--- interfacial/interfacial.tex 2011/07/11 22:34:42 3736 +++ interfacial/interfacial.tex 2011/09/30 19:37:13 3767 @@ -23,13 +23,13 @@ \setlength{\belowcaptionskip}{30 pt} %\renewcommand\citemid{\ } % no comma in optional reference note -\bibpunct{[}{]}{,}{s}{}{;} -\bibliographystyle{aip} +\bibpunct{[}{]}{,}{n}{}{;} +\bibliographystyle{achemso} \begin{document} -\title{Simulating interfacial thermal conductance at metal-solvent - interfaces: the role of chemical capping agents} +\title{Simulating Interfacial Thermal Conductance at Metal-Solvent + Interfaces: the Role of Chemical Capping Agents} \author{Shenyu Kuang and J. Daniel Gezelter\footnote{Corresponding author. \ Electronic mail: gezelter@nd.edu} \\ @@ -44,24 +44,27 @@ Notre Dame, Indiana 46556} \begin{doublespace} \begin{abstract} + With the Non-Isotropic Velocity Scaling (NIVS) approach to Reverse + Non-Equilibrium Molecular Dynamics (RNEMD) it is possible to impose + an unphysical thermal flux between different regions of + inhomogeneous systems such as solid / liquid interfaces. We have + applied NIVS to compute the interfacial thermal conductance at a + metal / organic solvent interface that has been chemically capped by + butanethiol molecules. Our calculations suggest that vibrational + coupling between the metal and liquid phases is enhanced by the + capping agents, leading to a greatly enhanced conductivity at the + interface. Specifically, the chemical bond between the metal and + the capping agent introduces a vibrational overlap that is not + present without the capping agent, and the overlap between the + vibrational spectra (metal to cap, cap to solvent) provides a + mechanism for rapid thermal transport across the interface. Our + calculations also suggest that this is a non-monotonic function of + the fractional coverage of the surface, as moderate coverages allow + diffusive heat transport of solvent molecules that have been in + close contact with the capping agent. -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. - +Keywords: non-equilibrium, molecular dynamics, vibrational overlap, +coverage dependent. \end{abstract} \newpage @@ -73,251 +76,308 @@ Interfacial thermal conductance is extensively studied %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \section{Introduction} -Interfacial thermal conductance is extensively studied both -experimentally and computationally, due to its importance in nanoscale -science and technology. Reliability of nanoscale devices depends on -their thermal transport properties. Unlike bulk homogeneous materials, -nanoscale materials features significant presence of interfaces, and -these interfaces could dominate the heat transfer behavior of these -materials. Furthermore, these materials are generally heterogeneous, -which challenges traditional research methods for homogeneous systems. +Due to the importance of heat flow (and heat removal) in +nanotechnology, interfacial thermal conductance has been studied +extensively both experimentally and computationally.\cite{cahill:793} +Nanoscale materials have a significant fraction of their atoms at +interfaces, and the chemical details of these interfaces govern the +thermal transport properties. Furthermore, the interfaces are often +heterogeneous (e.g. solid - liquid), which provides a challenge to +computational methods which have been developed for homogeneous or +bulk systems. -Heat conductance of molecular and nano-scale interfaces will be -affected by the chemical details of the surface. Experimentally, -various interfaces have been investigated for their thermal -conductance properties. 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}; 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 -commonly 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}. +Experimentally, the thermal properties of a number of interfaces have +been investigated. Cahill and coworkers studied nanoscale thermal +transport from metal nanoparticle/fluid interfaces, to epitaxial +TiN/single crystal oxides interfaces, and 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 +cetyltrimethylammonium bromide (CTAB) on the 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 resistance 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} -Theoretical and computational studies were also engaged in the -interfacial thermal transport research in order to gain an -understanding of this phenomena at the molecular level. 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 alkylthiolate with relatively long chain -(8-20 carbon atoms)\cite{hase:2010,hase:2011}. However, -emsemble average measurements for heat conductance of interfaces -between the capping monolayer on Au and a solvent phase has yet to be -studied. The relatively low thermal flux through interfaces is -difficult to measure with Equilibrium MD or forward NEMD simulation -methods. Therefore, the Reverse NEMD (RNEMD) methods would have the -advantage of having this difficult to measure flux known when studying -the thermal transport across interfaces, given that the simulation -methods being able to effectively apply an unphysical flux in -non-homogeneous systems. +The acoustic mismatch model for interfacial conductance utilizes the +acoustic impedance ($Z_a = \rho_a v^s_a$) on both sides of the +interface.\cite{schwartz} Here, $\rho_a$ and $v^s_a$ are the density +and speed of sound in material $a$. The phonon transmission +probability at the $a-b$ interface is +\begin{equation} +t_{ab} = \frac{4 Z_a Z_b}{\left(Z_a + Z_b \right)^2}, +\end{equation} +and the interfacial conductance can then be approximated as +\begin{equation} +G_{ab} \approx \frac{1}{4} C_D v_D t_{ab} +\end{equation} +where $C_D$ is the Debye heat capacity of the hot side, and $v_D$ is +the Debye phonon velocity ($1/v_D^3 = 1/3v_L^3 + 2/3 v_T^3$) where +$v_L$ and $v_T$ are the longitudinal and transverse speeds of sound, +respectively. For the Au/hexane and Au/toluene interfaces, the +acoustic mismatch model predicts room-temperature $G \approx 87 \mbox{ + and } 129$ MW m$^{-2}$ K$^{-1}$, respectively. However, it is not +clear how one might apply the acoustic mismatch model to a +chemically-modified surface, particularly when the acoustic properties +of a monolayer film may not be well characterized. -Recently, we have developed the Non-Isotropic Velocity Scaling (NIVS) +More precise 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 be advantageous +in that they {\it apply} the difficult to measure quantity (flux), +while {\it measuring} the easily-computed quantity (the thermal +gradient). This is particularly true for inhomogeneous interfaces +where it would not be clear how to apply a gradient {\it a priori}. +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 chemical details of a +number of hydrophobic and hydrophilic aqueous interfaces. And +recently, Luo {\it et al.} studied the thermal conductance of +Au-SAM-Au junctions using the same approach, comparing to a constant +temperature difference method.\cite{Luo20101} While this latter +approach establishes more ideal Maxwell-Boltzmann distributions than +previous RNEMD methods, it does not guarantee momentum or kinetic +energy conservation. + +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 under steady states. +the two slabs. Furthermore, it allows effective thermal exchange +between particles of different identities, and thus makes the study of +interfacial conductance much simpler. -Our work presented here investigated the Au(111) surface with various -coverage of butanethiol, a capping agent with shorter carbon chain, -solvated with organic solvents of different molecular shapes. And -different models were used for both the capping agent and the solvent -force field parameters. With the NIVS algorithm applied, the thermal -transport through these interfacial systems was studied and the -underlying mechanism for this phenomena was investigated. +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. -[WHY STUDY AU-THIOL SURFACE; MAY CITE SHAOYI JIANG] - \section{Methodology} -\subsection{Algorithm} -[BACKGROUND FOR MD METHODS] -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. - -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 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. +\subsection{Imposed-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 +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 arbitrary identity, and +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 +of a simulation system with respective diagonal scaling matrices. To +determine these scaling factors in the matrices, 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 transport 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. -\subsection{Defining Interfacial Thermal Conductivity $G$} -For interfaces with a relatively low interfacial conductance, the bulk -regions on either side of an 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: +\subsection{Defining Interfacial Thermal Conductivity ($G$)} + +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 - + 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 imposed non-physical kinetic energy -transfer and ${\langle T_\mathrm{hot}\rangle}$ and ${\langle - T_\mathrm{cold}\rangle}$ are the average observed temperature of the -two separated phases. +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 $L_x \times L_y$, $E_{total} = J_z *(t)*(2 L_x L_y)$. -When the interfacial conductance is {\it not} small, two ways can be -used to define $G$. - -One way is to assume the temperature is discretely different on two -sides of the interface, $G$ can be calculated with the thermal flux -applied $J$ and the maximum temperature difference measured along the -thermal gradient max($\Delta T$), which occurs at the interface, as: +When the interfacial conductance is {\it not} small, there are two +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 dividing 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} -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 reach 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| - \Big/\left(\frac{\partial T}{\partial z}\right)^2 -\label{derivativeG} -\end{equation} +\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 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} -With the temperature profile obtained from simulations, one is able to +Another approach is to assume that the temperature is continuous and +differentiable throughout the space. Given that $\lambda$ is also +differentiable, $G$ can be defined as its gradient ($\nabla\lambda$) +projected along a vector normal to the interface ($\mathbf{\hat{n}}$) +and evaluated at the interface location ($z_0$). This quantity, +\begin{align} +G^\prime &= \left(\nabla\lambda \cdot \mathbf{\hat{n}}\right)_{z_0} \\ + &= \frac{\partial}{\partial z}\left(-\frac{J_z}{ + \left(\frac{\partial T}{\partial z}\right)}\right)_{z_0} \\ + &= J_z\left(\frac{\partial^2 T}{\partial z^2}\right)_{z_0} \Big/ + \left(\frac{\partial T}{\partial z}\right)_{z_0}^2 \label{derivativeG} +\end{align} +has the same units as the common definition for $G$, and the maximum +of its magnitude denotes where thermal conductivity has the largest +change, i.e. the interface. In the geometry used in this study, the +vector normal to the interface points along the $z$ axis, as do +$\vec{J}$ and the thermal gradient. This yields the simplified +expressions in Eq. \ref{derivativeG}. + +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}. -[IMPOSE G DEFINITION INTO OUR SYSTEMS] -To facilitate the use of the above definitions in calculating $G$ and -$G^\prime$, we have a metal slab with its (111) surfaces perpendicular -to the $z$-axis of our simulation cells. With or withour capping -agents on the surfaces, the metal slab is solvated with organic -solvents, as illustrated in Figure \ref{demoPic}. +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. \begin{figure} -\includegraphics[width=\linewidth]{demoPic} -\caption{A sample showing how a metal slab has its (111) surface - covered by capping agent molecules and solvated by hexane.} -\label{demoPic} -\end{figure} - -With a simulation cell setup following the above manner, one is able -to equilibrate the system and impose an unphysical thermal flux -between the liquid and the metal phase with the NIVS algorithm. Under -a stablized thermal gradient induced by periodically applying the -unphysical flux, one is able to obtain a temperature profile and the -physical thermal flux corresponding to it, which equals to the -unphysical flux applied by NIVS. These data enables the evaluation of -the interfacial thermal conductance of a surface. Figure \ref{gradT} -is an example how those stablized thermal gradient can be used to -obtain the 1st and 2nd derivatives of the temperature profile. - -\begin{figure} \includegraphics[width=\linewidth]{gradT} -\caption{The 1st and 2nd derivatives of temperature profile can be - obtained with finite difference approximation.} +\caption{A sample of Au (111) / butanethiol / hexane interfacial + system with the temperature profile after a kinetic energy flux has + been imposed. Note that the largest temperature jump in the thermal + profile (corresponding to the lowest interfacial conductance) is at + the interface between the butanethiol molecules (blue) and the + solvent (grey). First and second derivatives of the temperature + profile are obtained using a finite difference approximation (lower + panel).} \label{gradT} \end{figure} -[MAY INCLUDE POWER SPECTRUM PROTOCOL] - \section{Computational Details} \subsection{Simulation Protocol} -Our MD simulation code, OpenMD\cite{Meineke:2005gd,openmd}, has the -NIVS algorithm integrated and was used for our simulations. In our -simulations, Au is used to construct a metal slab with bare (111) -surface perpendicular to the $z$-axis. Different slab thickness (layer -numbers of Au) are simulated. This metal slab is first equilibrated -under normal pressure (1 atm) and a desired temperature. After -equilibration, butanethiol is used as the capping agent molecule to -cover the bare Au (111) surfaces evenly. The sulfur atoms in the -butanethiol molecules would occupy the three-fold sites of the -surfaces, and the maximal butanethiol capacity on Au surface is $1/3$ -of the total number of surface Au atoms[CITATIONs]. A series of -different coverage surfaces is investigated in order to study the -relation between coverage and conductance. +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. -[COVERAGE DISCRIPTION] -In the initial configurations for each coverage precentage, -butanethiols were distributed evenly on the Au(111) surfaces. However, -since the interaction descriptions between surface Au and butanethiol -is non-bonded in our simulations, the capping agent molecules are -allowed to migrate to an empty neighbor three-fold site during a -simulation. Therefore, the initial configuration would not severely -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. [MAY NEED FIGURES] +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 are equilibrated -under canonical ensemble, organic solvent molecules are packed in the -previously vacuum part of the simulation cells and guarantees that -short range repulsive interactions do not disrupt the -simulations\cite{packmol}. Two solvents are investigated, one which -has little vibrational overlap with the alkanethiol and plane-like -shape (toluene), and one which has similar vibrational frequencies and -chain-like shape ({\it n}-hexane). [MAY EXPLAIN WHY WE CHOOSE THEM] +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 spacing filled by solvent molecules, i.e. the gap between -periodically repeated Au-butanethiol surfaces should be carefully -chosen. A very long length scale for the thermal gradient axis ($z$) -may cause excessively hot or cold temperatures in the middle of the +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. And the -corresponding spacing is usually $35 \sim 60$\AA. +these extreme cases did not happen to our simulations. The spacing +between periodic images of the gold interfaces is $45 \sim 75$\AA in +our simulations. -The initial configurations generated by Packmol are further -equilibrated with the $x$ and $y$ dimensions fixed, only allowing -length scale change in $z$ dimension. This is to ensure that the -equilibration of liquid phase does not affect the metal crystal -structure in $x$ and $y$ dimensions. Further equilibration are run -under NVT and then NVE ensembles. +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 is implemented to impose a -periodic unphysical thermal flux between the metal and the liquid -phase. Most of our simulations are under an average temperature of -$\sim$200K. Therefore, this flux usually comes from the metal to the +After the systems reach equilibrium, NIVS was used to impose an +unphysical thermal flux between the metal and the liquid phases. Most +of our simulations were done under an average temperature of +$\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 excessively low temperature. This induced temperature -gradient is stablized and the simulation cell is devided evenly into -N slabs along the $z$-axis and the temperatures of each slab are -recorded. 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| +freeze due to lowered temperatures. After this induced temperature +gradient had stabilized, the temperature profile of the simulation cell +was recorded. To do this, the simulation cell is divided 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 @@ -325,114 +385,143 @@ G^\prime = |J_z|\Big|\frac{\partial^2 T}{\partial z^2} \Big/\left(\frac{\partial T}{\partial n}\right)^2 \label{derivativeG2} \end{equation} +The absolute values in Eq. \ref{derivativeG2} appear because the +direction of the flux $\vec{J}$ is in an opposing direction on either +side of the metal slab. +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 various components. Therefore, force field -parameter descriptions are needed for interactions both between the -same type of particles and between particles of different species. +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 References + \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 +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}. +Sutton-Chen potentials.\cite{Chen90} -Figure \ref{demoMol} demonstrates how we name our pseudo-atoms of the -organic solvent molecules in our simulations. +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. -\begin{figure} -\includegraphics[width=\linewidth]{demoMol} -\caption{Denomination of atoms or pseudo-atoms in our simulations: a) - UA-hexane; b) AA-hexane; c) UA-toluene; d) AA-toluene.} -\label{demoMol} -\end{figure} +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 slightly +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 both solvent molecules, straight chain {\it n}-hexane and aromatic -toluene, United-Atom (UA) and All-Atom (AA) models are used -respectively. The TraPPE-UA -parameters\cite{TraPPE-UA.alkanes,TraPPE-UA.alkylbenzenes} are used -for our UA solvent molecules. In these models, pseudo-atoms are -located at the carbon centers for alkyl groups. By eliminating -explicit hydrogen atoms, these models are simple and computationally -efficient, while maintains good accuracy. However, the TraPPE-UA for -alkanes is known to predict a lower boiling point than experimental -values. Considering that after an unphysical thermal flux is applied -to a system, the temperature of ``hot'' area in the liquid phase would be -significantly higher than the average, to prevent over heating and -boiling of the liquid phase, the average temperature in our -simulations should be much lower than the liquid boiling point. [MORE DISCUSSION] -For UA-toluene model, rigid body constraints are applied, so that the -benzene ring and the methyl-CRar bond are kept rigid. This would save -computational time.[MORE DETAILS] +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. For hexane, the OPLS-AA\cite{OPLSAA} -force field is used. [MORE DETAILS] -For toluene, the United Force Field developed by Rapp\'{e} {\it et - al.}\cite{doi:10.1021/ja00051a040} is adopted.[MORE DETAILS] +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 capping agent in our simulations, the butanethiol molecules can -either use UA or AA model. The TraPPE-UA force fields includes +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 adapt this -change and derive suitable parameters for butanethiol adsorbed on -Au(111) surfaces, we adopt the S parameters from Luedtke and -Landman\cite{landman:1998} and modify parameters for its neighbor C -atom for charge balance in the molecule. Note that the model choice -(UA or AA) of 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:[EQN'S] +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. -To describe the interactions between metal Au and non-metal capping -agent and solvent particles, 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\cite{hautman:4994} for the -Au(111) surface. As our simulations require the gold lattice slab to -be non-rigid so that it could accommodate kinetic energy for thermal -transport study purpose, the pair-wise form of potentials is -preferred. +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. -Besides, 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.[MORE DETAILS] - -However, the Lennard-Jones parameters between Au and other types of -particles in our simulations are not yet well-established. For these -interactions, we attempt to derive their parameters using the Mixing -Rule. To do this, the ``Metal-non-Metal'' (MnM) interaction parameters -for Au is first extracted from the Au-CH$_x$ parameters by applying -the Mixing Rule reversely. Table \ref{MnM} summarizes these ``MnM'' -parameters in our simulations. - \begin{table*} \begin{minipage}{\linewidth} \begin{center} - \caption{Lennard-Jones parameters for Au-non-Metal - interactions in our simulations.} - - \begin{tabular}{ccc} + \caption{Non-bonded interaction parameters (including cross + interactions with Au atoms) for both force fields used in this + work.} + \begin{tabular}{lllllll} \hline\hline - Non-metal atom & $\sigma$ & $\epsilon$ \\ - (or pseudo-atom) & \AA & kcal/mol \\ + & Site & $\sigma_{ii}$ & $\epsilon_{ii}$ & $q_i$ & + $\sigma_{Au-i}$ & $\epsilon_{Au-i}$ \\ + & & (\AA) & (kcal/mol) & ($e$) & (\AA) & (kcal/mol) \\ \hline - S & 2.40 & 8.465 \\ - CH3 & 3.54 & 0.2146 \\ - CH2 & 3.54 & 0.1749 \\ - CT3 & 3.365 & 0.1373 \\ - CT2 & 3.365 & 0.1373 \\ - CTT & 3.365 & 0.1373 \\ - HC & 2.865 & 0.09256 \\ - CHar & 3.4625 & 0.1680 \\ - CRar & 3.555 & 0.1604 \\ - CA & 3.173 & 0.0640 \\ - HA & 2.746 & 0.0414 \\ + 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{MnM} @@ -441,316 +530,131 @@ parameters in our simulations. \end{table*} -\section{Results and Discussions} -[MAY HAVE A BRIEF SUMMARY] -\subsection{How Simulation Parameters Affects $G$} -[MAY NOT PUT AT FIRST] -We have varied our protocol or other parameters of the simulations in -order to investigate how these factors would affect the measurement of -$G$'s. It turned out that while some of these parameters would not -affect the results substantially, some other changes to the -simulations would have a significant impact on the measurement -results. +\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. -In some of our simulations, we allowed $L_x$ and $L_y$ to change -during equilibrating the liquid phase. Due to the stiffness of the Au -slab, $L_x$ and $L_y$ would not change noticeably after -equilibration. Although $L_z$ could fluctuate $\sim$1\% after a system -is fully equilibrated in the NPT ensemble, this fluctuation, as well -as those comparably smaller to $L_x$ and $L_y$, would not be magnified -on the calculated $G$'s, as shown in Table \ref{AuThiolHexaneUA}. This -insensivity to $L_i$ fluctuations allows reliable measurement of $G$'s -without the necessity of extremely cautious equilibration process. +\subsection{Effects due to capping agent coverage} -As stated in our computational details, the spacing filled with -solvent molecules can be chosen within a range. This allows some -change of solvent molecule numbers for the same Au-butanethiol -surfaces. We did this study on our Au-butanethiol/hexane -simulations. Nevertheless, the results obtained from systems of -different $N_{hexane}$ did not indicate that the measurement of $G$ is -susceptible to this parameter. For computational efficiency concern, -smaller system size would be preferable, given that the liquid phase -structure is not affected. +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. -Our NIVS algorithm allows change of unphysical thermal flux both in -direction and in quantity. This feature extends our investigation of -interfacial thermal conductance. However, the magnitude of this -thermal flux is not arbitary if one aims to obtain a stable and -reliable thermal gradient. A temperature profile would be -substantially affected by noise when $|J_z|$ has a much too low -magnitude; while an excessively large $|J_z|$ that overwhelms the -conductance capacity of the interface would prevent a thermal gradient -to reach a stablized steady state. NIVS has the advantage of allowing -$J$ to vary in a wide range such that the optimal flux range for $G$ -measurement can generally be simulated by the algorithm. Within the -optimal range, we were able to study how $G$ would change according to -the thermal flux across the interface. For our simulations, we denote -$J_z$ to be positive when the physical thermal flux is from the liquid -to metal, and negative vice versa. The $G$'s measured under different -$J_z$ is listed in Table \ref{AuThiolHexaneUA} and [REF]. These -results do not suggest that $G$ is dependent 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 -couple $J_z$'s and do not need to test a large series of fluxes. +\begin{figure} +\includegraphics[width=\linewidth]{coverage} +\caption{The interfacial thermal conductivity ($G$) has a + non-monotonic dependence on the degree of surface capping. This + data is for the Au(111) / butanethiol / solvent interface with + various UA force fields at $\langle T\rangle \sim $200K.} +\label{coverage} +\end{figure} -%ADD MORE TO TABLE -\begin{table*} - \begin{minipage}{\linewidth} - \begin{center} - \caption{Computed interfacial thermal conductivity ($G$ and - $G^\prime$) 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.} - - \begin{tabular}{cccccccc} - \hline\hline - $\langle T\rangle$ & & $L_x$ & $L_y$ & $L_z$ & $J_z$ & - $G$ & $G^\prime$ \\ - (K) & $N_{hexane}$ & \multicolumn{3}{c}{(\AA)} & (GW/m$^2$) & - \multicolumn{2}{c}{(MW/m$^2$/K)} \\ - \hline - 200 & 266 & 29.86 & 25.80 & 113.1 & -0.96 & - 102() & 80.0() \\ - & 200 & 29.84 & 25.81 & 93.9 & 1.92 & - 129() & 87.3() \\ - & & 29.84 & 25.81 & 95.3 & 1.93 & - 131() & 77.5() \\ - & 166 & 29.84 & 25.81 & 85.7 & 0.97 & - 115() & 69.3() \\ - & & & & & 1.94 & - 125() & 87.1() \\ - 250 & 200 & 29.84 & 25.87 & 106.8 & 0.96 & - 81.8() & 67.0() \\ - & 166 & 29.87 & 25.84 & 94.8 & 0.98 & - 79.0() & 62.9() \\ - & & 29.84 & 25.85 & 95.0 & 1.44 & - 76.2() & 64.8() \\ - \hline\hline - \end{tabular} - \label{AuThiolHexaneUA} - \end{center} - \end{minipage} -\end{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. -Furthermore, we also attempted to increase system average temperatures -to above 200K. These simulations are first equilibrated in the NPT -ensemble under normal pressure. As stated above, the TraPPE-UA model -for hexane tends to predict a lower boiling point. In our simulations, -hexane had diffculty to remain in liquid phase when NPT equilibration -temperature is higher than 250K. Additionally, the equilibrated liquid -hexane density under 250K becomes lower than experimental value. This -expanded liquid phase leads to lower contact between hexane and -butanethiol as well.[MAY NEED FIGURE] And this reduced contact would -probably be accountable for a lower interfacial thermal conductance, -as shown in Table \ref{AuThiolHexaneUA}. +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. Capping agents are clearly +playing a major role in thermal transport at metal / organic solvent +surfaces. -A similar study for TraPPE-UA toluene agrees with the above result as -well. Having a higher boiling point, toluene tends to remain liquid in -our simulations even equilibrated under 300K in NPT -ensembles. Furthermore, the expansion of the toluene liquid phase is -not as significant as that of the hexane. This prevents severe -decrease of liquid-capping agent contact and the results (Table -\ref{AuThiolToluene}) show only a slightly decreased interface -conductance. Therefore, solvent-capping agent contact should play an -important role in the thermal transport process across the interface -in that higher degree of contact could yield increased conductance. +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. -[ADD Lxyz AND ERROR ESTIMATE TO TABLE] -\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.} - - \begin{tabular}{cccc} - \hline\hline - $\langle T\rangle$ & $J_z$ & $G$ & $G^\prime$ \\ - (K) & (GW/m$^2$) & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ - \hline - 200 & -1.86 & 180() & 135() \\ - & 2.15 & 204() & 113() \\ - & -3.93 & 175() & 114() \\ - 300 & -1.91 & 143() & 125() \\ - & -4.19 & 134() & 113() \\ - \hline\hline - \end{tabular} - \label{AuThiolToluene} - \end{center} - \end{minipage} -\end{table*} +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. -Besides lower interfacial thermal conductance, surfaces in relatively -high temperatures are susceptible to reconstructions, when -butanethiols have a full coverage on the Au(111) surface. These -reconstructions include surface Au atoms migrated outward to the S -atom layer, and butanethiol molecules embedded into the original -surface Au layer. The driving force for this behavior is the strong -Au-S interactions in our simulations. And these reconstructions lead -to higher ratio of Au-S attraction and thus is energetically -favorable. Furthermore, this phenomenon agrees with experimental -results\cite{doi:10.1021/j100035a033,doi:10.1021/la026493y}. Vlugt -{\it et al.} had kept their Au(111) slab rigid so that their -simulations can reach 300K without surface reconstructions. Without -this practice, simulating 100\% thiol covered interfaces under higher -temperatures could hardly avoid surface reconstructions. However, our -measurement is based on assuming homogeneity on $x$ and $y$ dimensions -so that measurement of $T$ at particular $z$ would be an effective -average of the particles of the same type. Since surface -reconstructions could eliminate the original $x$ and $y$ dimensional -homogeneity, measurement of $G$ is more difficult to conduct under -higher temperatures. Therefore, most of our measurements are -undertaken at $\langle T\rangle\sim$200K. +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. -However, when the surface is not completely covered by butanethiols, -the simulated system is more resistent to the reconstruction -above. Our Au-butanethiol/toluene system did not see this phenomena -even at $\langle T\rangle\sim$300K. The Au(111) surfaces have a 90\% coverage of -butanethiols and have empty three-fold sites. These empty sites could -help prevent surface reconstruction in that they provide other means -of capping agent relaxation. It is observed that butanethiols can -migrate to their neighbor empty sites during a simulation. Therefore, -we were able to obtain $G$'s for these interfaces even at a relatively -high temperature without being affected by surface reconstructions. +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{Influence of Capping Agent Coverage on $G$} -To investigate the influence of butanethiol coverage on interfacial -thermal conductance, a series of different coverage Au-butanethiol -surfaces is prepared and solvated with various organic -molecules. These systems are then equilibrated and their interfacial -thermal conductivity are measured with our NIVS algorithm. Table -\ref{tlnUhxnUhxnD} lists these results for direct comparison between -different coverages of butanethiol. To study the isotope effect in -interfacial thermal conductance, deuterated UA-hexane is included as -well. +\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. -It turned out that with partial covered butanethiol on the Au(111) -surface, the derivative definition for $G$ (Eq. \ref{derivativeG}) has -difficulty to apply, due to the difficulty in locating the maximum of -change of $\lambda$. Instead, the discrete definition -(Eq. \ref{discreteG}) is easier to apply, as max($\Delta T$) can still -be well-defined. Therefore, $G$'s (not $G^\prime$) are used for this -section. - -From Table \ref{tlnUhxnUhxnD}, one can see the significance of the -presence of capping agents. Even when a fraction of the Au(111) -surface sites are covered with butanethiols, the conductivity would -see an enhancement by at least a factor of 3. This indicates the -important role cappping agent is playing for thermal transport -phenomena on metal/organic solvent surfaces. - -Interestingly, as one could observe from our results, the maximum -conductance enhancement (largest $G$) happens while the surfaces are -about 75\% covered with butanethiols. This again indicates that -solvent-capping agent contact has an important role of the thermal -transport process. Slightly lower butanethiol coverage allows small -gaps between butanethiols to form. And these gaps could be filled with -solvent molecules, which acts like ``heat conductors'' on the -surface. The higher degree of interaction between these solvent -molecules and capping agents increases the enhancement effect and thus -produces a higher $G$ than densely packed butanethiol arrays. However, -once this maximum conductance enhancement is reached, $G$ decreases -when butanethiol coverage continues to decrease. Each capping agent -molecule reaches its maximum capacity for thermal -conductance. Therefore, even higher solvent-capping agent contact -would not offset this effect. Eventually, when butanethiol coverage -continues to decrease, solvent-capping agent contact actually -decreases with the disappearing of butanethiol molecules. In this -case, $G$ decrease could not be offset but instead accelerated. - -A comparison of the results obtained from differenet organic solvents -can also provide useful information of the interfacial thermal -transport process. The deuterated hexane (UA) results do not appear to -be much different from those of normal hexane (UA), given that -butanethiol (UA) is non-deuterated for both solvents. These UA model -studies, even though eliminating C-H vibration samplings, still have -C-C vibrational frequencies different from each other. However, these -differences in the infrared range do not seem to produce an observable -difference for the results of $G$. [MAY NEED FIGURE] - -Furthermore, results for rigid body toluene solvent, as well as other -UA-hexane solvents, are reasonable within the general experimental -ranges[CITATIONS]. This suggests that explicit hydrogen might not be a -required factor for modeling thermal transport phenomena of systems -such as Au-thiol/organic solvent. - -However, results for Au-butanethiol/toluene do not show an identical -trend with those for Au-butanethiol/hexane in that $G$'s remain at -approximately the same magnitue when butanethiol coverage differs from -25\% to 75\%. This might be rooted in the molecule shape difference -for plane-like toluene and chain-like {\it n}-hexane. Due to this -difference, toluene molecules have more difficulty in occupying -relatively small gaps among capping agents when their coverage is not -too low. Therefore, the solvent-capping agent contact may keep -increasing until the capping agent coverage reaches a relatively low -level. This becomes an offset for decreasing butanethiol molecules on -its effect to the process of interfacial thermal transport. Thus, one -can see a plateau of $G$ vs. butanethiol coverage in our results. - -[NEED ERROR ESTIMATE, MAY ALSO PUT J HERE] \begin{table*} \begin{minipage}{\linewidth} \begin{center} - \caption{Computed 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$200K using certain energy flux respectively.} - \begin{tabular}{cccc} - \hline\hline - Thiol & \multicolumn{3}{c}{$G$(MW/m$^2$/K)} \\ - coverage (\%) & hexane & hexane(D) & toluene \\ - \hline - 0.0 & 46.5() & 43.9() & 70.1() \\ - 25.0 & 151() & 153() & 249() \\ - 50.0 & 172() & 182() & 214() \\ - 75.0 & 242() & 229() & 244() \\ - 88.9 & 178() & - & - \\ - 100.0 & 137() & 153() & 187() \\ - \hline\hline - \end{tabular} - \label{tlnUhxnUhxnD} - \end{center} - \end{minipage} -\end{table*} - -\subsection{Influence of Chosen Molecule Model on $G$} -[MAY COMBINE W MECHANISM STUDY] - -In addition to UA solvent/capping agent models, AA models are included -in our simulations as well. Besides simulations of the same (UA or AA) -model for solvent and capping agent, different models can be applied -to different components. Furthermore, regardless of models chosen, -either the solvent or the capping agent can be deuterated, similar to -the previous section. Table \ref{modelTest} summarizes the results of -these studies. - -[MORE DATA; ERROR ESTIMATE] -\begin{table*} - \begin{minipage}{\linewidth} - \begin{center} - - \caption{Computed interfacial thermal conductivity ($G$ and + \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.} + $\langle T\rangle\sim$200K. Here ``D'' stands for deuterated + solvent or capping agent molecules. Error estimates are + indicated in parentheses.} - \begin{tabular}{ccccc} + \begin{tabular}{llccc} \hline\hline - Butanethiol model & Solvent & $J_z$ & $G$ & $G^\prime$ \\ - (or bare surface) & model & (GW/m$^2$) & + Butanethiol model & Solvent & $G$ & $G^\prime$ \\ + (or bare surface) & model & \multicolumn{2}{c}{(MW/m$^2$/K)} \\ \hline - UA & AA hexane & 1.94 & 135() & 129() \\ - & & 2.86 & 126() & 115() \\ - & AA toluene & 1.89 & 200() & 149() \\ - AA & UA hexane & 1.94 & 116() & 129() \\ - & AA hexane & 3.76 & 451() & 378() \\ - & & 4.71 & 432() & 334() \\ - & AA toluene & 3.79 & 487() & 290() \\ - AA(D) & UA hexane & 1.94 & 158() & 172() \\ - bare & AA hexane & 0.96 & 31.0() & 29.4() \\ + UA & UA hexane & 131(9) & 87(10) \\ + & UA hexane(D) & 153(5) & 136(13) \\ + & AA hexane & 131(6) & 122(10) \\ + & UA toluene & 187(16) & 151(11) \\ + & AA toluene & 200(36) & 149(53) \\ + \hline + AA & UA hexane & 116(9) & 129(8) \\ + & AA hexane & 442(14) & 356(31) \\ + & AA hexane(D) & 222(12) & 234(54) \\ + & UA toluene & 125(25) & 97(60) \\ + & AA toluene & 487(56) & 290(42) \\ + \hline + AA(D) & UA hexane & 158(25) & 172(4) \\ + & AA hexane & 243(29) & 191(11) \\ + & AA toluene & 364(36) & 322(67) \\ + \hline + bare & UA hexane & 46.5(3.2) & 49.4(4.5) \\ + & UA hexane(D) & 43.9(4.6) & 43.0(2.0) \\ + & AA hexane & 31.0(1.4) & 29.4(1.3) \\ + & UA toluene & 70.1(1.3) & 65.8(0.5) \\ \hline\hline \end{tabular} \label{modelTest} @@ -758,125 +662,337 @@ To facilitate direct comparison, the same system with \end{minipage} \end{table*} -To facilitate direct comparison, the same system with differnt models -for different components uses the same length scale for their -simulation cells. Without the presence of capping agent, using -different models for hexane yields similar results for both $G$ and -$G^\prime$, and these two definitions agree with eath other very -well. This indicates very weak interaction between the metal and the -solvent, and is a typical case for acoustic impedance mismatch between -these two phases. +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. -As for Au(111) surfaces completely covered by butanethiols, the choice -of models for capping agent and solvent could impact the measurement -of $G$ and $G^\prime$ quite significantly. For Au-butanethiol/hexane -interfaces, using AA model for both butanethiol and hexane yields -substantially higher conductivity values than using UA model for at -least one component of the solvent and capping agent, which exceeds -the upper bond of experimental value range. This is probably due to -the classically treated C-H vibrations in the AA model, which should -not be appreciably populated at normal temperatures. In comparison, -once either the hexanes or the butanethiols are deuterated, one can -see a significantly lower $G$ and $G^\prime$. In either of these -cases, the C-H(D) vibrational overlap between the solvent and the -capping agent is removed. [MAY NEED FIGURE] Conclusively, the -improperly treated C-H vibration in the AA model produced -over-predicted results accordingly. Compared to the AA model, the UA -model yields more reasonable results with higher computational -efficiency. +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. -However, for Au-butanethiol/toluene interfaces, having the AA -butanethiol deuterated did not yield a significant change in the -measurement results. -. , 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. +For the fully-covered surfaces, the choice of force field for the +capping agent and solvent has a large impact on the calculated 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. - -Although the QSC model for Au is known to predict an overly low value -for bulk metal gold conductivity[CITE NIVSRNEMD], our computational -results for $G$ and $G^\prime$ do not seem to be affected by this -drawback of the model for metal. Instead, the modeling of interfacial -thermal transport behavior relies mainly on an accurate description of -the interactions between components occupying the interfaces. +\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{Mechanism of Interfacial Thermal Conductance Enhancement - by Capping Agent} -%OR\subsection{Vibrational spectrum study on conductance mechanism} +\subsection{Effects due to methodology and simulation parameters} -[MAY INTRODUCE PROTOCOL IN METHODOLOGY/COMPUTATIONAL DETAIL, EQN'S] +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. -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. +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}). - The gold surfaces covered by -butanethiol molecules, compared to bare gold surfaces, 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. +\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 +arbitrary 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. -[MAY NEED TO CONVERT TO JPEG] +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 1 and 2 in the +supporting information. 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. + +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 diffusive 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. In raising +the average temperature from 200K to 250K, the density drop of +$\sim$20\% in the solvent phase leads to a $\sim$40\% 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 $\sim$20\% drop in thermal conductivity. + +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. + +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 been +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. Our 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, we +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 occurring 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. This supports the results of Luo {\it et + al.}\cite{Luo20101}, who reported $G$ for Au-SAM junctions roughly +twice as large as what we have computed for the thiol-liquid +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{The vibrational power spectrum for thiol-capped gold has an + additional vibrational peak at $\sim $165cm$^{-1}$. Bare gold + surfaces (both with and without a solvent over-layer) are missing + this peak. A similar peak at $\sim $165cm$^{-1}$ also appears in + the vibrational power spectrum for the butanethiol capping agents.} +\label{specAu} \end{figure} -[COMPARISON OF TWO G'S; AU SLAB WIDTHS; ETC] -% The results show that the two definitions used for $G$ yield -% comparable values, though $G^\prime$ tends to be smaller. +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 all-atom classical models include high +frequency modes which should be unpopulated at our relatively low +temperatures. This artifact is likely the cause of the high thermal +conductance in all-atom MD simulations. + +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 +vibrational coupling between the metal and the liquid phase can +therefore be enhanced 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 power spectra for UA models for the butanethiol + and hexane solvent (upper panel) show the high degree of overlap + between these two molecules, particularly at lower frequencies. + Deuterating a UA model for the solvent (lower panel) does not + decouple the two spectra to the same degree as in the AA force + field (see Fig \ref{aahxntln}).} +\label{uahxnua} +\end{figure} + \section{Conclusions} -The NIVS algorithm we developed has been applied to simulations of -Au-butanethiol surfaces with organic solvents. This algorithm allows -effective unphysical thermal flux transferred between the metal and -the liquid phase. With the flux applied, we were able to measure the -corresponding thermal gradient and to obtain interfacial thermal -conductivities. Our simulations have seen significant conductance -enhancement with the presence of capping agent, compared to the bare -gold/liquid interfaces. The acoustic impedance mismatch between the -metal and the liquid phase is effectively eliminated by proper capping -agent. Furthermore, the coverage precentage of the capping agent plays -an important role in the interfacial thermal transport process. +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 measurement results, particularly of the UA models, agree with -available experimental data. This indicates that our force field -parameters have a nice description of the interactions between the -particles at the interfaces. AA models tend to overestimate the +Our simulations have seen significant conductance enhancement in the +presence of capping agent, compared with the bare gold / liquid +interfaces. The vibrational coupling between the metal and the liquid +phase is enhanced by a chemically-bonded capping agent. Furthermore, +the coverage percentage 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 -vibration would be overly sampled. Compared to the AA models, the UA -models have higher computational efficiency with satisfactory -accuracy, and thus are preferable in interfacial thermal transport -modelings. +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. -Vlugt {\it et al.} has investigated the surface thiol structures for -nanocrystal gold and pointed out that they differs from those of the -Au(111) surface\cite{vlugt:cpc2007154}. This difference might lead to -change of interfacial thermal transport behavior as well. To -investigate this problem, an effective means to introduce thermal flux -and measure the corresponding thermal gradient is desirable for -simulating structures with spherical symmetry. +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. +\section{Supporting Information} +This information is available free of charge via the Internet at +http://pubs.acs.org. + +\newpage + \bibliography{interfacial} \end{doublespace}