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# Line 139 | Line 139 | + s^\prime(r_{ij})w^\prime({\bf r}_{ij},{\bf \Omega}_i
139   \frac{\nu_0}{2}[s(r_{ij})w({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j)
140   + s^\prime(r_{ij})w^\prime({\bf r}_{ij},{\bf \Omega}_i,{\bf
141   \Omega}_j)]\ .
142 + \label{stickyfunction}
143   \end{equation}
144   Here, $\nu_0$ is a strength parameter for the sticky potential, and
145   $s$ and $s^\prime$ are cubic switching functions which turn off the
# Line 151 | Line 152 | w^\prime({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j) =
152   while the $w^\prime$ function counters the normal aligned and
153   anti-aligned structures favored by point dipoles:
154   \begin{equation}
155 < w^\prime({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j) = (\cos\theta_{ij}-0.6)^2(\cos\theta_{ij}+0.8)^2-w^0,
155 > w^\prime({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j) = (\cos\theta_{ij}-0.6)^2(\cos\theta_{ij}+0.8)^2-w^\circ,
156   \end{equation}
157   It should be noted that $w$ is proportional to the sum of the $Y_3^2$
158   and $Y_3^{-2}$ spherical harmonics (a linear combination which
# Line 208 | Line 209 | cubic switching function at a cutoff radius.  Under th
209  
210   Long-range dipole-dipole interactions were accounted for in this study
211   by using either the reaction field method or by resorting to a simple
212 < cubic switching function at a cutoff radius.  Under the first method,
213 < the magnitude of the reaction field acting on dipole $i$ is
212 > cubic switching function at a cutoff radius.  The reaction field
213 > method was actually first used in Monte Carlo simulations of liquid
214 > water.\cite{Barker73} Under this method, the magnitude of the reaction
215 > field acting on dipole $i$ is
216   \begin{equation}
217   \mathcal{E}_{i} = \frac{2(\varepsilon_{s} - 1)}{2\varepsilon_{s} + 1}
218 < \frac{1}{r_{c}^{3}} \sum_{j\in{\mathcal{R}}} {\bf \mu}_{j} f(r_{ij})\  ,
218 > \frac{1}{r_{c}^{3}} \sum_{j\in{\mathcal{R}}} {\bf \mu}_{j} f(r_{ij}),
219   \label{rfequation}
220   \end{equation}
221   where $\mathcal{R}$ is the cavity defined by the cutoff radius
222   ($r_{c}$), $\varepsilon_{s}$ is the dielectric constant imposed on the
223   system (80 in the case of liquid water), ${\bf \mu}_{j}$ is the dipole
224 < moment vector of particle $j$ and $f(r_{ij})$ is a cubic switching
224 > moment vector of particle $j$, and $f(r_{ij})$ is a cubic switching
225   function.\cite{AllenTildesley} The reaction field contribution to the
226   total energy by particle $i$ is given by $-\frac{1}{2}{\bf
227   \mu}_{i}\cdot\mathcal{E}_{i}$ and the torque on dipole $i$ by ${\bf
# Line 232 | Line 235 | at the cutoff radius) and as a result we have two repa
235  
236   We have also performed a companion set of simulations {\it without} a
237   surrounding dielectric (i.e. using a simple cubic switching function
238 < at the cutoff radius) and as a result we have two reparamaterizations
239 < of SSD which could be used either with or without the Reaction Field
238 > at the cutoff radius), and as a result we have two reparamaterizations
239 > of SSD which could be used either with or without the reaction field
240   turned on.
241  
242   Simulations to obtain the preferred density were performed in the
# Line 248 | Line 251 | symplectic splitting method proposed by Dullweber {\it
251   need to be considered.
252  
253   Integration of the equations of motion was carried out using the
254 < symplectic splitting method proposed by Dullweber {\it et
255 < al.}\cite{Dullweber1997} Our reason for selecting this integrator
256 < centers on poor energy conservation of rigid body dynamics using
257 < traditional quaternion integration.\cite{Evans77,Evans77b} While quaternions
258 < may work well for orientational motion under NVT or NPT integrators,
259 < our limits on energy drift in the microcanonical ensemble were quite
260 < strict, and the drift under quaternions was substantially greater than
261 < in the symplectic splitting method.  This steady drift in the total
259 < energy has also been observed by Kol {\it et al.}\cite{Laird97}
254 > symplectic splitting method proposed by Dullweber, Leimkuhler, and
255 > McLachlan (DLM).\cite{Dullweber1997} Our reason for selecting this
256 > integrator centers on poor energy conservation of rigid body dynamics
257 > using traditional quaternion integration.\cite{Evans77,Evans77b} In
258 > typical microcanonical ensemble simulations, the energy drift when
259 > using quaternions was substantially greater than when using the DLM
260 > method (fig. \ref{timestep}).  This steady drift in the total energy
261 > has also been observed by Kol {\it et al.}\cite{Laird97}
262  
263   The key difference in the integration method proposed by Dullweber
264   \emph{et al.} is that the entire rotation matrix is propagated from
# Line 265 | Line 267 | The symplectic splitting method allows for Verlet styl
267   rotation matrix into quaternions for storage purposes makes trajectory
268   data quite compact.
269  
270 < The symplectic splitting method allows for Verlet style integration of
271 < both translational and orientational motion of rigid bodies. In this
270 > The DML method allows for Verlet style integration of both
271 > translational and orientational motion of rigid bodies. In this
272   integration method, the orientational propagation involves a sequence
273   of matrix evaluations to update the rotation
274   matrix.\cite{Dullweber1997} These matrix rotations are more costly
275   than the simpler arithmetic quaternion propagation. With the same time
276   step, a 1000 SSD particle simulation shows an average 7\% increase in
277 < computation time using the symplectic step method in place of
278 < quaternions. The additional expense per step is justified when one
279 < considers the ability to use time steps that are nearly twice as large
280 < under symplectic splitting than would be usable under quaternion
281 < dynamics.  The energy conservation of the two methods using a number
282 < of different time steps is illustrated in figure
277 > computation time using the DML method in place of quaternions. The
278 > additional expense per step is justified when one considers the
279 > ability to use time steps that are nearly twice as large under DML
280 > than would be usable under quaternion dynamics.  The energy
281 > conservation of the two methods using a number of different time steps
282 > is illustrated in figure
283   \ref{timestep}.
284  
285   \begin{figure}
# Line 285 | Line 287 | the symplectic step method proposed by Dullweber \emph
287   \epsfxsize=6in
288   \epsfbox{timeStep.epsi}
289   \caption{Energy conservation using both quaternion based integration and
290 < the symplectic step method proposed by Dullweber \emph{et al.} with
291 < increasing time step. The larger time step plots are shifted from the
292 < true energy baseline (that of $\Delta t$ = 0.1 fs) for clarity.}
290 > the symplectic splitting method proposed by Dullweber \emph{et al.}
291 > with increasing time step. The larger time step plots are shifted from
292 > the true energy baseline (that of $\Delta t$ = 0.1 fs) for clarity.}
293   \label{timestep}
294   \end{center}
295   \end{figure}
296  
297   In figure \ref{timestep}, the resulting energy drift at various time
298 < steps for both the symplectic step and quaternion integration schemes
299 < is compared.  All of the 1000 SSD particle simulations started with
300 < the same configuration, and the only difference was the method used to
301 < handle orientational motion. At time steps of 0.1 and 0.5 fs, both
302 < methods for propagating the orientational degrees of freedom conserve
303 < energy fairly well, with the quaternion method showing a slight energy
304 < drift over time in the 0.5 fs time step simulation. At time steps of 1
305 < and 2 fs, the energy conservation benefits of the symplectic step
306 < method are clearly demonstrated. Thus, while maintaining the same
307 < degree of energy conservation, one can take considerably longer time
308 < steps, leading to an overall reduction in computation time.
298 > steps for both the DML and quaternion integration schemes is compared.
299 > All of the 1000 SSD particle simulations started with the same
300 > configuration, and the only difference was the method used to handle
301 > orientational motion. At time steps of 0.1 and 0.5 fs, both methods
302 > for propagating the orientational degrees of freedom conserve energy
303 > fairly well, with the quaternion method showing a slight energy drift
304 > over time in the 0.5 fs time step simulation. At time steps of 1 and 2
305 > fs, the energy conservation benefits of the DML method are clearly
306 > demonstrated. Thus, while maintaining the same degree of energy
307 > conservation, one can take considerably longer time steps, leading to
308 > an overall reduction in computation time.
309  
310 < Energy drift in the symplectic step simulations was unnoticeable for
311 < time steps up to 3 fs. A slight energy drift on the
312 < order of 0.012 kcal/mol per nanosecond was observed at a time step of
313 < 4 fs, and as expected, this drift increases dramatically
314 < with increasing time step. To insure accuracy in our microcanonical
315 < simulations, time steps were set at 2 fs and kept at this value for
316 < constant pressure simulations as well.
310 > Energy drift in the simulations using DML integration was unnoticeable
311 > for time steps up to 3 fs. A slight energy drift on the order of 0.012
312 > kcal/mol per nanosecond was observed at a time step of 4 fs, and as
313 > expected, this drift increases dramatically with increasing time
314 > step. To insure accuracy in our microcanonical simulations, time steps
315 > were set at 2 fs and kept at this value for constant pressure
316 > simulations as well.
317  
318   Proton-disordered ice crystals in both the $I_h$ and $I_c$ lattices
319   were generated as starting points for all simulations. The $I_h$
# Line 428 | Line 430 | was what lead Ichiye {\it et al.} to recently reparame
430   simulations.\cite{Clancy94,Jorgensen98b} However, even without the
431   reaction field, the density around 300 K is still significantly lower
432   than experiment and comparable water models. This anomalous behavior
433 < was what lead Ichiye {\it et al.} to recently reparameterize
433 > was what lead Tan {\it et al.} to recently reparameterize
434   SSD.\cite{Ichiye03} Throughout the remainder of the paper our
435   reparamaterizations of SSD will be compared with the newer SSD1 model.
436  
# Line 446 | Line 448 | results.\cite{Gillen72,Mills73,Clancy94,Jorgensen01}
448   mean-square displacement as a function of time. The averaged results
449   from five sets of NVE simulations are displayed in figure
450   \ref{diffuse}, alongside experimental, SPC/E, and TIP5P
451 < results.\cite{Gillen72,Mills73,Clancy94,Jorgensen01}
451 > results.\cite{Gillen72,Holz00,Clancy94,Jorgensen01}
452  
453   \begin{figure}
454   \begin{center}
# Line 454 | Line 456 | and Experimental data [Refs. \citen{Gillen72} and \cit
456   \epsfbox{betterDiffuse.epsi}
457   \caption{Average self-diffusion constant as a function of temperature for
458   SSD, SPC/E [Ref. \citen{Clancy94}], TIP5P [Ref. \citen{Jorgensen01}],
459 < and Experimental data [Refs. \citen{Gillen72} and \citen{Mills73}]. Of
459 > and Experimental data [Refs. \citen{Gillen72} and \citen{Holz00}]. Of
460   the three water models shown, SSD has the least deviation from the
461   experimental values. The rapidly increasing diffusion constants for
462   TIP5P and SSD correspond to significant decrease in density at the
# Line 591 | Line 593 | The parameters available for tuning include the $\sigm
593   important properties. In this case, it would be ideal to correct the
594   densities while maintaining the accurate transport behavior.
595  
596 < The parameters available for tuning include the $\sigma$ and $\epsilon$
597 < Lennard-Jones parameters, the dipole strength ($\mu$), and the sticky
598 < attractive and dipole repulsive terms with their respective
599 < cutoffs. To alter the attractive and repulsive terms of the sticky
600 < potential independently, it is necessary to separate the terms as
601 < follows:
602 < \begin{equation}
601 < u_{ij}^{sp}
602 < ({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j) =
603 < \frac{\nu_0}{2}[s(r_{ij})w({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j)] + \frac{\nu_0^\prime}{2} [s^\prime(r_{ij})w^\prime({\bf r}_{ij},{\bf \Omega}_i,{\bf \Omega}_j)],
604 < \end{equation}
605 < where $\nu_0$ scales the strength of the tetrahedral attraction and
606 < $\nu_0^\prime$ scales the dipole repulsion term independently. The
607 < separation was performed for purposes of the reparameterization, but
608 < the final parameters were adjusted so that it is not necessary to
609 < separate the terms when implementing the adjusted water
610 < potentials. The results of the reparameterizations are shown in table
611 < \ref{params}. Note that the tetrahedral attractive and dipolar
612 < repulsive terms do not share the same lower cutoff ($r_l$) in the
613 < newly parameterized potentials.  We are calling these
614 < reparameterizations the Soft Sticky Dipole / Reaction Field
596 > The parameters available for tuning include the $\sigma$ and
597 > $\epsilon$ Lennard-Jones parameters, the dipole strength ($\mu$), the
598 > strength of the sticky potential ($\nu_0$), and the sticky attractive
599 > and dipole repulsive cubic switching function cutoffs ($r_l$, $r_u$
600 > and $r_l^\prime$, $r_u^\prime$ respectively). The results of the
601 > reparameterizations are shown in table \ref{params}. We are calling
602 > these reparameterizations the Soft Sticky Dipole / Reaction Field
603   (SSD/RF - for use with a reaction field) and Soft Sticky Dipole
604 < Enhanced (SSD/E - an attempt to improve the liquid structure in
604 > Extended (SSD/E - an attempt to improve the liquid structure in
605   simulations without a long-range correction).
606  
607   \begin{table}
# Line 628 | Line 616 | simulations without a long-range correction).
616   \ \ \ $\epsilon$ (kcal/mol) & 0.152 & 0.152 & 0.152 & 0.152\\
617   \ \ \ $\mu$ (D) & 2.35 & 2.35 & 2.42 & 2.48\\
618   \ \ \ $\nu_0$ (kcal/mol) & 3.7284 & 3.6613 & 3.90 & 3.90\\
619 + \ \ \ $\omega^\circ$ & 0.07715 & 0.07715 & 0.07715 & 0.07715\\
620   \ \ \ $r_l$ (\AA) & 2.75 & 2.75 & 2.40 & 2.40\\
621   \ \ \ $r_u$ (\AA) & 3.35 & 3.35 & 3.80 & 3.80\\
633 \ \ \ $\nu_0^\prime$ (kcal/mol) & 3.7284 & 3.6613 & 3.90 & 3.90\\
622   \ \ \ $r_l^\prime$ (\AA) & 2.75 & 2.75 & 2.75 & 2.75\\
623   \ \ \ $r_u^\prime$ (\AA) & 4.00 & 4.00 & 3.35 & 3.35\\
624   \end{tabular}
# Line 654 | Line 642 | and broadened the first peak of SSD/E and SSD/RF.}
642   \begin{figure}
643   \begin{center}
644   \epsfxsize=6in
645 < \epsfbox{dualsticky.ps}
645 > \epsfbox{dualsticky_bw.eps}
646   \caption{Isosurfaces of the sticky potential for SSD1 (left) and SSD/E \&
647   SSD/RF (right). Light areas correspond to the tetrahedral attractive
648   component, and darker areas correspond to the dipolar repulsive
# Line 806 | Line 794 | K, shown by SSD and SSD1 respectively.
794   \begin{center}
795   \epsfxsize=6in
796   \epsfbox{ssdeDiffuse.epsi}
797 < \caption{Plots of the diffusion constants calculated from SSD/E and SSD1,
798 < both without a reaction field, along with experimental results
799 < [Refs. \citen{Gillen72} and \citen{Mills73}]. The NVE calculations were
800 < performed at the average densities observed in the 1 atm NPT
801 < simulations for the respective models. SSD/E is slightly more fluid
802 < than experiment at all of the temperatures, but it is closer than SSD1
803 < without a long-range correction.}
797 > \caption{The diffusion constants calculated from SSD/E and SSD1,
798 > both without a reaction field, along with experimental results
799 > [Refs. \citen{Gillen72} and \citen{Holz00}]. The NVE calculations
800 > were performed at the average densities observed in the 1 atm NPT
801 > simulations for the respective models. SSD/E is slightly more mobile
802 > than experiment at all of the temperatures, but it is closer to
803 > experiment at biologically relevant temperatures than SSD1 without a
804 > long-range correction.}
805   \label{ssdediffuse}
806   \end{center}
807   \end{figure}
# Line 823 | Line 812 | without an active reaction field, both at the densitie
812   the densities, it is important that the excellent diffusive behavior
813   of SSD be maintained or improved. Figure \ref{ssdediffuse} compares
814   the temperature dependence of the diffusion constant of SSD/E to SSD1
815 < without an active reaction field, both at the densities calculated at
816 < 1 atm and at the experimentally calculated densities for super-cooled
817 < and liquid water. The diffusion constant for SSD/E is consistently
818 < higher than experiment, while SSD1 remains lower than experiment until
819 < relatively high temperatures (greater than 330 K). Both models follow
820 < the shape of the experimental curve well below 300 K but tend to
821 < diffuse too rapidly at higher temperatures, something that is
833 < especially apparent with SSD1.  This increasing diffusion relative to
815 > without an active reaction field at the densities calculated from
816 > their respective NPT simulations at 1 atm. The diffusion constant for
817 > SSD/E is consistently higher than experiment, while SSD1 remains lower
818 > than experiment until relatively high temperatures (around 360
819 > K). Both models follow the shape of the experimental curve well below
820 > 300 K but tend to diffuse too rapidly at higher temperatures, as seen
821 > in SSD1's crossing above 360 K.  This increasing diffusion relative to
822   the experimental values is caused by the rapidly decreasing system
823 < density with increasing temperature.  The densities of SSD1 decay more
824 < rapidly with temperature than do those of SSD/E, leading to more
825 < visible deviation from the experimental diffusion trend.  Thus, the
823 > density with increasing temperature.  Both SSD1 and SSD/E show this
824 > deviation in particle mobility, but this trend has different
825 > implications on the diffusive behavior of the models.  While SSD1
826 > shows more experimentally accurate diffusive behavior in the high
827 > temperature regimes, SSD/E shows more accurate behavior in the
828 > supercooled and biologically relevant temperature ranges.  Thus, the
829   changes made to improve the liquid structure may have had an adverse
830   affect on the density maximum, but they improve the transport behavior
831 < of SSD/E relative to SSD1.
831 > of SSD/E relative to SSD1 under the most commonly simulated
832 > conditions.
833  
834   \begin{figure}
835   \begin{center}
836   \epsfxsize=6in
837   \epsfbox{ssdrfDiffuse.epsi}
838 < \caption{Plots of the diffusion constants calculated from SSD/RF and SSD1,
838 > \caption{The diffusion constants calculated from SSD/RF and SSD1,
839   both with an active reaction field, along with experimental results
840 < [Refs. \citen{Gillen72} and \citen{Mills73}]. The NVE calculations
840 > [Refs. \citen{Gillen72} and \citen{Holz00}]. The NVE calculations
841   were performed at the average densities observed in the 1 atm NPT
842   simulations for both of the models. Note how accurately SSD/RF
843   simulates the diffusion of water throughout this temperature
844   range. The more rapidly increasing diffusion constants at high
845 < temperatures for both models is attributed to the significantly lower
846 < densities than observed in experiment.}
845 > temperatures for both models is attributed to lower calculated
846 > densities than those observed in experiment.}
847   \label{ssdrfdiffuse}
848   \end{center}
849   \end{figure}
# Line 859 | Line 851 | throughout the temperature range shown and with only a
851   In figure \ref{ssdrfdiffuse}, the diffusion constants for SSD/RF are
852   compared to SSD1 with an active reaction field. Note that SSD/RF
853   tracks the experimental results quantitatively, identical within error
854 < throughout the temperature range shown and with only a slight
855 < increasing trend at higher temperatures. SSD1 tends to diffuse more
856 < slowly at low temperatures and deviates to diffuse too rapidly at
854 > throughout most of the temperature range shown and exhibiting only a
855 > slight increasing trend at higher temperatures. SSD1 tends to diffuse
856 > more slowly at low temperatures and deviates to diffuse too rapidly at
857   temperatures greater than 330 K.  As stated above, this deviation away
858   from the ideal trend is due to a rapid decrease in density at higher
859   temperatures. SSD/RF does not suffer from this problem as much as SSD1
# Line 869 | Line 861 | reparameterization when using an altered long-range co
861   values. These results again emphasize the importance of careful
862   reparameterization when using an altered long-range correction.
863  
864 + \begin{table}
865 + \begin{center}
866 + \caption{Calculated and experimental properties of the single point waters and liquid water at 298 K and 1 atm. (a) Ref. [\citen{Mills73}]. (b) Calculated by integrating the data in ref. \citen{Head-Gordon00_1}. (c) Calculated by integrating the data in ref. \citen{Soper86}. (d) Calculated for 298 K from data in ref. [\citen{Eisenberg69}]. (e) Calculated for 298 K from data in ref. \citen{Krynicki66}.}
867 + \begin{tabular}{ l  c  c  c  c  c }
868 + \hline \\[-3mm]
869 + \ \ \ \ \ \  & \ \ \ SSD1 \ \ \ & \ SSD/E \ \ \ & \ SSD1 (RF) \ \
870 + \ & \ SSD/RF \ \ \ & \ Expt. \\
871 + \hline \\[-3mm]
872 + \ \ \ $\rho$ (g/cm$^3$) & 0.999 $\pm$0.001 & 0.996 $\pm$0.001 & 0.972 $\pm$0.002 & 0.997 $\pm$0.001 & 0.997 \\
873 + \ \ \ $C_p$ (cal/mol K) & 28.80 $\pm$0.11 & 25.45 $\pm$0.09 & 28.28 $\pm$0.06 & 23.83 $\pm$0.16 & 17.98 \\
874 + \ \ \ $D$ ($10^{-5}$ cm$^2$/s) & 1.78 $\pm$0.07 & 2.51 $\pm$0.18 & 2.00 $\pm$0.17 & 2.32 $\pm$0.06 & 2.299$^\text{a}$ \\
875 + \ \ \ Coordination Number & 3.9 & 4.3 & 3.8 & 4.4 & 4.7$^\text{b}$ \\
876 + \ \ \ H-bonds per particle & 3.7 & 3.6 & 3.7 & 3.7 & 3.5$^\text{c}$ \\
877 + \ \ \ $\tau_1$ (ps) & 10.9 $\pm$0.6 & 7.3 $\pm$0.4 & 7.5 $\pm$0.7 & 7.2 $\pm$0.4 & 5.7$^\text{d}$ \\
878 + \ \ \ $\tau_2$ (ps) & 4.7 $\pm$0.4 & 3.1 $\pm$0.2 & 3.5 $\pm$0.3 & 3.2 $\pm$0.2 & 2.3$^\text{e}$ \\
879 + \end{tabular}
880 + \label{liquidproperties}
881 + \end{center}
882 + \end{table}
883 +
884 + Table \ref{liquidproperties} gives a synopsis of the liquid state
885 + properties of the water models compared in this study along with the
886 + experimental values for liquid water at ambient conditions. The
887 + coordination number ($N_C$) and hydrogen bonds per particle ($N_H$)
888 + were calculated by integrating the following relations:
889 + \begin{equation}
890 + N_C = 4\pi\rho_{\text{OO}}\int_{0}^{a}r^2\text{g}_{\text{OO}}(r)dr,
891 + \end{equation}
892 + \begin{equation}
893 + N_H = 4\pi\rho_{\text{OH}}\int_{0}^{b}r^2\text{g}_{\text{OH}}(r)dr,
894 + \end{equation}
895 + where $\rho$ is the number density of the specified pair interactions,
896 + $a$ and $b$ are the radial locations of the minima following the first
897 + solvation shell peak in g$_\text{OO}(r)$ or g$_\text{OH}(r)$
898 + respectively. The number of hydrogen bonds stays relatively constant
899 + across all of the models, but the coordination numbers of SSD/E and
900 + SSD/RF show an improvement over SSD1. This improvement is primarily
901 + due to the widening of the first solvation shell peak, allowing the
902 + first minima to push outward. Comparing the coordination number with
903 + the number of hydrogen bonds can lead to more insight into the
904 + structural character of the liquid.  Because of the near identical
905 + values for SSD1, it appears to be a little too exclusive, in that all
906 + molecules in the first solvation shell are involved in forming ideal
907 + hydrogen bonds.  The differing numbers for the newly parameterized
908 + models indicate the allowance of more fluid configurations in addition
909 + to the formation of an acceptable number of ideal hydrogen bonds.
910 +
911 + The time constants for the self orientational autocorrelation function
912 + are also displayed in Table \ref{liquidproperties}. The dipolar
913 + orientational time correlation function ($\Gamma_{l}$) is described
914 + by:
915 + \begin{equation}
916 + \Gamma_{l}(t) = \langle P_l[\mathbf{u}_j(0)\cdot\mathbf{u}_j(t)]\rangle,
917 + \end{equation}
918 + where $P_l$ is a Legendre polynomial of order $l$ and $\mathbf{u}_j$
919 + is the unit vector of the particle dipole.\cite{Rahman71} From these
920 + correlation functions, the orientational relaxation time of the dipole
921 + vector can be calculated from an exponential fit in the long-time
922 + regime ($t > \tau_l$).\cite{Rothschild84} Calculation of these
923 + time constants were averaged from five detailed NVE simulations
924 + performed at the STP density for each of the respective models. It
925 + should be noted that the commonly cited value for $\tau_2$ of 1.9 ps
926 + was determined from the NMR data in reference \citen{Krynicki66} at a
927 + temperature near 34$^\circ$C.\cite{Rahman71} Because of the strong
928 + temperature dependence of $\tau_2$, it is necessary to recalculate it
929 + at 298 K to make proper comparisons. The value shown in Table
930 + \ref{liquidproperties} was calculated from the same NMR data in the
931 + fashion described in reference \citen{Krynicki66}. Similarly, $\tau_1$
932 + was recomputed for 298 K from the data in ref \citen{Eisenberg69}.
933 + Again, SSD/E and SSD/RF show improved behavior over SSD1, both with
934 + and without an active reaction field. Turning on the reaction field
935 + leads to much improved time constants for SSD1; however, these results
936 + also include a corresponding decrease in system density. Numbers
937 + published from the original SSD dynamics studies are shorter than the
938 + values observed here, and this difference can be attributed to the use
939 + of the Ewald sum technique versus a reaction field.\cite{Ichiye99}
940 +
941   \subsection{Additional Observations}
942  
943   \begin{figure}
944   \begin{center}
945   \epsfxsize=6in
946 < \epsfbox{povIce.ps}
946 > \epsfbox{icei_bw.eps}
947   \caption{A water lattice built from the crystal structure assumed by
948   SSD/E when undergoing an extremely restricted temperature NPT
949   simulation. This form of ice is referred to as ice-{\it i} to
# Line 954 | Line 1023 | super-cooled liquid regimes.
1023   significantly lower than the densities obtained from other water
1024   models (and experiment). Analysis of self-diffusion showed SSD to
1025   capture the transport properties of water well in both the liquid and
1026 < super-cooled liquid regimes.
1026 > supercooled liquid regimes.
1027  
1028   In order to correct the density behavior, the original SSD model was
1029   reparameterized for use both with and without a reaction field (SSD/RF
# Line 970 | Line 1039 | effectively simulations of super-cooled or metastable
1039   The existence of a novel low-density ice structure that is preferred
1040   by the SSD family of water models is somewhat troubling, since liquid
1041   simulations on this family of water models at room temperature are
1042 < effectively simulations of super-cooled or metastable liquids.  One
1043 < way to de-stabilize this unphysical ice structure would be to make the
1042 > effectively simulations of supercooled or metastable liquids.  One
1043 > way to destabilize this unphysical ice structure would be to make the
1044   range of angles preferred by the attractive part of the sticky
1045   potential much narrower.  This would require extensive
1046   reparameterization to maintain the same level of agreement with the

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