Neutron diffraction, NMR and molecular dynamics study of glucose dissolved in the ionic liquid 1-ethyl-3-methylimidazolium acetate

beta-D-glucose dissolved in the ionic liquid 1-ethyl-3-methylimidazolium acetate in a 6 : 1 molar ratio (ionic liquid : glucose) has been studied by neutron scattering, NMR and molecular dynamics simulations. Good agreement was found between simulated neutron scattering profiles generated for isotopically substituted liquid systems and those experimentally determined as well as between simulated and experimental diffusion coefficients obtained by Pulsed Field Gradient NMR spectroscopy. The overriding glucose-ionic liquid interactions in the liquid are hydrogen-bonding between acetate oxygens and sugar hydroxyl groups. The ionic liquid cation was found to play only a minor role in the solvation of the sugar and does not participate in hydrogen-bonding with the sugar to any significant degree. NOESY experiments lend further evidence that there is no direct interaction between sugar hydroxyl groups and acidic hydrogens on the ionic liquid cation.

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.