Small-angle neutron scattering and dynamic and static light scattering measurements were used to probe the structures of aqueous and organic-solvent-based magnetic fluids comprising dispersed magnetite nanoparticles (∼10 nm in diameter) stabilized against flocculation by adsorbed alkanoic acid layers. A core−shell model fitted to a set of neutron scattering spectra obtained from contrast variation experiments allowed the determination of the iron oxide core size and size distribution, the thicknesses of the surfactant shells, and the spatial arrangement of the individual particles. The magnetic colloidal particles appear to form compact fractal clusters with a fractal dimension of 2.52 and a correlation length of ∼350 Å in aqueous magnetic fluids, consistent with the structures of clusters observed directly using cryo-TEM (transmission electron microscopy), whereas chainlike clusters with a fractal dimension of 1.22 and a correlation length of ∼400 Å were found for organic-solvent-based magnetic fluids. The differences in cluster structure were attributed to the relative strengths of the particle−particle interaction energies. Weak interactions in the organic-solvent-based systems dictate the formation of small structures for which the apparent fractal dimensions are naturally small, whereas significantly stronger interparticle interactions in aqueous magnetic fluids result in larger, more compact clusters with higher fractal dimensions. The growth of the aqueous clusters beyond a certain size was inhibited by an increasingly high energy barrier (balance between repulsive electrostatic and attractive van der Waals interactions) with increasing cluster size. The aqueous clusters were stable against further growth when diluted with a surfactant solution but grew in time when diluted with pure water. In the latter case, the loss of part of the stabilizing secondary surfactant layer to the aqueous phase to satisfy thermodynamic partitioning constraints led to a destabilization in its dispersion. Light scattering studies indicated a change in the fractal dimension from 2.52 to about 1.20 as the clusters grew.

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Peng–Robinson equation of state is widely used with the classical van der Waals mixing rules to predict vapor liquid equilibria for systems containing hydrocarbons and related compounds. This model requires good values of the binary interaction parameter kij. In this work, we developed a semi-empirical correlation for kij partly based on the Huron–Vidal mixing rules. We obtained values for the adjustable parameters of the developed formula for over 60 binary systems and over 10 categories of components. The predictions of the new equation system were slightly better than the constant-kij model in most cases, except for 10 systems whose predictions were considerably improved with the new correlation.

This study focuses on developing a mathematical model for the electrochemical reduction of CO2 into CH3OH in a microfluidic flow cell. The present work is the first attempt to model the electro-reduction of CO2 to alcohols, which is a step forward towards the scale up of the process to industrial operation. The model features a simple geometry of a filter press cell in which the steady state isothermal reduction takes place. All significant physical phenomena occurring inside the cell are taken into account, including mass and charge balances and transport, fluid flow and electrode kinetics. The model is validated and fitted against experimental data and shows an average error of 20.2%. The model quantitatively demonstrated the dominance of the) (2 L CO c Concentration of CO2 in the liquid bulk, mol/m 3 cG Gas solubility in salt solution, mol/l cGo Gas solubility in water, mol/l CO Oxidized species concentration expression CR Reduced species concentration expression Di Diffusion coefficient of species i, m 2 /s Eeq Equilibrium potential of half-cell reaction, V F Faraday's constant FE Faradaic efficiency