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# Line 90 | Line 90 | model.\cite{Ichiye96,Ichiye96b,Ichiye99,Ichiye03} The
90   One recently developed model that largely succeeds in retaining the
91   accuracy of bulk properties while greatly reducing the computational
92   cost is the Soft Sticky Dipole (SSD) water
93 < model.\cite{Ichiye96,Ichiye96b,Ichiye99,Ichiye03} The SSD model was
94 < developed by Ichiye \emph{et al.} as a modified form of the
93 > model.\cite{Ichiye96,Ichiye96b,Ichiye99,Ichiye03} The SSD model
94 > was developed by Ichiye \emph{et al.} as a modified form of the
95   hard-sphere water model proposed by Bratko, Blum, and
96 < Luzar.\cite{Bratko85,Bratko95} SSD is a {\it single point} model which
97 < has an interaction site that is both a point dipole along with a
96 > Luzar.\cite{Bratko85,Bratko95} SSD is a {\it single point} model
97 > which has an interaction site that is both a point dipole along with a
98   Lennard-Jones core.  However, since the normal aligned and
99   anti-aligned geometries favored by point dipoles are poor mimics of
100   local structure in liquid water, a short ranged ``sticky'' potential
101   is also added.  The sticky potential directs the molecules to assume
102 < the proper hydrogen bond orientation in the first solvation
103 < shell.  
102 > the proper hydrogen bond orientation in the first solvation shell.
103  
104   The interaction between two SSD water molecules \emph{i} and \emph{j}
105   is given by the potential
# Line 169 | Line 168 | properties.  Indeed, SSD maintains reasonable agreemen
168   SSD decreased computer time by a factor of 6-7 compared to other
169   models.\cite{Ichiye96} What is most impressive is that this savings
170   did not come at the expense of accurate depiction of the liquid state
171 < properties.  Indeed, SSD maintains reasonable agreement with the Soper
172 < data for the structural features of liquid
171 > properties.  Indeed, SSD maintains reasonable agreement with the
172 > Soper data for the structural features of liquid
173   water.\cite{Soper86,Ichiye96} Additionally, the dynamical properties
174   exhibited by SSD agree with experiment better than those of more
175   computationally expensive models (like TIP3P and
# Line 178 | Line 177 | One feature of the SSD model is that it was parameteri
177   of solvent properties makes SSD a very attractive model for the
178   simulation of large scale biochemical simulations.
179  
180 < One feature of the SSD model is that it was parameterized for use with
181 < the Ewald sum to handle long-range interactions.  This would normally
182 < be the best way of handling long-range interactions in systems that
183 < contain other point charges.  However, our group has recently become
184 < interested in systems with point dipoles as mimics for neutral, but
185 < polarized regions on molecules (e.g. the zwitterionic head group
186 < regions of phospholipids).  If the system of interest does not contain
187 < point charges, the Ewald sum and even particle-mesh Ewald become
188 < computational bottlenecks.  Their respective ideal $N^\frac{3}{2}$ and
189 < $N\log N$ calculation scaling orders for $N$ particles can become
190 < prohibitive when $N$ becomes large.\cite{Darden99} In applying this
191 < water model in these types of systems, it would be useful to know its
192 < properties and behavior under the more computationally efficient
193 < reaction field (RF) technique, or even with a simple cutoff. This
194 < study addresses these issues by looking at the structural and
195 < transport behavior of SSD over a variety of temperatures with the
196 < purpose of utilizing the RF correction technique.  We then suggest
197 < modifications to the parameters that result in more realistic bulk
198 < phase behavior.  It should be noted that in a recent publication, some
199 < of the original investigators of the SSD water model have suggested
200 < adjustments to the SSD water model to address abnormal density
201 < behavior (also observed here), calling the corrected model
202 < SSD1.\cite{Ichiye03} In what follows, we compare our
203 < reparamaterization of SSD with both the original SSD and SSD1 models
204 < with the goal of improving the bulk phase behavior of an SSD-derived
205 < model in simulations utilizing the Reaction Field.
180 > One feature of the SSD model is that it was parameterized for
181 > use with the Ewald sum to handle long-range interactions.  This would
182 > normally be the best way of handling long-range interactions in
183 > systems that contain other point charges.  However, our group has
184 > recently become interested in systems with point dipoles as mimics for
185 > neutral, but polarized regions on molecules (e.g. the zwitterionic
186 > head group regions of phospholipids).  If the system of interest does
187 > not contain point charges, the Ewald sum and even particle-mesh Ewald
188 > become computational bottlenecks.  Their respective ideal
189 > $N^\frac{3}{2}$ and $N\log N$ calculation scaling orders for $N$
190 > particles can become prohibitive when $N$ becomes
191 > large.\cite{Darden99} In applying this water model in these types of
192 > systems, it would be useful to know its properties and behavior under
193 > the more computationally efficient reaction field (RF) technique, or
194 > even with a simple cutoff. This study addresses these issues by
195 > looking at the structural and transport behavior of SSD over a
196 > variety of temperatures with the purpose of utilizing the RF
197 > correction technique.  We then suggest modifications to the parameters
198 > that result in more realistic bulk phase behavior.  It should be noted
199 > that in a recent publication, some of the original investigators of
200 > the SSD water model have suggested adjustments to the SSD
201 > water model to address abnormal density behavior (also observed here),
202 > calling the corrected model SSD1.\cite{Ichiye03} In what
203 > follows, we compare our reparamaterization of SSD with both the
204 > original SSD and SSD1 models with the goal of improving
205 > the bulk phase behavior of an SSD-derived model in simulations
206 > utilizing the Reaction Field.
207  
208   \section{Methods}
209  
# Line 215 | Line 215 | field acting on dipole $i$ is
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} s(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 $s(r_{ij})$ 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 235 | 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
240 < turned on.
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
240 > field turned on.
241  
242 < Simulations to obtain the preferred density were performed in the
243 < isobaric-isothermal (NPT) ensemble, while all dynamical properties
244 < were obtained from microcanonical (NVE) simulations done at densities
245 < matching the NPT density for a particular target temperature.  The
246 < constant pressure simulations were implemented using an integral
247 < thermostat and barostat as outlined by Hoover.\cite{Hoover85,Hoover86}
248 < All molecules were treated as non-linear rigid bodies. Vibrational
249 < constraints are not necessary in simulations of SSD, because there are
250 < no explicit hydrogen atoms, and thus no molecular vibrational modes
251 < need to be considered.
242 > Simulations to obtain the preferred densities of the models were
243 > performed in the isobaric-isothermal (NPT) ensemble, while all
244 > dynamical properties were obtained from microcanonical (NVE)
245 > simulations done at densities matching the NPT density for a
246 > particular target temperature.  The constant pressure simulations were
247 > implemented using an integral thermostat and barostat as outlined by
248 > Hoover.\cite{Hoover85,Hoover86} All molecules were treated as
249 > non-linear rigid bodies. Vibrational constraints are not necessary in
250 > simulations of SSD, because there are no explicit hydrogen
251 > atoms, and thus no molecular vibrational modes 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
262 < energy has also been observed by Kol {\it et al.}\cite{Laird97}
254 > symplectic splitting method proposed by Dullweber, Leimkuhler, and
255 > McLachlan ({\sc dlm}).\cite{Dullweber1997} Our reason for selecting
256 > this integrator centers on poor energy conservation of rigid body
257 > dynamics using traditional quaternion
258 > integration.\cite{Evans77,Evans77b} In typical microcanonical ensemble
259 > simulations, the energy drift when using quaternions was substantially
260 > greater than when using the {\sc dlm} method (fig. \ref{timestep}).
261 > This steady drift in the total energy has also been observed by Kol
262 > {\it et al.}\cite{Laird97}
263  
264   The key difference in the integration method proposed by Dullweber
265   \emph{et al.} is that the entire rotation matrix is propagated from
# Line 268 | Line 268 | The symplectic splitting method allows for Verlet styl
268   rotation matrix into quaternions for storage purposes makes trajectory
269   data quite compact.
270  
271 < The symplectic splitting method allows for Verlet style integration of
272 < both translational and orientational motion of rigid bodies. In this
271 > The {\sc dlm} method allows for Verlet style integration of both
272 > translational and orientational motion of rigid bodies. In this
273   integration method, the orientational propagation involves a sequence
274   of matrix evaluations to update the rotation
275   matrix.\cite{Dullweber1997} These matrix rotations are more costly
276   than the simpler arithmetic quaternion propagation. With the same time
277 < step, a 1000 SSD particle simulation shows an average 7\% increase in
278 < computation time using the symplectic step method in place of
277 > step, a 1000 SSD particle simulation shows an average 7\%
278 > increase in computation time using the {\sc dlm} method in place of
279   quaternions. The additional expense per step is justified when one
280   considers the ability to use time steps that are nearly twice as large
281 < under symplectic splitting than would be usable under quaternion
282 < dynamics.  The energy conservation of the two methods using a number
283 < of different time steps is illustrated in figure
281 > under {\sc dlm} than would be usable under quaternion dynamics.  The
282 > energy conservation of the two methods using a number of different
283 > time steps is illustrated in figure
284   \ref{timestep}.
285  
286   \begin{figure}
287   \begin{center}
288   \epsfxsize=6in
289   \epsfbox{timeStep.epsi}
290 < \caption{Energy conservation using both quaternion based integration and
291 < the symplectic step method proposed by Dullweber \emph{et al.} with
292 < increasing time step. The larger time step plots are shifted from the
293 < true energy baseline (that of $\Delta t$ = 0.1 fs) for clarity.}
290 > \caption{Energy conservation using both quaternion-based integration and
291 > the {\sc dlm} method with increasing time step. The larger time step plots
292 > are shifted from the true energy baseline (that of $\Delta t$ = 0.1
293 > fs) for clarity.}
294   \label{timestep}
295   \end{center}
296   \end{figure}
297  
298   In figure \ref{timestep}, the resulting energy drift at various time
299 < steps for both the symplectic step and quaternion integration schemes
300 < is compared.  All of the 1000 SSD particle simulations started with
299 > steps for both the {\sc dlm} and quaternion integration schemes is
300 > compared.  All of the 1000 SSD particle simulations started with
301   the same configuration, and the only difference was the method used to
302   handle orientational motion. At time steps of 0.1 and 0.5 fs, both
303   methods for propagating the orientational degrees of freedom conserve
304   energy fairly well, with the quaternion method showing a slight energy
305   drift over time in the 0.5 fs time step simulation. At time steps of 1
306 < and 2 fs, the energy conservation benefits of the symplectic step
307 < method are clearly demonstrated. Thus, while maintaining the same
308 < degree of energy conservation, one can take considerably longer time
309 < steps, leading to an overall reduction in computation time.
306 > and 2 fs, the energy conservation benefits of the {\sc dlm} method are
307 > clearly demonstrated. Thus, while maintaining the same degree of
308 > energy conservation, one can take considerably longer time steps,
309 > leading to an overall reduction in computation time.
310  
311 < Energy drift in the symplectic step simulations was unnoticeable for
312 < time steps up to 3 fs. A slight energy drift on the
311 > Energy drift in the simulations using {\sc dlm} integration was
312 > unnoticeable for time steps up to 3 fs. A slight energy drift on the
313   order of 0.012 kcal/mol per nanosecond was observed at a time step of
314 < 4 fs, and as expected, this drift increases dramatically
315 < with increasing time step. To insure accuracy in our microcanonical
314 > 4 fs, and as expected, this drift increases dramatically with
315 > increasing time step. To insure accuracy in our microcanonical
316   simulations, time steps were set at 2 fs and kept at this value for
317   constant pressure simulations as well.
318  
319   Proton-disordered ice crystals in both the $I_h$ and $I_c$ lattices
320   were generated as starting points for all simulations. The $I_h$
321 < crystals were formed by first arranging the centers of mass of the SSD
322 < particles into a ``hexagonal'' ice lattice of 1024 particles. Because
323 < of the crystal structure of $I_h$ ice, the simulation box assumed an
324 < orthorhombic shape with an edge length ratio of approximately
325 < 1.00$\times$1.06$\times$1.23. The particles were then allowed to
326 < orient freely about fixed positions with angular momenta randomized at
327 < 400 K for varying times. The rotational temperature was then scaled
328 < down in stages to slowly cool the crystals to 25 K. The particles were
329 < then allowed to translate with fixed orientations at a constant
330 < pressure of 1 atm for 50 ps at 25 K. Finally, all constraints were
331 < removed and the ice crystals were allowed to equilibrate for 50 ps at
332 < 25 K and a constant pressure of 1 atm.  This procedure resulted in
333 < structurally stable $I_h$ ice crystals that obey the Bernal-Fowler
321 > crystals were formed by first arranging the centers of mass of the
322 > SSD particles into a ``hexagonal'' ice lattice of 1024
323 > particles. Because of the crystal structure of $I_h$ ice, the
324 > simulation box assumed an orthorhombic shape with an edge length ratio
325 > of approximately 1.00$\times$1.06$\times$1.23. The particles were then
326 > allowed to orient freely about fixed positions with angular momenta
327 > randomized at 400 K for varying times. The rotational temperature was
328 > then scaled down in stages to slowly cool the crystals to 25 K. The
329 > particles were then allowed to translate with fixed orientations at a
330 > constant pressure of 1 atm for 50 ps at 25 K. Finally, all constraints
331 > were removed and the ice crystals were allowed to equilibrate for 50
332 > ps at 25 K and a constant pressure of 1 atm.  This procedure resulted
333 > in structurally stable $I_h$ ice crystals that obey the Bernal-Fowler
334   rules.\cite{Bernal33,Rahman72} This method was also utilized in the
335   making of diamond lattice $I_c$ ice crystals, with each cubic
336   simulation box consisting of either 512 or 1000 particles. Only
# Line 357 | Line 357 | Our initial simulations focused on the original SSD wa
357  
358   \subsection{Density Behavior}
359  
360 < Our initial simulations focused on the original SSD water model, and
361 < an average density versus temperature plot is shown in figure
360 > Our initial simulations focused on the original SSD water model,
361 > and an average density versus temperature plot is shown in figure
362   \ref{dense1}. Note that the density maximum when using a reaction
363   field appears between 255 and 265 K.  There were smaller fluctuations
364   in the density at 260 K than at either 255 or 265, so we report this
# Line 371 | Line 371 | maximum in this same region (between 255 and 260 K).
371   \begin{figure}
372   \begin{center}
373   \epsfxsize=6in
374 < \epsfbox{denseSSD.eps}
374 > \epsfbox{denseSSDnew.eps}
375   \caption{Density versus temperature for TIP4P [Ref. \citen{Jorgensen98b}],
376   TIP3P [Ref. \citen{Jorgensen98b}], SPC/E [Ref. \citen{Clancy94}], SSD
377   without Reaction Field, SSD, and experiment [Ref. \citen{CRC80}]. The
# Line 383 | Line 383 | The density maximum for SSD compares quite favorably t
383   \end{center}
384   \end{figure}
385  
386 < The density maximum for SSD compares quite favorably to other simple
387 < water models. Figure \ref{dense1} also shows calculated densities of
388 < several other models and experiment obtained from other
386 > The density maximum for SSD compares quite favorably to other
387 > simple water models. Figure \ref{dense1} also shows calculated
388 > densities of several other models and experiment obtained from other
389   sources.\cite{Jorgensen98b,Clancy94,CRC80} Of the listed simple water
390 < models, SSD has a temperature closest to the experimentally observed
391 < density maximum. Of the {\it charge-based} models in
390 > models, SSD has a temperature closest to the experimentally
391 > observed density maximum. Of the {\it charge-based} models in
392   Fig. \ref{dense1}, TIP4P has a density maximum behavior most like that
393 < seen in SSD. Though not included in this plot, it is useful
394 < to note that TIP5P has a density maximum nearly identical to the
393 > seen in SSD. Though not included in this plot, it is useful to
394 > note that TIP5P has a density maximum nearly identical to the
395   experimentally measured temperature.
396  
397   It has been observed that liquid state densities in water are
398   dependent on the cutoff radius used both with and without the use of
399   reaction field.\cite{Berendsen98} In order to address the possible
400   effect of cutoff radius, simulations were performed with a dipolar
401 < cutoff radius of 12.0 \AA\ to complement the previous SSD simulations,
402 < all performed with a cutoff of 9.0 \AA. All of the resulting densities
403 < overlapped within error and showed no significant trend toward lower
404 < or higher densities as a function of cutoff radius, for simulations
405 < both with and without reaction field. These results indicate that
406 < there is no major benefit in choosing a longer cutoff radius in
407 < simulations using SSD. This is advantageous in that the use of a
408 < longer cutoff radius results in a significant increase in the time
409 < required to obtain a single trajectory.
401 > cutoff radius of 12.0 \AA\ to complement the previous SSD
402 > simulations, all performed with a cutoff of 9.0 \AA. All of the
403 > resulting densities overlapped within error and showed no significant
404 > trend toward lower or higher densities as a function of cutoff radius,
405 > for simulations both with and without reaction field. These results
406 > indicate that there is no major benefit in choosing a longer cutoff
407 > radius in simulations using SSD. This is advantageous in that
408 > the use of a longer cutoff radius results in a significant increase in
409 > the time required to obtain a single trajectory.
410  
411   The key feature to recognize in figure \ref{dense1} is the density
412   scaling of SSD relative to other common models at any given
413 < temperature. SSD assumes a lower density than any of the other listed
414 < models at the same pressure, behavior which is especially apparent at
415 < temperatures greater than 300 K. Lower than expected densities have
416 < been observed for other systems using a reaction field for long-range
417 < electrostatic interactions, so the most likely reason for the
418 < significantly lower densities seen in these simulations is the
413 > temperature. SSD assumes a lower density than any of the other
414 > listed models at the same pressure, behavior which is especially
415 > apparent at temperatures greater than 300 K. Lower than expected
416 > densities have been observed for other systems using a reaction field
417 > for long-range electrostatic interactions, so the most likely reason
418 > for the significantly lower densities seen in these simulations is the
419   presence of the reaction field.\cite{Berendsen98,Nezbeda02} In order
420   to test the effect of the reaction field on the density of the
421   systems, the simulations were repeated without a reaction field
# Line 431 | Line 431 | was what lead Ichiye {\it et al.} to recently reparame
431   simulations.\cite{Clancy94,Jorgensen98b} However, even without the
432   reaction field, the density around 300 K is still significantly lower
433   than experiment and comparable water models. This anomalous behavior
434 < was what lead Ichiye {\it et al.} to recently reparameterize
434 > was what lead Tan {\it et al.} to recently reparameterize
435   SSD.\cite{Ichiye03} Throughout the remainder of the paper our
436 < reparamaterizations of SSD will be compared with the newer SSD1 model.
436 > reparamaterizations of SSD will be compared with their newer SSD1
437 > model.
438  
439   \subsection{Transport Behavior}
440  
# Line 449 | Line 450 | results.\cite{Gillen72,Mills73,Clancy94,Jorgensen01}
450   mean-square displacement as a function of time. The averaged results
451   from five sets of NVE simulations are displayed in figure
452   \ref{diffuse}, alongside experimental, SPC/E, and TIP5P
453 < results.\cite{Gillen72,Mills73,Clancy94,Jorgensen01}
453 > results.\cite{Gillen72,Holz00,Clancy94,Jorgensen01}
454  
455   \begin{figure}
456   \begin{center}
457   \epsfxsize=6in
458   \epsfbox{betterDiffuse.epsi}
459   \caption{Average self-diffusion constant as a function of temperature for
460 < SSD, SPC/E [Ref. \citen{Clancy94}], TIP5P [Ref. \citen{Jorgensen01}],
461 < and Experimental data [Refs. \citen{Gillen72} and \citen{Mills73}]. Of
462 < the three water models shown, SSD has the least deviation from the
463 < experimental values. The rapidly increasing diffusion constants for
464 < TIP5P and SSD correspond to significant decrease in density at the
465 < higher temperatures.}
460 > SSD, SPC/E [Ref. \citen{Clancy94}], and TIP5P
461 > [Ref. \citen{Jorgensen01}] compared with experimental data
462 > [Refs. \citen{Gillen72} and \citen{Holz00}]. Of the three water models
463 > shown, SSD has the least deviation from the experimental values. The
464 > rapidly increasing diffusion constants for TIP5P and SSD correspond to
465 > significant decreases in density at the higher temperatures.}
466   \label{diffuse}
467   \end{center}
468   \end{figure}
# Line 477 | Line 478 | diffusion coefficients for SSD at experimental densiti
478   This behavior at higher temperatures is not particularly surprising
479   since the densities of both TIP5P and SSD are lower than experimental
480   water densities at higher temperatures.  When calculating the
481 < diffusion coefficients for SSD at experimental densities (instead of
482 < the densities from the NPT simulations), the resulting values fall
483 < more in line with experiment at these temperatures.
481 > diffusion coefficients for SSD at experimental densities
482 > (instead of the densities from the NPT simulations), the resulting
483 > values fall more in line with experiment at these temperatures.
484  
485   \subsection{Structural Changes and Characterization}
486  
# Line 498 | Line 499 | considerably lower than the experimental value.
499   \begin{center}
500   \epsfxsize=6in
501   \epsfbox{corrDiag.eps}
502 < \caption{Two dimensional illustration of angles involved in the
502 < correlations observed in Fig. \ref{contour}.}
502 > \caption{An illustration of angles involved in the correlations observed in Fig. \ref{contour}.}
503   \label{corrAngle}
504   \end{center}
505   \end{figure}
# Line 508 | Line 508 | correlations observed in Fig. \ref{contour}.}
508   \begin{center}
509   \epsfxsize=6in
510   \epsfbox{fullContours.eps}
511 < \caption{Contour plots of 2D angular g($r$)'s for 512 SSD systems at
512 < 100 K (A \& B) and 300 K (C \& D). Contour colors are inverted for
513 < clarity: dark areas signify peaks while light areas signify
514 < depressions. White areas have $g(r)$ values below 0.5 and black
515 < areas have values above 1.5.}
511 > \caption{Contour plots of 2D angular pair correlation functions for
512 > 512 SSD molecules at 100 K (A \& B) and 300 K (C \& D). Dark areas
513 > signify regions of enhanced density while light areas signify
514 > depletion relative to the bulk density. White areas have pair
515 > correlation values below 0.5 and black areas have values above 1.5.}
516   \label{contour}
517   \end{center}
518   \end{figure}
# Line 551 | Line 551 | oxygen-oxygen $g_\mathrm{OO}(r)$.\cite{Ichiye96} At lo
551  
552   This complex interplay between dipole and sticky interactions was
553   remarked upon as a possible reason for the split second peak in the
554 < oxygen-oxygen $g_\mathrm{OO}(r)$.\cite{Ichiye96} At low temperatures,
555 < the second solvation shell peak appears to have two distinct
556 < components that blend together to form one observable peak. At higher
557 < temperatures, this split character alters to show the leading 4 \AA\
558 < peak dominated by equatorial anti-parallel dipole orientations. There
559 < is also a tightly bunched group of axially arranged dipoles that most
560 < likely consist of the smaller fraction of aligned dipole pairs. The
561 < trailing component of the split peak at 5 \AA\ is dominated by aligned
562 < dipoles that assume hydrogen bond arrangements similar to those seen
563 < in the first solvation shell. This evidence indicates that the dipole
564 < pair interaction begins to dominate outside of the range of the
565 < dipolar repulsion term.  The energetically favorable dipole
566 < arrangements populate the region immediately outside this repulsion
567 < region (around 4 \AA), while arrangements that seek to satisfy both
568 < the sticky and dipole forces locate themselves just beyond this
569 < initial buildup (around 5 \AA).
554 > oxygen-oxygen pair correlation function,
555 > $g_\mathrm{OO}(r)$.\cite{Ichiye96} At low temperatures, the second
556 > solvation shell peak appears to have two distinct components that
557 > blend together to form one observable peak. At higher temperatures,
558 > this split character alters to show the leading 4 \AA\ peak dominated
559 > by equatorial anti-parallel dipole orientations. There is also a
560 > tightly bunched group of axially arranged dipoles that most likely
561 > consist of the smaller fraction of aligned dipole pairs. The trailing
562 > component of the split peak at 5 \AA\ is dominated by aligned dipoles
563 > that assume hydrogen bond arrangements similar to those seen in the
564 > first solvation shell. This evidence indicates that the dipole pair
565 > interaction begins to dominate outside of the range of the dipolar
566 > repulsion term.  The energetically favorable dipole arrangements
567 > populate the region immediately outside this repulsion region (around
568 > 4 \AA), while arrangements that seek to satisfy both the sticky and
569 > dipole forces locate themselves just beyond this initial buildup
570 > (around 5 \AA).
571  
572   From these findings, the split second peak is primarily the product of
573   the dipolar repulsion term of the sticky potential. In fact, the inner
# Line 577 | Line 578 | and a density considerably lower than the already low
578   since the second solvation shell would still be shifted too far
579   out. In addition, this would have an even more detrimental effect on
580   the system densities, leading to a liquid with a more open structure
581 < and a density considerably lower than the already low SSD density.  A
582 < better correction would be to include the quadrupole-quadrupole
583 < interactions for the water particles outside of the first solvation
584 < shell, but this would remove the simplicity and speed advantage of
585 < SSD.
581 > and a density considerably lower than the already low SSD
582 > density.  A better correction would be to include the
583 > quadrupole-quadrupole interactions for the water particles outside of
584 > the first solvation shell, but this would remove the simplicity and
585 > speed advantage of SSD.
586  
587   \subsection{Adjusted Potentials: SSD/RF and SSD/E}
588  
# Line 596 | Line 597 | strength of the sticky potential ($\nu_0$), and the st
597  
598   The parameters available for tuning include the $\sigma$ and
599   $\epsilon$ Lennard-Jones parameters, the dipole strength ($\mu$), the
600 < strength of the sticky potential ($\nu_0$), and the sticky attractive
601 < and dipole repulsive cubic switching function cutoffs ($r_l$, $r_u$
602 < and $r_l^\prime$, $r_u^\prime$ respectively). The results of the
603 < reparameterizations are shown in table \ref{params}. We are calling
604 < these reparameterizations the Soft Sticky Dipole / Reaction Field
605 < (SSD/RF - for use with a reaction field) and Soft Sticky Dipole
606 < Extended (SSD/E - an attempt to improve the liquid structure in
607 < simulations without a long-range correction).
600 > strength of the sticky potential ($\nu_0$), and the cutoff distances
601 > for the sticky attractive and dipole repulsive cubic switching
602 > function cutoffs ($r_l$, $r_u$ and $r_l^\prime$, $r_u^\prime$
603 > respectively). The results of the reparameterizations are shown in
604 > table \ref{params}. We are calling these reparameterizations the Soft
605 > Sticky Dipole / Reaction Field (SSD/RF - for use with a reaction
606 > field) and Soft Sticky Dipole Extended (SSD/E - an attempt to improve
607 > the liquid structure in simulations without a long-range correction).
608  
609   \begin{table}
610   \begin{center}
# Line 631 | Line 632 | simulations without a long-range correction).
632   \begin{center}
633   \epsfxsize=5in
634   \epsfbox{GofRCompare.epsi}
635 < \caption{Plots comparing experiment [Ref. \citen{Head-Gordon00_1}] with SSD/E
636 < and SSD1 without reaction field (top), as well as SSD/RF and SSD1 with
637 < reaction field turned on (bottom). The insets show the respective
638 < first peaks in detail. Note how the changes in parameters have lowered
639 < and broadened the first peak of SSD/E and SSD/RF.}
635 > \caption{Plots comparing experiment [Ref. \citen{Head-Gordon00_1}] with
636 > SSD/E and SSD1 without reaction field (top), as well as
637 > SSD/RF and SSD1 with reaction field turned on
638 > (bottom). The insets show the respective first peaks in detail. Note
639 > how the changes in parameters have lowered and broadened the first
640 > peak of SSD/E and SSD/RF.}
641   \label{grcompare}
642   \end{center}
643   \end{figure}
# Line 643 | Line 645 | and broadened the first peak of SSD/E and SSD/RF.}
645   \begin{figure}
646   \begin{center}
647   \epsfxsize=6in
648 < \epsfbox{dualsticky.ps}
649 < \caption{Isosurfaces of the sticky potential for SSD1 (left) and SSD/E \&
650 < SSD/RF (right). Light areas correspond to the tetrahedral attractive
651 < component, and darker areas correspond to the dipolar repulsive
652 < component.}
648 > \epsfbox{dualsticky_bw.eps}
649 > \caption{Positive and negative isosurfaces of the sticky potential for
650 > SSD1 (left) and SSD/E \& SSD/RF (right). Light areas
651 > correspond to the tetrahedral attractive component, and darker areas
652 > correspond to the dipolar repulsive component.}
653   \label{isosurface}
654   \end{center}
655   \end{figure}
# Line 660 | Line 662 | made while taking into consideration the new experimen
662   Phillips.\cite{Ichiye96,Soper86} New experimental x-ray scattering
663   data from the Head-Gordon lab indicates a slightly lower and shifted
664   first peak in the g$_\mathrm{OO}(r)$, so our adjustments to SSD were
665 < made while taking into consideration the new experimental
665 > made after taking into consideration the new experimental
666   findings.\cite{Head-Gordon00_1} Figure \ref{grcompare} shows the
667   relocation of the first peak of the oxygen-oxygen $g(r)$ by comparing
668   the revised SSD model (SSD1), SSD/E, and SSD/RF to the new
# Line 676 | Line 678 | density for the overall system.  This change in intera
678   see how altering the cutoffs changes the repulsive and attractive
679   character of the particles. With a reduced repulsive surface (darker
680   region), the particles can move closer to one another, increasing the
681 < density for the overall system.  This change in interaction cutoff also
682 < results in a more gradual orientational motion by allowing the
681 > density for the overall system.  This change in interaction cutoff
682 > also results in a more gradual orientational motion by allowing the
683   particles to maintain preferred dipolar arrangements before they begin
684   to feel the pull of the tetrahedral restructuring. As the particles
685   move closer together, the dipolar repulsion term becomes active and
# Line 693 | Line 695 | both of our adjusted models. Since SSD is a dipole bas
695   improves the densities, these changes alone are insufficient to bring
696   the system densities up to the values observed experimentally.  To
697   further increase the densities, the dipole moments were increased in
698 < both of our adjusted models. Since SSD is a dipole based model, the
699 < structure and transport are very sensitive to changes in the dipole
700 < moment. The original SSD simply used the dipole moment calculated from
701 < the TIP3P water model, which at 2.35 D is significantly greater than
702 < the experimental gas phase value of 1.84 D. The larger dipole moment
703 < is a more realistic value and improves the dielectric properties of
704 < the fluid. Both theoretical and experimental measurements indicate a
705 < liquid phase dipole moment ranging from 2.4 D to values as high as
706 < 3.11 D, providing a substantial range of reasonable values for a
707 < dipole moment.\cite{Sprik91,Kusalik02,Badyal00,Barriol64} Moderately
708 < increasing the dipole moments to 2.42 and 2.48 D for SSD/E and SSD/RF,
709 < respectively, leads to significant changes in the density and
710 < transport of the water models.
698 > both of our adjusted models. Since SSD is a dipole based model,
699 > the structure and transport are very sensitive to changes in the
700 > dipole moment. The original SSD simply used the dipole moment
701 > calculated from the TIP3P water model, which at 2.35 D is
702 > significantly greater than the experimental gas phase value of 1.84
703 > D. The larger dipole moment is a more realistic value and improves the
704 > dielectric properties of the fluid. Both theoretical and experimental
705 > measurements indicate a liquid phase dipole moment ranging from 2.4 D
706 > to values as high as 3.11 D, providing a substantial range of
707 > reasonable values for a dipole
708 > moment.\cite{Sprik91,Kusalik02,Badyal00,Barriol64} Moderately
709 > increasing the dipole moments to 2.42 and 2.48 D for SSD/E and
710 > SSD/RF, respectively, leads to significant changes in the
711 > density and transport of the water models.
712  
713   In order to demonstrate the benefits of these reparameterizations, a
714   series of NPT and NVE simulations were performed to probe the density
# Line 726 | Line 729 | collection times as stated previously.
729   \begin{center}
730   \epsfxsize=6in
731   \epsfbox{ssdeDense.epsi}
732 < \caption{Comparison of densities calculated with SSD/E to SSD1 without a
733 < reaction field, TIP3P [Ref. \citen{Jorgensen98b}], TIP5P
734 < [Ref. \citen{Jorgensen00}], SPC/E [Ref. \citen{Clancy94}] and
732 > \caption{Comparison of densities calculated with SSD/E to
733 > SSD1 without a reaction field, TIP3P [Ref. \citen{Jorgensen98b}],
734 > TIP5P [Ref. \citen{Jorgensen00}], SPC/E [Ref. \citen{Clancy94}] and
735   experiment [Ref. \citen{CRC80}]. The window shows a expansion around
736   300 K with error bars included to clarify this region of
737   interest. Note that both SSD1 and SSD/E show good agreement with
# Line 737 | Line 740 | Fig. \ref{ssdedense} shows the density profile for the
740   \end{center}
741   \end{figure}
742  
743 < Fig. \ref{ssdedense} shows the density profile for the SSD/E model
744 < in comparison to SSD1 without a reaction field, other common water
745 < models, and experimental results. The calculated densities for both
746 < SSD/E and SSD1 have increased significantly over the original SSD
747 < model (see fig. \ref{dense1}) and are in better agreement with the
748 < experimental values. At 298 K, the densities of SSD/E and SSD1 without
743 > Fig. \ref{ssdedense} shows the density profile for the SSD/E
744 > model in comparison to SSD1 without a reaction field, other
745 > common water models, and experimental results. The calculated
746 > densities for both SSD/E and SSD1 have increased
747 > significantly over the original SSD model (see
748 > fig. \ref{dense1}) and are in better agreement with the experimental
749 > values. At 298 K, the densities of SSD/E and SSD1 without
750   a long-range correction are 0.996$\pm$0.001 g/cm$^3$ and
751   0.999$\pm$0.001 g/cm$^3$ respectively.  These both compare well with
752   the experimental value of 0.997 g/cm$^3$, and they are considerably
753 < better than the SSD value of 0.967$\pm$0.003 g/cm$^3$. The changes to
754 < the dipole moment and sticky switching functions have improved the
755 < structuring of the liquid (as seen in figure \ref{grcompare}, but they
756 < have shifted the density maximum to much lower temperatures. This
757 < comes about via an increase in the liquid disorder through the
758 < weakening of the sticky potential and strengthening of the dipolar
759 < character. However, this increasing disorder in the SSD/E model has
760 < little effect on the melting transition. By monitoring $C_p$
761 < throughout these simulations, the melting transition for SSD/E was
762 < shown to occur at 235 K.  The same transition temperature observed
763 < with SSD and SSD1.
753 > better than the SSD value of 0.967$\pm$0.003 g/cm$^3$. The
754 > changes to the dipole moment and sticky switching functions have
755 > improved the structuring of the liquid (as seen in figure
756 > \ref{grcompare}, but they have shifted the density maximum to much
757 > lower temperatures. This comes about via an increase in the liquid
758 > disorder through the weakening of the sticky potential and
759 > strengthening of the dipolar character. However, this increasing
760 > disorder in the SSD/E model has little effect on the melting
761 > transition. By monitoring $C_p$ throughout these simulations, the
762 > melting transition for SSD/E was shown to occur at 235 K.  The
763 > same transition temperature observed with SSD and SSD1.
764  
765   \begin{figure}
766   \begin{center}
767   \epsfxsize=6in
768   \epsfbox{ssdrfDense.epsi}
769 < \caption{Comparison of densities calculated with SSD/RF to SSD1 with a
770 < reaction field, TIP3P [Ref. \citen{Jorgensen98b}], TIP5P
771 < [Ref. \citen{Jorgensen00}], SPC/E [Ref. \citen{Clancy94}], and
769 > \caption{Comparison of densities calculated with SSD/RF to
770 > SSD1 with a reaction field, TIP3P [Ref. \citen{Jorgensen98b}],
771 > TIP5P [Ref. \citen{Jorgensen00}], SPC/E [Ref. \citen{Clancy94}], and
772   experiment [Ref. \citen{CRC80}]. The inset shows the necessity of
773   reparameterization when utilizing a reaction field long-ranged
774 < correction - SSD/RF provides significantly more accurate densities
775 < than SSD1 when performing room temperature simulations.}
774 > correction - SSD/RF provides significantly more accurate
775 > densities than SSD1 when performing room temperature
776 > simulations.}
777   \label{ssdrfdense}
778   \end{center}
779   \end{figure}
# Line 795 | Line 800 | K, shown by SSD and SSD1 respectively.
800   \begin{center}
801   \epsfxsize=6in
802   \epsfbox{ssdeDiffuse.epsi}
803 < \caption{The diffusion constants calculated from SSD/E and SSD1,
804 < both without a reaction field, along with experimental results
805 < [Refs. \citen{Gillen72} and \citen{Holz00}]. The NVE calculations
806 < were performed at the average densities observed in the 1 atm NPT
807 < simulations for the respective models. SSD/E is slightly more mobile
808 < than experiment at all of the temperatures, but it is closer to
809 < experiment at biologically relavent temperatures than SSD1 without a
810 < long-range correction.}
803 > \caption{The diffusion constants calculated from SSD/E and
804 > SSD1 (both without a reaction field) along with experimental results
805 > [Refs. \citen{Gillen72} and \citen{Holz00}]. The NVE calculations were
806 > performed at the average densities observed in the 1 atm NPT
807 > simulations for the respective models. SSD/E is slightly more mobile
808 > than experiment at all of the temperatures, but it is closer to
809 > experiment at biologically relevant temperatures than SSD1 without a
810 > long-range correction.}
811   \label{ssdediffuse}
812   \end{center}
813   \end{figure}
# Line 810 | Line 815 | the densities, it is important that the excellent diff
815   The reparameterization of the SSD water model, both for use with and
816   without an applied long-range correction, brought the densities up to
817   what is expected for simulating liquid water. In addition to improving
818 < the densities, it is important that the excellent diffusive behavior
819 < of SSD be maintained or improved. Figure \ref{ssdediffuse} compares
820 < the temperature dependence of the diffusion constant of SSD/E to SSD1
821 < without an active reaction field at the densities calculated from the
822 < NPT simulations at 1 atm. The diffusion constant for SSD/E is
823 < consistently higher than experiment, while SSD1 remains lower than
824 < experiment until relatively high temperatures (around 360 K). Both
825 < models follow the shape of the experimental curve well below 300 K but
826 < tend to diffuse too rapidly at higher temperatures, as seen in SSD1's
827 < crossing above 360 K.  This increasing diffusion relative to the
828 < experimental values is caused by the rapidly decreasing system density
829 < with increasing temperature.  Both SSD1 and SSD/E show this deviation
830 < in diffusive behavior, but this trend has different implications on
831 < the diffusive behavior of the models.  While SSD1 shows more
832 < experimentally accurate diffusive behavior in the high temperature
833 < regimes, SSD/E shows more accurate behavior in the supercooled and
834 < biologically relavent temperature ranges.  Thus, the changes made to
835 < improve the liquid structure may have had an adverse affect on the
836 < density maximum, but they improve the transport behavior of SSD/E
837 < relative to SSD1 under the most commonly simulated conditions.
818 > the densities, it is important that the diffusive behavior of SSD be
819 > maintained or improved. Figure \ref{ssdediffuse} compares the
820 > temperature dependence of the diffusion constant of SSD/E to SSD1
821 > without an active reaction field at the densities calculated from
822 > their respective NPT simulations at 1 atm. The diffusion constant for
823 > SSD/E is consistently higher than experiment, while SSD1 remains lower
824 > than experiment until relatively high temperatures (around 360
825 > K). Both models follow the shape of the experimental curve well below
826 > 300 K but tend to diffuse too rapidly at higher temperatures, as seen
827 > in SSD1's crossing above 360 K.  This increasing diffusion relative to
828 > the experimental values is caused by the rapidly decreasing system
829 > density with increasing temperature.  Both SSD1 and SSD/E show this
830 > deviation in particle mobility, but this trend has different
831 > implications on the diffusive behavior of the models.  While SSD1
832 > shows more experimentally accurate diffusive behavior in the high
833 > temperature regimes, SSD/E shows more accurate behavior in the
834 > supercooled and biologically relevant temperature ranges.  Thus, the
835 > changes made to improve the liquid structure may have had an adverse
836 > affect on the density maximum, but they improve the transport behavior
837 > of SSD/E relative to SSD1 under the most commonly simulated
838 > conditions.
839  
840   \begin{figure}
841   \begin{center}
842   \epsfxsize=6in
843   \epsfbox{ssdrfDiffuse.epsi}
844 < \caption{The diffusion constants calculated from SSD/RF and SSD1,
845 < both with an active reaction field, along with experimental results
846 < [Refs. \citen{Gillen72} and \citen{Holz00}]. The NVE calculations
847 < were performed at the average densities observed in the 1 atm NPT
848 < simulations for both of the models. Note how accurately SSD/RF
849 < simulates the diffusion of water throughout this temperature
850 < range. The more rapidly increasing diffusion constants at high
851 < temperatures for both models is attributed to lower calculated
852 < densities than those observed in experiment.}
844 > \caption{The diffusion constants calculated from SSD/RF and
845 > SSD1 (both with an active reaction field) along with
846 > experimental results [Refs. \citen{Gillen72} and \citen{Holz00}]. The
847 > NVE calculations were performed at the average densities observed in
848 > the 1 atm NPT simulations for both of the models. SSD/RF
849 > simulates the diffusion of water throughout this temperature range
850 > very well. The rapidly increasing diffusion constants at high
851 > temperatures for both models can be attributed to lower calculated
852 > densities than those observed in experiment.}
853   \label{ssdrfdiffuse}
854   \end{center}
855   \end{figure}
# Line 862 | Line 868 | reparameterization when using an altered long-range co
868   reparameterization when using an altered long-range correction.
869  
870   \begin{table}
871 + \begin{minipage}{\linewidth}
872 + \renewcommand{\thefootnote}{\thempfootnote}
873   \begin{center}
874 < \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) Ref. [\citen{Eisenberg69}]. (e) Calculated for 298 K from data in ref. \citen{Krynicki66}.}
874 > \caption{Properties of the single-point water models compared with
875 > experimental data at ambient conditions}
876   \begin{tabular}{ l  c  c  c  c  c }
877   \hline \\[-3mm]
878   \ \ \ \ \ \  & \ \ \ SSD1 \ \ \ & \ SSD/E \ \ \ & \ SSD1 (RF) \ \
# Line 871 | Line 880 | reparameterization when using an altered long-range co
880   \hline \\[-3mm]
881   \ \ \ $\rho$ (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 \\
882   \ \ \ $C_p$ (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 \\
883 < \ \ \ $D$ ($10^{-5}$ 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}$ \\
884 < \ \ \ Coordination Number & 3.9 & 4.3 & 3.8 & 4.4 & 4.7$^\text{b}$ \\
885 < \ \ \ H-bonds per particle & 3.7 & 3.6 & 3.7 & 3.7 & 3.4$^\text{c}$ \\
886 < \ \ \ $\tau_1^\mu$ (ps) & 10.9 $\pm$0.6 & 7.3 $\pm$0.4 & 7.5 $\pm$0.7 & 7.2 $\pm$0.4 & 4.76$^\text{d}$ \\
887 < \ \ \ $\tau_2^\mu$ (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}$ \\
883 > \ \ \ $D$ ($10^{-5}$ cm$^2$/s) & 1.78 $\pm$0.07 & 2.51 $\pm$0.18 &
884 > 2.00 $\pm$0.17 & 2.32 $\pm$0.06 & 2.299\cite{Mills73} \\
885 > \ \ \ Coordination Number ($n_C$) & 3.9 & 4.3 & 3.8 & 4.4 &
886 > 4.7\footnote{Calculated by integrating $g_{\text{OO}}(r)$ in
887 > Ref. \citen{Head-Gordon00_1}} \\
888 > \ \ \ H-bonds per particle ($n_H$) & 3.7 & 3.6 & 3.7 & 3.7 &
889 > 3.5\footnote{Calculated by integrating $g_{\text{OH}}(r)$ in
890 > Ref. \citen{Soper86}}  \\
891 > \ \ \ $\tau_1$ (ps) & 10.9 $\pm$0.6 & 7.3 $\pm$0.4 & 7.5 $\pm$0.7 &
892 > 7.2 $\pm$0.4 & 5.7\footnote{Calculated for 298 K from data in Ref. \citen{Eisenberg69}} \\
893 > \ \ \ $\tau_2$ (ps) & 4.7 $\pm$0.4 & 3.1 $\pm$0.2 & 3.5 $\pm$0.3 & 3.2
894 > $\pm$0.2 & 2.3\footnote{Calculated for 298 K from data in
895 > Ref. \citen{Krynicki66}}
896   \end{tabular}
897   \label{liquidproperties}
898   \end{center}
899 + \end{minipage}
900   \end{table}
901  
902   Table \ref{liquidproperties} gives a synopsis of the liquid state
903   properties of the water models compared in this study along with the
904   experimental values for liquid water at ambient conditions. The
905 < coordination number and hydrogen bonds per particle were calculated by
906 < integrating the following relation:
905 > coordination number ($n_C$) and number of hydrogen bonds per particle
906 > ($n_H$) were calculated by integrating the following relations:
907   \begin{equation}
908 < 4\pi\rho\int_{0}^{a}r^2\text{g}(r)dr,
908 > n_C = 4\pi\rho_{\text{OO}}\int_{0}^{a}r^2\text{g}_{\text{OO}}(r)dr,
909   \end{equation}
910 < where $\rho$ is the number density of pair interactions, $a$ is the
911 < radial location of the minima following the first solvation shell
912 < peak, and g$(r)$ is either g$_\text{OO}(r)$ or g$_\text{OH}(r)$ for
913 < calculation of the coordination number or hydrogen bonds per particle
914 < respectively. The number of hydrogen bonds stays relatively constant
915 < across all of the models, but the coordination numbers of SSD/E and
916 < SSD/RF show an improvement over SSD1. This improvement is primarily
917 < due to the widening of the first solvation shell peak, allowing the
918 < first minima to push outward. Comparing the coordination number with
919 < the number of hydrogen bonds can lead to more insight into the
920 < structural character of the liquid.  Because of the near identical
921 < values for SSD1, it appears to be a little too exclusive, in that all
922 < molecules in the first solvation shell are involved in forming ideal
923 < hydrogen bonds.  The differing numbers for the newly parameterized
924 < models indicate the allowance of more fluid configurations in addition
925 < to the formation of an acceptable number of ideal hydrogen bonds.
910 > \begin{equation}
911 > n_H = 4\pi\rho_{\text{OH}}\int_{0}^{b}r^2\text{g}_{\text{OH}}(r)dr,
912 > \end{equation}
913 > where $\rho$ is the number density of the specified pair interactions,
914 > $a$ and $b$ are the radial locations of the minima following the first
915 > peak in g$_\text{OO}(r)$ or g$_\text{OH}(r)$ respectively. The number
916 > of hydrogen bonds stays relatively constant across all of the models,
917 > but the coordination numbers of SSD/E and SSD/RF show an
918 > improvement over SSD1.  This improvement is primarily due to
919 > extension of the first solvation shell in the new parameter sets.
920 > Because $n_H$ and $n_C$ are nearly identical in SSD1, it appears
921 > that all molecules in the first solvation shell are involved in
922 > hydrogen bonds.  Since $n_H$ and $n_C$ differ in the newly
923 > parameterized models, the orientations in the first solvation shell
924 > are a bit more ``fluid''.  Therefore SSD1 overstructures the
925 > first solvation shell and our reparameterizations have returned this
926 > shell to more realistic liquid-like behavior.
927  
928 < The time constants for the self orientational autocorrelation function
928 > The time constants for the orientational autocorrelation functions
929   are also displayed in Table \ref{liquidproperties}. The dipolar
930 < orientational time correlation function ($\Gamma_{l}$) is described
930 > orientational time correlation functions ($C_{l}$) are described
931   by:
932   \begin{equation}
933 < \Gamma_{l}(t) = \langle P_l[\mathbf{u}_j(0)\cdot\mathbf{u}_j(t)]\rangle,
933 > C_{l}(t) = \langle P_l[\hat{\mathbf{u}}_j(0)\cdot\hat{\mathbf{u}}_j(t)]\rangle,
934   \end{equation}
935 < where $P_l$ is a Legendre polynomial of order $l$ and $\mathbf{u}_j$
936 < is the unit vector of the particle dipole.\cite{Rahman71} From these
937 < correlation functions, the orientational relaxation time of the dipole
938 < vector can be calculated from an exponential fit in the long-time
939 < regime ($t > \tau_l^\mu$).\cite{Rothschild84} Calculation of these
940 < time constants were averaged from five detailed NVE simulations
941 < performed at the STP density for each of the respective models. Again,
942 < SSD/E and SSD/RF show improved behavior over SSD1 both with and
943 < without an active reaction field. Numbers published from the original
944 < SSD dynamics studies appear closer to the experimental values, and we
945 < attribute this discrepancy to the implimentation of an Ewald sum
946 < versus a reaction field.
935 > where $P_l$ are Legendre polynomials of order $l$ and
936 > $\hat{\mathbf{u}}_j$ is the unit vector pointing along the molecular
937 > dipole.\cite{Rahman71} From these correlation functions, the
938 > orientational relaxation time of the dipole vector can be calculated
939 > from an exponential fit in the long-time regime ($t >
940 > \tau_l$).\cite{Rothschild84} Calculation of these time constants were
941 > averaged over five detailed NVE simulations performed at the ambient
942 > conditions for each of the respective models. It should be noted that
943 > the commonly cited value of 1.9 ps for $\tau_2$ was determined from
944 > the NMR data in Ref. \citen{Krynicki66} at a temperature near
945 > 34$^\circ$C.\cite{Rahman71} Because of the strong temperature
946 > dependence of $\tau_2$, it is necessary to recalculate it at 298 K to
947 > make proper comparisons. The value shown in Table
948 > \ref{liquidproperties} was calculated from the same NMR data in the
949 > fashion described in Ref. \citen{Krynicki66}. Similarly, $\tau_1$ was
950 > recomputed for 298 K from the data in Ref. \citen{Eisenberg69}.
951 > Again, SSD/E and SSD/RF show improved behavior over SSD1, both with
952 > and without an active reaction field. Turning on the reaction field
953 > leads to much improved time constants for SSD1; however, these results
954 > also include a corresponding decrease in system density.
955 > Orientational relaxation times published in the original SSD dynamics
956 > papers are smaller than the values observed here, and this difference
957 > can be attributed to the use of the Ewald sum.\cite{Ichiye99}
958  
959   \subsection{Additional Observations}
960  
961   \begin{figure}
962   \begin{center}
963   \epsfxsize=6in
964 < \epsfbox{povIce.ps}
965 < \caption{A water lattice built from the crystal structure assumed by
966 < SSD/E when undergoing an extremely restricted temperature NPT
967 < simulation. This form of ice is referred to as ice-{\it i} to
968 < emphasize its simulation origins. This image was taken of the (001)
939 < face of the crystal.}
964 > \epsfbox{icei_bw.eps}
965 > \caption{The most stable crystal structure assumed by the SSD family
966 > of water models.  We refer to this structure as Ice-{\it i} to
967 > indicate its origins in computer simulation.  This image was taken of
968 > the (001) face of the crystal.}
969   \label{weirdice}
970   \end{center}
971   \end{figure}
972  
973   While performing a series of melting simulations on an early iteration
974 < of SSD/E not discussed in this paper, we observed recrystallization
975 < into a novel structure not previously known for water.  After melting
976 < at 235 K, two of five systems underwent crystallization events near
977 < 245 K.  The two systems remained crystalline up to 320 and 330 K,
978 < respectively.  The crystal exhibits an expanded zeolite-like structure
979 < that does not correspond to any known form of ice.  This appears to be
980 < an artifact of the point dipolar models, so to distinguish it from the
981 < experimentally observed forms of ice, we have denoted the structure
982 < Ice-$\sqrt{\smash[b]{-\text{I}}}$ (ice-{\it i}).  A large enough
974 > of SSD/E not discussed in this paper, we observed
975 > recrystallization into a novel structure not previously known for
976 > water.  After melting at 235 K, two of five systems underwent
977 > crystallization events near 245 K.  The two systems remained
978 > crystalline up to 320 and 330 K, respectively.  The crystal exhibits
979 > an expanded zeolite-like structure that does not correspond to any
980 > known form of ice.  This appears to be an artifact of the point
981 > dipolar models, so to distinguish it from the experimentally observed
982 > forms of ice, we have denoted the structure
983 > Ice-$\sqrt{\smash[b]{-\text{I}}}$ (Ice-{\it i}).  A large enough
984   portion of the sample crystallized that we have been able to obtain a
985 < near ideal crystal structure of ice-{\it i}. Figure \ref{weirdice}
985 > near ideal crystal structure of Ice-{\it i}. Figure \ref{weirdice}
986   shows the repeating crystal structure of a typical crystal at 5
987   K. Each water molecule is hydrogen bonded to four others; however, the
988   hydrogen bonds are bent rather than perfectly straight. This results
# Line 963 | Line 993 | Initial simulations indicated that ice-{\it i} is the
993   configuration. Though not ideal, these flexed hydrogen bonds are
994   favorable enough to stabilize an entire crystal generated around them.
995  
996 < Initial simulations indicated that ice-{\it i} is the preferred ice
996 > Initial simulations indicated that Ice-{\it i} is the preferred ice
997   structure for at least the SSD/E model. To verify this, a comparison
998   was made between near ideal crystals of ice~$I_h$, ice~$I_c$, and
999 < ice-{\it i} at constant pressure with SSD/E, SSD/RF, and
999 > Ice-{\it i} at constant pressure with SSD/E, SSD/RF, and
1000   SSD1. Near-ideal versions of the three types of crystals were cooled
1001 < to 1 K, and the enthalpies of each were compared using all three water
1002 < models. With every model in the SSD family, ice-{\it i} had the lowest
1003 < calculated enthalpy: 5\% lower than $I_h$ with SSD1, 6.5\% lower with
1004 < SSD/E, and 7.5\% lower with SSD/RF.  The enthalpy data is summarized
1005 < in Table \ref{iceenthalpy}.
1001 > to 1 K, and enthalpies of formation of each were compared using all
1002 > three water models.  Enthalpies were estimated from the
1003 > isobaric-isothermal simulations using $H=U+P_{\text ext}V$ where
1004 > $P_{\text ext}$ is the applied pressure.  A constant value of -60.158
1005 > kcal / mol has been added to place our zero for the enthalpies of
1006 > formation for these systems at the traditional state (elemental forms
1007 > at standard temperature and pressure).  With every model in the SSD
1008 > family, Ice-{\it i} had the lowest calculated enthalpy of formation.
1009  
1010   \begin{table}
1011   \begin{center}
1012 < \caption{Enthalpies (in kcal / mol) of the three crystal structures (at 1
1013 < K) exhibited by the SSD family of water models}
1012 > \caption{Enthalpies of Formation (in kcal / mol) of the three crystal
1013 > structures (at 1 K) exhibited by the SSD family of water models}
1014   \begin{tabular}{ l  c  c  c  }
1015   \hline \\[-3mm]
1016   \ \ \ Water Model \ \ \  & \ \ \ Ice-$I_h$ \ \ \ & \ Ice-$I_c$\ \  & \
1017   Ice-{\it i} \\
1018   \hline \\[-3mm]
1019 < \ \ \ SSD/E & -12.286 & -12.292 & -13.590 \\
1020 < \ \ \ SSD/RF & -12.935 & -12.917 & -14.022 \\
1021 < \ \ \ SSD1 & -12.496 & -12.411 & -13.417 \\
1022 < \ \ \ SSD1 (RF) & -12.504 & -12.411 & -13.134 \\
1019 > \ \ \ SSD/E & -72.444 & -72.450 & -73.748 \\
1020 > \ \ \ SSD/RF & -73.093 & -73.075 & -74.180 \\
1021 > \ \ \ SSD1 & -72.654 & -72.569 & -73.575 \\
1022 > \ \ \ SSD1 (RF) & -72.662 & -72.569 & -73.292 \\
1023   \end{tabular}
1024   \label{iceenthalpy}
1025   \end{center}
# Line 1004 | Line 1037 | constant were studied for the SSD water model, both wi
1037   \section{Conclusions}
1038  
1039   The density maximum and temperature dependence of the self-diffusion
1040 < constant were studied for the SSD water model, both with and without
1041 < the use of reaction field, via a series of NPT and NVE
1040 > constant were studied for the SSD water model, both with and
1041 > without the use of reaction field, via a series of NPT and NVE
1042   simulations. The constant pressure simulations showed a density
1043   maximum near 260 K. In most cases, the calculated densities were
1044   significantly lower than the densities obtained from other water
1045 < models (and experiment). Analysis of self-diffusion showed SSD to
1046 < capture the transport properties of water well in both the liquid and
1047 < super-cooled liquid regimes.
1045 > models (and experiment). Analysis of self-diffusion showed SSD
1046 > to capture the transport properties of water well in both the liquid
1047 > and supercooled liquid regimes.
1048  
1049   In order to correct the density behavior, the original SSD model was
1050   reparameterized for use both with and without a reaction field (SSD/RF
# Line 1025 | Line 1058 | by the SSD family of water models is somewhat troublin
1058   simulations of biochemical systems.
1059  
1060   The existence of a novel low-density ice structure that is preferred
1061 < by the SSD family of water models is somewhat troubling, since liquid
1062 < simulations on this family of water models at room temperature are
1063 < effectively simulations of super-cooled or metastable liquids.  One
1064 < way to de-stabilize this unphysical ice structure would be to make the
1061 > by the SSD family of water models is somewhat troubling, since
1062 > liquid simulations on this family of water models at room temperature
1063 > are effectively simulations of supercooled or metastable liquids.  One
1064 > way to destabilize this unphysical ice structure would be to make the
1065   range of angles preferred by the attractive part of the sticky
1066   potential much narrower.  This would require extensive
1067   reparameterization to maintain the same level of agreement with the
1068   experiments.
1069  
1070 < Additionally, our initial calculations show that the ice-{\it i}
1070 > Additionally, our initial calculations show that the Ice-{\it i}
1071   structure may also be a preferred crystal structure for at least one
1072   other popular multi-point water model (TIP3P), and that much of the
1073   simulation work being done using this popular model could also be at

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