Using molecular dynamics (MD) simulations in conjunction with the SPC/E water model, we optimize ionic force-field parameters for seven different halide and alkali ions, considering a total of eight ion-pairs. Our strategy is based on simultaneous optimizing single-ion and ion-pair properties, i.e., we first fix ion-water parameters based on single-ion solvation free energies, and in a second step determine the cation-anion interaction parameters (traditionally given by mixing or combination rules) based on the Kirkwood-Buff theory without modification of the ion-water interaction parameters. In doing so, we have introduced scaling factors for the cation-anion Lennard-Jones (LJ) interaction that quantify deviations from the standard mixing rules. For the rather size-symmetric salt solutions involving bromide and chloride ions, the standard mixing rules work fine. On the other hand, for the iodide and fluoride solutions, corresponding to the largest and smallest anion considered in this work, a rescaling of the mixing rules was necessary. For iodide, the experimental activities suggest more tightly bound ion pairing than given by the standard mixing rules, which is achieved in simulations by reducing the scaling factor of the cation-anion LJ energy. For fluoride, the situation is different and the simulations show too large attraction between fluoride and cations when compared with experimental data. For NaF, the situation can be rectified by increasing the cation-anion LJ energy. For KF, it proves necessary to increase the effective cation-anion Lennard-Jones diameter. The optimization strategy outlined in this work can be easily adapted to different kinds of ions.
We develop force field parameters for the divalent cations Mg(2+), Ca(2+), Sr(2+), and Ba(2+) for molecular dynamics simulations with the simple point charge-extended (SPC/E) water model. We follow an approach introduced recently for the optimization of monovalent ions, based on the simultaneous optimization of single-ion and ion-pair properties. We consider the solvation free energy of the divalent cations as the relevant single-ion property. As a probe for ion-pair properties we compute the activity derivatives of the salt solutions. The optimization of the ionic force fields is done in two consecutive steps. First, the cation solvation free energy is determined as a function of the Lennard-Jones (LJ) parameters. The peak in the ion-water radial distribution function (RDF) is used as a check of the structural properties of the ions. Second, the activity derivatives of the electrolytes MgY(2), CaY(2), BaY(2), SrY(2) are determined through Kirkwood-Buff solution theory, where Y = Cl(-), Br(-), I(-). The activity derivatives are determined for the restricted set of LJ parameters which reproduce the exact solvation free energy of the divalent cations. The optimal ion parameters are those that match the experimental activity data and therefore simultaneously reproduce single-ion and ion-pair thermodynamic properties. For Ca(2+), Ba(2+), and Sr(2+) such LJ parameters exist. On the other hand, for Mg(2+) the experimental activity derivatives can only be reproduced if we generalize the combination rule for the anion-cation LJ interaction and rescale the effective cation-anion LJ radius, which is a modification that leaves the cation solvation free energy invariant. The divalent cation force fields are transferable within acceptable accuracy, meaning the same cation force field is valid for all halide ions Cl(-), Br(-), I(-) tested in this study.
The nitrogen-vacancy center in diamond is a promising candidate for realizing the spin qubits concept in quantum information. Even though this defect is known for a long time, its electronic structure and other properties have not yet been explored in detail. We study the properties of the nitrogen-vacancy center in diamond through density functional theory within the local spin density approximation, using supercell calculations. While this theory is strictly applicable for ground state properties, we are able to give an estimate for the energy sequence of the excited states of this defect. We also calculate the hyperfine tensors in the ground state. The results clearly show that: (i) the spin density and the appropriate hyperfine constants are spread along a plane and unevenly distributed around the core of the defect; (ii) the measurable hyperfine constants can be found within about 7Å from the vacancy site. These results have important implications on the decoherence of the electron spin which is crucial in realizing the spin qubits in diamond.
Abstract. We present a multiscale approach to the modeling of polymer dynamics in the presence of a fluid solvent. The approach combines Langevin Molecular Dynamics (MD) techniques with a mesoscopic Lattice-Boltzmann (LB) method for the solvent dynamics. A unique feature of the present approach is that hydrodynamic interactions between the solute macromolecule and the aqueous solvent are handled explicitly, and yet in a computationally tractable way due to the dual particle-field nature of the LB solver. The suitability of the present LB-MD multiscale approach is demonstrated for the problem of polymer fast translocation through a nanopore. We also provide an interpretation of our results in the context of DNA translocation through a nanopore, a problem that has attracted much theoretical and experimental attention recently.Key words. multiscale modeling, lattice-boltzmann method, solvent-solute interactions, polymer translocation, DNA AMS subject classifications. 68U20, 92-08, 92C051. Introduction. Mathematical modeling and computer simulation of biological systems is in a stage of burgeoning growth. Advances in computer technology but also, perhaps more importantly, breakthroughs in simulational methods are helping to reduce the gap between quantitative models and actual biological behavior. The main challenge remains the wide and disparate range of spatio-temporal scales involved in the dynamical evolution of complex biological systems. In response to this challenge, various strategies have been developed recently, which are in general referred to as "multiscale modeling". Some representative examples include hybrid continuum-molecular dynamics algorithms [1], heterogeneous multiscale methods [2], and the so-called equation-free approach [3]. These methods combine different levels of the statistical description of matter (for instance, continuum and atomistic) into a composite computational scheme, in which information is exchanged through appropriate hand-shaking regions between the scales. Vital to the success of this information exchange procedure is a careful design of proper hand-shaking interfaces.Kinetic theory lies naturally between the continuum and atomistic descriptions, and should therefore provide an ideal framework for the development of robust multiscale methodologies. However, until recently, this approach has been hindered by the fact that the central equation of kinetic theory, that is, the Boltzmann equation, was perceived as an equally demanding approach as molecular dynamics from the computational point of view, and of very limited use for dense fluids due to the lack of many-body correlations. As a result, multiscale modeling of nanoflows has developed mostly in the direction of the continuum/molecular dynamics paradigm [1].Over the last decade and a half, major developments in lattice kinetic theory [4,5]
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