COMETA Consortium

The Sicilian e-Infrastructure:
COMETA Consortium
Simulation and Theory of
Polar/Apolar Fluid Mixtures
D. Costa1, F. Saija2, G. Munaò2, C. Caccamo2
1
Consorzio COMETA and Dip. di Fisica, Università di Messina, Ctr. Papardo – 98166 Messina (dino.costa@unime.it)
2 CNR- Istituto Processi Chimico-Fisici, Contrada. Papardo, Salita Sperone – 98158 Messina
3 Dipartimento di Fisica, Università di Messina, Contrada Papardo – 98166 Messina
Molecular Dynamics simulation and Reference Interaction Site Model (RISM) theory have been used to study fluid mixtures
composed by methanol (CH3OH) and carbon tetrachloride (CCl4), focusing in particular on the low concentration regime of
methanol. Simulations clearly show the modifications in the associating properties of the methanol induced by the presence
of the apolar solvent: the liquid structure of pure methanol is characterized by winding chains of hydrogen-bonded
monomers; upon dilution, the methanol tends to preserve its local order, whereas a significant fraction of chains closes to
form cyclic structures, with important implications for the thermodynamic properties of the system. Theoretical results
qualitatively follow the simulation trends. An analysis of performances on the GRID architecture of the Consorzio COMETA is
shortly presented.
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Motivations
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Molecular Geometries
Interaction Potentials
The interaction potential between any site α on a molecule and another site β on
a different molecule at distance r apart is written as:
»“
–
qα qβ
σαβ ”12 “ σαβ ”6
LJ
coul
+
vαβ (r) ≡ vαβ
(r) + vαβ
(r) = 4ǫαβ
−
r
r
r
Monohydric alcohols and their mixtures with nonpolar solvents constitute a
class of complex fluids particularly useful for the investigation of the selfaggregation properties of liquids interacting via hydrogen bonds [1] The
CH3 OH/CCl4 mixture in particular has been characterized by means of
several experimental [2,3] and theoretical tools (see e.g. [4] and references).
The purpose of the present study is manyfold:
Methanol parameters
– the simulation of relatively large systems, accessible through the GRID
facilities, allows us to address the crucial issue of the modification of the
aggregation properties of methanol in the mixture, at the microscopic
scale and even in the high dilution regime.
– A comparison is planned between our simulations and the experimental
data generated in the IPCF laboratory of CNR [5]. Simulations will also
provide the necessary benchmark to gauge the accuracy of the liquid
state theories for molecular fluids currently adopted by the group at the
Physics Department [6].
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Geometry of the CCl4 (left) and CH3 OH (right) models. The C site of the
methanol represents the CH3 group. All diameters roughly correspond to the
“collisional diameters” σXX reported in next table. The distances among the interaction sites are: LCH3 O = 1.4246 Å, LOH = 0.9451 Å, and LCH3 H = 1.9437 Å
(∠ CH3 OH = 108.5◦ ) for CH3 OH; LCCl = 1.766 Å (∠ ClCCl = 109.5◦ ) for CCl4 .
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Plan of Simulations
qCH3
qO
-0.265
0.700
qH
ǫCH3 CH3
ǫOO
σCH3 CH3
σOO
-0.435
0.2070
0.1700
3.7750
3.0710
Carbon Tetrachloride parameters
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2
q
ǫCC
ǫClCl
σCC
σClCl
0
0.1016
0.2034
4.600
3.500
Partial charges q are in e units, the potential well depth ǫ is in K cal/mol and
the “collisional diameters” σ in Å. Data for CH3 OH and CCl4 are taken from [7]
and [8], respectively. Lorentz-Berthelot rules apply for all cross-interactions.
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Results II - Microscopic configurations
Results I - Local order in the fluid
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Parallel Molecular Dynamics package MOLDY [9] with:
Molecules handled as rigid bodies using the quaternion algorithm
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5
χM=0.1
χM=0.1
NVT simulations at room conditions via the Nosè-Hoover thermostat
Ewald summation for the long-range part of interaction
4
χM=0.5
4
χM=0.5
30
30
χM=0.9
χM=0.9
3
g(r)
Link cell with no minimum image convention
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NCH3 OH
NCCl4
Ntot
MD steps
0.1
876
7872
41988
40 000
0.5
1458
1458
11664
300 000
0.9
2624
292
9332
40 000
0
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Ideal Scaling
10
True Scaling
True Scaling
Log(Time)
Time (mins)
1000
8
500
6
0
0
20
40
# CPU’s
60
4
0
2
4
6
Log(# CPU’s)
Running time vs the number of CPU. The structure of the problem at issue (where
the sample size is large in comparison with the typical spatial range of molecular
interactions) produces an almost ideal scaling of the computer time. In this case
in fact, a proper partition scheme of the simulation box into several subsystems
minimizes the communication requirements among the parts of the sample, and
this process in turn optimally copes with a parallel split of the computational
load among the various processors.
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OO
1
0
0
2
4
6
1
8
0
r[A]
Radial distribution functions (RDF) of O and H sites of methanol (in black) and
corresponding coordination numbers (CN, in red), at several methanol concentrations. The sharp increase of RDF accompanied by the constancy of CN reflect
the tendency of the methanol to preserve the local environment typical of the
pure liquid, notwithstanding the progressive dilution of such species [4].
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Conclusions and perspectives
Extensive MD simulations of liquid mixtures formed by CH3 OH and CCl4
at different concentrations are presented. The use of computer simulations
provides a powerful tool to understand the origin of the self-association phenomena driven by mutual hydrogen-bond interactions, from a detailed microscopic point of view.
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Ideal Scaling
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Analysis of performances
1500
OH
r[A]
χM is the concentration of methanol. NCCl4 and NCH3 OH are the number of
molecules of carbon tetrachloride and methanol, respectively. Ntot is the total
number of interaction sites.
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2
10
χM
N(r)
3
20
The computing facilities available at the Consorzio COMETA open the possibility to deal with larger systems and longer time trajectories, in comparison with the typical sizes investigated in the past [4, 7, 8]. This opportunity
allows the investigation of physical properties otherwise practically unaccessible with normal computational resources.
– The accurate determination of the microscopic behaviour of the methanol
in the low concentration regime is one of these aspects.
– Another important issue concerns the long-range behaviour of the correlation functions. This is related to the structure factors, directly calculated in experiments, and to the macroscopic properties of the system
through the compressibility route to thermodynamics.
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Snapshots of equilibrated configurations. For clarity sake, only the O (in red)
and H (in white) sites of methanol are drawn. In the equimolar mixture (left),
the formation of linear chains provides the dominant mechanism of aggregation
of methanol molecules. At low concentration (χM = 0.1, right) chains tend to
form cyclic structures (rings), with an evident increase of isolated monomers.
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References
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[1] C. A. Angell in Hydrogen Bonded Liquids, J. C. Dore and J. Texeira eds.
(Kluwer Academic Publishers, Dordrecht, 1991).
[2] G. C. Paraskevopoulos and R. W. Missen, Trans. Faraday Soc. 57, 869 (1962);
J.-E. A. Otterstedt and R. W. Missen, Trans. Faraday Soc. 57, 879 (1962).
[3] M. Musso, H. Torii, P. Ottaviani, A. Asenbaum, and M. G. Giorgini, J. Phys.
Chem. A 106, 10152 (2002).
[4] R. Veldhuizen and S. W. de Leeuw, J. Chem. Phys. 105, 2828 (1996).
[5] M. Pieruccini, F. Saija, C. Vasi, and M. Musso, Chem. Phys. Lett. 382, 523
(2003); F. Aliotta, M. Musso, R. Ponterio, F. Saija, and G. Salvato, J. Phys.
Chem. B 108, 12972 (2004); B. Fazio, M. Pieruccini, and C. Vasi, J. Phys.
Chem. B 109, 16075 (2005).
[6] D. Costa, G. Munaò, F. Saija, and C. Caccamo, J. Chem. Phys. 127, 224501
(2007).
[7] W. L. Jorgensen, J. Phys. Chem. 90, 1276 (1986).
[8] I. R. McDonald, D. G. Bounds, and M. L. Klein, Mol. Phys. 45, 521 (1982).
[9] K. Refson, Comp. Phys. Comm. 126, 309 (200); see also the webpage
www.earth.ox.ac.uk/∼keithr/moldy.html.
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Acknowledgment: This work makes
use of results produced by the PI2S2 Project managed by the consorzio COMETA,
a project co-funded by the Italian Ministry of University and Research (MIUR)
within the Piano Operativo
Nazionale Ricerca Scientifica, Sviluppo Tecnologico, Alta Formazione (PON 2000-2006). More information is available at http://www.pi2s2.it and http://www.consorzio-cometa.it
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