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Molecular Mechanism of Gas Solubility in Liquid: Constant Chemical Potential Molecular Dynamics Simulations

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 Added by Tarak Karmakar Dr.
 Publication date 2020
  fields Physics
and research's language is English




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Accurate prediction of a gas solubility in a liquid is crucial in many areas of chemistry, and a detailed understanding of the molecular mechanism of the gas solvation continues to be an active area of research. Here, we extend the idea of constant chemical potential molecular dynamics (C{mu}MD) approach to the calculation of the gas solubility in the liquid under constant gas chemical potential conditions. As a representative example, we utilize this method to calculate the isothermal solubility of carbon dioxide in water. Additionally, we provide microscopic insight into the mechanism of solvation that preferentially occurs in areas of the surface where the hydrogen network is broken.



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Molecular Dynamics studies of chemical processes in solution are of great value in a wide spectrum of applications, which range from nano-technology to pharmaceutical chemistry. However, these calculations are affected by severe finite-size effects, such as the solution being depleted as the chemical process proceeds, which influence the outcome of the simulations. To overcome these limitations, one must allow the system to exchange molecules with a macroscopic reservoir, thus sampling a Grand-Canonical ensemble. Despite the fact that different remedies have been proposed, this still represents a key challenge in molecular simulations. In the present work we propose the Constant Chemical Potential Molecular Dynamics (C$mu$MD) method, which introduces an external force that controls the environment of the chemical process of interest. This external force, drawing molecules from a finite reservoir, maintains the chemical potential constant in the region where the process takes place. We have applied the C$mu$MD method to the paradigmatic case of urea crystallization in aqueous solution. As a result, we have been able to study crystal growth dynamics under constant supersaturation conditions, and to extract growth rates and free-energy barriers.
We present a molecular dynamics simulation method for the computation of the solubility of organic crystals in solution. The solubility is calculated based on the equilibrium free energy difference between the solvated solute and its crystallized state at the crystal surface kink site. In order to efficiently sample the growth and dissolution process, we have carried out well-tempered Metadynamics simulations with a collective variable that captures the slow degrees of freedom, namely the solute diffusion to and adsorption at the kink site together with the desolvation of the kink site. Simulations were performed at different solution concentrations using constant chemical potential molecular dynamics and the solubility was identified at the concentration at which the free energy values between the grown and dissolved kink states were equal. The effectiveness of this method is demonstrated by its success in reproducing the experimental trends of solubility of urea and naphthalene in a variety of solvents.
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Although aqueous electrolytes are among the most important solutions, the molecular simulation of their intertwined properties of chemical potentials, solubility and activity coefficients has remained a challenging problem, and has attracted considerable recent interest. In this perspectives review, we focus on the simplest case of aqueous sodium chloride at ambient conditions and discuss the two main factors that have impeded progress. The first is lack of consensus with respect to the appropriate methodology for force field (FF) development. We examine how most commonly used FFs have been developed, and emphasize the importance of distinguishing between Training Set Properties used to fit the FF parameters, and Test Set Properties, which are pure predictions of additional properties. The second is disagreement among solubility results obtained, even using identical FFs and thermodynamic conditions. Solubility calculations have been approached using both thermodynamic--based methods and direct molecular dynamics--based methods implementing coexisting solution and solid phases. Although convergence has been very recently achieved among results based on the former approach, there is as yet no general agreement with simulation results based on the latter methodology. We also propose a new method to directly calculate the electrolyte standard chemical potential in the Henry-Law ideality model. We conclude by making recommendations for calculating solubility, chemical potentials and activity coefficients, and outline a potential path for future progress.
A widely spread method of crystal preparation is to precipitate it from a supersaturated solution. In such a process, control of solution concentration is of paramount importance. Nucleation process, polymorph selection, and crystal habits depend crucially on this thermodynamic parameter. When performing simulations in the canonical ensemble as the crystalline phase is deposited the solution is depleted of solutes. This unavoidable modification of the thermodynamic conditions leads to significant artifact. Here we adopt the idea of the constant chemical potential molecular dynamics approach of Perego et al. [J. Chem. Phys. 2015, 142, 144113] to the study of nucleation. Our method allows determining the crystal nucleus size and nucleation rates at constant supersaturation. As an example we study the homogeneous nucleation of sodium chloride from its supersaturated aqueous solution.
Efficient computational methods that are capable of supporting experimental measures obtained at constant values of pH and redox potential are important tools as they serve to, among other things, provide additional atomic level information that cannot be obtained experimentally. Replica Exchange is an enhanced sampling technique that allows converged results to be obtained faster in comparison to regular molecular dynamics simulations. In this work we report the implementation, also available with GPU-accelerated code, of pH and redox potential (E) as options for multidimensional REMD simulations in AMBER. Previous publications have only reported multidimensional REMD simulations with the temperature and Hamiltonian dimensions. In this work results are shown for N-acetylmicroperoxidase-8 (NAcMP8) axially connected to a histidine peptide. This is a small system that contains only a single heme group. We compare results from E,pH-REMD, E,T-REMD and E,T,pH-REMD to one dimensional REMD simulations and to simulations without REMD. We show that 2D-REMD simulations improve sampling convergence in comparison to 1D-REMD simulations, and that 3D-REMD further improves convergence in comparison to 2D-REMD simulations. Also, our computational benchmarks show that our multidimensional REMD calculations have a small and bearable computational performance, essentially the same as one dimensional REMD. However, in multidimensional REMD a significantly higher number of replicas is required as the number of replicas scales geometrically with the number of dimensions, which requires additional computational resources. In addition to the pH dependence on standard redox potential values and the redox potential dependence on pKa values,we also investigate the influence of the temperature in our results. We observe an agreement between our computational results and theoretical predictions.
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