A direct method for determination of chemical potential with molecular dynamics simulations

Excess entropy scaling law: A potential energy landscape view

The relationship between excess entropy and diffusion is revisited by means of large-scale computer simulation combined to supervised learning approach to determine the excess entropy for the Lennard-Jones potential. Results reveal a strong correlation with the properties of the potential energy landscape (PEL). In particular the exponential law holding in the liquid is seen to be linked with the landscape-influenced regime of the PEL whereas the fluidlike power-law corresponds to the free diffusion regime.

Local Grand Canonical Monte Carlo Simulation Method for Confined Fluids

We describe a new local grand canonical Monte Carlo method to treat fluids in pores in chemical equilibrium with a reference bulk. The method is applied to Lennard-Jones particles in pores of different geometry and is shown to be much more accurate and efficient than other techniques such as traditional grand canonical simulations or Widom's particle insertion method. It utilizes a penalty potential to create a gas phase, which is in equilibrium with a more dense liquid component in the pore. Grand canonical Monte Carlo moves are employed in the gas phase, and the system then maintains chemical equilibrium by "diffusion" of particles. This creates an interface, which means that the confined fluid needs to occupy a large enough volume so that this is not an issue. We also applied the method to confined charged fluids and show how it can be used to determine local electrostatic potentials in the confined fluid, which are properly referenced to the bulk. This precludes the need to determine the Donnan potential (which controls electrochemical equilibrium) explicitly. Prior approaches have used explicit bulk simulations to measure this potential difference, which are significantly costly from a computational point of view. One outcome of our analysis is that pores of finite cross-section create a potential difference with the bulk via a small but nonzero linear charge density, which diminishes as ∼1/ln(L), where L is the pore length.

Chemical potential perturbation: a method to predict chemical potentials in periodic molecular simulations

A new method, called chemical potential perturbation (CPP), has been developed to predict the chemical potential as a function of density in periodic molecular simulations. The CPP method applies a spatially varying external force field to the simulation, causing the density to depend upon position in the simulation cell. Following equilibration the homogeneous (uniform or bulk) chemical potential as a function of density can be determined relative to some reference state after correcting for the effects of the inhomogeneity of the system. We compare three different methods of approximating this correction. The first method uses the van der Waals density gradient theory to approximate the inhomogeneous Helmholtz free energy density. The second method uses the local pressure tensor to approximate the homogeneous pressure. The third method uses the Triezenberg-Zwanzig definition of surface tension to approximate the inhomogeneous free energy density. If desired, the homogeneous pressure and Helmholtz free energy can also be predicted by the new method, as well as binodal and spinodal densities of a two-phase fluid region. The CPP method is tested using a Lennard-Jones (LJ) fluid at vapor, liquid, two-phase, and supercritical conditions. Satisfactory agreement is found between the CPP method and an LJ equation of state. The efficiency of the CPP method is compared to that for Widom's method under the tested conditions. In particular, the new method works well for dense fluids where Widom's method starts to fail.

Reaction ensemble molecular dynamics: direct simulation of the dynamic equilibrium properties of chemically reacting mixtures

A molecular simulation method to study the dynamics of chemically reacting mixtures is presented. The method uses a combination of stochastic and dynamic simulation steps, allowing for the simulation of both thermodynamic and transport properties. The method couples a molecular dynamics simulation cell (termed dynamic cell) to a reaction mixture simulation cell (termed control cell) that is formulated upon the reaction ensemble Monte Carlo (RxMC) method, hence the term reaction ensemble molecular dynamics. Thermodynamic and transport properties are calculated in the dynamic cell by using a constant-temperature molecular dynamics simulation method. RxMC forward and reverse reaction steps are performed in the control cell only, while molecular dynamics steps are performed in both the dynamic cell and the control cell. The control cell, which acts as a sink and source reservoir, is maintained at reaction equilibrium conditions via the RxMC algorithm. The reaction ensemble molecular dynamics method is analogous to the grand canonical ensemble molecular dynamics technique, while using some elements of the osmotic molecular dynamics method, and so simulates conditions that directly relate to real, open systems. The accuracy and stability of the method is assessed by considering the ammonia synthesis reaction N2 +3 H2 <-->2N H3 . It is shown to be a viable method for predicting the effects of nonideal environments on the dynamic properties (particularly diffusion) as well as reaction equilibria for chemically reacting mixtures.