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L. F. Vega et al.
depth” (a measure of how strongly the two particles attract each other, or energy of
interaction between groups/atoms), respectively.
Molecular simulation allows a systematic and controlled study of various relevant variables of the studied system. The two main molecular simulation methods
used are Monte Carlo (MC) and molecular dynamics (MD) [71]. MC methods are
expansively used for complex molecules calculations, in systems where the temporal
evolution is not needed, for instance, for calculating properties such as adsorption
at equilibrium [72] as well as for systems for which MD simulations are not affordable yet, due to time scale limitations. One desirable facet of MC is that during
configurational sampling, only energies instead of forces are evaluated. The simulation can be performed with physically unnatural motions, and thus, the efficiency
increases significantly. Conversely, MD simulations provide the real-time evolution
of the system, and it is the method of choice for calculating transport properties such
as diffusivity, viscosity or thermal conductivity.
Coexisting vapour and liquid phases or liquid–liquid phases are usually calculated
by Monte Carlo simulations using the Gibbs Ensemble method [73]. In this technique,
the two phases are simulated in two independent boxes, imposing the equality of
temperature, pressure and chemical potential between them, according to the phase
rule. The two coexisting phases are monitored simultaneously as separate subsystems
without the presence of an interface. This is the natural choice for phase equilibria
calculations from molecular simulations when no information of the interface or
the transport properties is needed, considerably saving computing time. The method
is routinely used to validate force fields, by comparing the phase equilibria results
from the Gibbs Ensemble simulations to those experimentally obtained for the same
system. In the context of this work, the Gibbs Ensemble Monte Carlo method has
been used by Raabe and Maginn and Raabe to validate the developed force fields for
the HFOs [74–78].
Furthermore, the Grand Canonical Monte Carlo (GCMC) simulation method is an
appropriate choice for modelling phase equilibrium systems in confined media, such
as adsorption phenomena [79], and it has been extensively used to obtain thermophysical properties in nanoporous adsorbent materials [80–83]. In this method, the
temperature, volume and chemical potential are fixed. Since the chemical potential is
the same in both phases, the number of molecules inside the pore varies, depending
on the thermodynamic conditions, being its average one of the most meaningful
quantities to be extracted from GCMC [84]. Therefore, adsorption isotherms can be
obtained by performing a series of simulations at different pressures and be directly
compared to the experimentally measured ones, while also providing information on
the location and conformation of the molecules inside the materials. The reader is
referred to excellent textbooks in the field for a further inclusive treatment of these
and other simulation methods [70, 71].
L. F. Vega et al.
depth” (a measure of how strongly the two particles attract each other, or energy of
interaction between groups/atoms), respectively.
Molecular simulation allows a systematic and controlled study of various relevant variables of the studied system. The two main molecular simulation methods
used are Monte Carlo (MC) and molecular dynamics (MD) [71]. MC methods are
expansively used for complex molecules calculations, in systems where the temporal
evolution is not needed, for instance, for calculating properties such as adsorption
at equilibrium [72] as well as for systems for which MD simulations are not affordable yet, due to time scale limitations. One desirable facet of MC is that during
configurational sampling, only energies instead of forces are evaluated. The simulation can be performed with physically unnatural motions, and thus, the efficiency
increases significantly. Conversely, MD simulations provide the real-time evolution
of the system, and it is the method of choice for calculating transport properties such
as diffusivity, viscosity or thermal conductivity.
Coexisting vapour and liquid phases or liquid–liquid phases are usually calculated
by Monte Carlo simulations using the Gibbs Ensemble method [73]. In this technique,
the two phases are simulated in two independent boxes, imposing the equality of
temperature, pressure and chemical potential between them, according to the phase
rule. The two coexisting phases are monitored simultaneously as separate subsystems
without the presence of an interface. This is the natural choice for phase equilibria
calculations from molecular simulations when no information of the interface or
the transport properties is needed, considerably saving computing time. The method
is routinely used to validate force fields, by comparing the phase equilibria results
from the Gibbs Ensemble simulations to those experimentally obtained for the same
system. In the context of this work, the Gibbs Ensemble Monte Carlo method has
been used by Raabe and Maginn and Raabe to validate the developed force fields for
the HFOs [74–78].
Furthermore, the Grand Canonical Monte Carlo (GCMC) simulation method is an
appropriate choice for modelling phase equilibrium systems in confined media, such
as adsorption phenomena [79], and it has been extensively used to obtain thermophysical properties in nanoporous adsorbent materials [80–83]. In this method, the
temperature, volume and chemical potential are fixed. Since the chemical potential is
the same in both phases, the number of molecules inside the pore varies, depending
on the thermodynamic conditions, being its average one of the most meaningful
quantities to be extracted from GCMC [84]. Therefore, adsorption isotherms can be
obtained by performing a series of simulations at different pressures and be directly
compared to the experimentally measured ones, while also providing information on
the location and conformation of the molecules inside the materials. The reader is
referred to excellent textbooks in the field for a further inclusive treatment of these
and other simulation methods [70, 71].