--- interfacial/interfacial.tex 2011/05/09 19:08:08 3725 +++ interfacial/interfacial.tex 2011/07/29 21:06:30 3759 @@ -22,9 +22,9 @@ \setlength{\abovecaptionskip}{20 pt} \setlength{\belowcaptionskip}{30 pt} -%\renewcommand\citemid{\ } % no comma in optional referenc note -\bibpunct{[}{]}{,}{s}{}{;} -\bibliographystyle{aip} +%\renewcommand\citemid{\ } % no comma in optional reference note +\bibpunct{[}{]}{,}{n}{}{;} +\bibliographystyle{achemso} \begin{document} @@ -45,20 +45,22 @@ We have developed a Non-Isotropic Velocity Scaling alg \begin{abstract} -We have developed a Non-Isotropic Velocity Scaling algorithm for -setting up and maintaining stable thermal gradients in non-equilibrium -molecular dynamics simulations. This approach effectively imposes -unphysical thermal flux even between particles of different -identities, conserves linear momentum and kinetic energy, and -minimally perturbs the velocity profile of a system when compared with -previous RNEMD methods. We have used this method to simulate thermal -conductance at metal / organic solvent interfaces both with and -without the presence of thiol-based capping agents. We obtained -values comparable with experimental values, and observed significant -conductance enhancement with the presence of capping agents. Computed -power spectra indicate the acoustic impedance mismatch between metal -and liquid phase is greatly reduced by the capping agents and thus -leads to higher interfacial thermal transfer efficiency. +With the Non-Isotropic Velocity Scaling algorithm (NIVS) we have +developed, an unphysical thermal flux can be effectively set up even +for non-homogeneous systems like interfaces in non-equilibrium +molecular dynamics simulations. In this work, this algorithm is +applied for simulating thermal conductance at metal / organic solvent +interfaces with various coverages of butanethiol capping +agents. Different solvents and force field models were tested. Our +results suggest that the United-Atom models are able to provide an +estimate of the interfacial thermal conductivity comparable to +experiments in our simulations with satisfactory computational +efficiency. From our results, the acoustic impedance mismatch between +metal and liquid phase is effectively reduced by the capping +agents, and thus leads to interfacial thermal conductance +enhancement. Furthermore, this effect is closely related to the +capping agent coverage on the metal surfaces and the type of solvent +molecules, and is affected by the models used in the simulations. \end{abstract} @@ -71,338 +73,933 @@ leads to higher interfacial thermal transfer efficienc %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Introduction} +Due to the importance of heat flow in nanotechnology, interfacial +thermal conductance has been studied extensively both experimentally +and computationally.\cite{cahill:793} Unlike bulk materials, nanoscale +materials have a significant fraction of their atoms at interfaces, +and the chemical details of these interfaces govern the heat transfer +behavior. Furthermore, the interfaces are +heterogeneous (e.g. solid - liquid), which provides a challenge to +traditional methods developed for homogeneous systems. -Interfacial thermal conductance is extensively studied both -experimentally and computationally, and systems with interfaces -present are generally heterogeneous. Although interfaces are commonly -barriers to heat transfer, it has been -reported\cite{doi:10.1021/la904855s} that under specific circustances, -e.g. with certain capping agents present on the surface, interfacial -conductance can be significantly enhanced. However, heat conductance -of molecular and nano-scale interfaces will be affected by the -chemical details of the surface and is challenging to -experimentalist. The lower thermal flux through interfaces is even -more difficult to measure with EMD and forward NEMD simulation -methods. Therefore, developing good simulation methods will be -desirable in order to investigate thermal transport across interfaces. +Experimentally, various interfaces have been investigated for their +thermal conductance. Cahill and coworkers studied nanoscale thermal +transport from metal nanoparticle/fluid interfaces, to epitaxial +TiN/single crystal oxides interfaces, to hydrophilic and hydrophobic +interfaces between water and solids with different self-assembled +monolayers.\cite{Wilson:2002uq,PhysRevB.67.054302,doi:10.1021/jp048375k,PhysRevLett.96.186101} +Wang {\it et al.} studied heat transport through +long-chain hydrocarbon monolayers on gold substrate at individual +molecular level,\cite{Wang10082007} Schmidt {\it et al.} studied the +role of CTAB on thermal transport between gold nanorods and +solvent,\cite{doi:10.1021/jp8051888} and Juv\'e {\it et al.} studied +the cooling dynamics, which is controlled by thermal interface +resistence of glass-embedded metal +nanoparticles.\cite{PhysRevB.80.195406} Although interfaces are +normally considered barriers for heat transport, Alper {\it et al.} +suggested that specific ligands (capping agents) could completely +eliminate this barrier +($G\rightarrow\infty$).\cite{doi:10.1021/la904855s} -Recently, we have developed the Non-Isotropic Velocity Scaling (NIVS) +Theoretical and computational models have also been used to study the +interfacial thermal transport in order to gain an understanding of +this phenomena at the molecular level. Recently, Hase and coworkers +employed Non-Equilibrium Molecular Dynamics (NEMD) simulations to +study thermal transport from hot Au(111) substrate to a self-assembled +monolayer of alkylthiol with relatively long chain (8-20 carbon +atoms).\cite{hase:2010,hase:2011} However, ensemble averaged +measurements for heat conductance of interfaces between the capping +monolayer on Au and a solvent phase have yet to be studied with their +approach. The comparatively low thermal flux through interfaces is +difficult to measure with Equilibrium +MD\cite{doi:10.1080/0026897031000068578} or forward NEMD simulation +methods. Therefore, the Reverse NEMD (RNEMD) +methods\cite{MullerPlathe:1997xw,kuang:164101} would have the +advantage of applying this difficult to measure flux (while measuring +the resulting gradient), given that the simulation methods being able +to effectively apply an unphysical flux in non-homogeneous systems. +Garde and coworkers\cite{garde:nl2005,garde:PhysRevLett2009} applied +this approach to various liquid interfaces and studied how thermal +conductance (or resistance) is dependent on chemistry details of +interfaces, e.g. hydrophobic and hydrophilic aqueous interfaces. + +Recently, we have developed a Non-Isotropic Velocity Scaling (NIVS) algorithm for RNEMD simulations\cite{kuang:164101}. This algorithm retains the desirable features of RNEMD (conservation of linear momentum and total energy, compatibility with periodic boundary conditions) while establishing true thermal distributions in each of -the two slabs. Furthermore, it allows more effective thermal exchange -between particles of different identities, and thus enables extensive -study of interfacial conductance. +the two slabs. Furthermore, it allows effective thermal exchange +between particles of different identities, and thus makes the study of +interfacial conductance much simpler. +The work presented here deals with the Au(111) surface covered to +varying degrees by butanethiol, a capping agent with short carbon +chain, and solvated with organic solvents of different molecular +properties. Different models were used for both the capping agent and +the solvent force field parameters. Using the NIVS algorithm, the +thermal transport across these interfaces was studied and the +underlying mechanism for the phenomena was investigated. + \section{Methodology} -\subsection{Algorithm} -There have been many algorithms for computing thermal conductivity -using molecular dynamics simulations. However, interfacial conductance -is at least an order of magnitude smaller. This would make the -calculation even more difficult for those slowly-converging -equilibrium methods. Imposed-flux non-equilibrium -methods\cite{MullerPlathe:1997xw} have the flux set {\it a priori} and -the response of temperature or momentum gradients are easier to -measure than the flux, if unknown, and thus, is a preferable way to -the forward NEMD methods. Although the momentum swapping approach for -flux-imposing can be used for exchanging energy between particles of -different identity, the kinetic energy transfer efficiency is affected -by the mass difference between the particles, which limits its -application on heterogeneous interfacial systems. +\subsection{Imposd-Flux Methods in MD Simulations} +Steady state MD simulations have an advantage in that not many +trajectories are needed to study the relationship between thermal flux +and thermal gradients. For systems with low interfacial conductance, +one must have a method capable of generating or measuring relatively +small fluxes, compared to those required for bulk conductivity. This +requirement makes the calculation even more difficult for +slowly-converging equilibrium methods.\cite{Viscardy:2007lq} Forward +NEMD methods impose a gradient (and measure a flux), but at interfaces +it is not clear what behavior should be imposed at the boundaries +between materials. Imposed-flux reverse non-equilibrium +methods\cite{MullerPlathe:1997xw} set the flux {\it a priori} and +the thermal response becomes an easy-to-measure quantity. Although +M\"{u}ller-Plathe's original momentum swapping approach can be used +for exchanging energy between particles of different identity, the +kinetic energy transfer efficiency is affected by the mass difference +between the particles, which limits its application on heterogeneous +interfacial systems. -The non-isotropic velocity scaling (NIVS)\cite{kuang:164101} approach in -non-equilibrium MD simulations is able to impose relatively large -kinetic energy flux without obvious perturbation to the velocity -distribution of the simulated systems. Furthermore, this approach has +The non-isotropic velocity scaling (NIVS) \cite{kuang:164101} approach +to non-equilibrium MD simulations is able to impose a wide range of +kinetic energy fluxes without obvious perturbation to the velocity +distributions of the simulated systems. Furthermore, this approach has the advantage in heterogeneous interfaces in that kinetic energy flux can be applied between regions of particles of arbitary identity, and -the flux quantity is not restricted by particle mass difference. +the flux will not be restricted by difference in particle mass. The NIVS algorithm scales the velocity vectors in two separate regions of a simulation system with respective diagonal scaling matricies. To determine these scaling factors in the matricies, a set of equations including linear momentum conservation and kinetic energy conservation -constraints and target momentum/energy flux satisfaction is -solved. With the scaling operation applied to the system in a set -frequency, corresponding momentum/temperature gradients can be built, -which can be used for computing transportation properties and other -applications related to momentum/temperature gradients. The NIVS -algorithm conserves momenta and energy and does not depend on an -external thermostat. +constraints and target energy flux satisfaction is solved. With the +scaling operation applied to the system in a set frequency, bulk +temperature gradients can be easily established, and these can be used +for computing thermal conductivities. The NIVS algorithm conserves +momenta and energy and does not depend on an external thermostat. -(wondering how much detail of algorithm should be put here...) +\subsection{Defining Interfacial Thermal Conductivity ($G$)} -\subsection{Force Field Parameters} -Our simulation systems consists of metal gold lattice slab solvated by -organic solvents. In order to study the role of capping agents in -interfacial thermal conductance, butanethiol is chosen to cover gold -surfaces in comparison to no capping agent present. +For an interface with relatively low interfacial conductance, and a +thermal flux between two distinct bulk regions, the regions on either +side of the interface rapidly come to a state in which the two phases +have relatively homogeneous (but distinct) temperatures. The +interfacial thermal conductivity $G$ can therefore be approximated as: +\begin{equation} + G = \frac{E_{total}}{2 t L_x L_y \left( \langle T_\mathrm{hot}\rangle - + \langle T_\mathrm{cold}\rangle \right)} +\label{lowG} +\end{equation} +where ${E_{total}}$ is the total imposed non-physical kinetic energy +transfer during the simulation and ${\langle T_\mathrm{hot}\rangle}$ +and ${\langle T_\mathrm{cold}\rangle}$ are the average observed +temperature of the two separated phases. For an applied flux $J_z$ +operating over a simulation time $t$ on a periodically-replicated slab +of dimensions $L_x \times L_y$, $E_{total} = J_z *(t)*(2 L_x L_y)$. -The Au-Au interactions in metal lattice slab is described by the -quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The QSC -potentials include zero-point quantum corrections and are -reparametrized for accurate surface energies compared to the -Sutton-Chen potentials\cite{Chen90}. - -Straight chain {\it n}-hexane and aromatic toluene are respectively -used as solvents. For hexane, both United-Atom\cite{TraPPE-UA.alkanes} -and All-Atom\cite{OPLSAA} force fields are used for comparison; for -toluene, United-Atom\cite{TraPPE-UA.alkylbenzenes} force fields are -used with rigid body constraints applied. (maybe needs more details -about rigid body) - -Buatnethiol molecules are used as capping agent for some of our -simulations. United-Atom\cite{TraPPE-UA.thiols} and All-Atom models -are respectively used corresponding to the force field type of -solvent. - -To describe the interactions between metal Au and non-metal capping -agent and solvent, we refer to Vlugt\cite{vlugt:cpc2007154} and derive -other interactions which are not parametrized in their work. (can add -hautman and klein's paper here and more discussion; need to put -aromatic-metal interaction approximation here) - -[TABULATED FORCE FIELD PARAMETERS NEEDED] - -\section{Computational Details} -\subsection{System Geometry} -Our simulation systems consists of a lattice Au slab with the (111) -surface perpendicular to the $z$-axis, and a solvent layer between the -periodic Au slabs along the $z$-axis. To set up the interfacial -system, the Au slab is first equilibrated without solvent under room -pressure and a desired temperature. After the metal slab is -equilibrated, United-Atom or All-Atom butanethiols are replicated on -the Au surface, each occupying the (??) among three Au atoms, and is -equilibrated under NVT ensemble. According to (CITATION), the maximal -thiol capacity on Au surface is $1/3$ of the total number of surface -Au atoms. - -\cite{packmol} - -\subsection{Simulation Parameters} - When the interfacial conductance is {\it not} small, there are two -ways to define $G$. If we assume the temperature is discretely -different on two sides of the interface, $G$ can be calculated with -the thermal flux applied $J$ and the temperature difference measured -$\Delta T$ as: +ways to define $G$. One common way is to assume the temperature is +discrete on the two sides of the interface. $G$ can be calculated +using the applied thermal flux $J$ and the maximum temperature +difference measured along the thermal gradient max($\Delta T$), which +occurs at the Gibbs deviding surface (Figure \ref{demoPic}). This is +known as the Kapitza conductance, which is the inverse of the Kapitza +resistance. \begin{equation} -G=\frac{J}{\Delta T} + G=\frac{J}{\Delta T} \label{discreteG} \end{equation} -We can as well assume a continuous temperature profile along the -thermal gradient axis $z$ and define $G$ as the change of bulk thermal -conductivity $\lambda$ at a defined interfacial point: + +\begin{figure} +\includegraphics[width=\linewidth]{method} +\caption{Interfacial conductance can be calculated by applying an + (unphysical) kinetic energy flux between two slabs, one located + within the metal and another on the edge of the periodic box. The + system responds by forming a thermal response or a gradient. In + bulk liquids, this gradient typically has a single slope, but in + interfacial systems, there are distinct thermal conductivity + domains. The interfacial conductance, $G$ is found by measuring the + temperature gap at the Gibbs dividing surface, or by using second + derivatives of the thermal profile.} +\label{demoPic} +\end{figure} + +The other approach is to assume a continuous temperature profile along +the thermal gradient axis (e.g. $z$) and define $G$ at the point where +the magnitude of thermal conductivity ($\lambda$) change reaches its +maximum, given that $\lambda$ is well-defined throughout the space: \begin{equation} G^\prime = \Big|\frac{\partial\lambda}{\partial z}\Big| = \Big|\frac{\partial}{\partial z}\left(-J_z\Big/ \left(\frac{\partial T}{\partial z}\right)\right)\Big| - = J_z\Big|\frac{\partial^2 T}{\partial z^2}\Big| + = |J_z|\Big|\frac{\partial^2 T}{\partial z^2}\Big| \Big/\left(\frac{\partial T}{\partial z}\right)^2 \label{derivativeG} \end{equation} -With the temperature profile obtained from simulations, one is able to + +With temperature profiles obtained from simulation, one is able to approximate the first and second derivatives of $T$ with finite -difference method and thus calculate $G^\prime$. +difference methods and calculate $G^\prime$. In what follows, both +definitions have been used, and are compared in the results. -In what follows, both definitions are used for calculation and comparison. +To investigate the interfacial conductivity at metal / solvent +interfaces, we have modeled a metal slab with its (111) surfaces +perpendicular to the $z$-axis of our simulation cells. The metal slab +has been prepared both with and without capping agents on the exposed +surface, and has been solvated with simple organic solvents, as +illustrated in Figure \ref{gradT}. -\section{Results} -\subsection{Toluene Solvent} +With the simulation cell described above, we are able to equilibrate +the system and impose an unphysical thermal flux between the liquid +and the metal phase using the NIVS algorithm. By periodically applying +the unphysical flux, we obtained a temperature profile and its spatial +derivatives. Figure \ref{gradT} shows how an applied thermal flux can +be used to obtain the 1st and 2nd derivatives of the temperature +profile. -The simulations follow a protocol similar to the previous gold/water -interfacial systems. The results (Table \ref{AuThiolToluene}) show a -significant conductance enhancement compared to the gold/water -interface without capping agent and agree with available experimental -data. This indicates that the metal-metal potential, though not -predicting an accurate bulk metal thermal conductivity, does not -greatly interfere with the simulation of the thermal conductance -behavior across a non-metal interface. The solvent model is not -particularly volatile, so the simulation cell does not expand -significantly under higher temperature. We did not observe a -significant conductance decrease when the temperature was increased to -300K. The results show that the two definitions used for $G$ yield -comparable values, though $G^\prime$ tends to be smaller. +\begin{figure} +\includegraphics[width=\linewidth]{gradT} +\caption{A sample of Au-butanethiol/hexane interfacial system and the + temperature profile after a kinetic energy flux is imposed to + it. The 1st and 2nd derivatives of the temperature profile can be + obtained with finite difference approximation (lower panel).} +\label{gradT} +\end{figure} +\section{Computational Details} +\subsection{Simulation Protocol} +The NIVS algorithm has been implemented in our MD simulation code, +OpenMD\cite{Meineke:2005gd,openmd}, and was used for our simulations. +Metal slabs of 6 or 11 layers of Au atoms were first equilibrated +under atmospheric pressure (1 atm) and 200K. After equilibration, +butanethiol capping agents were placed at three-fold hollow sites on +the Au(111) surfaces. These sites are either {\it fcc} or {\it + hcp} sites, although Hase {\it et al.} found that they are +equivalent in a heat transfer process,\cite{hase:2010} so we did not +distinguish between these sites in our study. The maximum butanethiol +capacity on Au surface is $1/3$ of the total number of surface Au +atoms, and the packing forms a $(\sqrt{3}\times\sqrt{3})R30^\circ$ +structure\cite{doi:10.1021/ja00008a001,doi:10.1021/cr9801317}. A +series of lower coverages was also prepared by eliminating +butanethiols from the higher coverage surface in a regular manner. The +lower coverages were prepared in order to study the relation between +coverage and interfacial conductance. + +The capping agent molecules were allowed to migrate during the +simulations. They distributed themselves uniformly and sampled a +number of three-fold sites throughout out study. Therefore, the +initial configuration does not noticeably affect the sampling of a +variety of configurations of the same coverage, and the final +conductance measurement would be an average effect of these +configurations explored in the simulations. + +After the modified Au-butanethiol surface systems were equilibrated in +the canonical (NVT) ensemble, organic solvent molecules were packed in +the previously empty part of the simulation cells.\cite{packmol} Two +solvents were investigated, one which has little vibrational overlap +with the alkanethiol and which has a planar shape (toluene), and one +which has similar vibrational frequencies to the capping agent and +chain-like shape ({\it n}-hexane). + +The simulation cells were not particularly extensive along the +$z$-axis, as a very long length scale for the thermal gradient may +cause excessively hot or cold temperatures in the middle of the +solvent region and lead to undesired phenomena such as solvent boiling +or freezing when a thermal flux is applied. Conversely, too few +solvent molecules would change the normal behavior of the liquid +phase. Therefore, our $N_{solvent}$ values were chosen to ensure that +these extreme cases did not happen to our simulations. The spacing +between periodic images of the gold interfaces is $45 \sim 75$\AA. + +The initial configurations generated are further equilibrated with the +$x$ and $y$ dimensions fixed, only allowing the $z$-length scale to +change. This is to ensure that the equilibration of liquid phase does +not affect the metal's crystalline structure. Comparisons were made +with simulations that allowed changes of $L_x$ and $L_y$ during NPT +equilibration. No substantial changes in the box geometry were noticed +in these simulations. After ensuring the liquid phase reaches +equilibrium at atmospheric pressure (1 atm), further equilibration was +carried out under canonical (NVT) and microcanonical (NVE) ensembles. + +After the systems reach equilibrium, NIVS was used to impose an +unphysical thermal flux between the metal and the liquid phases. Most +of our simulations were done under an average temperature of +$\sim$200K. Therefore, thermal flux usually came from the metal to the +liquid so that the liquid has a higher temperature and would not +freeze due to lowered temperatures. After this induced temperature +gradient had stablized, the temperature profile of the simulation cell +was recorded. To do this, the simulation cell is devided evenly into +$N$ slabs along the $z$-axis. The average temperatures of each slab +are recorded for 1$\sim$2 ns. When the slab width $d$ of each slab is +the same, the derivatives of $T$ with respect to slab number $n$ can +be directly used for $G^\prime$ calculations: \begin{equation} + G^\prime = |J_z|\Big|\frac{\partial^2 T}{\partial z^2}\Big| + \Big/\left(\frac{\partial T}{\partial z}\right)^2 + = |J_z|\Big|\frac{1}{d^2}\frac{\partial^2 T}{\partial n^2}\Big| + \Big/\left(\frac{1}{d}\frac{\partial T}{\partial n}\right)^2 + = |J_z|\Big|\frac{\partial^2 T}{\partial n^2}\Big| + \Big/\left(\frac{\partial T}{\partial n}\right)^2 +\label{derivativeG2} +\end{equation} + +All of the above simulation procedures use a time step of 1 fs. Each +equilibration stage took a minimum of 100 ps, although in some cases, +longer equilibration stages were utilized. + +\subsection{Force Field Parameters} +Our simulations include a number of chemically distinct components. +Figure \ref{demoMol} demonstrates the sites defined for both +United-Atom and All-Atom models of the organic solvent and capping +agents in our simulations. Force field parameters are needed for +interactions both between the same type of particles and between +particles of different species. + +\begin{figure} +\includegraphics[width=\linewidth]{structures} +\caption{Structures of the capping agent and solvents utilized in + these simulations. The chemically-distinct sites (a-e) are expanded + in terms of constituent atoms for both United Atom (UA) and All Atom + (AA) force fields. Most parameters are from + Refs. \protect\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes,TraPPE-UA.thiols} + (UA) and \protect\cite{OPLSAA} (AA). Cross-interactions with the Au + atoms are given in Table \ref{MnM}.} +\label{demoMol} +\end{figure} + +The Au-Au interactions in metal lattice slab is described by the +quantum Sutton-Chen (QSC) formulation.\cite{PhysRevB.59.3527} The QSC +potentials include zero-point quantum corrections and are +reparametrized for accurate surface energies compared to the +Sutton-Chen potentials.\cite{Chen90} + +For the two solvent molecules, {\it n}-hexane and toluene, two +different atomistic models were utilized. Both solvents were modeled +using United-Atom (UA) and All-Atom (AA) models. The TraPPE-UA +parameters\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} are used +for our UA solvent molecules. In these models, sites are located at +the carbon centers for alkyl groups. Bonding interactions, including +bond stretches and bends and torsions, were used for intra-molecular +sites closer than 3 bonds. For non-bonded interactions, Lennard-Jones +potentials are used. + +By eliminating explicit hydrogen atoms, the TraPPE-UA models are +simple and computationally efficient, while maintaining good accuracy. +However, the TraPPE-UA model for alkanes is known to predict a slighly +lower boiling point than experimental values. This is one of the +reasons we used a lower average temperature (200K) for our +simulations. If heat is transferred to the liquid phase during the +NIVS simulation, the liquid in the hot slab can actually be +substantially warmer than the mean temperature in the simulation. The +lower mean temperatures therefore prevent solvent boiling. + +For UA-toluene, the non-bonded potentials between intermolecular sites +have a similar Lennard-Jones formulation. The toluene molecules were +treated as a single rigid body, so there was no need for +intramolecular interactions (including bonds, bends, or torsions) in +this solvent model. + +Besides the TraPPE-UA models, AA models for both organic solvents are +included in our studies as well. The OPLS-AA\cite{OPLSAA} force fields +were used. For hexane, additional explicit hydrogen sites were +included. Besides bonding and non-bonded site-site interactions, +partial charges and the electrostatic interactions were added to each +CT and HC site. For toluene, a flexible model for the toluene molecule +was utilized which included bond, bend, torsion, and inversion +potentials to enforce ring planarity. + +The butanethiol capping agent in our simulations, were also modeled +with both UA and AA model. The TraPPE-UA force field includes +parameters for thiol molecules\cite{TraPPE-UA.thiols} and are used for +UA butanethiol model in our simulations. The OPLS-AA also provides +parameters for alkyl thiols. However, alkyl thiols adsorbed on Au(111) +surfaces do not have the hydrogen atom bonded to sulfur. To derive +suitable parameters for butanethiol adsorbed on Au(111) surfaces, we +adopt the S parameters from Luedtke and Landman\cite{landman:1998} and +modify the parameters for the CTS atom to maintain charge neutrality +in the molecule. Note that the model choice (UA or AA) for the capping +agent can be different from the solvent. Regardless of model choice, +the force field parameters for interactions between capping agent and +solvent can be derived using Lorentz-Berthelot Mixing Rule: +\begin{eqnarray} + \sigma_{ij} & = & \frac{1}{2} \left(\sigma_{ii} + \sigma_{jj}\right) \\ + \epsilon_{ij} & = & \sqrt{\epsilon_{ii}\epsilon_{jj}} +\end{eqnarray} + +To describe the interactions between metal (Au) and non-metal atoms, +we refer to an adsorption study of alkyl thiols on gold surfaces by +Vlugt {\it et al.}\cite{vlugt:cpc2007154} They fitted an effective +Lennard-Jones form of potential parameters for the interaction between +Au and pseudo-atoms CH$_x$ and S based on a well-established and +widely-used effective potential of Hautman and Klein for the Au(111) +surface.\cite{hautman:4994} As our simulations require the gold slab +to be flexible to accommodate thermal excitation, the pair-wise form +of potentials they developed was used for our study. + +The potentials developed from {\it ab initio} calculations by Leng +{\it et al.}\cite{doi:10.1021/jp034405s} are adopted for the +interactions between Au and aromatic C/H atoms in toluene. However, +the Lennard-Jones parameters between Au and other types of particles, +(e.g. AA alkanes) have not yet been established. For these +interactions, the Lorentz-Berthelot mixing rule can be used to derive +effective single-atom LJ parameters for the metal using the fit values +for toluene. These are then used to construct reasonable mixing +parameters for the interactions between the gold and other atoms. +Table \ref{MnM} summarizes the ``metal/non-metal'' parameters used in +our simulations. + \begin{table*} \begin{minipage}{\linewidth} \begin{center} - \caption{Computed interfacial thermal conductivity ($G$ and - $G^\prime$) values for the Au/butanethiol/toluene interface at - different temperatures using a range of energy fluxes.} - - \begin{tabular}{cccc} + \caption{Non-bonded interaction parameters (including cross + interactions with Au atoms) for both force fields used in this + work.} + \begin{tabular}{lllllll} \hline\hline - $\langle T\rangle$ & $J_z$ & $G$ & $G^\prime$ \\ - (K) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ + & Site & $\sigma_{ii}$ & $\epsilon_{ii}$ & $q_i$ & + $\sigma_{Au-i}$ & $\epsilon_{Au-i}$ \\ + & & (\AA) & (kcal/mol) & ($e$) & (\AA) & (kcal/mol) \\ \hline - 200 & 1.86 & 180 & 135 \\ - & 2.15 & 204 & 113 \\ - & 3.93 & 175 & 114 \\ - 300 & 1.91 & 143 & 125 \\ - & 4.19 & 134 & 113 \\ + United Atom (UA) + &CH3 & 3.75 & 0.1947 & - & 3.54 & 0.2146 \\ + &CH2 & 3.95 & 0.0914 & - & 3.54 & 0.1749 \\ + &CHar & 3.695 & 0.1003 & - & 3.4625 & 0.1680 \\ + &CRar & 3.88 & 0.04173 & - & 3.555 & 0.1604 \\ + \hline + All Atom (AA) + &CT3 & 3.50 & 0.066 & -0.18 & 3.365 & 0.1373 \\ + &CT2 & 3.50 & 0.066 & -0.12 & 3.365 & 0.1373 \\ + &CTT & 3.50 & 0.066 & -0.065 & 3.365 & 0.1373 \\ + &HC & 2.50 & 0.030 & 0.06 & 2.865 & 0.09256 \\ + &CA & 3.55 & 0.070 & -0.115 & 3.173 & 0.0640 \\ + &HA & 2.42 & 0.030 & 0.115 & 2.746 & 0.0414 \\ + \hline + Both UA and AA + & S & 4.45 & 0.25 & - & 2.40 & 8.465 \\ \hline\hline \end{tabular} - \label{AuThiolToluene} + \label{MnM} \end{center} \end{minipage} \end{table*} -\subsection{Hexane Solvent} -Using the united-atom model, different coverages of capping agent, -temperatures of simulations and numbers of solvent molecules were all -investigated and Table \ref{AuThiolHexaneUA} shows the results of -these computations. The number of hexane molecules in our simulations -does not affect the calculations significantly. However, a very long -length scale for the thermal gradient axis ($z$) may cause excessively -hot or cold temperatures in the middle of the solvent region and lead -to undesired phenomena such as solvent boiling or freezing, while too -few solvent molecules would change the normal behavior of the liquid -phase. Our $N_{hexane}$ values were chosen to ensure that these -extreme cases did not happen to our simulations. +\section{Results} +There are many factors contributing to the measured interfacial +conductance; some of these factors are physically motivated +(e.g. coverage of the surface by the capping agent coverage and +solvent identity), while some are governed by parameters of the +methodology (e.g. applied flux and the formulas used to obtain the +conductance). In this section we discuss the major physical and +calculational effects on the computed conductivity. -Table \ref{AuThiolHexaneUA} enables direct comparison between -different coverages of capping agent, when other system parameters are -held constant. With high coverage of butanethiol on the gold surface, -the interfacial thermal conductance is enhanced -significantly. Interestingly, a slightly lower butanethiol coverage -leads to a moderately higher conductivity. This is probably due to -more solvent/capping agent contact when butanethiol molecules are -not densely packed, which enhances the interactions between the two -phases and lowers the thermal transfer barrier of this interface. -% [COMPARE TO AU/WATER IN PAPER] +\subsection{Effects due to capping agent coverage} -It is also noted that the overall simulation temperature is another -factor that affects the interfacial thermal conductance. One -possibility of this effect may be rooted in the decrease in density of -the liquid phase. We observed that when the average temperature -increases from 200K to 250K, the bulk hexane density becomes lower -than experimental value, as the system is equilibrated under NPT -ensemble. This leads to lower contact between solvent and capping -agent, and thus lower conductivity. +A series of different initial conditions with a range of surface +coverages was prepared and solvated with various with both of the +solvent molecules. These systems were then equilibrated and their +interfacial thermal conductivity was measured with the NIVS +algorithm. Figure \ref{coverage} demonstrates the trend of conductance +with respect to surface coverage. -Conductivity values are more difficult to obtain under higher -temperatures. This is because the Au surface tends to undergo -reconstructions in relatively high temperatures. Surface Au atoms can -migrate outward to reach higher Au-S contact; and capping agent -molecules can be embedded into the surface Au layer due to the same -driving force. This phenomenon agrees with experimental -results\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}. A surface -fully covered in capping agent is more susceptible to reconstruction, -possibly because fully coverage prevents other means of capping agent -relaxation, such as migration to an empty neighbor three-fold site. +\begin{figure} +\includegraphics[width=\linewidth]{coverage} +\caption{Comparison of interfacial thermal conductivity ($G$) values + for the Au-butanethiol/solvent interface with various UA models and + different capping agent coverages at $\langle T\rangle\sim$200K.} +\label{coverage} +\end{figure} -%MAY ADD MORE DATA TO TABLE +In partially covered surfaces, the derivative definition for +$G^\prime$ (Eq. \ref{derivativeG}) becomes difficult to apply, as the +location of maximum change of $\lambda$ becomes washed out. The +discrete definition (Eq. \ref{discreteG}) is easier to apply, as the +Gibbs dividing surface is still well-defined. Therefore, $G$ (not +$G^\prime$) was used in this section. + +From Figure \ref{coverage}, one can see the significance of the +presence of capping agents. When even a small fraction of the Au(111) +surface sites are covered with butanethiols, the conductivity exhibits +an enhancement by at least a factor of 3. Cappping agents are clearly +playing a major role in thermal transport at metal / organic solvent +surfaces. + +We note a non-monotonic behavior in the interfacial conductance as a +function of surface coverage. The maximum conductance (largest $G$) +happens when the surfaces are about 75\% covered with butanethiol +caps. The reason for this behavior is not entirely clear. One +explanation is that incomplete butanethiol coverage allows small gaps +between butanethiols to form. These gaps can be filled by transient +solvent molecules. These solvent molecules couple very strongly with +the hot capping agent molecules near the surface, and can then carry +away (diffusively) the excess thermal energy from the surface. + +There appears to be a competition between the conduction of the +thermal energy away from the surface by the capping agents (enhanced +by greater coverage) and the coupling of the capping agents with the +solvent (enhanced by interdigitation at lower coverages). This +competition would lead to the non-monotonic coverage behavior observed +here. + +Results for rigid body toluene solvent, as well as the UA hexane, are +within the ranges expected from prior experimental +work.\cite{Wilson:2002uq,cahill:793,PhysRevB.80.195406} This suggests +that explicit hydrogen atoms might not be required for modeling +thermal transport in these systems. C-H vibrational modes do not see +significant excited state population at low temperatures, and are not +likely to carry lower frequency excitations from the solid layer into +the bulk liquid. + +The toluene solvent does not exhibit the same behavior as hexane in +that $G$ remains at approximately the same magnitude when the capping +coverage increases from 25\% to 75\%. Toluene, as a rigid planar +molecule, cannot occupy the relatively small gaps between the capping +agents as easily as the chain-like {\it n}-hexane. The effect of +solvent coupling to the capping agent is therefore weaker in toluene +except at the very lowest coverage levels. This effect counters the +coverage-dependent conduction of heat away from the metal surface, +leading to a much flatter $G$ vs. coverage trend than is observed in +{\it n}-hexane. + +\subsection{Effects due to Solvent \& Solvent Models} +In addition to UA solvent and capping agent models, AA models have +also been included in our simulations. In most of this work, the same +(UA or AA) model for solvent and capping agent was used, but it is +also possible to utilize different models for different components. +We have also included isotopic substitutions (Hydrogen to Deuterium) +to decrease the explicit vibrational overlap between solvent and +capping agent. Table \ref{modelTest} summarizes the results of these +studies. + \begin{table*} \begin{minipage}{\linewidth} \begin{center} - \caption{Computed interfacial thermal conductivity ($G$ and - $G^\prime$) values for the Au/butanethiol/hexane interface - with united-atom model and different capping agent coverage - and solvent molecule numbers at different temperatures using a - range of energy fluxes.} - \begin{tabular}{cccccc} + \caption{Computed interfacial thermal conductance ($G$ and + $G^\prime$) values for interfaces using various models for + solvent and capping agent (or without capping agent) at + $\langle T\rangle\sim$200K. (D stands for deuterated solvent + or capping agent molecules; ``Avg.'' denotes results that are + averages of simulations under different applied thermal flux + values $(J_z)$. Error estimates are indicated in + parentheses.)} + + \begin{tabular}{llccc} \hline\hline - Thiol & $\langle T\rangle$ & & $J_z$ & $G$ & $G^\prime$ \\ - coverage (\%) & (K) & $N_{hexane}$ & (GW/m$^2$) & + Butanethiol model & Solvent & $J_z$ & $G$ & $G^\prime$ \\ + (or bare surface) & model & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ \hline - 0.0 & 200 & 200 & 0.96 & 43.3 & 42.7 \\ - & & & 1.91 & 45.7 & 42.9 \\ - & & 166 & 0.96 & 43.1 & 53.4 \\ - 88.9 & 200 & 166 & 1.94 & 172 & 108 \\ - 100.0 & 250 & 200 & 0.96 & 81.8 & 67.0 \\ - & & 166 & 0.98 & 79.0 & 62.9 \\ - & & & 1.44 & 76.2 & 64.8 \\ - & 200 & 200 & 1.92 & 129 & 87.3 \\ - & & & 1.93 & 131 & 77.5 \\ - & & 166 & 0.97 & 115 & 69.3 \\ - & & & 1.94 & 125 & 87.1 \\ + UA & UA hexane & Avg. & 131(9) & 87(10) \\ + & UA hexane(D) & 1.95 & 153(5) & 136(13) \\ + & AA hexane & Avg. & 131(6) & 122(10) \\ + & UA toluene & 1.96 & 187(16) & 151(11) \\ + & AA toluene & 1.89 & 200(36) & 149(53) \\ + \hline + AA & UA hexane & 1.94 & 116(9) & 129(8) \\ + & AA hexane & Avg. & 442(14) & 356(31) \\ + & AA hexane(D) & 1.93 & 222(12) & 234(54) \\ + & UA toluene & 1.98 & 125(25) & 97(60) \\ + & AA toluene & 3.79 & 487(56) & 290(42) \\ + \hline + AA(D) & UA hexane & 1.94 & 158(25) & 172(4) \\ + & AA hexane & 1.92 & 243(29) & 191(11) \\ + & AA toluene & 1.93 & 364(36) & 322(67) \\ + \hline + bare & UA hexane & Avg. & 46.5(3.2) & 49.4(4.5) \\ + & UA hexane(D) & 0.98 & 43.9(4.6) & 43.0(2.0) \\ + & AA hexane & 0.96 & 31.0(1.4) & 29.4(1.3) \\ + & UA toluene & 1.99 & 70.1(1.3) & 65.8(0.5) \\ \hline\hline \end{tabular} - \label{AuThiolHexaneUA} + \label{modelTest} \end{center} \end{minipage} \end{table*} -For the all-atom model, the liquid hexane phase was not stable under NPT -conditions. Therefore, the simulation length scale parameters are -adopted from previous equilibration results of the united-atom model -at 200K. Table \ref{AuThiolHexaneAA} shows the results of these -simulations. The conductivity values calculated with full capping -agent coverage are substantially larger than observed in the -united-atom model, and is even higher than predicted by -experiments. It is possible that our parameters for metal-non-metal -particle interactions lead to an overestimate of the interfacial -thermal conductivity, although the active C-H vibrations in the -all-atom model (which should not be appreciably populated at normal -temperatures) could also account for this high conductivity. The major -thermal transfer barrier of Au/butanethiol/hexane interface is between -the liquid phase and the capping agent, so extra degrees of freedom -such as the C-H vibrations could enhance heat exchange between these -two phases and result in a much higher conductivity. +To facilitate direct comparison between force fields, systems with the +same capping agent and solvent were prepared with the same length +scales for the simulation cells. +On bare metal / solvent surfaces, different force field models for +hexane yield similar results for both $G$ and $G^\prime$, and these +two definitions agree with each other very well. This is primarily an +indicator of weak interactions between the metal and the solvent, and +is a typical case for acoustic impedance mismatch between these two +phases. + +For the fully-covered surfaces, the choice of force field for the +capping agent and solvent has a large impact on the calulated values +of $G$ and $G^\prime$. The AA thiol to AA solvent conductivities are +much larger than their UA to UA counterparts, and these values exceed +the experimental estimates by a large measure. The AA force field +allows significant energy to go into C-H (or C-D) stretching modes, +and since these modes are high frequency, this non-quantum behavior is +likely responsible for the overestimate of the conductivity. Compared +to the AA model, the UA model yields more reasonable conductivity +values with much higher computational efficiency. + +\subsubsection{Are electronic excitations in the metal important?} +Because they lack electronic excitations, the QSC and related embedded +atom method (EAM) models for gold are known to predict unreasonably +low values for bulk conductivity +($\lambda$).\cite{kuang:164101,ISI:000207079300006,Clancy:1992} If the +conductance between the phases ($G$) is governed primarily by phonon +excitation (and not electronic degrees of freedom), one would expect a +classical model to capture most of the interfacial thermal +conductance. Our results for $G$ and $G^\prime$ indicate that this is +indeed the case, and suggest that the modeling of interfacial thermal +transport depends primarily on the description of the interactions +between the various components at the interface. When the metal is +chemically capped, the primary barrier to thermal conductivity appears +to be the interface between the capping agent and the surrounding +solvent, so the excitations in the metal have little impact on the +value of $G$. + +\subsection{Effects due to methodology and simulation parameters} + +We have varied the parameters of the simulations in order to +investigate how these factors would affect the computation of $G$. Of +particular interest are: 1) the length scale for the applied thermal +gradient (modified by increasing the amount of solvent in the system), +2) the sign and magnitude of the applied thermal flux, 3) the average +temperature of the simulation (which alters the solvent density during +equilibration), and 4) the definition of the interfacial conductance +(Eqs. (\ref{discreteG}) or (\ref{derivativeG})) used in the +calculation. + +Systems of different lengths were prepared by altering the number of +solvent molecules and extending the length of the box along the $z$ +axis to accomodate the extra solvent. Equilibration at the same +temperature and pressure conditions led to nearly identical surface +areas ($L_x$ and $L_y$) available to the metal and capping agent, +while the extra solvent served mainly to lengthen the axis that was +used to apply the thermal flux. For a given value of the applied +flux, the different $z$ length scale has only a weak effect on the +computed conductivities (Table \ref{AuThiolHexaneUA}). + +\subsubsection{Effects of applied flux} +The NIVS algorithm allows changes in both the sign and magnitude of +the applied flux. It is possible to reverse the direction of heat +flow simply by changing the sign of the flux, and thermal gradients +which would be difficult to obtain experimentally ($5$ K/\AA) can be +easily simulated. However, the magnitude of the applied flux is not +arbitary if one aims to obtain a stable and reliable thermal gradient. +A temperature gradient can be lost in the noise if $|J_z|$ is too +small, and excessive $|J_z|$ values can cause phase transitions if the +extremes of the simulation cell become widely separated in +temperature. Also, if $|J_z|$ is too large for the bulk conductivity +of the materials, the thermal gradient will never reach a stable +state. + +Within a reasonable range of $J_z$ values, we were able to study how +$G$ changes as a function of this flux. In what follows, we use +positive $J_z$ values to denote the case where energy is being +transferred by the method from the metal phase and into the liquid. +The resulting gradient therefore has a higher temperature in the +liquid phase. Negative flux values reverse this transfer, and result +in higher temperature metal phases. The conductance measured under +different applied $J_z$ values is listed in Tables +\ref{AuThiolHexaneUA} and \ref{AuThiolToluene}. These results do not +indicate that $G$ depends strongly on $J_z$ within this flux +range. The linear response of flux to thermal gradient simplifies our +investigations in that we can rely on $G$ measurement with only a +small number $J_z$ values. + \begin{table*} \begin{minipage}{\linewidth} \begin{center} - \caption{Computed interfacial thermal conductivity ($G$ and - $G^\prime$) values for the Au/butanethiol/hexane interface - with all-atom model and different capping agent coverage at - 200K using a range of energy fluxes.} + $G^\prime$) values for the 100\% covered Au-butanethiol/hexane + interfaces with UA model and different hexane molecule numbers + at different temperatures using a range of energy + fluxes. Error estimates indicated in parenthesis.} - \begin{tabular}{cccc} + \begin{tabular}{ccccccc} \hline\hline - Thiol & $J_z$ & $G$ & $G^\prime$ \\ - coverage (\%) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ + $\langle T\rangle$ & $N_{hexane}$ & $\rho_{hexane}$ & + $J_z$ & $G$ & $G^\prime$ \\ + (K) & & (g/cm$^3$) & (GW/m$^2$) & + \multicolumn{2}{c}{(MW/m$^2$/K)} \\ \hline - 0.0 & 0.95 & 28.5 & 27.2 \\ - & 1.88 & 30.3 & 28.9 \\ - 100.0 & 2.87 & 551 & 294 \\ - & 3.81 & 494 & 193 \\ + 200 & 266 & 0.672 & -0.96 & 102(3) & 80.0(0.8) \\ + & 200 & 0.688 & 0.96 & 125(16) & 90.2(15) \\ + & & & 1.91 & 139(10) & 101(10) \\ + & & & 2.83 & 141(6) & 89.9(9.8) \\ + & 166 & 0.681 & 0.97 & 141(30) & 78(22) \\ + & & & 1.92 & 138(4) & 98.9(9.5) \\ + \hline + 250 & 200 & 0.560 & 0.96 & 75(10) & 61.8(7.3) \\ + & & & -0.95 & 49.4(0.3) & 45.7(2.1) \\ + & 166 & 0.569 & 0.97 & 80.3(0.6) & 67(11) \\ + & & & 1.44 & 76.2(5.0) & 64.8(3.8) \\ + & & & -0.95 & 56.4(2.5) & 54.4(1.1) \\ + & & & -1.85 & 47.8(1.1) & 53.5(1.5) \\ \hline\hline \end{tabular} - \label{AuThiolHexaneAA} + \label{AuThiolHexaneUA} \end{center} \end{minipage} \end{table*} -%subsubsection{Vibrational spectrum study on conductance mechanism} -To investigate the mechanism of this interfacial thermal conductance, -the vibrational spectra of various gold systems were obtained and are -shown as in the upper panel of Fig. \ref{vibration}. To obtain these -spectra, one first runs a simulation in the NVE ensemble and collects -snapshots of configurations; these configurations are used to compute -the velocity auto-correlation functions, which is used to construct a -power spectrum via a Fourier transform. The gold surfaces covered by -butanethiol molecules exhibit an additional peak observed at a -frequency of $\sim$170cm$^{-1}$, which is attributed to the vibration -of the S-Au bond. This vibration enables efficient thermal transport -from surface Au atoms to the capping agents. Simultaneously, as shown -in the lower panel of Fig. \ref{vibration}, the large overlap of the -vibration spectra of butanethiol and hexane in the all-atom model, -including the C-H vibration, also suggests high thermal exchange -efficiency. The combination of these two effects produces the drastic -interfacial thermal conductance enhancement in the all-atom model. +The sign of $J_z$ is a different matter, however, as this can alter +the temperature on the two sides of the interface. The average +temperature values reported are for the entire system, and not for the +liquid phase, so at a given $\langle T \rangle$, the system with +positive $J_z$ has a warmer liquid phase. This means that if the +liquid carries thermal energy via convective transport, {\it positive} +$J_z$ values will result in increased molecular motion on the liquid +side of the interface, and this will increase the measured +conductivity. +\subsubsection{Effects due to average temperature} + +We also studied the effect of average system temperature on the +interfacial conductance. The simulations are first equilibrated in +the NPT ensemble at 1 atm. The TraPPE-UA model for hexane tends to +predict a lower boiling point (and liquid state density) than +experiments. This lower-density liquid phase leads to reduced contact +between the hexane and butanethiol, and this accounts for our +observation of lower conductance at higher temperatures as shown in +Table \ref{AuThiolHexaneUA}. In raising the average temperature from +200K to 250K, the density drop of ~20\% in the solvent phase leads to +a ~65\% drop in the conductance. + +Similar behavior is observed in the TraPPE-UA model for toluene, +although this model has better agreement with the experimental +densities of toluene. The expansion of the toluene liquid phase is +not as significant as that of the hexane (8.3\% over 100K), and this +limits the effect to ~20\% drop in thermal conductivity (Table +\ref{AuThiolToluene}). + +Although we have not mapped out the behavior at a large number of +temperatures, is clear that there will be a strong temperature +dependence in the interfacial conductance when the physical properties +of one side of the interface (notably the density) change rapidly as a +function of temperature. + +\begin{table*} + \begin{minipage}{\linewidth} + \begin{center} + \caption{Computed interfacial thermal conductivity ($G$ and + $G^\prime$) values for a 90\% coverage Au-butanethiol/toluene + interface at different temperatures using a range of energy + fluxes. Error estimates indicated in parenthesis.} + + \begin{tabular}{ccccc} + \hline\hline + $\langle T\rangle$ & $\rho_{toluene}$ & $J_z$ & $G$ & $G^\prime$ \\ + (K) & (g/cm$^3$) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ + \hline + 200 & 0.933 & 2.15 & 204(12) & 113(12) \\ + & & -1.86 & 180(3) & 135(21) \\ + & & -3.93 & 176(5) & 113(12) \\ + \hline + 300 & 0.855 & -1.91 & 143(5) & 125(2) \\ + & & -4.19 & 135(9) & 113(12) \\ + \hline\hline + \end{tabular} + \label{AuThiolToluene} + \end{center} + \end{minipage} +\end{table*} + +Besides the lower interfacial thermal conductance, surfaces at +relatively high temperatures are susceptible to reconstructions, +particularly when butanethiols fully cover the Au(111) surface. These +reconstructions include surface Au atoms which migrate outward to the +S atom layer, and butanethiol molecules which embed into the surface +Au layer. The driving force for this behavior is the strong Au-S +interactions which are modeled here with a deep Lennard-Jones +potential. This phenomenon agrees with reconstructions that have beeen +experimentally +observed.\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}. Vlugt +{\it et al.} kept their Au(111) slab rigid so that their simulations +could reach 300K without surface +reconstructions.\cite{vlugt:cpc2007154} Since surface reconstructions +blur the interface, the measurement of $G$ becomes more difficult to +conduct at higher temperatures. For this reason, most of our +measurements are undertaken at $\langle T\rangle\sim$200K where +reconstruction is minimized. + +However, when the surface is not completely covered by butanethiols, +the simulated system appears to be more resistent to the +reconstruction. O ur Au / butanethiol / toluene system had the Au(111) +surfaces 90\% covered by butanethiols, but did not see this above +phenomena even at $\langle T\rangle\sim$300K. That said, we did +observe butanethiols migrating to neighboring three-fold sites during +a simulation. Since the interface persisted in these simulations, +were able to obtain $G$'s for these interfaces even at a relatively +high temperature without being affected by surface reconstructions. + +\section{Discussion} + +The primary result of this work is that the capping agent acts as an +efficient thermal coupler between solid and solvent phases. One of +the ways the capping agent can carry out this role is to down-shift +between the phonon vibrations in the solid (which carry the heat from +the gold) and the molecular vibrations in the liquid (which carry some +of the heat in the solvent). + +To investigate the mechanism of interfacial thermal conductance, the +vibrational power spectrum was computed. Power spectra were taken for +individual components in different simulations. To obtain these +spectra, simulations were run after equilibration in the +microcanonical (NVE) ensemble and without a thermal +gradient. Snapshots of configurations were collected at a frequency +that is higher than that of the fastest vibrations occuring in the +simulations. With these configurations, the velocity auto-correlation +functions can be computed: +\begin{equation} +C_A (t) = \langle\vec{v}_A (t)\cdot\vec{v}_A (0)\rangle +\label{vCorr} +\end{equation} +The power spectrum is constructed via a Fourier transform of the +symmetrized velocity autocorrelation function, +\begin{equation} + \hat{f}(\omega) = + \int_{-\infty}^{\infty} C_A (t) e^{-2\pi it\omega}\,dt +\label{fourier} +\end{equation} + +\subsection{The role of specific vibrations} +The vibrational spectra for gold slabs in different environments are +shown as in Figure \ref{specAu}. Regardless of the presence of +solvent, the gold surfaces which are covered by butanethiol molecules +exhibit an additional peak observed at a frequency of +$\sim$165cm$^{-1}$. We attribute this peak to the S-Au bonding +vibration. This vibration enables efficient thermal coupling of the +surface Au layer to the capping agents. Therefore, in our simulations, +the Au / S interfaces do not appear to be the primary barrier to +thermal transport when compared with the butanethiol / solvent +interfaces. + \begin{figure} \includegraphics[width=\linewidth]{vibration} -\caption{Vibrational spectra obtained for gold in different - environments (upper panel) and for Au/thiol/hexane simulation in - all-atom model (lower panel).} -\label{vibration} +\caption{Vibrational power spectra for gold in different solvent + environments. The presence of the butanethiol capping molecules + adds a vibrational peak at $\sim$165cm$^{-1}$. The butanethiol + spectra exhibit a corresponding peak.} +\label{specAu} \end{figure} -% 600dpi, letter size. too large? +Also in this figure, we show the vibrational power spectrum for the +bound butanethiol molecules, which also exhibits the same +$\sim$165cm$^{-1}$ peak. +\subsection{Overlap of power spectra} +A comparison of the results obtained from the two different organic +solvents can also provide useful information of the interfacial +thermal transport process. In particular, the vibrational overlap +between the butanethiol and the organic solvents suggests a highly +efficient thermal exchange between these components. Very high +thermal conductivity was observed when AA models were used and C-H +vibrations were treated classically. The presence of extra degrees of +freedom in the AA force field yields higher heat exchange rates +between the two phases and results in a much higher conductivity than +in the UA force field. + +The similarity in the vibrational modes available to solvent and +capping agent can be reduced by deuterating one of the two components +(Fig. \ref{aahxntln}). Once either the hexanes or the butanethiols +are deuterated, one can observe a significantly lower $G$ and +$G^\prime$ values (Table \ref{modelTest}). + +\begin{figure} +\includegraphics[width=\linewidth]{aahxntln} +\caption{Spectra obtained for all-atom (AA) Au / butanethiol / solvent + systems. When butanethiol is deuterated (lower left), its + vibrational overlap with hexane decreases significantly. Since + aromatic molecules and the butanethiol are vibrationally dissimilar, + the change is not as dramatic when toluene is the solvent (right).} +\label{aahxntln} +\end{figure} + +For the Au / butanethiol / toluene interfaces, having the AA +butanethiol deuterated did not yield a significant change in the +measured conductance. Compared to the C-H vibrational overlap between +hexane and butanethiol, both of which have alkyl chains, the overlap +between toluene and butanethiol is not as significant and thus does +not contribute as much to the heat exchange process. + +Previous observations of Zhang {\it et al.}\cite{hase:2010} indicate +that the {\it intra}molecular heat transport due to alkylthiols is +highly efficient. Combining our observations with those of Zhang {\it + et al.}, it appears that butanethiol acts as a channel to expedite +heat flow from the gold surface and into the alkyl chain. The +acoustic impedance mismatch between the metal and the liquid phase can +therefore be effectively reduced with the presence of suitable capping +agents. + +Deuterated models in the UA force field did not decouple the thermal +transport as well as in the AA force field. The UA models, even +though they have eliminated the high frequency C-H vibrational +overlap, still have significant overlap in the lower-frequency +portions of the infrared spectra (Figure \ref{uahxnua}). Deuterating +the UA models did not decouple the low frequency region enough to +produce an observable difference for the results of $G$ (Table +\ref{modelTest}). + +\begin{figure} +\includegraphics[width=\linewidth]{uahxnua} +\caption{Vibrational spectra obtained for normal (upper) and + deuterated (lower) hexane in Au-butanethiol/hexane + systems. Butanethiol spectra are shown as reference. Both hexane and + butanethiol were using United-Atom models.} +\label{uahxnua} +\end{figure} + +\section{Conclusions} +The NIVS algorithm has been applied to simulations of +butanethiol-capped Au(111) surfaces in the presence of organic +solvents. This algorithm allows the application of unphysical thermal +flux to transfer heat between the metal and the liquid phase. With the +flux applied, we were able to measure the corresponding thermal +gradients and to obtain interfacial thermal conductivities. Under +steady states, 2-3 ns trajectory simulations are sufficient for +computation of this quantity. + +Our simulations have seen significant conductance enhancement in the +presence of capping agent, compared with the bare gold / liquid +interfaces. The acoustic impedance mismatch between the metal and the +liquid phase is effectively eliminated by a chemically-bonded capping +agent. Furthermore, the coverage precentage of the capping agent plays +an important role in the interfacial thermal transport +process. Moderately low coverages allow higher contact between capping +agent and solvent, and thus could further enhance the heat transfer +process, giving a non-monotonic behavior of conductance with +increasing coverage. + +Our results, particularly using the UA models, agree well with +available experimental data. The AA models tend to overestimate the +interfacial thermal conductance in that the classically treated C-H +vibrations become too easily populated. Compared to the AA models, the +UA models have higher computational efficiency with satisfactory +accuracy, and thus are preferable in modeling interfacial thermal +transport. + +Of the two definitions for $G$, the discrete form +(Eq. \ref{discreteG}) was easier to use and gives out relatively +consistent results, while the derivative form (Eq. \ref{derivativeG}) +is not as versatile. Although $G^\prime$ gives out comparable results +and follows similar trend with $G$ when measuring close to fully +covered or bare surfaces, the spatial resolution of $T$ profile +required for the use of a derivative form is limited by the number of +bins and the sampling required to obtain thermal gradient information. + +Vlugt {\it et al.} have investigated the surface thiol structures for +nanocrystalline gold and pointed out that they differ from those of +the Au(111) surface.\cite{landman:1998,vlugt:cpc2007154} This +difference could also cause differences in the interfacial thermal +transport behavior. To investigate this problem, one would need an +effective method for applying thermal gradients in non-planar +(i.e. spherical) geometries. + \section{Acknowledgments} Support for this project was provided by the National Science Foundation under grant CHE-0848243. Computational time was provided by the Center for Research Computing (CRC) at the University of Notre -Dame. \newpage +Dame. +\newpage \bibliography{interfacial}