Identifying the dominant transport mechanism in single nanoscale pores and 3D nanoporous media.

Gas transport mechanisms can be categorized into viscous flow and mass diffusion, both of which may coexist in a porous media with multiscale pore sizes. To determine the dominant transport mechanism and its contribution to gas transport capacity, the gas viscous flow and mass diffusion processes are analyzed in single nanoscale pores via a theoretical method, and are simulated in 3D nanoporous media via pore-scale lattice Boltzmann methods. The apparent permeability from the viscous flow and apparent diffusivity from the mass diffusion are estimated. A dimensionless parameter, i.e., the diffusion-flow ratio, is proposed to evaluate the dominant transport mechanism, which is a function of the apparent permeability, apparent diffusivity, bulk dynamic viscosity, and working pressure. The results show that the apparent permeability increases by approximately two orders of magnitude when the average Knudsen number (Kn avg) of the nanoporous media or Knudsen number (Kn) of single nanoscale pores increases from 0.1 to 10. Under the same conditions, the increment in the apparent diffusivity is only approximately one order of magnitude. When Kn < 0.01, the apparent permeability has a lower bound (i.e., absolute permeability). When Kn > 10, the apparent diffusivity has an upper bound (i.e., Knudsen diffusivity). The dominant transport mechanism in single nanoscale pores is the viscous flow for 0.01 < Kn < 100, where the maximum diffusion-flow ratio is less than one. In nanoporous media, the dominant transport relies heavily on Kn avg and the structural parameters. For nanoporous media with the pore throat diameter of 3 nm, Kn avg = 0.2 is the critical point, above which the mass diffusion is dominant; otherwise, the viscous flow is dominant. As Kn avg increases to 3.4, the mass diffusion is overwhelming, with the maximum diffusion-flow ratio reaching ∼4.

Surface complexation modeling of Cd(II) adsorption on mixtures of hydrous ferric oxide, quartz and kaolinite.

Cadmium adsorption was measured as a function of ionic strength (0.001-0.1M NaNO(3)), and spanning a range of sorbate/sorbent ratios, on pure hydrous ferric oxide (HFO), kaolinite, and quartz and also on binary and ternary mixtures of the three solids. Diffuse- layer surface complexation models (DLMs) were parameterized to fit Cd sorption data for the pure kaolinite and quartz systems. Cd adsorption on kaolinite was modeled using a two-site DLM, with formation of a monodentate Cd complex on a variable charge site and Cd binding to a permanent exchange site; Cd adsorption on quartz was described using a one-site DLM with formation of a mondentate Cd complex on a variable charge site. These DLMs, together with the Dzombak and Morel DLM for HFO, were used to predict Cd adsorption on the binary and ternary mineral mixtures using a simple component additivity approach. In general, the predicted adsorption edges were in good agreement with measured data, with statistically similar goodness of fit compared to that obtained for the pure mineral systems. However, in some cases the model overpredicted Cd sorption, possibly indicating that interaction of the solids may prevent Cd from accessing all of the sorption sites.

Surface complexation modeling of Cu(II) adsorption on mixtures of hydrous ferric oxide and kaolinite.

BACKGROUND: The application of surface complexation models (SCMs) to natural sediments and soils is hindered by a lack of consistent models and data for large suites of metals and minerals of interest. Furthermore, the surface complexation approach has mostly been developed and tested for single solid systems. Few studies have extended the SCM approach to systems containing multiple solids. RESULTS: Cu adsorption was measured on pure hydrous ferric oxide (HFO), pure kaolinite (from two sources) and in systems containing mixtures of HFO and kaolinite over a wide range of pH, ionic strength, sorbate/sorbent ratios and, for the mixed solid systems, using a range of kaolinite/HFO ratios. Cu adsorption data measured for the HFO and kaolinite systems was used to derive diffuse layer surface complexation models (DLMs) describing Cu adsorption. Cu adsorption on HFO is reasonably well described using a 1-site or 2-site DLM. Adsorption of Cu on kaolinite could be described using a simple 1-site DLM with formation of a monodentate Cu complex on a variable charge surface site. However, for consistency with models derived for weaker sorbing cations, a 2-site DLM with a variable charge and a permanent charge site was also developed. CONCLUSION: Component additivity predictions of speciation in mixed mineral systems based on DLM parameters derived for the pure mineral systems were in good agreement with measured data. Discrepancies between the model predictions and measured data were similar to those observed for the calibrated pure mineral systems. The results suggest that quantifying specific interactions between HFO and kaolinite in speciation models may not be necessary. However, before the component additivity approach can be applied to natural sediments and soils, the effects of aging must be further studied and methods must be developed to estimate reactive surface areas of solid constituents in natural samples.