ViewVC Help
View File | Revision Log | Show Annotations | View Changeset | Root Listing
root/group/trunk/NPthiols/NPthiols.tex
(Generate patch)

Comparing trunk/NPthiols/NPthiols.tex (file contents):
Revision 4131 by kstocke1, Wed May 21 19:45:22 2014 UTC vs.
Revision 4374 by skucera, Mon Oct 26 14:23:50 2015 UTC

# Line 1 | Line 1
1 < \documentclass[journal = jctcce, manuscript = article]{achemso}
2 < \setkeys{acs}{usetitle = true}
3 <
4 < \usepackage{caption}
5 < \usepackage{geometry}
6 < \usepackage{natbib}
7 < \usepackage{setspace}
8 < \usepackage{xkeyval}
9 < %%%%%%%%%%%%%%%%%%%%%%%
10 < \usepackage{amsmath}
11 < \usepackage{amssymb}
1 > %% ****** Start of file template.aps ****** %
2 > %%
3 > %%
4 > %%   This file is part of the APS files in the REVTeX 4 distribution.
5 > %%   Version 4.0 of REVTeX, August 2001
6 > %%
7 > %%
8 > %%   Copyright (c) 2001 The American Physical Society.
9 > %%
10 > %%   See the REVTeX 4 README file for restrictions and more information.
11 > %%
12 > %
13 > % This is a template for producing manuscripts for use with REVTEX 4.0
14 > % Copy this file to another name and then work on that file.
15 > % That way, you always have this original template file to use.
16 > %
17 > % Group addresses by affiliation; use superscriptaddress for long
18 > % author lists, or if there are many overlapping affiliations.
19 > % For Phys. Rev. appearance, change preprint to twocolumn.
20 > % Choose pra, prb, prc, prd, pre, prl, prstab, or rmp for journal
21 > %  Add 'draft' option to mark overfull boxes with black boxes
22 > %  Add 'showpacs' option to make PACS codes appear
23 > %\documentclass[aps,jcp,twocolumn,showpacs,superscriptaddress,groupedaddress]{revtex4}  % for review and submission
24 > \documentclass[aps,jcp,preprint,showpacs,superscriptaddress,groupedaddress]{revtex4}  % for double-spaced preprint
25 > \usepackage{graphicx}  % needed for figures
26 > \usepackage{dcolumn}   % needed for some tables
27 > \usepackage{bm}        % for math
28 > \usepackage{amssymb}   % for math
29 > %\usepackage{booktabs}
30 > \usepackage{multirow}
31 > \usepackage{tablefootnote}
32   \usepackage{times}
33 < \usepackage{mathptm}
34 < \usepackage{caption}
15 < \usepackage{tabularx}
16 < \usepackage{longtable}
17 < \usepackage{graphicx}
18 < \usepackage{achemso}
19 < \usepackage{wrapfig}
20 < \usepackage[version=3]{mhchem}  % this is a great package for formatting chemical reactions
21 < \usepackage{url}
33 > \usepackage[version=3]{mhchem}
34 > \usepackage{lineno}
35  
36 < \title{Simulations of Interfacial Thermal Conductance of Alkanethiolate Ligand-Protected Gold Nanoparticles}
36 > \begin{document}
37  
38 + \title{Interfacial Thermal Conductance of Thiolate-Protected
39 +  Gold Nanospheres}
40   \author{Kelsey M. Stocker}
41 + \author{Suzanne M. Neidhart}
42   \author{J. Daniel Gezelter}
43   \email{gezelter@nd.edu}
44 < \affiliation[University of Notre Dame]{251 Nieuwland Science Hall\\ Department of Chemistry and Biochemistry\\ University of Notre Dame\\ Notre Dame, Indiana 46556}
44 > \affiliation{Department of Chemistry and Biochemistry, University of
45 >  Notre Dame, Notre Dame, IN 46556}
46  
47 < \begin{document}
47 > \begin{abstract}
48 >  Molecular dynamics simulations of thiolate-protected and solvated
49 >  gold nanoparticles were carried out in the presence of a
50 >  non-equilibrium heat flux between the solvent and the core of the
51 >  particle.  The interfacial thermal conductance ($G$) was computed
52 >  for these interfaces, and the behavior of the thermal conductance
53 >  was studied as a function of particle size, ligand flexibility, and
54 >  ligand chain length. In all cases, thermal conductance of the
55 >  ligand-protected particles was higher than the bare metal--solvent
56 >  interface.  A number of mechanisms for the enhanced conductance were
57 >  investigated, including thiolate-driven corrugation of the metal
58 >  surface, solvent ordering at the interface, solvent-ligand
59 >  interpenetration, and ligand ordering relative to the particle
60 >  surface.  MORE HERE.
61 > \end{abstract}
62  
63 < \begin{tocentry}
64 < % \includegraphics[width=9cm]{figures/TOC}
65 < \end{tocentry}
63 > \pacs{}
64 > \keywords{}
65 > \maketitle
66  
67 < \newcolumntype{A}{p{1.5in}}
37 < \newcolumntype{B}{p{0.75in}}
67 > \section{Introduction}
68  
69 < % \author{Kelsey M. Stocker and J. Daniel
70 < %   Gezelter\footnote{Corresponding author. \ Electronic mail:
71 < %     gezelter@nd.edu} \\
72 < %   251 Nieuwland Science Hall, \\
73 < %       Department of Chemistry and Biochemistry,\\
74 < %       University of Notre Dame\\
75 < %       Notre Dame, Indiana 46556}
69 > Heat transport across various nanostructured interfaces has been the
70 > subject of intense experimental
71 > interest,\cite{Wilson:2002uq,Ge:2004yg,Shenogina:2009ix,Wang10082007,Schmidt:2008ad,Juve:2009pt,Alper:2010pd}
72 > and the interfacial thermal conductance, $G$, is the principal
73 > quantity of interest for understanding interfacial heat
74 > transport.\cite{Cahill:2003fk} Because nanoparticles have a
75 > significant fraction of their atoms at the particle / solvent
76 > interface, the chemical details of these interfaces govern the thermal
77 > transport properties.
78  
79 < %\date{\today}
79 > Previously, reverse nonequilibrium molecular dynamics (RNEMD) methods
80 > have been applied to calculate the interfacial thermal conductance at
81 > flat (111) metal / organic solvent interfaces that had been chemically
82 > protected by varying coverages of alkanethiolate groups.\cite{Kuang:2011ef}
83 > These simulations suggested an explanation for the increased thermal
84 > conductivity at alkanethiol-capped metal surfaces compared with bare
85 > metal interfaces.  Specifically, the chemical bond between the metal
86 > and the ligand introduces a vibrational overlap that is not present
87 > without the protecting group, and the overlap between the vibrational
88 > spectra (metal to ligand, ligand to solvent) provides a mechanism for
89 > rapid thermal transport across the interface. The simulations also
90 > suggested that this phenomenon is a non-monotonic function of the
91 > fractional coverage of the surface, as moderate coverages allow
92 > diffusive heat transport of solvent molecules that come into close
93 > contact with the ligands.
94  
95 < %\maketitle
95 > Simulations of {\it mixed-chain} alkylthiolate surfaces showed that
96 > solvent trapped close to the interface can be efficient at moving
97 > thermal energy away from the surface.\cite{Stocker:2013cl} Trapped
98 > solvent molecules that were aligned with nearby
99 > ligands (but which were less able to diffuse into the bulk) were able
100 > to increase the thermal conductance of the interface.  This indicates
101 > that the ligand-to-solvent vibrational energy transfer is a key
102 > feature for increasing particle-to-solvent thermal conductance.
103  
104 < %\begin{doublespace}
104 > Recently, we extended RNEMD methods for use in non-periodic geometries
105 > by creating scaling/shearing moves between concentric regions of a
106 > simulation.\cite{Stocker:2014qq} In this work, we apply this
107 > non-periodic variant of RNEMD to investigate the role that {\it
108 >  curved} nanoparticle surfaces play in heat and mass transport.  On
109 > planar surfaces, we discovered that orientational ordering of surface
110 > protecting ligands had a large effect on the heat conduction from the
111 > metal to the solvent.  Smaller nanoparticles have high surface
112 > curvature that creates gaps in well-ordered self-assembled monolayers,
113 > and the effect of those gaps on the thermal conductance is unknown.
114  
53 \begin{abstract}
54        
55 \end{abstract}
56
57 \newpage
58
115   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
60 %               INTRODUCTION
61 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
62 \section{Introduction}
63
64 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
116   %               INTERFACIAL THERMAL CONDUCTANCE OF METALLIC NANOPARTICLES
117   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
118 < \section{Interfacial Thermal Conductance of Metallic Nanoparticles}
118 > %\section{Interfacial Thermal Conductance of Metallic Nanoparticles}
119  
120 < For a solvated nanoparticle, we can define a critical interfacial thermal conductance value,
120 > For a solvated nanoparticle, it is possible to define a critical value
121 > for the interfacial thermal conductance,
122   \begin{equation}
123 < G_c = \frac{3 C_f \Lambda_f}{r C_p}
123 > G_c = \frac{3 C_s \Lambda_s}{R C_p}
124   \end{equation}
125 + which depends on the solvent heat capacity, $C_s$, solvent thermal
126 + conductivity, $\Lambda_s$, particle radius, $R$, and nanoparticle heat
127 + capacity, $C_p$.\cite{Wilson:2002uq} In the limit of infinite
128 + interfacial thermal conductance, $G \gg G_c$, cooling of the
129 + nanoparticle is limited by the solvent properties, $C_s$ and
130 + $\Lambda_s$.  In the opposite limit, $G \ll G_c$, the heat dissipation
131 + is controlled by the thermal conductance of the particle / fluid
132 + interface. It is this regime with which we are concerned, where
133 + properties of ligands and the particle surface may be tuned to
134 + manipulate the rate of cooling for solvated nanoparticles.  Based on
135 + estimates of $G$ from previous simulations as well as experimental
136 + results for solvated nanostructures, gold nanoparticles solvated in
137 + hexane are in the $G \ll G_c$ regime for radii smaller than 40 nm. The
138 + particles included in this study are more than an order of magnitude
139 + smaller than this critical radius, so the heat dissipation should be
140 + controlled entirely by the surface features of the particle / ligand /
141 + solvent interface.
142  
74 dependent upon the fluid heat capacity, $C_f$, fluid thermal conductivity, $\Lambda_f$, particle radius, $r$, and nanoparticle heat capacity, $C_p$.\cite{Wilson:2002uq} In the infinite interfacial thermal conductance limit $G >> G_c$, the particle cooling rate is limited by the fluid properties, $C_f$ and $\Lambda_f$. In the opposite limit ($G << G_c$), the heat dissipation is controlled by the thermal conductance of the particle / fluid interface. It is this regime with which we are concerned, where properties of the interface may be tuned to manipulate the rate of cooling for a solvated nanoparticle. Based on $G$ values from previous simulations of gold nanoparticles solvated in hexane and experimental results for solvated nanostructures, it appears that we are in the $G << G_c$ regime for gold nanoparticles of radius $<$ 400 \AA\ solvated in hexane. The particles included in this study are more than an order of magnitude smaller than this critical radius. The heat dissipation should thus be controlled entirely by the surface features of the particle / ligand / solvent interface.
75
76 % Understanding how the structural details of the interfaces affect the energy flow between the particle and its surroundings is essential in designing and functionalizing metallic nanoparticles for use in plasmonic photothermal therapies,\cite{Jain:2007ux,Petrova:2007ad,Gnyawali:2008lp,Mazzaglia:2008to,Huff:2007ye,Larson:2007hw} which rely on the ability of metallic nanoparticles to absorb light in the near-IR, a portion of the spectrum in which living tissue is very nearly transparent. The relevant physical property controlling the transfer of this energy as heat into the surrounding tissue is the interfacial thermal conductance, $G$, which can be somewhat difficult to determine experimentally.\cite{Wilson:2002uq,Plech:2005kx}
77 %
78 % Metallic particles have also been proposed for use in efficient thermal-transfer fluids, although careful experiments by Eapen \textit{et al.} have shown that metal-particle-based nanofluids have thermal conductivities that match Maxwell predictions.\cite{Eapen:2007th} The likely cause of previously reported non-Maxwell behavior\cite{Eastman:2001wb,Keblinski:2002bx,Lee:1999ct,Xue:2003ya,Xue:2004oa} is percolation networks of nanoparticles exchanging energy via the solvent,\cite{Eapen:2007mw} so it is important to get a detailed molecular picture of particle-ligand and ligand-solvent interactions in order to understand the thermal behavior of complex fluids. To date, there have been some reported values from experiment\cite{Wilson:2002uq,doi:10.1021jp8051888,doi:10.1021jp048375k,Ge2005,Park2012}) of $G$ for ligand-protected nanoparticles embedded in liquids, but there is still a significant gap in knowledge about how chemically distinct ligands or protecting groups will affect heat transport from the particles. In particular, the dearth of atomistic, dynamic information available from molecular dynamics simulations means that the heat transfer mechanisms at these nanoparticle surfaces remain largely unclear.
79
143   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
144   %               STRUCTURE OF SELF-ASSEMBLED MONOLAYERS ON NANOPARTICLES
145   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
146 < \section{Structure of Self-Assembled Monolayers on Nanoparticles}
146 > \subsection{Structures of Self-Assembled Monolayers on Nanoparticles}
147  
148 < Though the ligand packing on planar surfaces is characterized for many different ligands and surface facets, it is not obvious \emph{a priori} how the same ligands will behave on the highly curved surfaces of nanoparticles. Thus, as more applications of ligand-stabilized nanostructures have become apparent, the structure and dynamics of ligands on metallic nanoparticles have been studied extensively.\cite{Badia1996:2,Badia1996,Henz2007,Badia1997:2,Badia1997,Badia2000} Badia, \textit{et al.} used transmission electron microscopy to determine that alkanethiol ligands on gold nanoparticles pack approximately 30\% more densely than on planar Au(111) surfaces.\cite{Badia1996:2} Subsequent experiments demonstrated that even at full coverages, surface curvature creates voids between linear ligand chains that can be filled via interdigitation of ligands on neighboring particles.\cite{Badia1996} The molecular dynamics simulations of Henz, \textit{et al.} indicate that at low coverages, the thiolate alkane chains will lie flat on the nanoparticle surface\cite{Henz2007} Above 90\% coverage, the ligands stand upright and recover the rigidity and tilt angle displayed on planar facets. Their simulations also indicate a high degree of mixing between the thiolate sulfur atoms and surface gold atoms at high coverages.
148 > Though the ligand packing on planar surfaces has been characterized
149 > for many different ligands and surface facets, it is not obvious
150 > \emph{a priori} how the same ligands will behave on the highly curved
151 > surfaces of spherical nanoparticles. Thus, as new applications of
152 > ligand-stabilized nanostructures have been proposed, the structure and
153 > dynamics of ligands on metallic nanoparticles have been studied using
154 > molecular simulation,\cite{Henz2007,Henz:2008qf} NMR, XPS, FTIR,
155 > calorimetry, and surface
156 > microscopies.\cite{Badia1996:2,Badia1996,Badia1997:2,Badia1997,Badia2000}
157 > Badia, \textit{et al.} used transmission electron microscopy to
158 > determine that alkanethiol ligands on gold nanoparticles pack
159 > approximately 30\% more densely than on planar Au(111)
160 > surfaces.\cite{Badia1996:2} Subsequent experiments demonstrated that
161 > even at full coverages, surface curvature creates voids between linear
162 > ligand chains that can be filled via interdigitation of ligands on
163 > neighboring particles.\cite{Badia1996} The molecular dynamics
164 > simulations of Henz, \textit{et al.} indicate that at low coverages,
165 > the thiolate alkane chains will lie flat on the nanoparticle
166 > surface\cite{Henz2007,Henz:2008qf} Above 90\% coverage, the ligands
167 > stand upright and recover the rigidity and tilt angle displayed on
168 > planar facets. Their simulations also indicate a high degree of mixing
169 > between the thiolate sulfur atoms and surface gold atoms at high
170 > coverages.
171  
172 + In this work, thiolated gold nanospheres were modeled using a united
173 + atom force field and non-equilibrium molecular dynamics. Gold
174 + nanoparticles with radii ranging from 10 - 25 \AA\ were created from a
175 + bulk fcc lattice.  These particles were passivated with a 50\%
176 + coverage -- based on coverage densities reported by Badia \textit{et
177 +  al.} -- of a selection of thiolates of varying chain lengths and
178 + flexibilities. The passivated particles were then solvated in hexane.
179 + Details of the models and simulation protocol follow in the next
180 + section.
181 +
182   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
183 + %               COMPUTATIONAL DETAILS
184 + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
185 + \section{Computational Details}
186 +
187 + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
188   %               NON-PERIODIC VSS-RNEMD METHODOLOGY
189   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
190 < \section{Non-Periodic Velocity Shearing and Scaling RNEMD Methodology}
190 > \subsection{Creating a thermal flux between particles and solvent}
191  
192 < Non-periodic VSS-RNEMD, explained in detail in Chapter 4, periodically applies a series of velocity scaling and shearing moves at regular intervals to impose a flux between two concentric spherical regions.
193 <
194 < To simultaneously impose a thermal flux ($J_r$) between the shells we
195 < use energy conservation constraints,
192 > The non-periodic variant of VSS-RNEMD\cite{Stocker:2014qq} applies a
193 > series of velocity scaling and shearing moves at regular intervals to
194 > impose a flux between two concentric spherical regions. To impose a
195 > thermal flux between the shells (without an accompanying angular
196 > shear), we solve for scaling coefficients $a$ and $b$,
197   \begin{eqnarray}
198 < K_a - J_r \Delta t & = & a^2 \left(K_a - \frac{1}{2}\langle
199 < \omega_a \rangle \cdot \overleftrightarrow{I_a} \cdot \langle \omega_a
99 < \rangle \right) + \frac{1}{2} \mathbf{c}_a \cdot \overleftrightarrow{I_a}
100 < \cdot \mathbf{c}_a \label{eq:Kc}\\
101 < K_b + J_r \Delta t & = & b^2 \left(K_b - \frac{1}{2}\langle
102 < \omega_b \rangle \cdot \overleftrightarrow{I_b} \cdot \langle \omega_b
103 < \rangle \right) + \frac{1}{2} \mathbf{c}_b \cdot \overleftrightarrow{I_b} \cdot \mathbf{c}_b \label{eq:Kh}
198 >        a = \sqrt{1 - \frac{q_r \Delta t}{K_a - K_a^\mathrm{rot}}}\\ \nonumber\\
199 >        b = \sqrt{1 + \frac{q_r \Delta t}{K_b - K_b^\mathrm{rot}}}
200   \end{eqnarray}
201 < Simultaneous solution of these quadratic formulae for the scaling coefficients, $a$ and $b$, will ensure that
202 < the simulation samples from the original microcanonical (NVE) ensemble. Here $K_{\{a,b\}}$ is the instantaneous
203 < translational kinetic energy of each shell. At each time interval, we solve for $a$, $b$, $\mathbf{c}_a$, and
204 < $\mathbf{c}_b$, subject to the imposed angular momentum flux, $j_r(\mathbf{L})$, and thermal flux, $J_r$,
205 < values.
201 > at each time interval.  These scaling coefficients conserve total
202 > kinetic energy and angular momentum subject to an imposed heat rate,
203 > $q_r$.  The coefficients also depend on the instantaneous kinetic
204 > energy, $K_{\{a,b\}}$, and the total rotational kinetic energy of each
205 > shell, $K_{\{a,b\}}^\mathrm{rot} = \sum_i m_i \left( \mathbf{v}_i
206 >  \times \mathbf{r}_i \right)^2 / 2$.
207  
208 + The scaling coefficients are determined and the velocity changes are
209 + applied at regular intervals,
210 + \begin{eqnarray}
211 +        \mathbf{v}_i \leftarrow a \left ( \mathbf{v}_i - \left < \omega_a \right > \times \mathbf{r}_i \right ) + \left < \omega_a \right > \times \mathbf{r}_i~~\:\\
212 +        \mathbf{v}_j \leftarrow b \left ( \mathbf{v}_j - \left < \omega_b \right > \times \mathbf{r}_j \right ) + \left < \omega_b \right > \times \mathbf{r}_j.
213 + \end{eqnarray}
214 + Here $\left < \omega_a \right > \times \mathbf{r}_i$ is the
215 + contribution to the velocity of particle $i$ due to the overall
216 + angular velocity of the $a$ shell. In the absence of an angular
217 + momentum flux, the angular velocity $\left < \omega_a \right >$ of the
218 + shell is nearly 0 and the resultant particle velocity is a nearly
219 + linear scaling of the initial velocity by the coefficient $a$ or $b$.
220 +
221 + Repeated application of this thermal energy exchange yields a radial
222 + temperature profile for the solvated nanoparticles that depends
223 + linearly on the applied heat rate, $q_r$. Similar to the behavior in
224 + the slab geometries, the temperature profiles have discontinuities at
225 + the interfaces between dissimilar materials.  The size of the
226 + discontinuity depends on the interfacial thermal conductance, which is
227 + the primary quantity of interest.
228 +
229   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
230   %               CALCULATING TRANSPORT PROPERTIES
231   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
114 \section{Calculating Transport Properties from Non-Periodic VSS-RNEMD}
115
232   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
233   %               INTERFACIAL THERMAL CONDUCTANCE
234   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
235   \subsection{Interfacial Thermal Conductance}
236  
237 < As described in Chapter 4, we can describe the thermal conductance of each spherical shell as the inverse Kapitza resistance. To describe the thermal conductance for an interface of considerable thickness, such as the ligand layers shown here, we can sum the individual thermal resistances of each concentric spherical shell to arrive at the total thermal resistance, or the inverse of the total interfacial thermal conductance:
237 > As described in earlier work,\cite{Stocker:2014qq} the thermal
238 > conductance of each spherical shell may be defined as the inverse
239 > Kapitza resistance of the shell. To describe the thermal conductance
240 > of an interface of considerable thickness -- such as the ligand layers
241 > shown here -- we can sum the individual thermal resistances of each
242 > concentric spherical shell to arrive at the inverse of the total
243 > interfacial thermal conductance. In slab geometries, the intermediate
244 > temperatures cancel, but for concentric spherical shells, the
245 > intermediate temperatures and surface areas remain in the final sum,
246 > requiring the use of a series of individual resistance terms:
247  
248   \begin{equation}
249    \frac{1}{G} = R_\mathrm{total} = \frac{1}{q_r} \sum_i \left(T_{i+i} -
250      T_i\right) 4 \pi r_i^2.
251   \end{equation}
252  
253 < The longest ligand considered here is in excess of 15 \AA\ in length, requiring the use of at least 10 spherical shells to describe the total interfacial thermal conductance.
253 > The longest ligand considered here is in excess of 15 \AA\ in length,
254 > and we use 10 concentric spherical shells to describe the total
255 > interfacial thermal conductance of the ligand layer.
256  
257   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
131 %               COMPUTATIONAL DETAILS
132 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
133 \section{Computational Details}
134
135 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
258   %               FORCE FIELDS
259   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
260   \subsection{Force Fields}
261  
262 < Gold -- gold interactions are described by the quantum Sutton-Chen (QSC) model,\cite{PhysRevB.59.3527} described in detail in Chapter 1.
262 > Throughout this work, gold -- gold interactions are described by the
263 > quantum Sutton-Chen (QSC) model.\cite{Qi:1999ph} Previous
264 > work\cite{Kuang:2011ef} has demonstrated that the electronic
265 > contributions to heat conduction (which are missing from the QSC
266 > model) across heterogeneous metal / non-metal interfaces are
267 > negligible compared to phonon excitation, which is captured by the
268 > classical model. The hexane solvent is described by the TraPPE united
269 > atom model,\cite{TraPPE-UA.alkanes} where sites are located at the
270 > carbon centers for alkyl groups. The TraPPE-UA model for hexane
271 > provides both computational efficiency and reasonable accuracy for
272 > bulk thermal conductivity values. Bonding interactions were used for
273 > intra-molecular sites closer than 3 bonds. Effective Lennard-Jones
274 > potentials were used for non-bonded interactions.
275  
276 < Hexane molecules are described by the TraPPE united atom model,\cite{TraPPE-UA.alkanes} detailed in Chapter 3, which provides good computational efficiency and reasonable accuracy for bulk thermal conductivity values. In this model, sites are located at the carbon centers for alkyl groups. Bonding interactions, including bond stretches, bends and torsions, were used for intra-molecular sites closer than 3 bonds. For non-bonded interactions, Lennard-Jones potentials were used.
276 > To describe the interactions between metal (Au) and non-metal atoms,
277 > potential energy terms were adapted from an adsorption study of alkyl
278 > thiols on gold surfaces by Vlugt, \textit{et
279 >  al.}\cite{vlugt:cpc2007154} They fit an effective pair-wise
280 > Lennard-Jones form of potential parameters for the interaction between
281 > Au and pseudo-atoms CH$_x$ and S based on a well-established and
282 > widely-used effective potential of Hautman and Klein for the Au(111)
283 > surface.\cite{hautman:4994}
284  
285 < To describe the interactions between metal (Au) and non-metal atoms, potential energy terms were adapted from an adsorption study of alkyl thiols on gold surfaces by Vlugt, \textit{et al.}\cite{vlugt:cpc2007154} They fit an effective pair-wise 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}
285 > Additional terms to represent thiolated alkenes and conjugated ligand
286 > moieties were parameterized as part of this work and are available in
287 > the supporting information.
288  
289   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
290   %               SIMULATION PROTOCOL
291   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
292   \subsection{Simulation Protocol}
293  
294 < The various sized gold nanoparticles were created from a bulk fcc lattice and were thermally equilibrated prior to the addition of ligands. A 50\% coverage of ligands (based on coverages reported by Badia, \textit{et al.}\cite{Badia1996:2}) were placed on the surface of the equilibrated nanoparticles using Packmol\cite{packmol}. The nanoparticle / ligand complexes were briefly thermally equilibrated before Packmol was used to solvate the structures within a spherical droplet of hexane. The thickness of the solvent layer was chosen to be at least 1.5$\times$ the radius of the nanoparticle / ligand structure. The fully solvated system was equilibrated in the Langevin Hull under 50 atm of pressure with a target temperature of 250 K for at least 1 nanosecond.
294 > Gold nanospheres with radii ranging from 10 - 25 \AA\ were created
295 > from a bulk fcc lattice and were thermally equilibrated prior to the
296 > addition of ligands. A 50\% coverage of ligands (based on coverages
297 > reported by Badia, \textit{et al.}\cite{Badia1996:2}) were placed on
298 > the surface of the equilibrated nanoparticles using
299 > Packmol\cite{packmol}. We have chosen three lengths for the
300 > straight-chain ligands, $C_4$, $C_8$, and $C_{12}$, differentiated by
301 > the number of carbons in the chains.  Additionally, to explore the
302 > effects of ligand flexibility, we have used three levels of ligand
303 > ``stiffness''.  The most flexible chain is a fully saturated
304 > alkanethiolate, while moderate rigidity is introduced using an alkene
305 > thiolate with one double bond in the penultimate (solvent-facing)
306 > carbon-carbon location.  The most rigid ligands are fully-conjugated
307 > chains where all of the carbons are represented with conjugated (aryl)
308 > united-atom carbon atoms (CHar or terminal CH2ar).
309  
310 < Once equilibrated, thermal fluxes were applied for
311 < 1 nanosecond, until stable temperature gradients had
312 < developed. Systems were run under moderate pressure
313 < (50 atm) and average temperature (250K) to maintain a compact solvent cluster and avoid formation of a vapor phase near the heated metal surface.  Pressure was applied to the
314 < system via the non-periodic Langevin Hull.\cite{Vardeman2011} However,
315 < thermal coupling to the external temperature and pressure bath was
316 < removed to avoid interference with the imposed RNEMD flux.
310 > The nanoparticle / ligand complexes were thermally equilibrated to
311 > allow for ligand conformational flexibility. Packmol was then used to
312 > solvate the structures inside a spherical droplet of hexane. The
313 > thickness of the solvent layer was chosen to be at least 1.5$\times$
314 > the combined radius of the nanoparticle / ligand structure. The fully
315 > solvated system was equilibrated for at least 1 ns using the Langevin
316 > Hull to apply 50 atm of pressure and a target temperature of 250
317 > K.\cite{Vardeman2011} Typical system sizes ranged from 18,310 united
318 > atom sites for the 10 \AA\ particles with $C_4$ ligands to 89,490
319 > sites for the 25 \AA\ particles with $C_{12}$ ligands.  Figure
320 > \ref{fig:NP25_C12h1} shows one of the solvated 25 \AA\ nanoparticles
321 > passivated with the $C_{12}$ alkane thiolate ligands.
322  
323 < Because the method conserves \emph{total} angular momentum and energy, systems
324 < which contain a metal nanoparticle embedded in a significant volume of
325 < solvent will still experience nanoparticle diffusion inside the
326 < solvent droplet.  To aid in measuring an accurate temperature profile for these
327 < systems, a single gold atom at the origin of the coordinate system was
328 < assigned a mass $10,000 \times$ its original mass. The bonded and
329 < nonbonded interactions for this atom remain unchanged and the heavy
330 < atom is excluded from the RNEMD velocity scaling.  The only effect of this
331 < gold atom is to effectively pin the nanoparticle at the origin of the
170 < coordinate system, thereby preventing translational diffusion of the nanoparticle due to Brownian motion.
323 > \begin{figure}
324 >  \includegraphics[width=\linewidth]{figures/NP25_C12h1}
325 >  \caption{A 25 \AA\ radius gold nanoparticle protected with a
326 >    half-monolayer of TraPPE-UA dodecanethiolate (C$_{12}$) ligands
327 >    and solvated in TraPPE-UA hexane. The interfacial thermal
328 >    conductance is computed by applying a kinetic energy flux between
329 >    the nanoparticle and an outer shell of solvent.}
330 >  \label{fig:NP25_C12h1}
331 > \end{figure}
332  
333 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
334 < %               INTERFACIAL THERMAL CONDUCTANCE
335 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
336 < \section{Interfacial Thermal Conductance}
333 > Once equilibrated, thermal fluxes were applied for 1 ns, until stable
334 > temperature gradients had developed. Systems were run under moderate
335 > pressure (50 atm) with an average temperature (250K) that maintained a
336 > compact solvent cluster and avoided formation of a vapor layer near
337 > the heated metal surface.  Pressure was applied to the system via the
338 > non-periodic Langevin Hull.\cite{Vardeman2011} However, thermal
339 > coupling to the external temperature bath was removed to avoid
340 > interference with the imposed RNEMD flux.
341  
342 + \begin{figure}
343 +        \includegraphics[width=\linewidth]{figures/temp_profile}
344 +        \caption{Radial temperature profile for a 25 \AA\ radius
345 +          particle protected with a 50\% coverage of TraPPE-UA
346 +          butanethiolate (C$_4$) ligands and solvated in TraPPE-UA
347 +          hexane. A kinetic energy flux is applied between RNEMD
348 +          region A and RNEMD region B. The size of the temperature
349 +          discontinuity at the interface is governed by the
350 +          interfacial thermal conductance.}
351 +        \label{fig:temp_profile}
352 + \end{figure}
353 +
354 + Because the method conserves \emph{total} angular momentum and energy,
355 + systems which contain a metal nanoparticle embedded in a significant
356 + volume of solvent will still experience nanoparticle diffusion inside
357 + the solvent droplet.  To aid in measuring an accurate temperature
358 + profile for these systems, a single gold atom at the origin of the
359 + coordinate system was assigned a mass $10,000 \times$ its original
360 + mass. The bonded and nonbonded interactions for this atom remain
361 + unchanged and the heavy atom is excluded from the RNEMD velocity
362 + scaling.  The only effect of this gold atom is to effectively pin the
363 + nanoparticle at the origin of the coordinate system, thereby
364 + preventing translational diffusion of the nanoparticle due to Brownian
365 + motion.
366 +
367 + To provide statistical independence, five separate configurations were
368 + simulated for each particle radius and ligand. The structures were
369 + unique, starting at the point of ligand placement, in order to sample
370 + multiple surface-ligand configurations.
371 +
372 +
373   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
374   %               EFFECT OF PARTICLE SIZE
375   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
376 < \subsection{Effect of Particle Size}
376 > \section{Results}
377  
378 < I have modeled four sizes of nanoparticles ($r =$ 10, 15, 20, and 25 \AA). The smallest particle size produces the lowest interfacial thermal conductance value regardless of protecting group. Between the other three sizes of nanoparticles, there is no discernible dependence of the interfacial thermal conductance on the nanoparticle size. It is likely that the differences in local curvature of the nanoparticle sizes studied here do not disrupt the ligand packing and behavior in drastically different ways.
378 > We modeled four sizes of nanoparticles ($R =$ 10, 15, 20, and 25
379 > \AA). The smallest particle size produces the lowest interfacial
380 > thermal conductance values for most of the of protecting groups
381 > (Fig. \ref{fig:NPthiols_G}).  Between the other three sizes of
382 > nanoparticles, there is no systematic dependence of the interfacial
383 > thermal conductance on the nanoparticle size. It is likely that the
384 > differences in local curvature of the nanoparticle sizes studied here
385 > do not disrupt the ligand packing and behavior in drastically
386 > different ways.
387  
388   \begin{figure}
389 <        \includegraphics[width=\linewidth]{figures/NPthiols_Gcombo}
390 <        \caption{Interfacial thermal conductance ($G$) and corrugation values for 4 sizes of solvated nanoparticles that are bare or protected with a 50\% coverage of C$_{4}$, C$_{8}$, or C$_{12}$ alkanethiolate ligands.}
391 <        \label{fig:NPthiols_Gcombo}
389 >  \includegraphics[width=\linewidth]{figures/G3}
390 >  \caption{Interfacial thermal conductance ($G$) values for 4
391 >      sizes of solvated nanoparticles that are bare or protected with
392 >      a 50\% coverage of C$_{4}$, C$_{8}$, or C$_{12}$ thiolate
393 >      ligands. Ligands of different flexibility are shown in separate
394 >      panels.  The middle panel indicates ligands which have a single
395 >      carbon-carbon double bond in the penultimate position.}
396 >  \label{fig:NPthiols_G}
397   \end{figure}
398  
399   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
400   %               EFFECT OF LIGAND CHAIN LENGTH
401   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
193 \subsection{Effect of Ligand Chain Length}
402  
403 < I have studied three lengths of alkanethiolate ligands -- S(CH$_2$)$_3$CH$_3$, S(CH$_2$)$_7$CH$_3$, and S(CH$_2$)$_{11}$CH$_3$ -- referred to as C$_4$, C$_8$, and C$_{12}$ respectively, on each of the four nanoparticle sizes.
403 > Unlike our previous study of varying thiolate ligand chain lengths on
404 > planar Au(111) surfaces, the interfacial thermal conductance of
405 > ligand-protected nanospheres exhibits a distinct dependence on the
406 > ligand identity. A half-monolayer coverage of ligands yields
407 > interfacial conductance that is strongly dependent on both ligand
408 > length and flexibility.
409  
410 < Unlike my previous study of varying thiolate ligand chain lengths on Au(111) surfaces, the interfacial thermal conductance of ligand-protected nanoparticles exhibits a distinct non-monotonic dependence on the ligand length. For the three largest particle sizes, a half-monolayer coverage of $C_4$ yields the highest interfacial thermal conductance and the next-longest ligand $C_8$ provides a nearly equivalent boost. The longest ligand $C_{12}$ offers only a marginal ($\sim$ 10 \%) increase in the interfacial thermal conductance over a bare nanoparticle.
410 > There are many factors that could be playing a role in the
411 > ligand-dependent conductuance.  The sulfur-gold interaction is
412 > particularly strong, and the presence of the ligands can easily
413 > disrupt the crystalline structure of the gold at the surface of the
414 > particles, providing more efficient scattering of phonons into the
415 > ligand / solvent layer. This effect would be particularly important at
416 > small particle sizes.
417  
418 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
419 < %               HEAT TRANSFER MECHANISMS
420 < %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
421 < \section{Mechanisms for Heat Transfer}
418 > In previous studies of mixed-length ligand layers with full coverage,
419 > we observed that ligand-solvent alignment was an important factor for
420 > heat transfer into the solvent.  With high surface curvature and lower
421 > effective coverages, ligand behavior also becomes more complex. Some
422 > chains may be lying down on the surface, and solvent may not be
423 > penetrating the ligand layer to the same degree as in the planar
424 > surfaces.  
425 >
426 > Additionally, the ligand flexibility directly alters the vibrational
427 > density of states for the layer that mediates the transfer of phonons
428 > between the metal and the solvent. This could be a partial explanation
429 > for the observed differences between the fully conjugated and more
430 > flexible ligands.
431  
432 < \begin{figure}
433 <        \includegraphics[width=\linewidth]{figures/NPthiols_combo}
434 <        \caption{Computed solvent escape rates, ligand orientational P$_2$ values, and interfacial solvent orientational $P_2$ values for 4 sizes of solvated nanoparticles that are bare or protected with a 50\% coverage of C$_{4}$, C$_{8}$, or C$_{12}$ alkanethiolate ligands.}
435 <        \label{fig:NPthiols_combo}
436 < \end{figure}
432 > In the following sections we provide details on how we
433 > measure surface corrugation, solvent-ligand interpenetration, and
434 > ordering of the solvent and ligand at the surfaces of the
435 > nanospheres.  We also investigate the overlap between vibrational
436 > densities of states for the various ligands.
437  
438   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
439   %               CORRUGATION OF PARTICLE SURFACE
440   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
441 < \subsection{Corrugation of Particle Surface}
441 > \subsection{Corrugation of the Particle Surface}
442  
443 < The bonding sites for thiols on gold surfaces have been studied extensively and include configurations beyond the traditional atop, bridge, and hollow sites found on planar surfaces. In particular, the deep potential well between the gold atoms and the thiolate sulfurs leads to insertion of the sulfur into the gold lattice and displacement of interfacial gold atoms. The degree of ligand-induced surface restructuring may have an impact on the interfacial thermal conductance and is an important phenomenon to quantify.
443 > The bonding sites for thiols on gold surfaces have been studied
444 > extensively and include configurations beyond the traditional atop,
445 > bridge, and hollow sites found on planar surfaces. In particular, the
446 > deep potential well between the gold atoms and the thiolate sulfur
447 > atoms leads to insertion of the sulfur into the gold lattice and
448 > displacement of interfacial gold atoms. The degree of ligand-induced
449 > surface restructuring may have an impact on the interfacial thermal
450 > conductance and is an important phenomenon to quantify.
451  
452 < Henz, \textit{et al.}\cite{Henz2007} used the metal density as a function of radius to measure the degree of mixing between the thiol sulfurs and surface gold atoms at the edge of a nanoparticle. Although metal density is important, disruption of the local crystalline ordering would have a large effect on the phonon spectrum in the particles. To measure this effect, I used the fraction of gold atoms exhibiting local fcc ordering as a function of radius to describe the ligand-induced disruption of the nanoparticle surface.
452 > Henz, \textit{et al.}\cite{Henz2007,Henz:2008qf} used the metal
453 > density as a function of radius to measure the degree of mixing
454 > between the thiol sulfurs and surface gold atoms at the edge of a
455 > nanoparticle. Although metal density is important, disruption of the
456 > local crystalline ordering would also have a large effect on the
457 > phonon spectrum in the particles. To measure this effect, we use the
458 > fraction of gold atoms exhibiting local fcc ordering as a function of
459 > radius to describe the ligand-induced disruption of the nanoparticle
460 > surface.
461  
462 < The local bond orientational order can be described using the model proposed by Steinhardt \textit{et al.},\cite{Steinhardt1983} where spherical harmonics are associated with a central atom and its nearest neighbors. The local bonding environment, $\bar{q}_{\ell m}$, for each atom in the system can be determined by averaging over the spherical harmonics between the central atom and each of its neighbors. A global average orientational bond order parameter, $\bar{Q}_{\ell m}$, is the average over each $\bar{q}_{\ell m}$ for all atoms in the system. The third-order rotationally invariant combination of $\bar{Q}_{\ell m}$, $\hat{W}_4$, is utilized here. Ideal face-centered cubic (fcc), body-centered cubic (bcc), hexagonally close-packed (hcp), and simple cubic (sc), have values in the $\ell$ = 4 $\hat{W}$ invariant of -0.159, 0.134, 0.159, and 0.159, respectively. $\hat{W}_4$ has an extreme value for fcc structures, making it ideal for measuring local fcc order. The distribution of $\hat{W}_4$ local bond orientational order parameters, $p(\hat{W}_4)$, can provide information about individual atoms that are central to local fcc ordering.
462 > The local bond orientational order can be described using the method
463 > of Steinhardt \textit{et al.}\cite{Steinhardt1983} The local bonding
464 > environment, $\bar{q}_{\ell m}$, for each atom in the system is
465 > determined by averaging over the spherical harmonics between that atom
466 > and each of its neighbors,
467 > \begin{equation}
468 > \bar{q}_{\ell m} = \sum_i Y_\ell^m(\theta_i, \phi_i)
469 > \end{equation}
470 > where $\theta_i$ and $\phi_i$ are the relative angular coordinates of
471 > neighbor $i$ in the laboratory frame.  A global average orientational
472 > bond order parameter, $\bar{Q}_{\ell m}$, is the average over each
473 > $\bar{q}_{\ell m}$ for all atoms in the system. To remove the
474 > dependence on the laboratory coordinate frame, the third order
475 > rotationally invariant combination of $\bar{Q}_{\ell m}$,
476 > $\hat{w}_\ell$, is utilized here.\cite{Steinhardt1983,Vardeman:2008fk}
477  
478 < The fraction of fcc ordered gold atoms at a given radius
478 > For $\ell=4$, the ideal face-centered cubic (fcc), body-centered cubic
479 > (bcc), hexagonally close-packed (hcp), and simple cubic (sc) local
480 > structures exhibit $\hat{w}_4$ values of -0.159, 0.134, 0.159, and
481 > 0.159, respectively. Because $\hat{w}_4$ exhibits an extreme value for
482 > fcc structures, it is ideal for measuring local fcc
483 > ordering. The spatial distribution of $\hat{w}_4$ local bond
484 > orientational order parameters, $p(\hat{w}_4 , r)$, can provide
485 > information about the location of individual atoms that are central to
486 > local fcc ordering.
487  
488 + The fraction of fcc-ordered gold atoms at a given radius in the
489 + nanoparticle,
490   \begin{equation}
491 <        f_{fcc} = \int_{-\infty}^{w_i} p(\hat{W}_4) d \hat{W}_4
491 >        f_\mathrm{fcc}(r) = \int_{-\infty}^{w_c} p(\hat{w}_4, r) d \hat{w}_4
492   \end{equation}
493 + is described by the distribution of the local bond orientational order
494 + parameters, $p(\hat{w}_4, r)$, and $w_c$, a cutoff for the peak
495 + $\hat{w}_4$ value displayed by fcc structures. A $w_c$ value of -0.12
496 + was chosen to isolate the fcc peak in $\hat{w}_4$.
497  
498 < is described by the distribution of the local bond orientational order parameter, $p(\hat{W}_4)$, and $w_i$, a cutoff for the peak $\hat{W}_4$ value displayed by fcc structures. A $w_i$ value of -0.12 was chosen to isolate the fcc peak in $\hat{W}_4$.
498 > As illustrated in Figure \ref{fig:Corrugation}, the presence of
499 > ligands decreases the fcc ordering of the gold atoms at the
500 > nanoparticle surface. For the smaller nanoparticles, this disruption
501 > extends into the core of the nanoparticle, indicating widespread
502 > disruption of the lattice.
503  
229 As illustrated in Figure \ref{fig:Corrugation}, the presence of ligands decreases the fcc ordering of the gold atoms at the nanoparticle surface. For the smaller nanoparticles, this disruption extends into the core of the nanoparticle, indicating widespread disruption of the lattice.
230
504   \begin{figure}
505 <        \includegraphics[width=\linewidth]{figures/NP10_fcc}
506 <        \caption{Fraction of gold atoms with fcc ordering as a function of radius for a 10 \AA\ radius nanoparticle. The decreased fraction of fcc ordered atoms in ligand-protected nanoparticles relative to bare particles indicates restructuring of the nanoparticle surface by the thiolate sulfur atoms.}
507 <        \label{fig:Corrugation}
505 >  \includegraphics[width=\linewidth]{figures/fcc}
506 >  \caption{Fraction of gold atoms with fcc ordering as a function of
507 >    radius for a 10 \AA\ radius nanoparticle. The decreased fraction
508 >    of fcc-ordered atoms in ligand-protected nanoparticles relative to
509 >    bare particles indicates restructuring of the nanoparticle surface
510 >    by the thiolate sulfur atoms.}
511 >  \label{fig:Corrugation}
512   \end{figure}
513  
514 < We may describe the thickness of the disrupted nanoparticle surface by defining a corrugation factor, $c$, as the ratio of the radius at which the fraction of gold atoms with fcc ordering is 0.9 and the radius at which the fraction is 0.5.
514 > We may describe the thickness of the disrupted nanoparticle surface by
515 > defining a corrugation factor, $c$, as the ratio of the radius at
516 > which the fraction of gold atoms with fcc ordering is 0.9 and the
517 > radius at which the fraction is 0.5.
518  
519   \begin{equation}
520 <        c = 1 - \frac{r(f_{fcc} = 0.9)}{r(f_{fcc} = 0.5)}
520 >        c = 1 - \frac{r(f_\mathrm{fcc} = 0.9)}{r(f_\mathrm{fcc} = 0.5)}
521   \end{equation}
522  
523 < A clean, unstructured interface will have a sharp drop in $f_{fcc}$ at the edge of the particle ($c \rightarrow$ 0). In the opposite limit where the entire nanoparticle surface is restructured, the radius at which there is a high probability of fcc ordering moves dramatically inward ($c \rightarrow$ 1).
523 > A sharp interface will have a steep drop in $f_\mathrm{fcc}$ at the
524 > edge of the particle ($c \rightarrow$ 0). In the opposite limit where
525 > the entire nanoparticle surface is restructured by ligands, the radius
526 > at which there is a high probability of fcc ordering moves
527 > dramatically inward ($c \rightarrow$ 1).
528  
529 < The computed corrugation factors are shown in Figure \ref{fig:NPthiols_Gcombo} for bare nanoparticles and for ligand-protected particles as a function of ligand chain length. The largest nanoparticles are only slightly restructured by the presence of ligands on the surface, while the smallest particle ($r$ = 10 \AA) exhibits significant disruption of the original fcc ordering when covered with a half-monolayer of thiol ligands.
529 > The computed corrugation factors are shown in Figure
530 > \ref{fig:NPthiols_corrugation} for bare nanoparticles and for
531 > ligand-protected particles as a function of ligand chain length. The
532 > largest nanoparticles are only slightly restructured by the presence
533 > of ligands on the surface, while the smallest particle ($r$ = 10 \AA)
534 > exhibits significant disruption of the original fcc ordering when
535 > covered with a half-monolayer of thiol ligands.
536  
537 + \begin{figure}
538 +  \includegraphics[width=\linewidth]{figures/C3.pdf}
539 +  \caption{Computed corrugation values for 4 sizes of solvated
540 +    nanoparticles that are bare or protected with a 50\% coverage of
541 +    C$_{4}$, C$_{8}$, or C$_{12}$ thiolate ligands.  The smallest (10
542 +    \AA ) particles show significant disruption to their crystal
543 +    structures, and the length and stiffness of the ligands is a
544 +    contributing factor to the surface disruption.}
545 +  \label{fig:NPthiols_corrugation}
546 + \end{figure}
547 +
548 + Because the thiolate ligands do not significantly alter the larger
549 + particle crystallinity, the surface corrugation does not seem to be a
550 + likely candidate to explain the large increase in thermal conductance
551 + at the interface when ligands are added.
552 +
553   % \begin{equation}
554   %       C = \frac{r_{bare}(\rho_{\scriptscriptstyle{0.85}}) - r_{capped}(\rho_{\scriptscriptstyle{0.85}})}{r_{bare}(\rho_{\scriptscriptstyle{0.85}})}.
555   % \end{equation}
556   %
557   % Here, $r_{bare}(\rho_{\scriptscriptstyle{0.85}})$ is the radius of a bare nanoparticle at which the density is $85\%$ the bulk value and $r_{capped}(\rho_{\scriptscriptstyle{0.85}})$ is the corresponding radius for a particle of the same size with a layer of ligands. $C$ has a value of 0 for a bare particle and approaches $1$ as the degree of surface atom mixing increases.
558  
559 +
560 +
561 +
562   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
563   %               MOBILITY OF INTERFACIAL SOLVENT
564   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
565 < \subsection{Mobility of Interfacial Solvent}
565 > % \subsection{Mobility of Interfacial Solvent}
566  
567 < As in the planar case described in Chapter 3, I use a survival correlation function, $C(t)$, to measure the residence time of a solvent molecule in the nanoparticle thiolate layer. This function correlates the identity of all hexane molecules within the radial range of the thiolate layer at two separate times. If the solvent molecule is present at both times, the configuration contributes a $1$, while the absence of the molecule at the later time indicates that the solvent molecule has migrated into the bulk, and this configuration contributes a $0$. A steep decay in $C(t)$ indicates a high turnover rate of solvent molecules from the chain region to the bulk. We may define the escape rate for trapped solvent molecules at the interface as
567 > % Another possible mechanism for increasing interfacial conductance is
568 > % the mobility of the interfacial solvent.  We used a survival
569 > % correlation function, $C(t)$, to measure the residence time of a
570 > % solvent molecule in the nanoparticle thiolate
571 > % layer.\cite{Stocker:2013cl} This function correlates the identity of
572 > % all hexane molecules within the radial range of the thiolate layer at
573 > % two separate times. If the solvent molecule is present at both times,
574 > % the configuration contributes a $1$, while the absence of the molecule
575 > % at the later time indicates that the solvent molecule has migrated
576 > % into the bulk, and this configuration contributes a $0$. A steep decay
577 > % in $C(t)$ indicates a high turnover rate of solvent molecules from the
578 > % chain region to the bulk. We may define the escape rate for trapped
579 > % solvent molecules at the interface as
580 > % \begin{equation}
581 > %  k_\mathrm{escape} = \left( \int_0^T C(t) dt \right)^{-1}
582 > %   \label{eq:mobility}
583 > % \end{equation}
584 > % where T is the length of the simulation. This is a direct measure of
585 > % the rate at which solvent molecules initially entangled in the
586 > % thiolate layer can escape into the bulk. When $k_\mathrm{escape}
587 > % \rightarrow 0$, the solvent becomes permanently trapped in the
588 > % interfacial region.
589  
590 < \begin{equation}
591 < k_{escape} = \left( \int_0^T C(t) dt \right)^{-1}
592 <  \label{eq:mobility}
593 < \end{equation}
590 > % The solvent escape rates for bare and ligand-protected nanoparticles
591 > % are shown in Figure \ref{fig:NPthiols_combo}. As the ligand chain
592 > % becomes longer and more flexible, interfacial solvent molecules become
593 > % trapped in the ligand layer and the solvent escape rate decreases.
594 > % This mechanism contributes a partial explanation as to why the longer
595 > % ligands have significantly lower thermal conductance.
596  
265 where T is the length of the simulation. This is a direct measure of the rate at which solvent molecules initially entangled in the thiolate layer can escape into the bulk. As $k_{escape} \rightarrow 0$, the solvent becomes permanently trapped in the interfacial region.
266
267 The solvent escape rates for bare and ligand-protected nanoparticles are shown in Figure \ref{fig:NPthiols_combo}. As the ligand chain becomes longer and more flexible, interfacial solvent molecules becomes trapped in the ligand layer and the solvent escape rate decreases.
268
597   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
598   %               ORIENTATION OF LIGAND CHAINS
599   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
600   \subsection{Orientation of Ligand Chains}
601  
602 < I have previously observed that as the ligand chain length increases in length, it becomes significantly more flexible. Thus, different lengths of ligands should favor different chain orientations on the surface of the nanoparticle. To determine the distribution of ligand orientations relative to the particle surface I examine the probability of each $\cos{(\theta)}$,
603 <
602 > As the saturated ligand chain length increases in length, it exhibits
603 > significantly more conformational flexibility. Thus, different lengths
604 > of ligands should favor different chain orientations on the surface of
605 > the nanoparticle. To determine the distribution of ligand orientations
606 > relative to the particle surface we examine the probability of finding
607 > a ligand with a particular orientation relative to the surface normal
608 > of the nanoparticle,
609   \begin{equation}
610   \cos{(\theta)}=\frac{\vec{r}_i\cdot\hat{u}_i}{|\vec{r}_i||\hat{u}_i|}
611   \end{equation}
612 + where $\vec{r}_{i}$ is the vector between the cluster center of mass
613 + and the sulfur atom on ligand molecule {\it i}, and $\hat{u}_{i}$ is
614 + the  vector between the sulfur atom and \ce{CH3} pseudo-atom on ligand
615 + molecule {\it i}. As depicted in Figure \ref{fig:NP_pAngle}, $\theta
616 + \rightarrow 180^{\circ}$ for a ligand chain standing upright on the
617 + particle ($\cos{(\theta)} \rightarrow -1$) and $\theta \rightarrow
618 + 90^{\circ}$ for a ligand chain lying down on the surface
619 + ($\cos{(\theta)} \rightarrow 0$). As the thiolate alkane chain
620 + increases in length and becomes more flexible, the ligands are more
621 + willing to lie down on the nanoparticle surface and exhibit increased
622 + population at $\cos{(\theta)} = 0$.
623  
280 where $\vec{r}_{i}$ is the vector between the cluster center of mass and the sulfur atom on ligand molecule {\it i}, and $\hat{u}_{i}$ is the vector between the sulfur atom and CH3 pseudo-atom on ligand molecule {\it i}. As depicted in Figure \ref{fig:NP_pAngle}, $\theta \rightarrow 180^{\circ}$ for a ligand chain standing upright on the particle ($\cos{(\theta)} \rightarrow -1$) and $\theta \rightarrow 90^{\circ}$ for a ligand chain lying down on the surface ($\cos{(\theta)} \rightarrow 0$). As the thiolate alkane chain increases in length and becomes more flexible, the ligands are more likely to lie down on the nanoparticle surface and there will be increased population at $\cos{(\theta)} = 0$.
281
624   \begin{figure}
625 <        \includegraphics[width=\linewidth]{figures/NP_pAngle}
626 <        \caption{The two extreme cases of ligand orientation relative to the nanoparticle surface: the ligand completely outstretched ($\cos{(\theta)} = -1$) and the ligand fully lying down on the particle surface ($\cos{(\theta)} = 0$).}
627 <        \label{fig:NP_pAngle}
625 >  \includegraphics[width=\linewidth]{figures/NP_pAngle}
626 >  \caption{The two extreme cases of ligand orientation relative to the
627 >    nanoparticle surface: the ligand completely outstretched
628 >    ($\cos{(\theta)} = -1$) and the ligand fully lying down on the
629 >    particle surface ($\cos{(\theta)} = 0$).}
630 >  \label{fig:NP_pAngle}
631   \end{figure}
632  
633 < % \begin{figure}
634 < %       \includegraphics[width=\linewidth]{figures/thiol_pAngle}
635 < %       \caption{}
291 < %       \label{fig:thiol_pAngle}
292 < % \end{figure}
293 <
294 < A single number describing the average ligand chain orientation relative to the nanoparticle surface may be achieved by calculating a P$_2$ order parameter from the distribution of $\cos(\theta)$ values.
295 <
633 > An order parameter describing the average ligand chain orientation relative to
634 > the nanoparticle surface is available using the second order Legendre
635 > parameter,
636   \begin{equation}
637 <        P_2(\cos(\theta)) = \left < \frac{1}{2} \left (3\cos^2(\theta) - 1 \right ) \right >
637 >        P_2 = \left< \frac{1}{2} \left(3\cos^2(\theta) - 1 \right) \right>
638   \end{equation}
639  
640 < A ligand chain that is perpendicular to the particle surface has a P$_2$ value of 1, while a ligand chain lying flat on the nanoparticle surface has a P$_2$ value of $-\frac{1}{2}$. Disordered ligand layers will exhibit a mean P$_2$ value of 0. As shown in Figure \ref{fig:NPthiols_combo} the ligand P$_2$ value approaches 0 as ligand chain length -- and ligand flexibility -- increases.
640 > Ligand populations that are perpendicular to the particle surface have
641 > $P_2$ values of 1, while ligand populations lying flat on the
642 > nanoparticle surface have $P_2$ values of $-0.5$. Disordered ligand
643 > layers will exhibit mean $P_2$ values of 0. As shown in Figure
644 > \ref{fig:NPthiols_P2} the ligand $P_2$ values approaches 0 as
645 > ligand chain length -- and ligand flexibility -- increases.
646  
647   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
648   %               ORIENTATION OF INTERFACIAL SOLVENT
649   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
650   \subsection{Orientation of Interfacial Solvent}
651  
652 < I also examined the distribution of \emph{hexane} molecule orientations relative to the particle surface using the same $\cos{(\theta)}$ analysis utilized for the ligand chain orientations. In this case, $\vec{r}_i$ is the vector between the particle center of mass and one of the \ce{CH2} pseudo-atoms in the middle of hexane molecule $i$ and $\hat{u}_i$ is the vector between the two \ce{CH3} pseudo-atoms on molecule $i$. Since we are only interested in the orientation of solvent molecules near the ligand layer, I selected only the hexane molecules within a specific $r$-range, between the edge of the particle and the end of the ligand chains. A large population of hexane molecules with $\cos{(\theta)} \cong -1$ would indicate interdigitation of the solvent molecules between the upright ligand chains. A more random distribution of $\cos{(\theta)}$ values indicates either little penetration of the ligand layer by the solvent, or a very disordered arrangement of ligand chains on the particle surface. Again, P$_2$ order parameter values may be obtained from the distribution of $\cos(\theta)$ values.
653 <
654 < The average orientation of the interfacial solvent molecules is notably flat on the \emph{bare} nanoparticle surface. This blanket of hexane molecules on the particle surface may act as an insulating layer, increasing the interfacial thermal resistance. As the length (and flexibility) of the ligand increases, the average interfacial solvent P$_2$ value approaches 0, indicating random orientation of the ligand chains. The average orientation of solvent within the $C_8$ and $C_{12}$ ligand layers is essentially totally random. Solvent molecules in the interfacial region of $C_4$ ligand-protected nanoparticles do not lie as flat on the surface as in the case of the bare particles, but are not as random as the longer ligand lengths.
655 <
656 < These results are particularly interesting in light of the results described in Chapter 3, where solvent molecules readily filled the vertical gaps between neighboring ligand chains and there was a strong correlation between ligand and solvent molecular orientations. It appears that the introduction of surface curvature and a lower ligand packing density creates a very disordered ligand layer that lacks well-formed channels for the solvent molecules to occupy.
652 > Similarly, we examined the distribution of \emph{hexane} molecule
653 > orientations relative to the particle surface using the same angular
654 > analysis utilized for the ligand chain orientations. In this case,
655 > $\vec{r}_i$ is the vector between the particle center of mass and one
656 > of the \ce{CH2} pseudo-atoms in the middle of hexane molecule $i$ and
657 > $\hat{u}_i$ is the vector between the two \ce{CH3} pseudo-atoms on
658 > molecule $i$. Since we are only interested in the orientation of
659 > solvent molecules near the ligand layer, we select only the hexane
660 > molecules within a specific $r$-range, between the edge of the
661 > particle and the end of the ligand chains. A large population of
662 > hexane molecules with $\cos{(\theta)} \sim \pm 1$ would indicate
663 > interdigitation of the solvent molecules between the upright ligand
664 > chains. A more random distribution of $\cos{(\theta)}$ values
665 > indicates a disordered arrangement of solvent molecules near the particle
666 > surface. Again, $P_2$ order parameter values provide a population
667 > analysis for the solvent that is close to the particle surface.
668  
669 < % \begin{figure}
670 < %       \includegraphics[width=\linewidth]{figures/hex_pAngle}
671 < %       \caption{}
672 < %       \label{fig:hex_pAngle}
673 < % \end{figure}
669 > The average orientation of the interfacial solvent molecules is
670 > notably flat on the \emph{bare} nanoparticle surfaces. This blanket of
671 > hexane molecules on the particle surface may act as an insulating
672 > layer, increasing the interfacial thermal resistance. As the length
673 > (and flexibility) of the ligand increases, the average interfacial
674 > solvent P$_2$ value approaches 0, indicating a more random orientation
675 > of the ligand chains. The average orientation of solvent within the
676 > $C_8$ and $C_{12}$ ligand layers is essentially random. Solvent
677 > molecules in the interfacial region of $C_4$ ligand-protected
678 > nanoparticles do not lie as flat on the surface as in the case of the
679 > bare particles, but are not as randomly oriented as the longer ligand
680 > lengths.
681  
682 + \begin{figure}
683 +  \includegraphics[width=\linewidth]{figures/P2_3.pdf}
684 +  \caption{Computed ligand and interfacial solvent orientational $P_2$
685 +    values for 4 sizes of solvated nanoparticles that are bare or
686 +    protected with a 50\% coverage of C$_{4}$, C$_{8}$, or C$_{12}$
687 +    alkanethiolate ligands. Increasing stiffness of the ligand orients
688 +    these molecules normal to the particle surface, while the length
689 +    of the ligand chains works to prevent solvent from lying flat on
690 +    the surface.}
691 +  \label{fig:NPthiols_P2}
692 + \end{figure}
693 +
694 + These results are particularly interesting in light of our previous
695 + results\cite{Stocker:2013cl}, where solvent molecules readily filled
696 + the vertical gaps between neighboring ligand chains and there was a
697 + strong correlation between ligand and solvent molecular
698 + orientations. It appears that the introduction of surface curvature
699 + and a lower ligand packing density creates a disordered ligand layer
700 + that lacks well-formed channels for the solvent molecules to occupy.
701 +
702   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
703   %               SOLVENT PENETRATION OF LIGAND LAYER
704   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
705   \subsection{Solvent Penetration of Ligand Layer}
706  
707 < We may also determine the extent of ligand -- solvent interaction by calculating the hexane density as a function of $r$. Figure \ref{fig:hex_density} shows representative radial hexane density profiles for a solvated 25 \AA\ radius nanoparticle with no ligands, and 50\% coverage of C$_{4}$, C$_{8}$, and C$_{12}$ thiolates.
707 > The extent of ligand -- solvent interaction is also determined by the
708 > degree to which these components occupy the same region of space
709 > adjacent to the nanoparticle. The radial density profiles of these
710 > components help determine this degree of interaction.  Figure
711 > \ref{fig:density} shows representative density profiles for solvated
712 > 25 \AA\ radius nanoparticles with no ligands, and with a 50\% coverage
713 > of C$_{4}$, C$_{8}$, and C$_{12}$ thiolates.
714  
715   \begin{figure}
716 <        \includegraphics[width=\linewidth]{figures/hex_density}
717 <        \caption{Radial hexane density profiles for 25 \AA\ radius nanoparticles with no ligands (circles), C$_{4}$ ligands (squares), C$_{8}$ ligands (triangles), and C$_{12}$ ligands (diamonds). As ligand chain length increases, the nearby solvent is excluded from the ligand layer. Some solvent is present inside the particle $r_{max}$ location due to faceting of the nanoparticle surface.}
718 <        \label{fig:hex_density}
716 >  \includegraphics[width=\linewidth]{figures/density}
717 >  \caption{Radial density profiles for 25 \AA\ radius nanoparticles
718 >    with no ligands (circles), C$_{4}$ ligands (squares), C$_{8}$
719 >    ligands (diamonds), and C$_{12}$ ligands (triangles). Ligand
720 >    density is indicated with filled symbols, solvent (hexane) density
721 >    is indicated with open symbols. As ligand chain length increases,
722 >    the nearby solvent is excluded from the ligand layer.  The
723 >    conjugated ligands (upper panel) can create a separated solvent
724 >    shell within the ligand layer and also allow significantly more
725 >    solvent to penetrate close to the particle.}
726 >  \label{fig:density}
727   \end{figure}
728  
729 < The differences between the radii at which the hexane surrounding the ligand-covered particles reaches bulk density correspond nearly exactly to the differences between the lengths of the ligand chains. Beyond the edge of the ligand layer, the solvent reaches its bulk density within a few angstroms. The differing shapes of the density curves indicate that the solvent is increasingly excluded from the ligand layer as the chain length increases.
729 > The differences between the radii at which the hexane surrounding the
730 > ligand-covered particles reaches bulk density correspond nearly
731 > exactly to the differences between the lengths of the ligand
732 > chains. Beyond the edge of the ligand layer, the solvent reaches its
733 > bulk density within a few angstroms. The differing shapes of the
734 > density curves indicate that the solvent is increasingly excluded from
735 > the ligand layer as the chain length increases.
736  
737 + The conjugated ligands create a distinct solvent shell within the
738 + ligand layer and also allow significantly more solvent to penetrate
739 + close to the particle.  We define a density overlap parameter,
740 + \begin{equation}
741 + O_{l-s} = \frac{1}{V} \int_0^{r_\mathrm{max}} 4 \pi r^2 \frac{4 \rho_l(r) \rho_s(r)}{\left(\rho_l(r) +
742 +    \rho_s(r)\right)^2} dr
743 + \end{equation}
744 + where $\rho_l(r)$ and $\rho_s(r)$ are the ligand and solvent densities
745 + at a radius $r$, and $V$ is the total integration volume
746 + ($V = 4\pi r_\mathrm{max}^3 / 3$).  The fraction in the integrand is a
747 + dimensionless quantity that is unity when ligand and solvent densities
748 + are identical at radius $r$, but falls to zero when either of the two
749 + components are excluded from that region.
750 +
751 + \begin{figure}
752 +  \includegraphics[width=\linewidth]{figures/rho3}
753 +  \caption{Density overlap parameters ($O_{l-s}$) for solvated
754 +    nanoparticles protected by thiolate ligands. In general, the
755 +    rigidity of the fully-conjugated ligands provides the easiest
756 +    route for solvent to enter the interfacial region. Additionally,
757 +    shorter chains allow a greater degree of solvent penetration of
758 +    the ligand layer.}
759 +  \label{fig:rho3}
760 + \end{figure}
761 +
762 + The density overlap parameters are shown in Fig. \ref{fig:rho3}.  The
763 + calculated overlap parameters indicate that the conjugated ligand
764 + allows for the most solvent penetration close to the particle, and
765 + that shorter chains generally permit greater solvent penetration in
766 + the interfacial region. Increasing overlap can certainly allow for
767 + enhanced thermal transport, but this is clearly not the only
768 + contributing factor. Even when the solvent and ligand are in close
769 + physical contact, there must also be good vibrational overlap between
770 + the phonon densities of states in the ligand and solvent to transmit
771 + vibrational energy between the two materials.
772 +
773 + \subsection{Ligand-mediated Vibrational Overlap}
774 +
775 + In phonon scattering models for interfacial thermal
776 + conductance,\cite{Swartz:1989uq,Young:1989xy,Cahill:2003fk,Reddy:2005fk,Schmidt:2010nr}
777 + the frequency-dependent transmission probability
778 + ($t_{a \rightarrow b}(\omega)$) predicts phonon transfer between
779 + materials $a$ and $b$.  Many of the models for interfacial phonon
780 + transmission estimate this quantity using the phonon density of states
781 + and group velocity, and make use of a Debye model for the density of
782 + states in the solid.
783 +
784 + A consensus picture is that in order to transfer the energy carried by
785 + an incoming phonon of frequency $\omega$ on the $a$ side, the phonon
786 + density of states on the $b$ side must have a phonon of the same
787 + frequency. The overlap of the phonon densities of states, particularly
788 + at low frequencies, therefore contributes to the transfer of heat.
789 + Phonon scattering must also be done in a direction perpendicular to
790 + the interface.  In the geometries described here, there are two
791 + interfaces (particle $\rightarrow$ ligand, and ligand $\rightarrow$
792 + solvent), and the vibrational overlap between the ligand and the other
793 + two components is going to be relevant to heat transfer.
794 +
795 + To estimate the relevant densities of states, we have projected the
796 + velocity of each atom $i$ in the region of the interface onto a
797 + direction normal to the interface. For the nanosphere geometries
798 + studied here, the normal direction depends on the instantaneous
799 + positon of the atom relative to the center of mass of the particle.
800 + \begin{equation}
801 + v_i^\perp(t) = \mathbf{v}_i(t) \cdot \frac{\mathbf{r}_i(t)}{\left|\mathbf{r}_i(t)\right|}
802 + \end{equation}
803 + The quantity $v_i^\perp(t)$ measures the instantaneous velocity of
804 + atom $i$ in a direction perpendicular to the nanoparticle interface.
805 + In the interfacial region, the autocorrelation function of these
806 + velocities,
807 + \begin{equation}
808 +  C_\perp(t) = \left< v_i^\perp(t) \cdot v_i^\perp(0) \right>,
809 + \end{equation}
810 + will include contributions from all of the phonon modes present at the
811 + interface.  The Fourier transform of the time-symmetrized
812 + autocorrelation function provides an estimate of the vibrational
813 + density of states,\cite{Shin:2010sf}
814 + \begin{equation}
815 +  \rho(\omega) = \frac{1}{\tau} \int_{-\tau/2}^{\tau/2} C_\perp(t) e^{-i
816 +    \omega t} dt.
817 + \end{equation}
818 + In Fig.~\ref{fig:vdos} we show the low-frequency region of the
819 + normalized vibrational densities of states for the three chemical
820 + components (gold nanoparticle, C$_{12}$ ligands, and interfacial
821 + solvent).  The double bond in the penultimate location is a small
822 + perturbation on ligands of this size, and that is reflected in
823 + relatively similar spectra in the lower panels.  The fully conjugated
824 + ligand, however, pushes the peak in the lowest frequency band from
825 + $\sim 29 \mathrm{cm}^{-1}$ to $\sim 55 \mathrm{cm}^{-1}$, yielding
826 + significant overlap with the density of states in the nanoparticle.
827 + This ligand also increases the overlap with the solvent density of
828 + states in a band between 280 and 380 $\mathrm{cm}^{-1}$.  This
829 + provides some physical basis for the high interfacial conductance
830 + observed for the fully conjugated $C_8$ and $C_{12}$ ligands.
831 +
832 + \begin{figure}
833 +  \includegraphics[width=\linewidth]{figures/rho_omega_12}
834 +  \caption{The low frequency portion of the vibrational density of
835 +    states for three chemical components (gold nanoparticles, C$_{12}$
836 +    ligands, and hexane solvent). These densities of states were
837 +    computed using the velocity autocorrelation functions for atoms in
838 +    the interfacial region, constructed with velocities projected onto
839 +    a direction normal to the interface.}
840 +  \label{fig:vdos}
841 + \end{figure}
842 +
843 + The similarity between the density of states for the alkanethiolate
844 + and penultimate ligands also helps explain why the interfacial
845 + conductance is nearly the same for these two ligands, particularly at
846 + longer chain lengths.
847 +
848   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
849   %               DISCUSSION
850   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
851   \section{Discussion}
852  
853 < The chemical bond between the metal and the ligand introduces vibrational overlap that is not present between the bare metal surface and solvent. Thus, regardless of ligand chain length, the presence of a half-monolayer ligand coverage yields a higher interfacial thermal conductance value than the bare nanoparticle. The dependence of the interfacial thermal conductance on ligand chain length is primarily explained by increased ligand flexibility. The shortest and least flexible ligand ($C_4$), which exhibits the highest interfacial thermal conductance value, is oriented more normal to the particle surface than the longer ligands and is least likely to trap solvent molecules within the ligand layer. The longer $C_8$ and $C_{12}$ ligands have increasingly disordered average orientations and correspondingly lower solvent escape rates.
853 > The chemical bond between the metal and the ligand introduces
854 > vibrational overlap that is not present between the bare metal surface
855 > and solvent. Thus, regardless of ligand identity or chain length, the
856 > presence of a half-monolayer ligand coverage yields a higher
857 > interfacial thermal conductance value than the bare nanoparticle.  The
858 > mechanism for the varying conductance for the different ligands is
859 > somewhat less clear.  Ligand-based alterations to vibrational density
860 > of states is a major contributor, but some of the ligands can disrupt
861 > the crystalline structure of the smaller nanospheres, while others can
862 > re-order the interfacial solvent and alter the interpenetration
863 > profile between ligand and solvent chains. Further work to separate
864 > the effects of ligand-solvent interpenetration and surface
865 > reconstruction is clearly needed for a complete picture of the heat
866 > transport in these systems.
867  
341 The heat transfer mechanisms proposed in Chapter 3 can also be applied to the non-periodic case. When the ligands are less tightly packed, the cooperative orientational ordering between the ligand and solvent decreases dramatically and the conductive heat transfer model plays a much smaller role in determining the total interfacial thermal conductance. Thus, heat transfer into the solvent relies primarily on the convective model, where solvent molecules pick up thermal energy from the ligands and diffuse into the bulk solvent. This mode of heat transfer is hampered by a slow solvent escape rate, which is clearly present in the randomly ordered long ligand layers.
342
868   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
869   % **ACKNOWLEDGMENTS**
870   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
871 < \begin{acknowledgement}
871 > \begin{acknowledgments}
872    Support for this project was provided by the National Science Foundation
873 <  under grant CHE-0848243. Computational time was provided by the
873 >  under grant CHE-1362211. Computational time was provided by the
874    Center for Research Computing (CRC) at the University of Notre Dame.
875 < \end{acknowledgement}
875 > \end{acknowledgments}
876  
352
877   \newpage
878 <
878 > \bibliographystyle{aip}
879   \bibliography{NPthiols}
880  
881 < \end{document}
881 > \end{document}

Diff Legend

Removed lines
+ Added lines
< Changed lines
> Changed lines