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

Comparing trunk/chainLength/GoldThiolsPaper.tex (file contents):
Revision 3847 by kstocke1, Fri Dec 21 18:52:01 2012 UTC vs.
Revision 3848 by gezelter, Fri Dec 21 18:55:17 2012 UTC

# Line 63 | Line 63
63   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
64   \section{Introduction}
65  
66 < The structural and dynamical details of interfaces between metal
67 < nanoparticles and solvents determines how energy flows between these
68 < particles and their surroundings. Understanding this energy flow is
69 < essential in designing and functionalizing metallic nanoparticles for
70 < plasmonic photothermal
71 < therapies,\cite{Jain:2007ux,Petrova:2007ad,Gnyawali:2008lp,Mazzaglia:2008to,Huff:2007ye,Larson:2007hw} which rely on the ability of metallic
72 < nanoparticles to absorb light in the near-IR, a portion of the
73 < spectrum in which living tissue is very nearly transparent.  The
74 < principle of this therapy is to pump the particles at high power at
75 < the plasmon resonance and to allow heat dissipation to kill targeted
76 < (e.g. cancerous) cells.  The relevant physical property controlling
77 < this transfer of energy is the interfacial thermal conductance, $G$,
78 < which can be somewhat difficult to determine
79 < experimentally.\cite{Wilson:2002uq,Plech:2005kx}
66 > The structural details of the interfaces of metal nanoparticles
67 > determines how energy flows between these particles and their
68 > surroundings. Understanding this energy flow is essential in designing
69 > and functionalizing metallic nanoparticles for plasmonic photothermal
70 > therapies,\cite{Jain:2007ux,Petrova:2007ad,Gnyawali:2008lp,Mazzaglia:2008to,Huff:2007ye,Larson:2007hw}
71 > which rely on the ability of metallic nanoparticles to absorb light in
72 > the near-IR, a portion of the spectrum in which living tissue is very
73 > nearly transparent.  The relevant physical property controlling the
74 > transfer of this energy as heat into the surrounding tissue is the
75 > interfacial thermal conductance, $G$, which can be somewhat difficult
76 > to determine experimentally.\cite{Wilson:2002uq,Plech:2005kx}
77  
78   Metallic particles have also been proposed for use in highly efficient
79 < thermal-transfer fluids, although careful experiments by Eapen {\it et al.}
80 < have shown that metal-particle-based ``nanofluids'' have thermal
81 < conductivities that match Maxwell predictions.\cite{Eapen:2007th} The
82 < likely cause of previously reported non-Maxwell
79 > thermal-transfer fluids, although careful experiments by Eapen {\it et
80 >  al.}  have shown that metal-particle-based ``nanofluids'' have
81 > thermal conductivities that match Maxwell
82 > predictions.\cite{Eapen:2007th} The likely cause of previously
83 > reported non-Maxwell
84   behavior\cite{Eastman:2001wb,Keblinski:2002bx,Lee:1999ct,Xue:2003ya,Xue:2004oa}
85   is percolation networks of nanoparticles exchanging energy via the
86   solvent,\cite{Eapen:2007mw} so it is vital to get a detailed molecular
87 < picture of particle-solvent interactions in order to understand the
88 < thermal behavior of complex fluids. To date, there have been few
89 < reported values (either from theory or experiment) for $G$ for
90 < ligand-protected nanoparticles embedded in liquids, and there is a
91 < significant gap in knowledge about how chemically distinct ligands or
92 < protecting groups will affect heat transport from the particles.
87 > picture of particle-ligand and particle-solvent interactions in order
88 > to understand the thermal behavior of complex fluids. To date, there
89 > have been few reported values (either from theory or experiment) for
90 > $G$ for ligand-protected nanoparticles embedded in liquids, and there
91 > is a significant gap in knowledge about how chemically distinct
92 > ligands or protecting groups will affect heat transport from the
93 > particles.
94  
95 < The thermal properties of various nanostructured interfaces have been
96 < investigated experimentally by a number of groups: Cahill and
95 > Experimentally, the thermal properties of various nanostructured
96 > interfaces have been investigated by a number of groups. Cahill and
97   coworkers studied nanoscale thermal transport from metal
98 < nanoparticle/fluid interfaces, to epitaxial TiN/single crystal oxides
98 > nanoparticle/fluid interfaces, to epitaxial TiN/single crystal oxide
99   interfaces, and hydrophilic and hydrophobic interfaces between water
100   and solids with different self-assembled
101   monolayers.\cite{cahill:793,Wilson:2002uq,PhysRevB.67.054302,doi:10.1021/jp048375k,PhysRevLett.96.186101}
# Line 125 | Line 124 | a mechanism for rapid thermal transport across the int
124   the vibrational spectra (metal to ligand, ligand to solvent) provides
125   a mechanism for rapid thermal transport across the interface.
126  
127 < One interesting result of our previous work was the observation of
128 < {\it non-monotonic dependence} of the thermal conductance on the
129 < coverage of a metal surface by a chemical protecting group.  Our
130 < explanation for this behavior was that gaps in surface coverage
131 < allowed solvent to penetrate close to the capping molecules that had
132 < been heated by the metal surface, to absorb thermal energy from these
133 < molecules, and then diffuse away.  The effect of surface coverage is
134 < relatively difficult to study as the individual protecting groups have
135 < lateral mobility on the surface and can aggregate to form domains on
136 < the timescale of the simulation.
127 > One notable result of our previous work was the observation of
128 > non-monotonic dependence of the thermal conductance on the coverage of
129 > a metal surface by a chemical protecting group.  Our explanation for
130 > this behavior was that gaps in surface coverage allowed solvent to
131 > penetrate close to the capping molecules that had been heated by the
132 > metal surface, to absorb thermal energy from these molecules, and then
133 > diffuse away.  The effect of surface coverage was relatively difficult
134 > to study as the individual protecting groups have lateral mobility on
135 > the surface and can aggregate to form domains on the timescale of the
136 > simulation.  
137  
138 < The work reported here involves the use of velocity shearing and
139 < scaling reverse non-equilibrium molecular dynamics (VSS-RNEMD) to
140 < study surfaces composed of mixed-length chains which collectively form
141 < a complete monolayer on the surfaces.  These complete (but
142 < mixed-chain) surfaces are significantly less prone to surface domain
143 < formation, and would allow us to further investigate the mechanism of
144 < heat transport to the solvent.
138 > To prevent lateral mobility of the surface ligands, the current work
139 > involves mixed-chain monolayers in which the length mismatch between
140 > long and short chains is sufficient to accomodate solvent
141 > molecules. These complete (but mixed-chain) surfaces are significantly
142 > less prone to surface domain formation, and allow us to further
143 > investigate the mechanism of heat transport to the solvent.  A thermal
144 > flux is created using velocity shearing and scaling reverse
145 > non-equilibrium molecular dynamics (VSS-RNEMD), and the resulting
146 > temperature profiles are analyzed to yield information about the
147 > interfacial thermal conductance.
148  
149 +
150   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
151   %                          **METHODOLOGY**
152   %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Line 202 | Line 205 | large.\cite{Maginn:2010}      
205   undesirable side-effects when the applied flux becomes
206   large.\cite{Maginn:2010}        
207  
208 < Instead of having momentum exchange between {\it individual particles}
209 < in each slab, the NIVS algorithm applies velocity scaling to all of
210 < the selected particles in both slabs.\cite{Kuang:2010uq} A combination
208 < of linear momentum, kinetic energy, and flux constraint equations
209 < governs the amount of velocity scaling performed at each step.  NIVS
210 < has been shown to be very effective at producing thermal gradients and
211 < for computing thermal conductivities, particularly for heterogeneous
212 < interfaces.  Although the NIVS algorithm can also be applied to impose
213 < a directional momentum flux, thermal anisotropy was observed in
214 < relatively high flux simulations, and the method is not suitable for
215 < imposing a shear flux or for computing shear viscosities.
216 <
217 < The most useful RNEMD
218 < approach developed so far utilizes a series of simultaneous velocity
219 < shearing and scaling exchanges between the two
220 < slabs.\cite{2012MolPh.110..691K} This method provides a set of
208 > The most useful alternative RNEMD approach developed so far utilizes a
209 > series of simultaneous velocity shearing and scaling exchanges between
210 > the two slabs.\cite{2012MolPh.110..691K} This method provides a set of
211   conservation constraints while simultaneously creating a desired flux
212   between the two slabs.  Satisfying the constraint equations ensures
213   that the new configurations are sampled from the same NVE ensemble.
# Line 296 | Line 286 | viscosity of SPC/E water over a wide range of temperat
286   kept to a minimum.  This ability to generate simultaneous thermal and
287   shear fluxes has been previously utilized to map out the shear
288   viscosity of SPC/E water over a wide range of temperatures (90~K) with
289 < a {\it single 1 ns simulation}.\cite{2012MolPh.110..691K}
289 > a single 1 ns simulation.\cite{2012MolPh.110..691K}
290  
291   \begin{figure}
292    \includegraphics[width=\linewidth]{figures/rnemd}

Diff Legend

– Removed lines
+ Added lines
< Changed lines
> Changed lines