well as other |
724 |
> |
UA-hexane solvents, are reasonable within the general experimental |
725 |
> |
ranges[CITATIONS]. This suggests that explicit hydrogen might not be a |
726 |
> |
required factor for modeling thermal transport phenomena of systems |
727 |
> |
such as Au-thiol/organic solvent. |
728 |
> |
|
729 |
> |
However, results for Au-butanethiol/toluene do not show an identical |
730 |
> |
trend with those for Au-butanethiol/hexane in that $G$ remains at |
731 |
> |
approximately the same magnitue when butanethiol coverage differs from |
732 |
> |
25\% to 75\%. This might be rooted in the molecule shape difference |
733 |
> |
for planar toluene and chain-like {\it n}-hexane. Due to this |
734 |
> |
difference, toluene molecules have more difficulty in occupying |
735 |
> |
relatively small gaps among capping agents when their coverage is not |
736 |
> |
too low. Therefore, the solvent-capping agent contact may keep |
737 |
> |
increasing until the capping agent coverage reaches a relatively low |
738 |
> |
level. This becomes an offset for decreasing butanethiol molecules on |
739 |
> |
its effect to the process of interfacial thermal transport. Thus, one |
740 |
> |
can see a plateau of $G$ vs. butanethiol coverage in our results. |
741 |
> |
|
742 |
> |
\begin{figure} |
743 |
> |
\includegraphics[width=\linewidth]{coverage} |
744 |
> |
\caption{Comparison of interfacial thermal conductivity ($G$) values |
745 |
> |
for the Au-butanethiol/solvent interface with various UA models and |
746 |
> |
different capping agent coverages at $\langle T\rangle\sim$200K |
747 |
> |
using certain energy flux respectively.} |
748 |
> |
\label{coverage} |
749 |
> |
\end{figure} |
750 |
> |
|
751 |
> |
\subsection{Influence of Chosen Molecule Model on $G$} |
752 |
> |
In addition to UA solvent/capping agent models, AA models are included |
753 |
> |
in our simulations as well. Besides simulations of the same (UA or AA) |
754 |
> |
model for solvent and capping agent, different models can be applied |
755 |
> |
to different components. Furthermore, regardless of models chosen, |
756 |
> |
either the solvent or the capping agent can be deuterated, similar to |
757 |
> |
the previous section. Table \ref{modelTest} summarizes the results of |
758 |
> |
these studies. |
759 |
> |
|
760 |
> |
\begin{table*} |
761 |
> |
\begin{minipage}{\linewidth} |
762 |
> |
\begin{center} |
763 |
> |
|
764 |
> |
\caption{Computed interfacial thermal conductivity ($G$ and |
765 |
> |
$G^\prime$) values for interfaces using various models for |
766 |
> |
solvent and capping agent (or without capping agent) at |
767 |
> |
$\langle T\rangle\sim$200K. (D stands for deuterated solvent |
768 |
> |
or capping agent molecules; ``Avg.'' denotes results that are |
769 |
> |
averages of simulations under different $J_z$'s. Error |
770 |
> |
estimates indicated in parenthesis.)} |
771 |
> |
|
772 |
> |
\begin{tabular}{llccc} |
773 |
> |
\hline\hline |
774 |
> |
Butanethiol model & Solvent & $J_z$ & $G$ & $G^\prime$ \\ |
775 |
> |
(or bare surface) & model & (GW/m$^2$) & |
776 |
> |
\multicolumn{2}{c}{(MW/m$^2$/K)} \\ |
777 |
> |
\hline |
778 |
> |
UA & UA hexane & Avg. & 131(9) & 87(10) \\ |
779 |
> |
& UA hexane(D) & 1.95 & 153(5) & 136(13) \\ |
780 |
> |
& AA hexane & Avg. & 131(6) & 122(10) \\ |
781 |
> |
& UA toluene & 1.96 & 187(16) & 151(11) \\ |
782 |
> |
& AA toluene & 1.89 & 200(36) & 149(53) \\ |
783 |
> |
\hline |
784 |
> |
AA & UA hexane & 1.94 & 116(9) & 129(8) \\ |
785 |
> |
& AA hexane & Avg. & 442(14) & 356(31) \\ |
786 |
> |
& AA hexane(D) & 1.93 & 222(12) & 234(54) \\ |
787 |
> |
& UA toluene & 1.98 & 125(25) & 97(60) \\ |
788 |
> |
& AA toluene & 3.79 & 487(56) & 290(42) \\ |
789 |
> |
\hline |
790 |
> |
AA(D) & UA hexane & 1.94 & 158(25) & 172(4) \\ |
791 |
> |
& AA hexane & 1.92 & 243(29) & 191(11) \\ |
792 |
> |
& AA toluene & 1.93 & 364(36) & 322(67) \\ |
793 |
> |
\hline |
794 |
> |
bare & UA hexane & Avg. & 46.5(3.2) & 49.4(4.5) \\ |
795 |
> |
& UA hexane(D) & 0.98 & 43.9(4.6) & 43.0(2.0) \\ |
796 |
> |
& AA hexane & 0.96 & 31.0(1.4) & 29.4(1.3) \\ |
797 |
> |
& UA toluene & 1.99 & 70.1(1.3) & 65.8(0.5) \\ |
798 |
> |
\hline\hline |
799 |
> |
\end{tabular} |
800 |
> |
\label{modelTest} |
801 |
> |
\end{center} |
802 |
> |
\end{minipage} |
803 |
> |
\end{table*} |
804 |
> |
|
805 |
> |
To facilitate direct comparison, the same system with differnt models |
806 |
> |
for different components uses the same length scale for their |
807 |
> |
simulation cells. Without the presence of capping agent, using |
808 |
> |
different models for hexane yields similar results for both $G$ and |
809 |
> |
$G^\prime$, and these two definitions agree with eath other very |
810 |
> |
well. This indicates very weak interaction between the metal and the |
811 |
> |
solvent, and is a typical case for acoustic impedance mismatch between |
812 |
> |
these two phases. |
813 |
> |
|
814 |
> |
As for Au(111) surfaces completely covered by butanethiols, the choice |
815 |
> |
of models for capping agent and solvent could impact the measurement |
816 |
> |
of $G$ and $G^\prime$ quite significantly. For Au-butanethiol/hexane |
817 |
> |
interfaces, using AA model for both butanethiol and hexane yields |
818 |
> |
substantially higher conductivity values than using UA model for at |
819 |
> |
least one component of the solvent and capping agent, which exceeds |
820 |
> |
the general range of experimental measurement results. This is |
821 |
> |
probably due to the classically treated C-H vibrations in the AA |
822 |
> |
model, which should not be appreciably populated at normal |
823 |
> |
temperatures. In comparison, once either the hexanes or the |
824 |
> |
butanethiols are deuterated, one can see a significantly lower $G$ and |
825 |
> |
$G^\prime$. In either of these cases, the C-H(D) vibrational overlap |
826 |
> |
between the solvent and the capping agent is removed. |
827 |
> |
[MAY NEED SPECTRA FIGURE] Conclusively, the |
828 |
> |
improperly treated C-H vibration in the AA model produced |
829 |
> |
over-predicted results accordingly. Compared to the AA model, the UA |
830 |
> |
model yields more reasonable results with higher computational |
831 |
> |
efficiency. |
832 |
> |
|
833 |
> |
However, for Au-butanethiol/toluene interfaces, having the AA |
834 |
> |
butanethiol deuterated did not yield a significant change in the |
835 |
> |
measurement results. Compared to the C-H vibrational overlap between |
836 |
> |
hexane and butanethiol, both of which have alkyl chains, that overlap |
837 |
> |
between toluene and butanethiol is not so significant and thus does |
838 |
> |
not have as much contribution to the ``Intramolecular Vibration |
839 |
> |
Redistribution''[CITE HASE]. Conversely, extra degrees of freedom such |
840 |
> |
as the C-H vibrations could yield higher heat exchange rate between |
841 |
> |
these two phases and result in a much higher conductivity. |
842 |
> |
|
843 |
> |
Although the QSC model for Au is known to predict an overly low value |
844 |
> |
for bulk metal gold conductivity\cite{kuang:164101}, our computational |
845 |
> |
results for $G$ and $G^\prime$ do not seem to be affected by this |
846 |
> |
drawback of the model for metal. Instead, our results suggest that the |
847 |
> |
modeling of interfacial thermal transport behavior relies mainly on |
848 |
> |
the accuracy of the interaction descriptions between components |
849 |
> |
occupying the interfaces. |
850 |
> |
|
851 |
> |
\subsection{Role of Capping Agent in Interfacial Thermal Conductance} |
852 |
|
To investigate the mechanism of this interfacial thermal conductance, |
853 |
|
the vibrational spectra of various gold systems were obtained and are |
854 |
< |
shown as in the upper panel of Fig. \ref{vibration}. To obtain these |
855 |
< |
spectra, one first runs a simulation in the NVE ensemble and collects |
856 |
< |
snapshots of configurations; these configurations are used to compute |
857 |
< |
the velocity auto-correlation functions, which is used to construct a |
858 |
< |
power spectrum via a Fourier transform. The gold surfaces covered by |
859 |
< |
butanethiol molecules exhibit an additional peak observed at a |
860 |
< |
frequency of $\sim$170cm$^{-1}$, which is attributed to the vibration |
861 |
< |
of the S-Au bond. This vibration enables efficient thermal transport |
862 |
< |
from surface Au atoms to the capping agents. Simultaneously, as shown |
863 |
< |
in the lower panel of Fig. \ref{vibration}, the large overlap of the |
386 |
< |
vibration spectra of butanethiol and hexane in the all-atom model, |
854 |
> |
shown as in Fig. \ref{vibration}. |
855 |
> |
[MAY RELATE TO HASE'S] |
856 |
> |
The gold surfaces covered by butanethiol molecules, compared to bare |
857 |
> |
gold surfaces, exhibit an additional peak observed at the frequency of |
858 |
> |
$\sim$170cm$^{-1}$, which is attributed to the S-Au bonding |
859 |
> |
vibration. This vibration enables efficient thermal transport from |
860 |
> |
surface Au layer to the capping agents. |
861 |
> |
[MAY PUT IN OTHER SECTION] Simultaneously, as shown in |
862 |
> |
the lower panel of Fig. \ref{vibration}, the large overlap of the |
863 |
> |
vibration spectra of butanethiol and hexane in the All-Atom model, |
864 |
|
including the C-H vibration, also suggests high thermal exchange |
865 |
|
efficiency. The combination of these two effects produces the drastic |
866 |
< |
interfacial thermal conductance enhancement in the all-atom model. |
866 |
> |
interfacial thermal conductance enhancement in the All-Atom model. |
867 |
|
|
868 |
+ |
[NEED SEPARATE FIGURE. MAY NEED TO CONVERT TO JPEG] |
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|
\begin{figure} |
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|
\includegraphics[width=\linewidth]{vibration} |
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|
\caption{Vibrational spectra obtained for gold in different |
872 |
< |
environments (upper panel) and for Au/thiol/hexane simulation in |
395 |
< |
all-atom model (lower panel).} |
872 |
> |
environments.} |
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|
\label{vibration} |
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|
\end{figure} |
398 |
– |
% 600dpi, letter size. too large? |
875 |
|
|
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+ |
[MAY ADD COMPARISON OF G AND G', AU SLAB WIDTHS, ETC] |
877 |
+ |
% The results show that the two definitions used for $G$ yield |
878 |
+ |
% comparable values, though $G^\prime$ tends to be smaller. |
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|
|
880 |
+ |
\section{Conclusions} |
881 |
+ |
The NIVS algorithm we developed has been applied to simulations of |
882 |
+ |
Au-butanethiol surfaces with organic solvents. This algorithm allows |
883 |
+ |
effective unphysical thermal flux transferred between the metal and |
884 |
+ |
the liquid phase. With the flux applied, we were able to measure the |
885 |
+ |
corresponding thermal gradient and to obtain interfacial thermal |
886 |
+ |
conductivities. Our simulations have seen significant conductance |
887 |
+ |
enhancement with the presence of capping agent, compared to the bare |
888 |
+ |
gold / liquid interfaces. The acoustic impedance mismatch between the |
889 |
+ |
metal and the liquid phase is effectively eliminated by proper capping |
890 |
+ |
agent. Furthermore, the coverage precentage of the capping agent plays |
891 |
+ |
an important role in the interfacial thermal transport process. |
892 |
+ |
|
893 |
+ |
Our measurement results, particularly of the UA models, agree with |
894 |
+ |
available experimental data. This indicates that our force field |
895 |
+ |
parameters have a nice description of the interactions between the |
896 |
+ |
particles at the interfaces. AA models tend to overestimate the |
897 |
+ |
interfacial thermal conductance in that the classically treated C-H |
898 |
+ |
vibration would be overly sampled. Compared to the AA models, the UA |
899 |
+ |
models have higher computational efficiency with satisfactory |
900 |
+ |
accuracy, and thus are preferable in interfacial thermal transport |
901 |
+ |
modelings. |
902 |
+ |
|
903 |
+ |
Vlugt {\it et al.} has investigated the surface thiol structures for |
904 |
+ |
nanocrystal gold and pointed out that they differs from those of the |
905 |
+ |
Au(111) surface\cite{vlugt:cpc2007154}. This difference might lead to |
906 |
+ |
change of interfacial thermal transport behavior as well. To |
907 |
+ |
investigate this problem, an effective means to introduce thermal flux |
908 |
+ |
and measure the corresponding thermal gradient is desirable for |
909 |
+ |
simulating structures with spherical symmetry. |
910 |
+ |
|
911 |
+ |
|
912 |
|
\section{Acknowledgments} |
913 |
|
Support for this project was provided by the National Science |
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|
Foundation under grant CHE-0848243. Computational time was provided by |
915 |
|
the Center for Research Computing (CRC) at the University of Notre |
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< |
Dame. \newpage |
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> |
Dame. \newpage |
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|
|
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|
\bibliography{interfacial} |
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|