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# Line 11 | Line 11 | medium.\cite{HuM._jp020581+,hartland02d}
11   rapid heat transfer to the surrounding
12   medium.\cite{HuM._jp020581+,hartland02d}
13  
14 < This paper reports on atomic-level simulations of the transient
14 > In this chapter, atomic-level simulations of the transient
15   response of metallic nanoparticles to the nearly instantaneous heating
16   undergone when photons are absorbed during ultrafast laser excitation
17 < experiments.  The time scale for heating (determined by the {\it e-ph}
17 > experiments are discussed. The time scale for heating (determined by the {\it e-ph}
18   coupling constant) is faster than a single period of the breathing
19   mode for spherical nanoparticles.\cite{Simon2001,HartlandG.V._jp0276092}
20   Hot-electron pressure and direct lattice heating contribute to the
# Line 33 | Line 33 | Results are presented in section \ref{bulkmod:sec:resu
33  
34   We outline our simulation techniques in section \ref{bulkmod:sec:details}.
35   Results are presented in section \ref{bulkmod:sec:results}.  We discuss our
36 < results in terms of Lamb's classical theory of elastic spheres in
36 > results in terms of Lamb's classical theory of elastic spheres \cite{Lamb1882} in
37   section \ref{bulkmod:sec:discussion}.
38  
39 < \section{COMPUTATIONAL DETAILS}
39 > \section{Computational Details}
40   \label{bulkmod:sec:details}
41  
42   Spherical Au nanoparticles were created in a standard FCC lattice at
# Line 46 | Line 46 | excluded from the simulation.
46   spacing (4.08 \AA) and any atoms outside the target radius were
47   excluded from the simulation.
48  
49 < \subsection{SIMULATION METHODOLOGY}
49 > \subsection{Simulation Methodology}
50  
51   Potentials were calculated using the Voter-Chen
52   parameterization~\cite{Voter:87} of the Embedded Atom Method ({\sc
53 < eam}), which has been widely used for MD simulations of metallic
54 < particles.%\cite{Voter:87,Daw84,FBD86,johnson89,Lu97}
55 < Like other transition metal potentials,%\cite{Finnis84,Ercolessi88,Chen90,Qi99,Ercolessi02}
56 < {\sc eam} describes bonding in metallic systems by including an
57 < attractive interaction which models the stabilization of a positively
58 < charged metal core ion in a sea of surrounding valence electrons.  A
59 < repulsive pair potential describes the interactions of the core ions
60 < with each other.  The {\sc eam} potential has the form:
61 < \begin{eqnarray}
62 < V & = & \sum_{i} F_{i}\left[\rho_{i}\right] + \sum_{i} \sum_{j \neq i}
63 < \phi_{ij}({\bf r}_{ij})  \\
64 < \rho_{i}  & = & \sum_{j \neq i} f_{j}({\bf r}_{ij})
65 < \end{eqnarray}
66 < where $\phi_{ij}$ is the (primarily repulsive) pairwise interaction
67 < between atoms $i$ and $j$.  $F_{i}[\rho_{i}]$ is an embedding function
68 < that determines the energy to embed the positively-charged core, $i$,
69 < in the electron density, $\rho_{i}$, due to the valence electrons of
70 < the surrounding $j$ atoms, and $f_{j}(r)$ describes the radial
71 < dependence of the field due to atom $j$. There is a cutoff distance,
72 < $r_{cut}$, which limits the summations in the {\sc eam} equation to
73 < the few dozen atoms surrounding atom $i$.  In these simulations, a
74 < cutoff radius of 10~\AA\ was used.
75 <
76 < %Mixing rules as outlined by Johnson~\cite{johnson89} were used to
77 < %compute the heterogenous pair potential,
78 < %
79 < %\begin{eqnarray}
80 < %\label{eq:johnson}
81 < %\phi_{ab}(r)=\frac{1}{2}\left(
82 < %\frac{f_{b}(r)}{f_{a}(r)}\phi_{aa}(r)+
83 < %\frac{f_{a}(r)}{f_{b}(r)}\phi_{bb}(r)
84 < %\right).
85 < %\end{eqnarray}
86 <
53 > eam}) as described in Section \ref{introSec:eam} of this dissertation.
54   Before starting the molecular dynamics runs, a relatively short
55   steepest-descent minimization was performed to relax the lattice in
56   the initial configuration.  To facilitate the study of the larger
# Line 110 | Line 77 | five independent samples.
77   The results presented below are averaged properties for each of the
78   five independent samples.
79  
80 < \subsection{ANALYSIS}
80 > \subsection{\label{bulkmod:sec:analysis}Analysis}
81  
82   Of primary interest when comparing our simulations to experiments is
83   the dynamics of the low-frequency breathing mode of the particles.  To
84 < study this motion, we need access to accurate measures of both the
84 > study this motion, access is needed to accurate measures of both the
85   volume and surface area as a function of time.  Throughout the
86 < simulations, we monitored both quantities using Barber {\it et al.}'s
86 > simulations, both quantities were monitored using Barber {\it et al.}'s
87   very fast quickhull algorithm to obtain the convex hull for the
88   collection of 3-d coordinates of all of atoms at each point in
89   time.~\cite{barber96quickhull,qhull} The convex hull is the smallest convex
# Line 135 | Line 102 | can be related to quantities that are relatively easil
102   \label{eq:Kdef}
103   \end{equation}
104   can be related to quantities that are relatively easily accessible
105 < from our molecular dynamics simulations.  We present here four
106 < different approaches for estimating the bulk modulus directly from
105 > from our molecular dynamics simulations. Four
106 > different approaches are presented here for estimating the bulk modulus directly from
107   basic or derived quantities:
108  
109   \begin{itemize}
110   \item The traditional ``Energetic'' approach
111  
112 < Using basic thermodynamics and one of the Maxwell relations, we write
112 > Using basic thermodynamics and one of the Maxwell relations, it can be written that
113   \begin{equation}
114   P = T\left(\frac{\partial S}{\partial V}\right)_{T} -
115   \left(\frac{\partial U}{\partial V}\right)_{T}.
# Line 200 | Line 167 | the most suitable way to obtain estimates of the bulk
167  
168   \item The Extended System Approach
169  
170 < Since we are performing these simulations in the NVT ensemble using
170 > Since these simulations are being performed in the NVT ensemble using
171   Nos\'e-Hoover thermostatting, the quantity conserved by our integrator
172   ($H_{NVT}$) can be expressed as:
173   \begin{equation}
# Line 224 | Line 191 | so fitting fluctuations of this quantity to obtain mea
191   \end{equation}
192   However, $H_{NVT}$ is essentially conserved during these simulations,
193   so fitting fluctuations of this quantity to obtain meaningful physical
194 < quantities is somewhat suspect.  We also note that this method would
194 > quantities is somewhat suspect.  It should also noted that this method would
195   fail in periodic systems because the volume itself is fixed in
196   periodic NVT simulations.
197  
# Line 251 | Line 218 | particles,
218   \begin{equation}
219   \overleftrightarrow{\mathsf{W}}  =  \sum_{i} \sum_{j>i}  \vec{r}_{ij} \otimes \vec{f}_{ij}
220   \end{equation}
221 < During the simulation, we record the internal pressure, $P$, as well as
221 > During the simulation, the internal pressure, $P$, is recorded as well as
222   the total energy, $U$, the extended system's hamiltonian, $H_{NVT}$,
223 < and the particle coordinates.  Once we have calculated the time
224 < dependent volume of the nanoparticle using the convex hull, we can use
225 < any of these four methods to estimate the bulk modulus.
223 > and the particle coordinates.  Once the time
224 > dependent volume of the nanoparticle has been calculated using the convex hull,
225 > any of these four methods can be used to estimate the bulk modulus.
226   \end{itemize}
227  
228 < We find, however, that only the fourth method (the direct pressure
228 > It is found, however, that only the fourth method (the direct pressure
229   approach) gives meaningful results.  Bulk moduli for the 35 \AA\
230   particle were computed with the traditional (Energy vs. Volume)
231   approach as well as the direct pressure approach.  A comparison of the
# Line 278 | Line 245 | the direct pressure method.
245   The Bulk moduli reported in the rest of this paper were computed using
246   the direct pressure method.
247  
248 < To study the frequency of the breathing mode, we have calculated the
249 < power spectrum for volume ($V$) fluctuations,
248 > To study the frequency of the breathing mode, the
249 > power spectrum for volume ($V$) fluctuations have been calculated according to,
250   \begin{equation}
251   \rho_{\Delta V}(\omega) = \int_{-\infty}^{\infty} \langle \Delta V(t)
252   \Delta V(0) \rangle e^{-i \omega t} dt
# Line 295 | Line 262 | analysis of the breathing dynamics follows in section
262   analysis of the breathing dynamics follows in section
263   \ref{bulkmod:sec:discussion}.
264  
265 < We have also computed the heat capacity for our simulations to verify
265 > The heat capacity for our simulations has also been computed to verify
266   the location of the melting transition.  Calculations of the heat
267   capacity were performed on the non-equilibrium, instantaneous heating
268   simulations, as well as on simulations of nanoparticles that were at
269   equilibrium at the target temperature.
270    
271 < \section{RESULTS}
271 > \section{Results}
272   \label{bulkmod:sec:results}
273  
274 < \subsection{THE BULK MODULUS AND HEAT CAPACITY}
274 > \subsection{The Bulk Modulus and Heat Capacity}
275  
276   The upper panel in Fig. \ref{fig:BmCp} shows the temperature
277   dependence of the Bulk Modulus ($K$).  In all samples, there is a
# Line 331 | Line 298 | from longer equilibrium trajectories should indicate {
298   Another feature of these transient (non-equilibrium) calculations is
299   the width of the peak in the heat capacity.  Calculation of $C_{p}$
300   from longer equilibrium trajectories should indicate {\it sharper}
301 < features in $C_{p}$ for the larger particles.  Since we are initiating
335 < and observing the melting process itself in these calculation, the
301 > features in $C_{p}$ for the larger particles.  Since the melting process itself is being initiated and observed in these calculations, the
302   smaller particles melt more rapidly, and thus exhibit sharper features
303   in $C_{p}$.  Indeed, longer trajectories do show that $T_{m}$ occurs
304   at lower temperatures and with sharper transitions in larger particles
# Line 354 | Line 320 | observed in the 40 ps simulations.
320  
321  
322  
323 < \subsection{BREATHING MODE DYNAMICS}
323 > \subsection{Breathing Mode Dynamics}
324  
325   Fig.\ref{fig:VolTime} shows representative samples of the volume
326   vs. time traces for the 20 \AA\ and 35 \AA\ particles at a number of
327 < different temperatures.  We can clearly see that the period of the
327 > different temperatures.  It can clearly be seen that the period of the
328   breathing mode is dependent on temperature, and that the coherent
329   oscillations of the particles' volume are destroyed after only a few
330   ps in the smaller particles, while they live on for 10-20 ps in the
# Line 394 | Line 360 | trace.
360   \begin{figure}[htbp]
361          \centering
362                  \includegraphics[height=3in]{images/volcorr.pdf}
363 <        \caption{Volume fluctuation autocorrelation functions for the 20 \AA\
364 <                and 35 \AA\ particles at a range of temperatures.  Successive
363 >        \caption{Volume fluctuation autocorrelation functions for the 20 \AA\ (lower panel)
364 >                and 35 \AA\ (upper panel) particles at a range of temperatures.  Successive
365                  temperatures have been translated upwards by one unit.  Note the beat
366                  pattern in the 20 \AA\ particle at 800K.}
367          \label{fig:volcorr}
# Line 404 | Line 370 | analyzed (Eq. (\ref{eq:volspect})), the samples which
370  
371   When the power spectrum of the volume autocorrelation functions are
372   analyzed (Eq. (\ref{eq:volspect})), the samples which exhibit beat
373 < patterns do indeed show multiple peaks in the power spectrum.  We plot
374 < the period corresponding to the two lowest frequency peaks in
409 < Fig. \ref{fig:Period}.  The smaller particles have the most evident
373 > patterns do indeed show multiple peaks in the power spectrum. The period corresponding to the two lowest frequency peaks is plotted in
374 > Fig. \ref{fig:Period}.  Smaller particles have the most evident
375   splitting, particularly as the temperature rises above the melting
376   points for these particles.
377  
# Line 420 | Line 385 | points for these particles.
385   \end{figure}
386  
387  
388 < \section{DISCUSSION}
388 > \section{Discussion}
389   \label{bulkmod:sec:discussion}
390  
391   Lamb's classical theory of elastic spheres~\cite{Lamb1882} provides
# Line 455 | Line 420 | propagation of the wave relative to the crystal plane.
420  
421   In crystalline materials, the speeds depend on the direction of
422   propagation of the wave relative to the crystal plane.\cite{Kittel:1996fk}
423 < For the remainder of our analysis, we assume the nanoparticles are
423 > For the remainder of our analysis, it is assumed that the nanoparticles are
424   isotropic (which should be valid only above the melting transition).
425   A more detailed analysis of the lower temperature particles would take
426   the crystal lattice into account.
427  
428 < If we use the experimental values for the elastic constants for 30
428 > Using the experimental values for the elastic constants for 30
429   \AA\ Au particles at 300K, the low-frequency longitudinal (breathing)
430   mode should have a period of 2.19 ps while the low-frequency
431   transverse (toroidal) mode should have a period of 2.11 ps.  Although
432 < the actual calculated frequencies in our simulations are off of these
432 > the actual calculated frequencies in the simulations are off of these
433   values, the difference in the periods (0.08 ps) is approximately half
434   of the splitting observed room-temperature simulations.  This,
435   therefore, may be an explanation for the low-temperature splitting in
# Line 477 | Line 442 | elastic spheres.\cite{Simon2001}
442   Lamb mode using the classical Lamb theory results for isotropic
443   elastic spheres.\cite{Simon2001}
444  
445 < \subsection{MELTED AND PARTIALLY-MELTED PARTICLES}
445 > \subsection{Melted and Partially-Melted Particles}
446  
447   Hartland {\it et al.} have extended the Lamb analysis to include
448   surface stress ($\gamma$).\cite{HartlandG.V._jp0276092} In this case, the

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