Potential Monte Carlo simulation

Sese, L. M., Path integral and effective potential Monte Carlo simulations of liquid nitrogen, hard-sphere and Lennard-Jones potentials, Mol. Phys. 1991, 74, 177-189... 

Soper, A.K., Empirical potential Monte Carlo simulation of fluid structure, Chem. Phys., 202, 295-306,1996. 

Mon K K and Griffiths R B 1985 Chemical potential by gradual insertion of a particle in Monte Carlo simulation Phys. Rev. A 31 956-9... 

Nezbeda I and Kolafa J 1991 A new version of the insertion particle method for determining the chemical potential by Monte Carlo simulation Mol. SImul. 5 391-403... 

The parameter /r tunes the stiffness of the potential. It is chosen such that the repulsive part of the Leimard-Jones potential makes a crossing of bonds highly improbable (e.g., k= 30). This off-lattice model has a rather realistic equation of state and reproduces many experimental features of polymer solutions. Due to the attractive interactions the model exhibits a liquid-vapour coexistence, and an isolated chain undergoes a transition from a self-avoiding walk at high temperatures to a collapsed globule at low temperatures. Since all interactions are continuous, the model is tractable by Monte Carlo simulations as well as by molecular dynamics. Generalizations of the Leimard-Jones potential to anisotropic pair interactions are available e.g., the Gay-Beme potential [29]. This latter potential has been employed to study non-spherical particles that possibly fomi liquid crystalline phases. 

The most important molecular interactions of all are those that take place in liquid water. For many years, chemists have worked to model liquid water, using molecular dynamics and Monte Carlo simulations. Until relatively recently, however, all such work was done using effective potentials [4T], designed to reproduce the condensed-phase properties but with no serious claim to represent the tme interactions between a pair of water molecules. 

We tested our recipe on many trial densities by Monte Carlo simulation, c. g., on the normal mixture tajrget densities of Jones et al. [14]. Examples of pair potentials U r) = Wy q r)) reconstructed in this way are given in Figure 3. 

I h c effect of temperature in Monte Carlo simulations is primarily to modulate the strength of in termolecular in teraelion s, since temperature en Lers the simulation on ly th rough the Ho I Urn an n factor exp(-.-Ab7k r), where. AH represents a difference in potential... 

Mesoscale simulations model a material as a collection of units, called beads. Each bead might represent a substructure, molecule, monomer, micelle, micro-crystalline domain, solid particle, or an arbitrary region of a fluid. Multiple beads might be connected, typically by a harmonic potential, in order to model a polymer. A simulation is then conducted in which there is an interaction potential between beads and sometimes dynamical equations of motion. This is very hard to do with extremely large molecular dynamics calculations because they would have to be very accurate to correctly reflect the small free energy differences between microstates. There are algorithms for determining an appropriate bead size from molecular dynamics and Monte Carlo simulations. 

Molecular Dynamics and Monte Carlo Simulations. At the heart of the method of molecular dynamics is a simulation model consisting of potential energy functions, or force fields. Molecular dynamics calculations represent a deterministic method, ie, one based on the assumption that atoms move according to laws of Newtonian mechanics. Molecular dynamics simulations can be performed for short time-periods, eg, 50—100 picoseconds, to examine localized very high frequency motions, such as bond length distortions, or, over much longer periods of time, eg, 500—2000 ps, in order to derive equiUbrium properties. It is worthwhile to summarize what properties researchers can expect to evaluate by performing molecular simulations ... 

In this seetion of our work we present examples of the applieation of eomputer simulation methods to study ehemieally assoeiating fluids. In the first ease we eonsider the adsorption and surfaee phase transitions by means of a eonstant pressure Monte Carlo simulation. The seeond example is foeused on the problem of ehemieal potential evaluation. 

Reeently, Rowley et al. [170,171] have introdueed a new method for the determination of the ehemieal potential from moleeular dynamies simulation. This method uses a semipermeable membrane and the simulation relies on the establishment of osmotie equilibrium aeross the membrane. Reeently, a similar teehnique has been used to ealeulate the ehemieal potentials of assoeiating fluids from the eanonieal ensemble Monte Carlo simulation [172,173]. Briefly, ehemieal assoeiation has been allowed in some seleeted parts of the system. Beeause of the sueking of the partieles into these parts of the simulation box, the density in other parts of the box falls. As long as... 

To test the results of the chemical potential evaluation, the grand canonical ensemble Monte Carlo simulation of the bulk associating fluid has also been performed. The algorithm of this simulation was identical to that described in Ref. 172. All the calculations have been performed for states far from the liquid-gas coexistence curve [173]. 

To conclude, the introduction of species-selective membranes into the simulation box results in the osmotic equilibrium between a part of the system containing the products of association and a part in which only a one-component Lennard-Jones fluid is present. The density of the fluid in the nonreactive part of the system is lower than in the reactive part, at osmotic equilibrium. This makes the calculations of the chemical potential efficient. The quahty of the results is similar to those from the grand canonical Monte Carlo simulation. The method is neither restricted to dimerization nor to spherically symmetric associative interactions. Even in the presence of higher-order complexes in large amounts, the proposed approach remains successful. 

For the equihbrium properties and for the kinetics under quasi-equilibrium conditions for the adsorbate, the transfer matrix technique is a convenient and accurate method to obtain not only the chemical potentials, as a function of coverage and temperature, but all other thermodynamic information, e.g., multiparticle correlators. We emphasize the economy of the computational effort required for the application of the technique. In particular, because it is based on an analytic method it does not suffer from the limitations of time and accuracy inherent in statistical methods such as Monte Carlo simulations. The task of variation of Hamiltonian parameters in the process of fitting a set of experimental data (thermodynamic and... 

P. Bryk, A. Patrykiejew, O. Pizio, S. Sokolowski. The chemical potential of Lennard-Jones associating fluids from osmotic Monte Carlo simulations. Mol Phys 92 949, 1997 A method for the determination of chemical potential for associating liquids. Mol Phys 90 665, 1997. 

In all these examples, the importance of good simulation and modeling cannot be stressed enough. A variety of methods have been used in this field to simulate the data in the cases studies described above. Blander et al. [4], for example, used a semi-empirical molecular orbital method, MNDO, to calculate the geometries of the free haloaluminate ions and used these as a basis for the modeling of the data by the RPSU model [12]. Badyal et al. [6] used reverse Monte Carlo simulations, whereas Bowron et al. [11] simulated the neutron data from [MMIM]C1 with the Empirical Potential Structure Refinement (EPSR) model [13]. 

---